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Sample records for optimal sensor fusion

  1. Desensitized Optimal Filtering and Sensor Fusion Toolkit

    NASA Technical Reports Server (NTRS)

    Karlgaard, Christopher D.

    2015-01-01

    Analytical Mechanics Associates, Inc., has developed a software toolkit that filters and processes navigational data from multiple sensor sources. A key component of the toolkit is a trajectory optimization technique that reduces the sensitivity of Kalman filters with respect to model parameter uncertainties. The sensor fusion toolkit also integrates recent advances in adaptive Kalman and sigma-point filters for non-Gaussian problems with error statistics. This Phase II effort provides new filtering and sensor fusion techniques in a convenient package that can be used as a stand-alone application for ground support and/or onboard use. Its modular architecture enables ready integration with existing tools. A suite of sensor models and noise distribution as well as Monte Carlo analysis capability are included to enable statistical performance evaluations.

  2. An Optimal Pulse System Design by Multichannel Sensors Fusion.

    PubMed

    Wang, Dimin; Zhang, David; Lu, Guangming

    2016-03-01

    Pulse diagnosis, recognized as an important branch of traditional Chinese medicine (TCM), has a long history for health diagnosis. Certain features in the pulse are known to be related with the physiological status, which have been identified as biomarkers. In recent years, an electronic equipment is designed to obtain the valuable information inside pulse. Single-point pulse acquisition platform has the benefit of low cost and flexibility, but is time consuming in operation and not standardized in pulse location. The pulse system with a single-type sensor is easy to implement, but is limited in extracting sufficient pulse information. This paper proposes a novel system with optimal design that is special for pulse diagnosis. We combine a pressure sensor with a photoelectric sensor array to make a multichannel sensor fusion structure. Then, the optimal pulse signal processing methods and sensor fusion strategy are introduced for the feature extraction. Finally, the developed optimal pulse system and methods are tested on pulse database acquired from the healthy subjects and the patients known to be afflicted with diabetes. The experimental results indicate that the classification accuracy is increased significantly under the optimal design and also demonstrate that the developed pulse system with multichannel sensors fusion is more effective than the previous pulse acquisition platforms. PMID:25608317

  3. Tier-scalable reconnaissance: the challenge of sensor optimization, sensor deployment, sensor fusion, and sensor interoperability

    NASA Astrophysics Data System (ADS)

    Fink, Wolfgang; George, Thomas; Tarbell, Mark A.

    2007-04-01

    Robotic reconnaissance operations are called for in extreme environments, not only those such as space, including planetary atmospheres, surfaces, and subsurfaces, but also in potentially hazardous or inaccessible operational areas on Earth, such as mine fields, battlefield environments, enemy occupied territories, terrorist infiltrated environments, or areas that have been exposed to biochemical agents or radiation. Real time reconnaissance enables the identification and characterization of transient events. A fundamentally new mission concept for tier-scalable reconnaissance of operational areas, originated by Fink et al., is aimed at replacing the engineering and safety constrained mission designs of the past. The tier-scalable paradigm integrates multi-tier (orbit atmosphere surface/subsurface) and multi-agent (satellite UAV/blimp surface/subsurface sensing platforms) hierarchical mission architectures, introducing not only mission redundancy and safety, but also enabling and optimizing intelligent, less constrained, and distributed reconnaissance in real time. Given the mass, size, and power constraints faced by such a multi-platform approach, this is an ideal application scenario for a diverse set of MEMS sensors. To support such mission architectures, a high degree of operational autonomy is required. Essential elements of such operational autonomy are: (1) automatic mapping of an operational area from different vantage points (including vehicle health monitoring); (2) automatic feature extraction and target/region-of-interest identification within the mapped operational area; and (3) automatic target prioritization for close-up examination. These requirements imply the optimal deployment of MEMS sensors and sensor platforms, sensor fusion, and sensor interoperability.

  4. Optimal sensor fusion for land vehicle navigation

    SciTech Connect

    Morrow, J.D.

    1990-10-01

    Position location is a fundamental requirement in autonomous mobile robots which record and subsequently follow x,y paths. The Dept. of Energy, Office of Safeguards and Security, Robotic Security Vehicle (RSV) program involves the development of an autonomous mobile robot for patrolling a structured exterior environment. A straight-forward method for autonomous path-following has been adopted and requires digitizing'' the desired road network by storing x,y coordinates every 2m along the roads. The position location system used to define the locations consists of a radio beacon system which triangulates position off two known transponders, and dead reckoning with compass and odometer. This paper addresses the problem of combining these two measurements to arrive at a best estimate of position. Two algorithms are proposed: the optimal'' algorithm treats the measurements as random variables and minimizes the estimate variance, while the average error'' algorithm considers the bias in dead reckoning and attempts to guarantee an average error. Data collected on the algorithms indicate that both work well in practice. 2 refs., 7 figs.

  5. Adaptive sensor fusion using genetic algorithms

    SciTech Connect

    Fitzgerald, D.S.; Adams, D.G.

    1994-08-01

    Past attempts at sensor fusion have used some form of Boolean logic to combine the sensor information. As an alteniative, an adaptive ``fuzzy`` sensor fusion technique is described in this paper. This technique exploits the robust capabilities of fuzzy logic in the decision process as well as the optimization features of the genetic algorithm. This paper presents a brief background on fuzzy logic and genetic algorithms and how they are used in an online implementation of adaptive sensor fusion.

  6. Improved data fusion through intelligent sensor management

    NASA Astrophysics Data System (ADS)

    Smith, Moira I.; Angell, Christopher R.; Hernandez, Marcel L.; Oxford, William J.

    2003-08-01

    This paper investigates how the targeting capability of a distributed data fusion system can be improved though the use of intelligent sensor management. The research reported here builds upon previous results from QinetiQ's air-to-ground fusion programme and sensor management research. QinetiQ's previously reported software test-bed for developing and evaluating data fusion algorithms has been enhanced to include intelligent sensor management functions and weapon fly-out models. In this paper details of the enhancements are provided together with a review of the sensor management algorithms employed. These include flight path optimization of airborne sensors to minimize target state estimation error, sensor activation control and sightline management of individual sensors for optimal targeting performance. Initial results from investigative studies are presented and conclusions are drawn.

  7. Soldier systems sensor fusion

    NASA Astrophysics Data System (ADS)

    Brubaker, Kathryne M.

    1998-08-01

    This paper addresses sensor fusion and its applications in emerging Soldier Systems integration and the unique challenges associated with the human platform. Technology that,provides the highest operational payoff in a lightweight warrior system must not only have enhanced capabilities, but have low power components resulting in order of magnitude reductions coupled with significant cost reductions. These reductions in power and cost will be achieved through partnership with industry and leveraging of commercial state of the art advancements in microelectronics and power sources. As new generation of full solution fire control systems (to include temperature, wind and range sensors) and target acquisition systems will accompany a new generation of individual combat weapons and upgrade existing weapon systems. Advanced lightweight thermal, IR, laser and video senors will be used for surveillance, target acquisition, imaging and combat identification applications. Multifunctional sensors will provide embedded training features in combat configurations allowing the soldier to 'train as he fights' without the traditional cost and weight penalties associated with separate systems. Personal status monitors (detecting pulse, respiration rate, muscle fatigue, core temperature, etc.) will provide commanders and highest echelons instantaneous medical data. Seamless integration of GPS and dead reckoning (compass and pedometer) and/or inertial sensors will aid navigation and increase position accuracy. Improved sensors and processing capability will provide earlier detection of battlefield hazards such as mines, enemy lasers and NBC (nuclear, biological, chemical) agents. Via the digitized network the situational awareness database will automatically be updated with weapon, medical, position and battlefield hazard data. Soldier Systems Sensor Fusion will ultimately establish each individual soldier as an individual sensor on the battlefield.

  8. Sensor fusion for synthetic vision

    NASA Technical Reports Server (NTRS)

    Pavel, M.; Larimer, J.; Ahumada, A.

    1991-01-01

    Display methodologies are explored for fusing images gathered by millimeter wave sensors with images rendered from an on-board terrain data base to facilitate visually guided flight and ground operations in low visibility conditions. An approach to fusion based on multiresolution image representation and processing is described which facilitates fusion of images differing in resolution within and between images. To investigate possible fusion methods, a workstation-based simulation environment is being developed.

  9. Multi-sensor fusion development

    NASA Astrophysics Data System (ADS)

    Bish, Sheldon; Rohrer, Matthew; Scheffel, Peter; Bennett, Kelly

    2016-05-01

    The U.S. Army Research Laboratory (ARL) and McQ Inc. are developing a generic sensor fusion architecture that involves several diverse processes working in combination to create a dynamic task-oriented, real-time informational capability. Processes include sensor data collection, persistent and observational data storage, and multimodal and multisensor fusion that includes the flexibility to modify the fusion program rules for each mission. Such a fusion engine lends itself to a diverse set of sensing applications and architectures while using open-source software technologies. In this paper, we describe a fusion engine architecture that combines multimodal and multi-sensor fusion within an Open Standard for Unattended Sensors (OSUS) framework. The modular, plug-and-play architecture of OSUS allows future fusion plugin methodologies to have seamless integration into the fusion architecture at the conceptual and implementation level. Although beyond the scope of this paper, this architecture allows for data and information manipulation and filtering for an array of applications.

  10. Passive-sensor data fusion

    NASA Astrophysics Data System (ADS)

    Kolitz, Stephan E.

    1991-08-01

    Problems in multi-sensor data fusion are addressed for passive (angle-only) sensors; the example used is a constellation of IR sensors on satellites in low-earth orbit, viewing up to several hundred ballistic missile targets. The sensor data used in the methodology of the report is 'post-detection,' with targets resolved on single pixels (it is possible for several targets to be resolved on the same pixel). A 'scan' by a sensor is modeled by the formation of a rectangular focal plane image of lit pixels (bits with value 1), representing the presence of at least one target, and unlit pixels (bits with value 0), representing the absence of a target, at a particular time. Approaches and algorithmic solutions are developed which address the following passive sensor data fusion problems: scan-to-scan target association, and association classification. The ultimate objective is to estimate target states, for use in a larger battle management system. Results indicate that successful scan-to-scan target association is feasible at scan rates >=2 Hz, independent of resolution. Sensor-to-sensor target association is difficult at low resolution; even with high-resolution sensors the performance of a standard two-sensor single scan approach is variable and unpredictable, since it is a function of the relative geometry of sensors and targets. A single-scan approach using the Varad algorithm and three sensors is not as sensitive to this relative geometry, but is usable only for high-resolution sensors. Innovative multi-scan and multi-sensor modifications of the three- sensor Varad algorithm are developed which provide excellent performance for a wide range of sensor resolutions. The multi-sensor multi-scan methodology also provides accurate information on the classification of target associations as correct or incorrect. For the scenarios examined with resolution cell sizes ranging from 300 m to 2 km, association errors are less than 5% and essentially no classification errors

  11. Experiments in predictive sensor fusion

    NASA Astrophysics Data System (ADS)

    Keller, James M.; Auephanwiriyakul, Sansanee; Gader, Paul D.

    2001-10-01

    Data fusion is a process of combining evidence from different information sources in order to make a better judgement. However, multiple sources can provide complementary information that can be used to increase the performance in detection and recognition. There are many frameworks within which to combine these pieces into a more meaningful answer. However, new information added might be redundant or even conflicting with the existing information. These questions arise: can we predict the value added by fusing their outputs together, if we know the general characteristics of a set of sensors. Can we specify the needed characteristics of a new sensor/algorithm to add to an existing suite to gain a desired improvement performance. The characteristic of a new sensor can be in any forms, e.g., the ratio of a target's signal to the clutter's signal, the position resolution etc. In this paper, we consider these questions in the context of fuzzy set theory and in particular, a soft decision level fusion scheme we developed for land mine detection scenarios. Here, we primarily consider the ratio of a target's signal. We develop a tool to estimate a final d-metric when the information form several sensor is fused through the linguistic Choquet fuzzy integral. We utilize this tool in the examination of the performance of d-metrics in a simulation environment. The approach is demonstrated for data obtained from an Advanced Technology Demonstration in vehicle-based mine detection.

  12. Multiple objective optimization for active sensor management

    NASA Astrophysics Data System (ADS)

    Page, Scott F.; Dolia, Alexander N.; Harris, Chris J.; White, Neil M.

    2005-03-01

    The performance of a multi-sensor data fusion system is inherently constrained by the configuration of the given sensor suite. Intelligent or adaptive control of sensor resources has been shown to offer improved fusion performance in many applications. Common approaches to sensor management select sensor observation tasks that are optimal in terms of a measure of information. However, optimising for information alone is inherently sub-optimal as it does not take account of any other system requirements such as stealth or sensor power conservation. We discuss the issues relating to developing a suite of performance metrics for optimising multi-sensor systems and propose some candidate metrics. In addition it may not always be necessary to maximize information gain, in some cases small increases in information gain may take place at the cost of large sensor resource requirements. Additionally, the problems of sensor tasking and placement are usually treated separately, leading to a lack of coherency between sensor management frameworks. We propose a novel approach based on a high level decentralized information-theoretic sensor management architecture that unifies the processes of sensor tasking and sensor placement into a single framework. Sensors are controlled using a minimax multiple objective optimisation approach in order to address probability of target detection, sensor power consumption, and sensor survivability whilst maintaining a target estimation covariance threshold. We demonstrate the potential of the approach through simulation of a multi-sensor, target tracking scenario and compare the results with a single objective information based approach.

  13. Two-dimensional optimal sensor placement

    SciTech Connect

    Zhang, H.

    1995-05-01

    A method for determining the optimal two-dimensional spatial placement of multiple sensors participating in a robot perception task is introduced in this paper. This work is motivated by the fact that sensor data fusion is an effective means of reducing uncertainties in sensor observations, and that the combined uncertainty varies with the relative placement of the sensors with respect to each other. The problem of optimal sensor placement is formulated and a solution is presented in the two dimensional space. The algebraic structure of the combined sensor uncertainty with respect to the placement of sensor is studied. A necessary condition for optimal placement is derived and this necessary condition is used to obtain an efficient closed-form solution for the global optimal placement. Numerical examples are provided to illustrate the effectiveness and efficiency of the solution. 11 refs.

  14. Sensor fusion for intelligent alarm analysis

    SciTech Connect

    Nelson, C.L.; Fitzgerald, D.S.

    1995-03-01

    The purpose of an intelligent alarm analysis system is to provide complete and manageable information to a central alarm station operator by applying alarm processing and fusion techniques to sensor information. This paper discusses the sensor fusion approach taken to perform intelligent alarm analysis for the Advanced Exterior Sensor (AES). The AES is an intrusion detection and assessment system designed for wide-area coverage, quick deployment, low false/nuisance alarm operation, and immediate visual assessment. It combines three sensor technologies (visible, infrared, and millimeter wave radar) collocated on a compact and portable remote sensor module. The remote sensor module rotates at a rate of 1 revolution per second to detect and track motion and provide assessment in a continuous 360` field-of-regard. Sensor fusion techniques are used to correlate and integrate the track data from these three sensors into a single track for operator observation. Additional inputs to the fusion process include environmental data, knowledge of sensor performance under certain weather conditions, sensor priority, and recent operator feedback. A confidence value is assigned to the track as a result of the fusion process. This helps to reduce nuisance alarms and to increase operator confidence in the system while reducing the workload of the operator.

  15. Optimal multisensor decision fusion of mine detection algorithms

    NASA Astrophysics Data System (ADS)

    Liao, Yuwei; Nolte, Loren W.; Collins, Leslie M.

    2003-09-01

    Numerous detection algorithms, using various sensor modalities, have been developed for the detection of mines in cluttered and noisy backgrounds. The performance for each detection algorithm is typically reported in terms of the Receiver Operating Characteristic (ROC), which is a plot of the probability of detection versus false alarm as a function of the threshold setting on the output decision variable of each algorithm. In this paper we present multi-sensor decision fusion algorithms that combine the local decisions of existing detection algorithms for different sensors. This offers, in certain situations, an expedient, attractive and much simpler alternative to "starting over" with the redesign of a new algorithm which fuses multiple sensors at the data level. The goal in our multi-sensor decision fusion approach is to exploit complimentary strengths of existing multi-sensor algorithms so as to achieve performance (ROC) that exceeds the performance of any sensor algorithm operating in isolation. Our approach to multi-sensor decision fusion is based on optimal signal detection theory, using the likelihood ratio. We consider the optimal fusion of local decisions for two sensors, GPR (ground penetrating radar) and MD (metal detector). A new robust algorithm for decision fusion is presented that addresses the problem that the statistics of the training data is not likely to exactly match the statistics of the test data. ROC's are presented and compared for real data.

  16. Enhanced chemical weapon warning via sensor fusion

    NASA Astrophysics Data System (ADS)

    Flaherty, Michael; Pritchett, Daniel; Cothren, Brian; Schwaiger, James

    2011-05-01

    Torch Technologies Inc., is actively involved in chemical sensor networking and data fusion via multi-year efforts with Dugway Proving Ground (DPG) and the Defense Threat Reduction Agency (DTRA). The objective of these efforts is to develop innovative concepts and advanced algorithms that enhance our national Chemical Warfare (CW) test and warning capabilities via the fusion of traditional and non-traditional CW sensor data. Under Phase I, II, and III Small Business Innovative Research (SBIR) contracts with DPG, Torch developed the Advanced Chemical Release Evaluation System (ACRES) software to support non real-time CW sensor data fusion. Under Phase I and II SBIRs with DTRA in conjunction with the Edgewood Chemical Biological Center (ECBC), Torch is using the DPG ACRES CW sensor data fuser as a framework from which to develop the Cloud state Estimation in a Networked Sensor Environment (CENSE) data fusion system. Torch is currently developing CENSE to implement and test innovative real-time sensor network based data fusion concepts using CW and non-CW ancillary sensor data to improve CW warning and detection in tactical scenarios.

  17. Sensor fusion for mobile robot navigation

    SciTech Connect

    Kam, M.; Zhu, X.; Kalata, P.

    1997-01-01

    The authors review techniques for sensor fusion in robot navigation, emphasizing algorithms for self-location. These find use when the sensor suite of a mobile robot comprises several different sensors, some complementary and some redundant. Integrating the sensor readings, the robot seeks to accomplish tasks such as constructing a map of its environment, locating itself in that map, and recognizing objects that should be avoided or sought. The review describes integration techniques in two categories: low-level fusion is used for direct integration of sensory data, resulting in parameter and state estimates; high-level fusion is used for indirect integration of sensory data in hierarchical architectures, through command arbitration and integration of control signals suggested by different modules. The review provides an arsenal of tools for addressing this (rather ill-posed) problem in machine intelligence, including Kalman filtering, rule-based techniques, behavior based algorithms and approaches that borrow from information theory, Dempster-Shafer reasoning, fuzzy logic and neural networks. It points to several further-research needs, including: robustness of decision rules; simultaneous consideration of self-location, motion planning, motion control and vehicle dynamics; the effect of sensor placement and attention focusing on sensor fusion; and adaptation of techniques from biological sensor fusion.

  18. Evaluation of taste solutions by sensor fusion

    SciTech Connect

    Kojima, Yohichiro; Sato, Eriko; Atobe, Masahiko; Nakashima, Miki; Kato, Yukihisa; Nonoue, Koichi; Yamano, Yoshimasa

    2009-05-23

    In our previous studies, properties of taste solutions were discriminated based on sound velocity and amplitude of ultrasonic waves propagating through the solutions. However, to make this method applicable to beverages which contain many taste substances, further studies are required. In this study, the waveform of an ultrasonic wave with frequency of approximately 5 MHz propagating through a solution was measured and subjected to frequency analysis. Further, taste sensors require various techniques of sensor fusion to effectively obtain chemical and physical parameter of taste solutions. A sensor fusion method of ultrasonic wave sensor and various sensors, such as the surface plasmon resonance (SPR) sensor, to estimate tastes were proposed and examined in this report. As a result, differences among pure water and two basic taste solutions were clearly observed as differences in their properties. Furthermore, a self-organizing neural network was applied to obtained data which were used to clarify the differences among solutions.

  19. Minimum energy information fusion in sensor networks

    SciTech Connect

    Chapline, G

    1999-05-11

    In this paper we consider how to organize the sharing of information in a distributed network of sensors and data processors so as to provide explanations for sensor readings with minimal expenditure of energy. We point out that the Minimum Description Length principle provides an approach to information fusion that is more naturally suited to energy minimization than traditional Bayesian approaches. In addition we show that for networks consisting of a large number of identical sensors Kohonen self-organization provides an exact solution to the problem of combing the sensor outputs into minimal description length explanations.

  20. Health-Enabled Smart Sensor Fusion Technology

    NASA Technical Reports Server (NTRS)

    Wang, Ray

    2012-01-01

    A process was designed to fuse data from multiple sensors in order to make a more accurate estimation of the environment and overall health in an intelligent rocket test facility (IRTF), to provide reliable, high-confidence measurements for a variety of propulsion test articles. The object of the technology is to provide sensor fusion based on a distributed architecture. Specifically, the fusion technology is intended to succeed in providing health condition monitoring capability at the intelligent transceiver, such as RF signal strength, battery reading, computing resource monitoring, and sensor data reading. The technology also provides analytic and diagnostic intelligence at the intelligent transceiver, enhancing the IEEE 1451.x-based standard for sensor data management and distributions, as well as providing appropriate communications protocols to enable complex interactions to support timely and high-quality flow of information among the system elements.

  1. Sensor fusion method for machine performance enhancement

    SciTech Connect

    Mou, J.I.; King, C.; Hillaire, R.; Jones, S.; Furness, R.

    1998-03-01

    A sensor fusion methodology was developed to uniquely integrate pre-process, process-intermittent, and post-process measurement and analysis technology to cost-effectively enhance the accuracy and capability of computer-controlled manufacturing equipment. Empirical models and computational algorithms were also developed to model, assess, and then enhance the machine performance.

  2. Evaluating fusion techniques for multi-sensor satellite image data

    SciTech Connect

    Martin, Benjamin W; Vatsavai, Raju

    2013-01-01

    Satellite image data fusion is a topic of interest in many areas including environmental monitoring, emergency response, and defense. Typically any single satellite sensor cannot provide all of the benefits offered by a combination of different sensors (e.g., high-spatial but low spectral resolution vs. low-spatial but high spectral, optical vs. SAR). Given the respective strengths and weaknesses of the different types of image data, it is beneficial to fuse many types of image data to extract as much information as possible from the data. Our work focuses on the fusion of multi-sensor image data into a unified representation that incorporates the potential strengths of a sensor in order to minimize classification error. Of particular interest is the fusion of optical and synthetic aperture radar (SAR) images into a single, multispectral image of the best possible spatial resolution. We explore various methods to optimally fuse these images and evaluate the quality of the image fusion by using K-means clustering to categorize regions in the fused images and comparing the accuracies of the resulting categorization maps.

  3. Sensor fusion for precision agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Information-based management of crop production systems known as precision agriculture relies on different sensor technologies aimed at characterization of spatial heterogeneity of a cropping environment. Remote and proximal sensing systems have been deployed to obtain high-resolution data pertainin...

  4. Sensor fusion for improved indoor navigation

    NASA Astrophysics Data System (ADS)

    Emilsson, Erika; Rydell, Joakim

    2012-09-01

    A reliable indoor positioning system providing high accuracy has the potential to increase the safety of first responders and military personnel significantly. To enable navigation in a broad range of environments and obtain more accurate and robust positioning results, we propose a multi-sensor fusion approach. We describe and evaluate a positioning system, based on sensor fusion between a foot-mounted inertial measurement unit (IMU) and a camera-based system for simultaneous localization and mapping (SLAM). The complete system provides accurate navigation in many relevant environments without depending on preinstalled infrastructure. The camera-based system uses both inertial measurements and visual data, thereby enabling navigation also in environments and scenarios where one of the sensors provides unreliable data during a few seconds. When sufficient light is available, the camera-based system generally provides good performance. The foot-mounted system provides accurate positioning when distinct steps can be detected, e.g., during walking and running, even in dark or smoke-filled environments. By combining the two systems, the integrated positioning system can be expected to enable accurate navigation in almost all kinds of environments and scenarios. In this paper we present results from initial tests, which show that the proposed sensor fusion improves the navigation solution considerably in scenarios where either the foot-mounted or camera-based system is unable to navigate on its own.

  5. Exploiting phase transitions for fusion optimization problems

    NASA Astrophysics Data System (ADS)

    Svenson, Pontus

    2005-05-01

    Many optimization problems that arise in multi-target tracking and fusion applications are known to be NP-complete, ie, believed to have worst-case complexities that are exponential in problem size. Recently, many such NP-complete problems have been shown to display threshold phenomena: it is possible to define a parameter such that the probability of a random problem instance having a solution jumps from 1 to 0 at a specific value of the parameter. It is also found that the amount of resources needed to solve the problem instance peaks at the transition point. Among the problems found to display this behavior are graph coloring (aka clustering, relevant for multi-target tracking), satisfiability (which occurs in resource allocation and planning problem), and the travelling salesperson problem. Physicists studying these problems have found intriguing similarities to phase transitions in spin models of statistical mechanics. Many methods previously used to analyze spin glasses have been used to explain some of the properties of the behavior at the transition point. It turns out that the transition happens because the fitness landscape of the problem changes as the parameter is varied. Some algorithms have been introduced that exploit this knowledge of the structure of the fitness landscape. In this paper, we review some of the experimental and theoretical work on threshold phenomena in optimization problems and indicate how optimization problems from tracking and sensor resource allocation could be analyzed using these results.

  6. Robot navigation using simple sensor fusion

    SciTech Connect

    Jollay, D.M.; Ricks, R.E.

    1988-01-01

    Sensors on an autonomous mobile system are essential in enviornment determination for navigation purposes. As is well documented in previous publications, sonar sensors are inadequate in providing a depiction of a real world environment and therefore do not provide accurate information for navigation, it not used in conjunction with another type of sensor. This paper describes a simple, inexpensive, and relatively fast navigation algorithm involving vision and sonar sensor fusion for use in navigating an autonomous robot in an unknown and potentially dynamic environment. Navigation of the mobile robot was accomplished by use of a TV camera as the primary sensor. Input data received from the camera were digitized through a video module and then processed using a dedicated vision system to enable detection of obstacles and to determine edge positions relative to the robot. Since 3D vision was not attempted due to its complex and time consuming nature, sonar sensors were then sued as secondary sensors in order to determine the proximity of detected obstacles. By then fusing the sensor data, the robot was able to navigate (quickly and collision free) to a given goal, achieving obstacle avoidance in real-time.

  7. Non-verbal communication through sensor fusion

    NASA Astrophysics Data System (ADS)

    Tairych, Andreas; Xu, Daniel; O'Brien, Benjamin M.; Anderson, Iain A.

    2016-04-01

    When we communicate face to face, we subconsciously engage our whole body to convey our message. In telecommunication, e.g. during phone calls, this powerful information channel cannot be used. Capturing nonverbal information from body motion and transmitting it to the receiver parallel to speech would make these conversations feel much more natural. This requires a sensing device that is capable of capturing different types of movements, such as the flexion and extension of joints, and the rotation of limbs. In a first embodiment, we developed a sensing glove that is used to control a computer game. Capacitive dielectric elastomer (DE) sensors measure finger positions, and an inertial measurement unit (IMU) detects hand roll. These two sensor technologies complement each other, with the IMU allowing the player to move an avatar through a three-dimensional maze, and the DE sensors detecting finger flexion to fire weapons or open doors. After demonstrating the potential of sensor fusion in human-computer interaction, we take this concept to the next level and apply it in nonverbal communication between humans. The current fingerspelling glove prototype uses capacitive DE sensors to detect finger gestures performed by the sending person. These gestures are mapped to corresponding messages and transmitted wirelessly to another person. A concept for integrating an IMU into this system is presented. The fusion of the DE sensor and the IMU combines the strengths of both sensor types, and therefore enables very comprehensive body motion sensing, which makes a large repertoire of gestures available to nonverbal communication over distances.

  8. Sensor fusion display evaluation using information integration models in enhanced/synthetic vision applications

    NASA Technical Reports Server (NTRS)

    Foyle, David C.

    1993-01-01

    Based on existing integration models in the psychological literature, an evaluation framework is developed to assess sensor fusion displays as might be implemented in an enhanced/synthetic vision system. The proposed evaluation framework for evaluating the operator's ability to use such systems is a normative approach: The pilot's performance with the sensor fusion image is compared to models' predictions based on the pilot's performance when viewing the original component sensor images prior to fusion. This allows for the determination as to when a sensor fusion system leads to: poorer performance than one of the original sensor displays, clearly an undesirable system in which the fused sensor system causes some distortion or interference; better performance than with either single sensor system alone, but at a sub-optimal level compared to model predictions; optimal performance compared to model predictions; or, super-optimal performance, which may occur if the operator were able to use some highly diagnostic 'emergent features' in the sensor fusion display, which were unavailable in the original sensor displays.

  9. Global optimization for multisensor fusion in seismic imaging

    SciTech Connect

    Barhen, J.; Protopopescu, V.; Reister, D.

    1997-06-01

    The accurate imaging of subsurface structures requires the fusion of data collected from large arrays of seismic sensors. The fusion process is formulated as an optimization problem and yields an extremely complex energy surface. Due to the very large number of local minima to be explored and escaped from, the seismic imaging problem has typically been tackled with stochastic optimization methods based on Monte Carlo techniques. Unfortunately, these algorithms are very cumbersome and computationally intensive. Here, the authors present TRUST--a novel deterministic algorithm for global optimization that they apply to seismic imaging. The excellent results demonstrate that TRUST may provide the necessary breakthrough to address major scientific and technological challenges in fields as diverse as seismic modeling, process optimization, and protein engineering.

  10. Sensor Fusion and Smart Sensor in Sports and Biomedical Applications.

    PubMed

    Mendes, José Jair Alves; Vieira, Mário Elias Marinho; Pires, Marcelo Bissi; Stevan, Sergio Luiz

    2016-01-01

    The following work presents an overview of smart sensors and sensor fusion targeted at biomedical applications and sports areas. In this work, the integration of these areas is demonstrated, promoting a reflection about techniques and applications to collect, quantify and qualify some physical variables associated with the human body. These techniques are presented in various biomedical and sports applications, which cover areas related to diagnostics, rehabilitation, physical monitoring, and the development of performance in athletes, among others. Although some applications are described in only one of two fields of study (biomedicine and sports), it is very likely that the same application fits in both, with small peculiarities or adaptations. To illustrate the contemporaneity of applications, an analysis of specialized papers published in the last six years has been made. In this context, the main characteristic of this review is to present the largest quantity of relevant examples of sensor fusion and smart sensors focusing on their utilization and proposals, without deeply addressing one specific system or technique, to the detriment of the others.

  11. Sensor Fusion and Smart Sensor in Sports and Biomedical Applications.

    PubMed

    Mendes, José Jair Alves; Vieira, Mário Elias Marinho; Pires, Marcelo Bissi; Stevan, Sergio Luiz

    2016-01-01

    The following work presents an overview of smart sensors and sensor fusion targeted at biomedical applications and sports areas. In this work, the integration of these areas is demonstrated, promoting a reflection about techniques and applications to collect, quantify and qualify some physical variables associated with the human body. These techniques are presented in various biomedical and sports applications, which cover areas related to diagnostics, rehabilitation, physical monitoring, and the development of performance in athletes, among others. Although some applications are described in only one of two fields of study (biomedicine and sports), it is very likely that the same application fits in both, with small peculiarities or adaptations. To illustrate the contemporaneity of applications, an analysis of specialized papers published in the last six years has been made. In this context, the main characteristic of this review is to present the largest quantity of relevant examples of sensor fusion and smart sensors focusing on their utilization and proposals, without deeply addressing one specific system or technique, to the detriment of the others. PMID:27669260

  12. Intelligent processing techniques for sensor fusion

    NASA Astrophysics Data System (ADS)

    Byrd, Katherine A.; Smith, Bart; Allen, Doug; Morris, Norman; Bjork, Charles A., Jr.; Deal-Giblin, Kim; Rushing, John A.

    1998-03-01

    Intelligent processing techniques which can effectively combine sensor data from disparate sensors by selecting and using only the most beneficial individual sensor data is a critical element of exoatmospheric interceptor systems. A major goal of these algorithms is to provide robust discrimination against stressing threats in poor a priori conditions, and to incorporate adaptive approaches in off- nominal conditions. This paper summarizes the intelligent processing algorithms being developed, implemented and tested to intelligently fuse data from passive infrared and active LADAR sensors at the measurement, feature and decision level. These intelligent algorithms employ dynamic selection of individual sensors features and the weighting of multiple classifier decisions to optimize performance in good a priori conditions and robustness in poor a priori conditions. Features can be dynamically selected based on an estimate of the feature confidence which is determined from feature quality and weighting terms derived from the quality of sensor data and expected phenomenology. Multiple classifiers are employed which use both fuzzy logic and knowledge based approaches to fuse the sensor data and to provide a target lethality estimate. Target designation decisions can be made by fusing weighted individual classifier decisions whose output contains an estimate of the confidence of the data and the discrimination decisions. The confidence in the data and decisions can be used in real time to dynamically select different sensor feature data or to request additional sensor data on specific objects that have not been confidently identified as being lethal or non- lethal. The algorithms are implemented in C within a graphic user interface framework. Dynamic memory allocation and the sequentialy implementation of the feature algorithms are employed. The baseline set of fused sensor discrimination algorithms with intelligent processing are described in this paper. Example results

  13. Fusion moves for Markov random field optimization.

    PubMed

    Lempitsky, Victor; Rother, Carsten; Roth, Stefan; Blake, Andrew

    2010-08-01

    The efficient application of graph cuts to Markov Random Fields (MRFs) with multiple discrete or continuous labels remains an open question. In this paper, we demonstrate one possible way of achieving this by using graph cuts to combine pairs of suboptimal labelings or solutions. We call this combination process the fusion move. By employing recently developed graph-cut-based algorithms (so-called QPBO-graph cut), the fusion move can efficiently combine two proposal labelings in a theoretically sound way, which is in practice often globally optimal. We demonstrate that fusion moves generalize many previous graph-cut approaches, which allows them to be used as building blocks within a broader variety of optimization schemes than were considered before. In particular, we propose new optimization schemes for computer vision MRFs with applications to image restoration, stereo, and optical flow, among others. Within these schemes the fusion moves are used 1) for the parallelization of MRF optimization into several threads, 2) for fast MRF optimization by combining cheap-to-compute solutions, and 3) for the optimization of highly nonconvex continuous-labeled MRFs with 2D labels. Our final example is a nonvision MRF concerned with cartographic label placement, where fusion moves can be used to improve the performance of a standard inference method (loopy belief propagation).

  14. Method and apparatus for sensor fusion

    NASA Technical Reports Server (NTRS)

    Krishen, Kumar (Inventor); Shaw, Scott (Inventor); Defigueiredo, Rui J. P. (Inventor)

    1991-01-01

    Method and apparatus for fusion of data from optical and radar sensors by error minimization procedure is presented. The method was applied to the problem of shape reconstruction of an unknown surface at a distance. The method involves deriving an incomplete surface model from an optical sensor. The unknown characteristics of the surface are represented by some parameter. The correct value of the parameter is computed by iteratively generating theoretical predictions of the radar cross sections (RCS) of the surface, comparing the predicted and the observed values for the RCS, and improving the surface model from results of the comparison. Theoretical RCS may be computed from the surface model in several ways. One RCS prediction technique is the method of moments. The method of moments can be applied to an unknown surface only if some shape information is available from an independent source. The optical image provides the independent information.

  15. Sensor fusion for hand-held multisensor landmine detection

    NASA Astrophysics Data System (ADS)

    Agarwal, Sanjeev; Chander, Venkat S.; Palit, Partha P.; Stanley, Joe; Mitchell, O. Robert

    2001-10-01

    Sensor fusion issues in a streamlined assimilation of multi-sensor information for landmine detection are discussed. In particular multi-sensor fusion in hand-held landmine detection system with ground penetrating radar (GPR) and metal detector sensors is investigated. The fusion architecture consists of feature extraction for individual sensors followed by a feed-forward neural network training to learn the feature space representation of the mine/no-mine classification. A correlation feature from GPR, and slope and energy feature from metal detector are used for discrimination. Various fusion strategies are discussed and results compared against each other and against individual sensors using ROC curves for the available multi-sensor data. Both feature level and decision level fusion have been investigated. Simple decision level fusion scheme based on Dempster-Shafer evidence accumulation, soft AND, MIN and MAX are compared. Feature level fusion using neural network training is shown to provide best results. However comparable performance is achieved using decision level sensor fusion based on Dempster-Shafer accumulation. It is noted that, the above simple feed-forward fusion scheme lacks a means to verify detections after a decision has been made. New detection algorithms that are more than anomaly detectors are needed. Preliminary results with features based on independent component analysis (ICA) show promising results towards this end.

  16. Fluorescent sensors based on bacterial fusion proteins

    NASA Astrophysics Data System (ADS)

    Prats Mateu, Batirtze; Kainz, Birgit; Pum, Dietmar; Sleytr, Uwe B.; Toca-Herrera, José L.

    2014-06-01

    Fluorescence proteins are widely used as markers for biomedical and technological purposes. Therefore, the aim of this project was to create a fluorescent sensor, based in the green and cyan fluorescent protein, using bacterial S-layers proteins as scaffold for the fluorescent tag. We report the cloning, expression and purification of three S-layer fluorescent proteins: SgsE-EGFP, SgsE-ECFP and SgsE-13aa-ECFP, this last containing a 13-amino acid rigid linker. The pH dependence of the fluorescence intensity of the S-layer fusion proteins, monitored by fluorescence spectroscopy, showed that the ECFP tag was more stable than EGFP. Furthermore, the fluorescent fusion proteins were reassembled on silica particles modified with cationic and anionic polyelectrolytes. Zeta potential measurements confirmed the particle coatings and indicated their colloidal stability. Flow cytometry and fluorescence microscopy showed that the fluorescence of the fusion proteins was pH dependent and sensitive to the underlying polyelectrolyte coating. This might suggest that the fluorescent tag is not completely exposed to the bulk media as an independent moiety. Finally, it was found out that viscosity enhanced the fluorescence intensity of the three fluorescent S-layer proteins.

  17. Sensor fusion for intelligent behavior on small unmanned ground vehicles

    NASA Astrophysics Data System (ADS)

    Kogut, G.; Ahuja, G.; Sights, B.; Pacis, E. B.; Everett, H. R.

    2007-04-01

    Sensors commonly mounted on small unmanned ground vehicles (UGVs) include visible light and thermal cameras, scanning LIDAR, and ranging sonar. Sensor data from these sensors is vital to emerging autonomous robotic behaviors. However, sensor data from any given sensor can become noisy or erroneous under a range of conditions, reducing the reliability of autonomous operations. We seek to increase this reliability through data fusion. Data fusion includes characterizing the strengths and weaknesses of each sensor modality and combining their data in a way such that the result of the data fusion provides more accurate data than any single sensor. We describe data fusion efforts applied to two autonomous behaviors: leader-follower and human presence detection. The behaviors are implemented and tested in a variety of realistic conditions.

  18. Cognitive foundations for model-based sensor fusion

    NASA Astrophysics Data System (ADS)

    Perlovsky, Leonid I.; Weijers, Bertus; Mutz, Chris W.

    2003-08-01

    Target detection, tracking, and sensor fusion are complicated problems, which usually are performed sequentially. First detecting targets, then tracking, then fusing multiple sensors reduces computations. This procedure however is inapplicable to difficult targets which cannot be reliably detected using individual sensors, on individual scans or frames. In such more complicated cases one has to perform functions of fusing, tracking, and detecting concurrently. This often has led to prohibitive combinatorial complexity and, as a consequence, to sub-optimal performance as compared to the information-theoretic content of all the available data. It is well appreciated that in this task the human mind is by far superior qualitatively to existing mathematical methods of sensor fusion, however, the human mind is limited in the amount of information and speed of computation it can cope with. Therefore, research efforts have been devoted toward incorporating "biological lessons" into smart algorithms, yet success has been limited. Why is this so, and how to overcome existing limitations? The fundamental reasons for current limitations are analyzed and a potentially breakthrough research and development effort is outlined. We utilize the way our mind combines emotions and concepts in the thinking process and present the mathematical approach to accomplishing this in the current technology computers. The presentation will summarize the difficulties encountered by intelligent systems over the last 50 years related to combinatorial complexity, analyze the fundamental limitations of existing algorithms and neural networks, and relate it to the type of logic underlying the computational structure: formal, multivalued, and fuzzy logic. A new concept of dynamic logic will be introduced along with algorithms capable of pulling together all the available information from multiple sources. This new mathematical technique, like our brain, combines conceptual understanding with

  19. Particle swarm optimization and uncertainty in Dempster-Shafer fusion

    NASA Astrophysics Data System (ADS)

    Ranney, Kenneth; Nasrabadi, Nasser

    2009-05-01

    Recent investigations into multi-sensor fusion have yielded a variety of data fusion algorithms. Some fuse imagery from multiple sensors at the pixel level, while others fuse outputs of detection algorithms-such as radar prescreeners or hyperspectral anomaly detectors-at the feature level. Many of the feature-level fusion algorithms build upon the foundation of Bayesian probability, and they assign probability to the event that a certain feature value is due either to a target or to clutter. A few of the feature-level fusion algorithms, however, exploit tools developed within the framework of the Dempster-Shafer (DS) theory of evidence. In these formulations some of the probability can be assigned to a third hypothesis representing uncertainty, and the algorithm developer must specify an uncertainty function that maps feature values to probability "mass" for this third hypothesis. Unfortunately, the DS paradigm lacks a standard method for assignment of mass to the "don't know" hypothesis for a particular input feature. In this paper we define a feature-level DS fusion algorithm and determine a method for specifying its uncertainty function. We begin by developing and describing a measure of performance based on the area under the receiver operating characteristic (ROC) curve. We then incorporate this measure of performance into a training procedure that exploits the dynamics of the particle swarm and is capable of discovering locally optimal uncertainty functions. We exercise the training algorithm using simulated data, and analyze the performance of its hypothesized optimal uncertainty function. Next we apply the newly developed training techniques to data produced by separate prescreener algorithms operating on measured Hyperspectral Imager (HSI) and synthetic aperture radar (SAR) data from the same scene. Finally, we quantify the performance of the entire DS fusion procedure using ROC curves.

  20. Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks

    PubMed Central

    Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Zhong, Xionghu

    2015-01-01

    Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones. PMID:26251908

  1. Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks.

    PubMed

    Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Zhong, Xionghu

    2015-08-05

    Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones.

  2. Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks.

    PubMed

    Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Zhong, Xionghu

    2015-01-01

    Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones. PMID:26251908

  3. Sensor fusion for intelligent process control.

    SciTech Connect

    Connors, John J.; Hill, Kevin; Hanekamp, David; Haley, William F.; Gallagher, Robert J.; Gowin, Craig; Farrar, Arthur R.; Sheaffer, Donald A.; DeYoung, Mark A.; Bertram, Lee A.; Dodge, Craig; Binion, Bruce; Walsh, Peter M.; Houf, William G.; Desam, Padmabhushana R.; Tiwary, Rajiv; Stokes, Michael R.; Miller, Alan J.; Michael, Richard W.; Mayer, Raymond M.; Jiao, Yu; Smith, Philip J.; Arbab, Mehran; Hillaire, Robert G.

    2004-08-01

    An integrated system for the fusion of product and process sensors and controls for production of flat glass was envisioned, having as its objective the maximization of throughput and product quality subject to emission limits, furnace refractory wear, and other constraints. Although the project was prematurely terminated, stopping the work short of its goal, the tasks that were completed show the value of the approach and objectives. Though the demonstration was to have been done on a flat glass production line, the approach is applicable to control of production in the other sectors of the glass industry. Furthermore, the system architecture is also applicable in other industries utilizing processes in which product uniformity is determined by ability to control feed composition, mixing, heating and cooling, chemical reactions, and physical processes such as distillation, crystallization, drying, etc. The first phase of the project, with Visteon Automotive Systems as industrial partner, was focused on simulation and control of the glass annealing lehr. That work produced the analysis and computer code that provide the foundation for model-based control of annealing lehrs during steady state operation and through color and thickness changes. In the second phase of the work, with PPG Industries as the industrial partner, the emphasis was on control of temperature and combustion stoichiometry in the melting furnace, to provide a wider operating window, improve product yield, and increase energy efficiency. A program of experiments with the furnace, CFD modeling and simulation, flow measurements, and sensor fusion was undertaken to provide the experimental and theoretical basis for an integrated, model-based control system utilizing the new infrastructure installed at the demonstration site for the purpose. In spite of the fact that the project was terminated during the first year of the second phase of the work, the results of these first steps toward implementation

  4. Sparse Downscaling and Adaptive Fusion of Multi-sensor Precipitation

    NASA Astrophysics Data System (ADS)

    Ebtehaj, M.; Foufoula, E.

    2011-12-01

    The past decades have witnessed a remarkable emergence of new sources of multiscale multi-sensor precipitation data including data from global spaceborne active and passive sensors, regional ground based weather surveillance radars and local rain-gauges. Resolution enhancement of remotely sensed rainfall and optimal integration of multi-sensor data promise a posteriori estimates of precipitation fluxes with increased accuracy and resolution to be used in hydro-meteorological applications. In this context, new frameworks are proposed for resolution enhancement and multiscale multi-sensor precipitation data fusion, which capitalize on two main observations: (1) sparseness of remotely sensed precipitation fields in appropriately chosen transformed domains, (e.g., in wavelet space) which promotes the use of the newly emerged theory of sparse representation and compressive sensing for resolution enhancement; (2) a conditionally Gaussian Scale Mixture (GSM) parameterization in the wavelet domain which allows exploiting the efficient linear estimation methodologies, while capturing the non-Gaussian data structure of rainfall. The proposed methodologies are demonstrated using a data set of coincidental observations of precipitation reflectivity images by the spaceborne precipitation radar (PR) aboard the Tropical Rainfall Measurement Mission (TRMM) satellite and ground-based NEXRAD weather surveillance Doppler radars. Uniqueness and stability of the solution, capturing non-Gaussian singular structure of rainfall, reduced uncertainty of estimation and efficiency of computation are the main advantages of the proposed methodologies over the commonly used standard Gaussian techniques.

  5. ELIPS: Toward a Sensor Fusion Processor on a Chip

    NASA Technical Reports Server (NTRS)

    Daud, Taher; Stoica, Adrian; Tyson, Thomas; Li, Wei-te; Fabunmi, James

    1998-01-01

    The paper presents the concept and initial tests from the hardware implementation of a low-power, high-speed reconfigurable sensor fusion processor. The Extended Logic Intelligent Processing System (ELIPS) processor is developed to seamlessly combine rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor in compact low power VLSI. The first demonstration of the ELIPS concept targets interceptor functionality; other applications, mainly in robotics and autonomous systems are considered for the future. The main assumption behind ELIPS is that fuzzy, rule-based and neural forms of computation can serve as the main primitives of an "intelligent" processor. Thus, in the same way classic processors are designed to optimize the hardware implementation of a set of fundamental operations, ELIPS is developed as an efficient implementation of computational intelligence primitives, and relies on a set of fuzzy set, fuzzy inference and neural modules, built in programmable analog hardware. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Following software demonstrations on several interceptor data, three important ELIPS building blocks (a fuzzy set preprocessor, a rule-based fuzzy system and a neural network) have been fabricated in analog VLSI hardware and demonstrated microsecond-processing times.

  6. Facility Monitoring: A Qualitative Theory for Sensor Fusion

    NASA Technical Reports Server (NTRS)

    Figueroa, Fernando

    2001-01-01

    Data fusion and sensor management approaches have largely been implemented with centralized and hierarchical architectures. Numerical and statistical methods are the most common data fusion methods found in these systems. Given the proliferation and low cost of processing power, there is now an emphasis on designing distributed and decentralized systems. These systems use analytical/quantitative techniques or qualitative reasoning methods for date fusion.Based on other work by the author, a sensor may be treated as a highly autonomous (decentralized) unit. Each highly autonomous sensor (HAS) is capable of extracting qualitative behaviours from its data. For example, it detects spikes, disturbances, noise levels, off-limit excursions, step changes, drift, and other typical measured trends. In this context, this paper describes a distributed sensor fusion paradigm and theory where each sensor in the system is a HAS. Hence, given the reach qualitative information from each HAS, a paradigm and formal definitions are given so that sensors and processes can reason and make decisions at the qualitative level. This approach to sensor fusion makes it possible the implementation of intuitive (effective) methods to monitor, diagnose, and compensate processes/systems and their sensors. This paradigm facilitates a balanced distribution of intelligence (code and/or hardware) to the sensor level, the process/system level, and a higher controller level. The primary application of interest is in intelligent health management of rocket engine test stands.

  7. Fuzzy controlled neural network for sensor fusion with adaptability to sensor failure

    NASA Astrophysics Data System (ADS)

    Chen, Judy; Kostrzewski, Andrew A.; Kim, Dai Hyun; Savant, Gajendra D.; Kim, Jeongdal; Vasiliev, Anatoly A.

    1997-10-01

    Artificial neural networks have proven to be powerful tools for sensor fusion, but they are not adaptable to sensor failure in a sensor suite. Physical Optics Corporation (POC) presents a new sensor fusion algorithm, applying fuzzy logic to give a neural network real-time adaptability to compensate for faulty sensors. Identifying data that originates from malfunctioning sensors, and excluding it from sensor fusion, allows the fuzzy neural network to achieve better results. A fuzzy logic-based functionality evaluator detects malfunctioning sensors in real time. A separate neural network is trained for each potential sensor failure situation. Since the number of possible sensor failure situations is large, the large number of neural networks is then fuzzified into a small number of fuzzy neural networks. Experimental results show the feasibility of the proposed approach -- the system correctly recognized airplane models in a computer simulation.

  8. Distributed fiber Bragg grating sensors information fusion and decoupling

    NASA Astrophysics Data System (ADS)

    Chen, Xiyuan

    2005-02-01

    Optical fiber sensors can be used to measure many different parameters including strain, temperature, pressure, displacement, electrical field, refractive index, rotation, position and vibrations. Among a variety of fiber sensors, fiber Bragg grating (FBG) has numerous advantages over other optical fiber sensors. One of the major advantages of this type of sensors is attributed to wavelength-encoded information given by the Bragg grating. Since the wavelength is an absolute parameter, signal from FBG may be processed such that its information remains immune to power fluctuations along the optical path. This inherent characteristic makes the FBG sensors very attractive for application in harsh environment, and on-site measurements. But FBG sensors can measure temperature and strain simultaneously; it is necessary to decouple measurement information. In the present paper, A distributed fiber Bragg grating sensors measurement system that measures global deformations of large surface online-based FBG sensors is introduced. Short overview of the measurement principle and the signal processing realized and fusion method as well as the application of the sensor in the field of large surface will be presented. A new fusion method based on the federal Kalman filter to decouple information of the temperature and strain is proposed. The algorithm of optimum estimation fusion for distributed FBG systems based on the model of deformation of beam is studied. Simulation results and experimental results show algorithm of fusion and decoupling is an efficient method for improving performance of distributed FBG sensors system.

  9. Driver drowsiness detection using multimodal sensor fusion

    NASA Astrophysics Data System (ADS)

    Andreeva, Elena O.; Aarabi, Parham; Philiastides, Marios G.; Mohajer, Keyvan; Emami, Majid

    2004-04-01

    This paper proposes a multi-modal sensor fusion algorithm for the estimation of driver drowsiness. Driver sleepiness is believed to be responsible for more than 30% of passenger car accidents and for 4% of all accident fatalities. In commercial vehicles, drowsiness is blamed for 58% of single truck accidents and 31% of commercial truck driver fatalities. This work proposes an innovative automatic sleep-onset detection system. Using multiple sensors, the driver"s body is studied as a mechanical structure of springs and dampeners. The sleep-detection system consists of highly sensitive triple-axial accelerometers to monitor the driver"s upper body in 3-D. The subject is modeled as a linear time-variant (LTV) system. An LMS adaptive filter estimation algorithm generates the transfer function (i.e. weight coefficients) for this LTV system. Separate coefficients are generated for the awake and asleep states of the subject. These coefficients are then used to train a neural network. Once trained, the neural network classifies the condition of the driver as either awake or asleep. The system has been tested on a total of 8 subjects. The tests were conducted on sleep-deprived individuals for the sleep state and on fully awake individuals for the awake state. When trained and tested on the same subject, the system detected sleep and awake states of the driver with a success rate of 95%. When the system was trained on three subjects and then retested on a fourth "unseen" subject, the classification rate dropped to 90%. Furthermore, it was attempted to correlate driver posture and sleepiness by observing how car vibrations propagate through a person"s body. Eight additional subjects were studied for this purpose. The results obtained in this experiment proved inconclusive which was attributed to significant differences in the individual habitual postures.

  10. Improved UXO detection via sensor fusion

    NASA Astrophysics Data System (ADS)

    Zhang, Yan; Li, Jing; Carin, Lawrence; Collins, Leslie M.

    2000-08-01

    Traditional algorithms for UXO remediation experience severe difficulties distinguishing buried targets from anthropic clutter, and in most cases UXO items are found among extensive surface clutter and shrapnel from ordnance operations. These problems render site mediation a very slow, labor intensive, and efficient process. While sensors have improved significantly over the past several years in their ability to detect conducting and/or permeable targets, reduction of the false alarm rate has proven to be a significantly more challenging problem. Our work has focused on the development of optimal signal processing algorithms that rigorously incorporate the underlying physics characteristics of the sensor and the anticipated UXO target in order to address the false alarm issue. In this paper, we describe several techniques for discriminating targets from clutter that have been applied to data obtained with the Multi-sensor Towed Array Detection System (MTADS) that has been developed by the Naval Research Laboratory. MTADS includes both EMI and magnetometer sensors. We describe a variety of signal processing techniques which incorporate physics-based models that have been applied to the data measured by MTADS during field demonstrations. We will compare and contrast the performance of the various algorithms as well as discussing tradeoffs, such as training requirements. The result of this analysis quantify the utility of fusing magnetometer and EMI dat. For example, the JPG-IV test, at the False Positive level obtained by NRL, one of our algorithms achieved a 13 percent improvement in True Positive level over the algorithm traditionally used for processing MTADS data.

  11. Detail preserving exposure fusion for a dual sensor camera

    NASA Astrophysics Data System (ADS)

    Chen, Kuo; Chen, Yueting; Feng, Huajun; Xu, Zhihai

    2014-11-01

    Dual sensor cameras are widely used to capture multi-exposure image of high dynamic range scene without ghost effect. The local details and luminance contrast can not be achieved well at the same time by conventional exposure fusion. A novel technique of exposure fusion is proposed to balance the local details and global luminance adaptively for dual sensor camera. Such fusion weight map is calculated by a new down-up-sampling method. And then, a guided filter is employed to refine the weight map and exposure fusion is realized using pixel by pixel approach. Finally, multiple experiments are carried out and six common exposure fusion algorithms are compared to verify the proposed exposure fusion technique. The experimental results show that the proposed method performs excellently and robustly with highest spatial frequency and visual fidelity.

  12. Real-Time Blackboards For Sensor Fusions

    NASA Astrophysics Data System (ADS)

    Johnson, Donald H.; Shaw, Scott W.; Reynolds, Steven; Himayat, Nageen

    1989-09-01

    Multi-sensor fusion, at the most basic level, can be cast into a concise, elegant model. Reality demands, however, that this model be modified and augmented. These modifications often result in software systems that are confusing in function and difficult to debug. This problem can be ameliorated by adopting an object-oriented, data-flow programming style. For real-time applications, this approach simplifies data communications and storage management. The concept of object-oriented, data-flow programming is conveniently embodied in the black-board style of software architecture. Blackboard systems allow diverse programs access to a central data base. When the blackboard is described as an object, it can be distributed over multiple processors for real-time applications. Choosing the appropriate parallel architecture is the subject of ongoing research. A prototype blackboard has been constructed to fuse optical image regions and Doppler radar events. The system maintains tracks of simulated targets in real time. The results of this simulation have been used to direct further research on real-time blackboard systems.

  13. Land mine detection through GPR and EMI sensor fusion

    NASA Astrophysics Data System (ADS)

    Weisenseel, Robert A.; Castanon, David A.; Karl, William C.

    1999-12-01

    In this paper, we develop a system to exploit sensor fusion for detecting and locating plastic A/P mines. We design and test the system using data from Monte Carlo electromagnetic induction spectroscopy (EMIS) and ground penetrating radar (GPR) simulations. We include the effects of both random soil surface variability and sensor noise. In the presence of a rough surface and a heterogeneous, multi-element clutter environment, we obtain good results fusing EMIS and GPR data using a statistical approach. More generally, we demonstrate a framework for simulating and testing sensor configurations and sensor fusion approaches for landmine and unexploded ordinance (UXO) detection systems. Taking advantage of high- fidelity electromagnetic simulation, we develop a controlled environment for testing sensor fusion concepts, from varied sensor arrangements to detection algorithms. In this environment, we can examine the effect of changing mine structure, soil parameters, and sensor geometry on the sensor fusion problem. We can then generalize these results to produce mine detectors robust to real-world variations.

  14. Research on the strategy of underwater united detection fusion and communication using multi-sensor

    NASA Astrophysics Data System (ADS)

    Xu, Zhenhua; Huang, Jianguo; Huang, Hai; Zhang, Qunfei

    2011-09-01

    In order to solve the distributed detection fusion problem of underwater target detection, when the signal to noise ratio (SNR) of the acoustic channel is low, a new strategy for united detection fusion and communication using multiple sensors was proposed. The performance of detection fusion was studied and compared based on the Neyman-Pearson principle when the binary phase shift keying (BPSK) and on-off keying (OOK) modes were used by the local sensors. The comparative simulation and analysis between the optimal likelihood ratio test and the proposed strategy was completed, and both the theoretical analysis and simulation indicate that using the proposed new strategy could improve the detection performance effectively. In theory, the proposed strategy of united detection fusion and communication is of great significance to the establishment of an underwater target detection system.

  15. Multi-Sensor Data Fusion Technique

    NASA Astrophysics Data System (ADS)

    Rodier, S. D.; Hu, Y.; Vaughan, M.; Hlavka, D.; Arnold, T.

    2006-12-01

    We describe a data fusion technique for combining lidar measurements with correlative observations made by passive sensors. Simultaneous measurements obtained by the Cloud Physics Lidar (CPL)1 and the MODIS Airborne Simulator (MAS)2 serve as inputs to a Kohonen self-organizing map (SOM)3 algorithm, which in turn classifies the collocated MAS+CPL pixels according to scene type; i.e., according to the number, the type, and the vertical locations of the cloud and aerosol layers present. Tests conducted using the MAS data alone show that the SOM algorithm recognizes a much greater percentage of the pixels containing high, thin clouds than does the standard MAS cloud mask algorithm. Results obtained when using the combined measurements identify a greater number of distinct classes of data (i.e., scene types) within individual MAS pixels, and thus will allow the selection of more accurate physical models for the retrievals of radiatively significant properties. The wealth of information gained by including the lidar profile in the SOM algorithm clustering study is, however, limited by (to) the instruments nadir only footprint. To fully utilize this information a method for extending or transferring the classification to the full passive swath was developed. We will describe our technique for extending the classifications derived from the nadir track analysis, where we have coincident measurements from both instruments, to the full passive sensor swath, for which we have only MAS measurements. Preliminary validation studies show that we can expect a classification success rate of better than 70 percent when applying this method. The recent CALIPSO-CloudSat validation campaign will provide additional datasets to validate our technique. REFERENCES M. J. McGill, D. L. Hlavka, W. D. Hart, V. S. Scott, J. D. Spinhirne, and B. Schmid, "The cloud physics lidar: Instrument description and initial measurement results", Applied Optics, 41, pp. 3725 3734, 2002. King, M. D., Y. J

  16. Nadaraya-Watson estimator for sensor fusion problems

    SciTech Connect

    Rao, N.S.V.

    1996-10-01

    The classical Nadaraya-Watson estimator is shown to solve a generic sensor fusion problem where the underlying sensor error densities are not known but a sample is available. By employing Haar kernels this estimator is shown to yield finite sample guarantees and also to be efficiently computable. Two simulation examples, and a robotics example involving the detection of a door using arrays of ultrasonic and infrared sensors, are presented to illustrate the performance.

  17. IMM filtering on parametric data for multi-sensor fusion

    NASA Astrophysics Data System (ADS)

    Shafer, Scott; Owen, Mark W.

    2014-06-01

    In tracking, many types of sensor data can be obtained and utilized to distinguish a particular target. Commonly, kinematic information is used for tracking, but this can be combined with identification attributes and parametric information passively collected from the targets emitters. Along with the standard tracking process (predict, associate, score, update, and initiate) that operates in all kinematic trackers, parametric data can also be utilized to perform these steps and provide a means for feature fusion. Feature fusion, utilizing parametrics from multiple sources, yields a rich data set providing many degrees of freedom to separate and correlate data into appropriate tracks. Parametric radar data can take on many dynamics to include: stable, agile, jitter, and others. By utilizing a running sample mean and sample variance a good estimate of radar parametrics is achieved. However, when dynamics are involved, a severe lag can occur and a non-optimal estimate is achieved. This estimate can yield incorrect associations in feature space and cause track fragmentation or miscorrelation. In this paper we investigate the accuracy of the interacting multiple model (IMM) filter at estimating the first and second moments of radar parametrics. The algorithm is assessed by Monte Carlo simulation and compared against a running sample mean/variance technique. We find that the IMM approach yields a better result due to its ability to quickly adapt to dynamical systems with the proper model and tuning.

  18. Physiological Sensor Signals Classification for Healthcare Using Sensor Data Fusion and Case-Based Reasoning

    PubMed Central

    Begum, Shahina; Barua, Shaibal; Ahmed, Mobyen Uddin

    2014-01-01

    Today, clinicians often do diagnosis and classification of diseases based on information collected from several physiological sensor signals. However, sensor signal could easily be vulnerable to uncertain noises or interferences and due to large individual variations sensitivity to different physiological sensors could also vary. Therefore, multiple sensor signal fusion is valuable to provide more robust and reliable decision. This paper demonstrates a physiological sensor signal classification approach using sensor signal fusion and case-based reasoning. The proposed approach has been evaluated to classify Stressed or Relaxed individuals using sensor data fusion. Physiological sensor signals i.e., Heart Rate (HR), Finger Temperature (FT), Respiration Rate (RR), Carbon dioxide (CO2) and Oxygen Saturation (SpO2) are collected during the data collection phase. Here, sensor fusion has been done in two different ways: (i) decision-level fusion using features extracted through traditional approaches; and (ii) data-level fusion using features extracted by means of Multivariate Multiscale Entropy (MMSE). Case-Based Reasoning (CBR) is applied for the classification of the signals. The experimental result shows that the proposed system could classify Stressed or Relaxed individual 87.5% accurately compare to an expert in the domain. So, it shows promising result in the psychophysiological domain and could be possible to adapt this approach to other relevant healthcare systems. PMID:24995374

  19. Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

    NASA Technical Reports Server (NTRS)

    2004-01-01

    Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate

  20. Neural networks for sensor fusion of meteorological measurements

    NASA Astrophysics Data System (ADS)

    Yee, Young P.; Measure, Edward M.; Cogan, James L.; Bleiweis, Max

    2001-03-01

    The collection and management of vast quantities of meteorological data, including satellite-based as well as ground- based measurements, is presenting great challenges in the optimal usage of this information. To address these issues, the Army Laboratory has developed neural networks for combining for combining multi-sensor meteorological data for Army battlefield weather forecasting models. As a demonstration of this data fusion methodology, multi-sensor data was taken from the Meteorological Measurement Set Profiler (MMSP-POC) system and from satellites with orbits coinciding with the geographical locations of interest. The MMS Profiler-POC comprises a suite of remote sensing instrumentation and surface measuring devices. Neural network techniques were used to retrieve temperature and wind information from a combination of polar orbiter and/ or geostationary satellite observations and ground-based measurements. Back-propagation neural networks were constructed which use satellite radiances, simulated microwave radiometer measurements, and other ground-based measurements as inputs and produced temperature and wind profiles as outputs. The network was trained with Rawinsonde measurements used as truth-values. The final outcome will be an integrated, merged temperature/wind profile from the surface up to the upper troposphere.

  1. Sensor Fusion Based Model for Collision Free Mobile Robot Navigation

    PubMed Central

    Almasri, Marwah; Elleithy, Khaled; Alajlan, Abrar

    2015-01-01

    Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot’s wheels, and 24 fuzzy rules for the robot’s movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes. PMID:26712766

  2. Sensor Fusion Based Model for Collision Free Mobile Robot Navigation.

    PubMed

    Almasri, Marwah; Elleithy, Khaled; Alajlan, Abrar

    2015-01-01

    Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot's wheels, and 24 fuzzy rules for the robot's movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes. PMID:26712766

  3. Sensor Fusion Based Model for Collision Free Mobile Robot Navigation.

    PubMed

    Almasri, Marwah; Elleithy, Khaled; Alajlan, Abrar

    2015-12-26

    Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot's wheels, and 24 fuzzy rules for the robot's movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes.

  4. Multivariable optimization of fusion reactor blankets

    SciTech Connect

    Meier, W.R.

    1984-04-01

    The optimization problem consists of four key elements: a figure of merit for the reactor, a technique for estimating the neutronic performance of the blanket as a function of the design variables, constraints on the design variables and neutronic performance, and a method for optimizing the figure of merit subject to the constraints. The first reactor concept investigated uses a liquid lithium blanket for breeding tritium and a steel blanket to increase the fusion energy multiplication factor. The capital cost per unit of net electric power produced is minimized subject to constraints on the tritium breeding ratio and radiation damage rate. The optimal design has a 91-cm-thick lithium blanket denatured to 0.1% /sup 6/Li. The second reactor concept investigated uses a BeO neutron multiplier and a LiAlO/sub 2/ breeding blanket. The total blanket thickness is minimized subject to constraints on the tritium breeding ratio, the total neutron leakage, and the heat generation rate in aluminum support tendons. The optimal design consists of a 4.2-cm-thick BeO multiplier and 42-cm-thick LiAlO/sub 2/ breeding blanket enriched to 34% /sup 6/Li.

  5. Decentralized sensor fusion for Ubiquitous Networking Robotics in Urban Areas.

    PubMed

    Sanfeliu, Alberto; Andrade-Cetto, Juan; Barbosa, Marco; Bowden, Richard; Capitán, Jesús; Corominas, Andreu; Gilbert, Andrew; Illingworth, John; Merino, Luis; Mirats, Josep M; Moreno, Plínio; Ollero, Aníbal; Sequeira, João; Spaan, Matthijs T J

    2010-01-01

    In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted. PMID:22294927

  6. Decentralized Sensor Fusion for Ubiquitous Networking Robotics in Urban Areas

    PubMed Central

    Sanfeliu, Alberto; Andrade-Cetto, Juan; Barbosa, Marco; Bowden, Richard; Capitán, Jesús; Corominas, Andreu; Gilbert, Andrew; Illingworth, John; Merino, Luis; Mirats, Josep M.; Moreno, Plínio; Ollero, Aníbal; Sequeira, João; Spaan, Matthijs T.J.

    2010-01-01

    In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted. PMID:22294927

  7. Decentralized sensor fusion for Ubiquitous Networking Robotics in Urban Areas.

    PubMed

    Sanfeliu, Alberto; Andrade-Cetto, Juan; Barbosa, Marco; Bowden, Richard; Capitán, Jesús; Corominas, Andreu; Gilbert, Andrew; Illingworth, John; Merino, Luis; Mirats, Josep M; Moreno, Plínio; Ollero, Aníbal; Sequeira, João; Spaan, Matthijs T J

    2010-01-01

    In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted.

  8. A hierarchical structure approach to MultiSensor Information Fusion

    SciTech Connect

    Maren, A.J.; Pap, R.M.; Harston, C.T.

    1989-12-31

    A major problem with image-based MultiSensor Information Fusion (MSIF) is establishing the level of processing at which information should be fused. Current methodologies, whether based on fusion at the pixel, segment/feature, or symbolic levels, are each inadequate for robust MSIF. Pixel-level fusion has problems with coregistration of the images or data. Attempts to fuse information using the features of segmented images or data relies an a presumed similarity between the segmentation characteristics of each image or data stream. Symbolic-level fusion requires too much advance processing to be useful, as we have seen in automatic target recognition tasks. Image-based MSIF systems need to operate in real-time, must perform fusion using a variety of sensor types, and should be effective across a wide range of operating conditions or deployment environments. We address this problem through developing a new representation level which facilitates matching and information fusion. The Hierarchical Scene Structure (HSS) representation, created using a multilayer, cooperative/competitive neural network, meets this need. The MSS is intermediate between a pixel-based representation and a scene interpretation representation, and represents the perceptual organization of an image. Fused HSSs will incorporate information from multiple sensors. Their knowledge-rich structure aids top-down scene interpretation via both model matching and knowledge-based,region interpretation.

  9. A hierarchical structure approach to MultiSensor Information Fusion

    SciTech Connect

    Maren, A.J. . Space Inst.); Pap, R.M.; Harston, C.T. )

    1989-01-01

    A major problem with image-based MultiSensor Information Fusion (MSIF) is establishing the level of processing at which information should be fused. Current methodologies, whether based on fusion at the pixel, segment/feature, or symbolic levels, are each inadequate for robust MSIF. Pixel-level fusion has problems with coregistration of the images or data. Attempts to fuse information using the features of segmented images or data relies an a presumed similarity between the segmentation characteristics of each image or data stream. Symbolic-level fusion requires too much advance processing to be useful, as we have seen in automatic target recognition tasks. Image-based MSIF systems need to operate in real-time, must perform fusion using a variety of sensor types, and should be effective across a wide range of operating conditions or deployment environments. We address this problem through developing a new representation level which facilitates matching and information fusion. The Hierarchical Scene Structure (HSS) representation, created using a multilayer, cooperative/competitive neural network, meets this need. The MSS is intermediate between a pixel-based representation and a scene interpretation representation, and represents the perceptual organization of an image. Fused HSSs will incorporate information from multiple sensors. Their knowledge-rich structure aids top-down scene interpretation via both model matching and knowledge-based,region interpretation.

  10. Sensor fusion methods for high performance active vibration isolation systems

    NASA Astrophysics Data System (ADS)

    Collette, C.; Matichard, F.

    2015-04-01

    Sensor noise often limits the performance of active vibration isolation systems. Inertial sensors used in such systems can be selected through a wide variety of instrument noise and size characteristics. However, the most sensitive instruments are often the biggest and the heaviest. Consequently, high-performance active isolators sometimes embed many tens of kilograms in instrumentation. The weight and size of instrumentation can add unwanted constraint on the design. It tends to lower the structures natural frequencies and reduces the collocation between sensors and actuators. Both effects tend to reduce feedback control performance and stability. This paper discusses sensor fusion techniques that can be used in order to increase the control bandwidth (and/or the stability). For this, the low noise inertial instrument signal dominates the fusion at low frequency to provide vibration isolation. Other types of sensors (relative motion, smaller but noisier inertial, or force sensors) are used at higher frequencies to increase stability. Several sensor fusion configurations are studied. The paper shows the improvement that can be expected for several case studies including a rigid equipment, a flexible equipment, and a flexible equipment mounted on a flexible support structure.

  11. A Motion Tracking and Sensor Fusion Module for Medical Simulation.

    PubMed

    Shen, Yunhe; Wu, Fan; Tseng, Kuo-Shih; Ye, Ding; Raymond, John; Konety, Badrinath; Sweet, Robert

    2016-01-01

    Here we introduce a motion tracking or navigation module for medical simulation systems. Our main contribution is a sensor fusion method for proximity or distance sensors integrated with inertial measurement unit (IMU). Since IMU rotation tracking has been widely studied, we focus on the position or trajectory tracking of the instrument moving freely within a given boundary. In our experiments, we have found that this module reliably tracks instrument motion. PMID:27046606

  12. Conflict management based on belief function entropy in sensor fusion.

    PubMed

    Yuan, Kaijuan; Xiao, Fuyuan; Fei, Liguo; Kang, Bingyi; Deng, Yong

    2016-01-01

    Wireless sensor network plays an important role in intelligent navigation. It incorporates a group of sensors to overcome the limitation of single detection system. Dempster-Shafer evidence theory can combine the sensor data of the wireless sensor network by data fusion, which contributes to the improvement of accuracy and reliability of the detection system. However, due to different sources of sensors, there may be conflict among the sensor data under uncertain environment. Thus, this paper proposes a new method combining Deng entropy and evidence distance to address the issue. First, Deng entropy is adopted to measure the uncertain information. Then, evidence distance is applied to measure the conflict degree. The new method can cope with conflict effectually and improve the accuracy and reliability of the detection system. An example is illustrated to show the efficiency of the new method and the result is compared with that of the existing methods. PMID:27330904

  13. STAC: a comprehensive sensor fusion model for scene characterization

    NASA Astrophysics Data System (ADS)

    Kira, Zsolt; Wagner, Alan R.; Kennedy, Chris; Zutty, Jason; Tuell, Grady

    2015-05-01

    We are interested in data fusion strategies for Intelligence, Surveillance, and Reconnaissance (ISR) missions. Advances in theory, algorithms, and computational power have made it possible to extract rich semantic information from a wide variety of sensors, but these advances have raised new challenges in fusing the data. For example, in developing fusion algorithms for moving target identification (MTI) applications, what is the best way to combine image data having different temporal frequencies, and how should we introduce contextual information acquired from monitoring cell phones or from human intelligence? In addressing these questions we have found that existing data fusion models do not readily facilitate comparison of fusion algorithms performing such complex information extraction, so we developed a new model that does. Here, we present the Spatial, Temporal, Algorithm, and Cognition (STAC) model. STAC allows for describing the progression of multi-sensor raw data through increasing levels of abstraction, and provides a way to easily compare fusion strategies. It provides for unambiguous description of how multi-sensor data are combined, the computational algorithms being used, and how scene understanding is ultimately achieved. In this paper, we describe and illustrate the STAC model, and compare it to other existing models.

  14. Multiple image sensor data fusion through artificial neural networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

    With multisensor data fusion technology, the data from multiple sensors are fused in order to make a more accurate estimation of the environment through measurement, processing and analysis. Artificial neural networks are the computational models that mimic biological neural networks. With high per...

  15. Sensor feature fusion for detecting buried objects

    SciTech Connect

    Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.; Hernandez, J.E.; Buhl, M.R.; Schaich, P.C.; Kane, R.J.; Barth, M.J.; DelGrande, N.K.

    1993-04-01

    Given multiple registered images of the earth`s surface from dual-band sensors, our system fuses information from the sensors to reduce the effects of clutter and improve the ability to detect buried or surface target sites. The sensor suite currently includes two sensors (5 micron and 10 micron wavelengths) and one ground penetrating radar (GPR) of the wide-band pulsed synthetic aperture type. We use a supervised teaming pattern recognition approach to detect metal and plastic land mines buried in soil. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in a two step process to classify a subimage. Thee first step, referred to as feature selection, determines the features of sub-images which result in the greatest separability among the classes. The second step, image labeling, uses the selected features and the decisions from a pattern classifier to label the regions in the image which are likely to correspond to buried mines. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the sensors add value to the detection system. The most important features from the various sensors are fused using supervised teaming pattern classifiers (including neural networks). We present results of experiments to detect buried land mines from real data, and evaluate the usefulness of fusing feature information from multiple sensor types, including dual-band infrared and ground penetrating radar. The novelty of the work lies mostly in the combination of the algorithms and their application to the very important and currently unsolved operational problem of detecting buried land mines from an airborne standoff platform.

  16. Context extraction for local fusion for landmine detection with multi-sensor systems

    NASA Astrophysics Data System (ADS)

    Frigui, Hichem; Gader, Paul D.; Ben Abdallah, Ahmed Chamseddine

    2009-05-01

    We present a local method for fusing the results of several landmine detectors using Ground Penetrating Radar (GPR) and Wideband Electro-Magnetic Induction (WEMI) sensors. The detectors considered include Edge Histogram Descriptor (EHD), Hidden Markov Models (HMM), and Spectral Correlation Feature (SCF) for the GPR sensor, and a feature-based classifier for the metal detector. The above detectors use different types of features and different classification methods. Our approach, called Context Extraction for Local Fusion with Feature Discrimination(CELF-FD), is a local approach that adapts the fusion method to different regions of the feature space. It is based on a novel objective function that combines context identification and multi-algorithm fusion criteria into a joint objective function. The context identification component thrives to partition the input feature space into clusters and identify the relevant features within each cluster. The fusion component thrives to learns the optimal fusion parameters within each cluster. Results on large and diverse GPR and WEMI data collections show that the proposed method can identify meaningful and coherent clusters and that these clusters require different fusion parameters. Our initial experiments have also indicated that CELF-FD outperforms the original CELF algorithm and all individual detectors.

  17. Fusion of intraoperative force sensoring, surface reconstruction and biomechanical modeling

    NASA Astrophysics Data System (ADS)

    Röhl, S.; Bodenstedt, S.; Küderle, C.; Suwelack, S.; Kenngott, H.; Müller-Stich, B. P.; Dillmann, R.; Speidel, S.

    2012-02-01

    Minimally invasive surgery is medically complex and can heavily benefit from computer assistance. One way to help the surgeon is to integrate preoperative planning data into the surgical workflow. This information can be represented as a customized preoperative model of the surgical site. To use it intraoperatively, it has to be updated during the intervention due to the constantly changing environment. Hence, intraoperative sensor data has to be acquired and registered with the preoperative model. Haptic information which could complement the visual sensor data is still not established. In addition, biomechanical modeling of the surgical site can help in reflecting the changes which cannot be captured by intraoperative sensors. We present a setting where a force sensor is integrated into a laparoscopic instrument. In a test scenario using a silicone liver phantom, we register the measured forces with a reconstructed surface model from stereo endoscopic images and a finite element model. The endoscope, the instrument and the liver phantom are tracked with a Polaris optical tracking system. By fusing this information, we can transfer the deformation onto the finite element model. The purpose of this setting is to demonstrate the principles needed and the methods developed for intraoperative sensor data fusion. One emphasis lies on the calibration of the force sensor with the instrument and first experiments with soft tissue. We also present our solution and first results concerning the integration of the force sensor as well as accuracy to the fusion of force measurements, surface reconstruction and biomechanical modeling.

  18. Multi-sensor management for data fusion in target tracking

    NASA Astrophysics Data System (ADS)

    Li, Xiaokun; Chen, Genshe; Blasch, Erik; Patrick, Jim; Yang, Chun; Kadar, Ivan

    2009-05-01

    Multi-sensor management for data fusion in target tracking concerns issues of sensor assignment and scheduling by managing or coordinating the use of multiple sensor resources. Since a centralized sensor management technique has a crucial limitation in that the failure of the central node would cause whole system failure, a decentralized sensor management (DSM) scheme is increasingly important in modern multi-sensor systems. DSM is afforded in modern systems through increased bandwidth, wireless communication, and enhanced power. However, protocols for system control are needed to management device access. As game theory offers learning models for distributed allocations of surveillance resources and provides mechanisms to handle the uncertainty of surveillance area, we propose an agent-based negotiable game theoretic approach for decentralized sensor management (ANGADS). With the decentralized sensor management scheme, sensor assignment occurs locally, and there is no central node and thus reduces the risk of whole-system failure. Simulation results for a multi-sensor target-tracking scenario demonstrate the applicability of the proposed approach.

  19. Integration of multiple sensor fusion in controller design.

    PubMed

    Abdelrahman, Mohamed; Kandasamy, Parameshwaran

    2003-04-01

    The main focus of this research is to reduce the risk of a catastrophic response of a feedback control system when some of the feedback data from the system sensors are not reliable, while maintaining a reasonable performance of the control system. In this paper a methodology for integrating multiple sensor fusion into the controller design is presented. The multiple sensor fusion algorithm produces, in addition to the estimate of the measurand, a parameter that measures the confidence in the estimated value. This confidence is integrated as a parameter into the controller to produce fast system response when the confidence in the estimate is high, and a slow response when the confidence in the estimate is low. Conditions for the stability of the system with the developed controller are discussed. This methodology is demonstrated on a cupola furnace model. The simulations illustrate the advantages of the new methodology.

  20. Multi-sensor data fusion framework for CNC machining monitoring

    NASA Astrophysics Data System (ADS)

    Duro, João A.; Padget, Julian A.; Bowen, Chris R.; Kim, H. Alicia; Nassehi, Aydin

    2016-01-01

    Reliable machining monitoring systems are essential for lowering production time and manufacturing costs. Existing expensive monitoring systems focus on prevention/detection of tool malfunctions and provide information for process optimisation by force measurement. An alternative and cost-effective approach is monitoring acoustic emissions (AEs) from machining operations by acting as a robust proxy. The limitations of AEs include high sensitivity to sensor position and cutting parameters. In this paper, a novel multi-sensor data fusion framework is proposed to enable identification of the best sensor locations for monitoring cutting operations, identifying sensors that provide the best signal, and derivation of signals with an enhanced periodic component. Our experimental results reveal that by utilising the framework, and using only three sensors, signal interpretation improves substantially and the monitoring system reliability is enhanced for a wide range of machining parameters. The framework provides a route to overcoming the major limitations of AE based monitoring.

  1. Sensor fusion II: Human and machine strategies; Proceedings of the Meeting, Philadelphia, PA, Nov. 6-9, 1989

    NASA Technical Reports Server (NTRS)

    Schenker, Paul S. (Editor)

    1990-01-01

    Various papers on human and machine strategies in sensor fusion are presented. The general topics addressed include: active vision, measurement and analysis of visual motion, decision models for sensor fusion, implementation of sensor fusion algorithms, applying sensor fusion to image analysis, perceptual modules and their fusion, perceptual organization and object recognition, planning and the integration of high-level knowledge with perception, using prior knowledge and context in sensor fusion.

  2. Sensor Fusion for Nuclear Proliferation Activity Monitoring

    SciTech Connect

    Adel Ghanem, Ph D

    2007-03-30

    The objective of Phase 1 of this STTR project is to demonstrate a Proof-of-Concept (PoC) of the Geo-Rad system that integrates a location-aware SmartTag (made by ZonTrak) and a radiation detector (developed by LLNL). It also includes the ability to transmit the collected radiation data and location information to the ZonTrak server (ZonService). The collected data is further transmitted to a central server at LLNL (the Fusion Server) to be processed in conjunction with overhead imagery to generate location estimates of nuclear proliferation and radiation sources.

  3. A Data Fusion Method in Wireless Sensor Networks

    PubMed Central

    Izadi, Davood; Abawajy, Jemal H.; Ghanavati, Sara; Herawan, Tutut

    2015-01-01

    The success of a Wireless Sensor Network (WSN) deployment strongly depends on the quality of service (QoS) it provides regarding issues such as data accuracy, data aggregation delays and network lifetime maximisation. This is especially challenging in data fusion mechanisms, where a small fraction of low quality data in the fusion input may negatively impact the overall fusion result. In this paper, we present a fuzzy-based data fusion approach for WSN with the aim of increasing the QoS whilst reducing the energy consumption of the sensor network. The proposed approach is able to distinguish and aggregate only true values of the collected data as such, thus reducing the burden of processing the entire data at the base station (BS). It is also able to eliminate redundant data and consequently reduce energy consumption thus increasing the network lifetime. We studied the effectiveness of the proposed data fusion approach experimentally and compared it with two baseline approaches in terms of data collection, number of transferred data packets and energy consumption. The results of the experiments show that the proposed approach achieves better results than the baseline approaches. PMID:25635417

  4. Sensor-fusion-based biometric identity verification

    SciTech Connect

    Carlson, J.J.; Bouchard, A.M.; Osbourn, G.C.; Martinez, R.F.; Bartholomew, J.W.; Jordan, J.B.; Flachs, G.M.; Bao, Z.; Zhu, L.

    1998-02-01

    Future generation automated human biometric identification and verification will require multiple features/sensors together with internal and external information sources to achieve high performance, accuracy, and reliability in uncontrolled environments. The primary objective of the proposed research is to develop a theoretical and practical basis for identifying and verifying people using standoff biometric features that can be obtained with minimal inconvenience during the verification process. The basic problem involves selecting sensors and discovering features that provide sufficient information to reliably verify a person`s identity under the uncertainties caused by measurement errors and tactics of uncooperative subjects. A system was developed for discovering hand, face, ear, and voice features and fusing them to verify the identity of people. The system obtains its robustness and reliability by fusing many coarse and easily measured features into a near minimal probability of error decision algorithm.

  5. Distributed Sensor Fusion for Scalar Field Mapping Using Mobile Sensor Networks.

    PubMed

    La, Hung Manh; Sheng, Weihua

    2013-04-01

    In this paper, autonomous mobile sensor networks are deployed to measure a scalar field and build its map. We develop a novel method for multiple mobile sensor nodes to build this map using noisy sensor measurements. Our method consists of two parts. First, we develop a distributed sensor fusion algorithm by integrating two different distributed consensus filters to achieve cooperative sensing among sensor nodes. This fusion algorithm has two phases. In the first phase, the weighted average consensus filter is developed, which allows each sensor node to find an estimate of the value of the scalar field at each time step. In the second phase, the average consensus filter is used to allow each sensor node to find a confidence of the estimate at each time step. The final estimate of the value of the scalar field is iteratively updated during the movement of the mobile sensors via weighted average. Second, we develop the distributed flocking-control algorithm to drive the mobile sensors to form a network and track the virtual leader moving along the field when only a small subset of the mobile sensors know the information of the leader. Experimental results are provided to demonstrate our proposed algorithms.

  6. Coresident sensor fusion and compression using the wavelet transform

    SciTech Connect

    Yocky, D.A.

    1996-03-11

    Imagery from coresident sensor platforms, such as unmanned aerial vehicles, can be combined using, multiresolution decomposition of the sensor images by means of the two-dimensional wavelet transform. The wavelet approach uses the combination of spatial/spectral information at multiple scales to create a fused image. This can be done in both an ad hoc or model-based approach. We compare results from commercial ``fusion`` software and the ad hoc, wavelet approach. Results show the wavelet approach outperforms the commercial algorithms and also supports efficient compression of the fused image.

  7. Optimization Strategies for Sensor and Actuator Placement

    NASA Technical Reports Server (NTRS)

    Padula, Sharon L.; Kincaid, Rex K.

    1999-01-01

    This paper provides a survey of actuator and sensor placement problems from a wide range of engineering disciplines and a variety of applications. Combinatorial optimization methods are recommended as a means for identifying sets of actuators and sensors that maximize performance. Several sample applications from NASA Langley Research Center, such as active structural acoustic control, are covered in detail. Laboratory and flight tests of these applications indicate that actuator and sensor placement methods are effective and important. Lessons learned in solving these optimization problems can guide future research.

  8. Use of data fusion to optimize contaminant transport predictions

    SciTech Connect

    Eeckhout, E. van

    1997-10-01

    The original data fusion workstation, as envisioned by Coleman Research Corp., was constructed under funding from DOE (EM-50) in the early 1990s. The intent was to demonstrate the viability of fusion and analysis of data from various types of sensors for waste site characterization, but primarily geophysical. This overall concept changed over time and evolved more towards hydrogeological (groundwater) data fusion after some initial geophysical fusion work focused at Coleman. This initial geophysical fusion platform was tested at Hanford and Fernald, and the later hydrogeological fusion work has been demonstrated at Pantex, Savannah River, the US Army Letterkenny Depot, a DoD Massachusetts site and a DoD California site. The hydrogeologic data fusion package has been spun off to a company named Fusion and Control Technology, Inc. This package is called the Hydrological Fusion And Control Tool (Hydro-FACT) and is being sold as a product that links with the software package, MS-VMS (MODFLOW-SURFACT Visual Modeling System), sold by HydroGeoLogic, Inc. MODFLOW is a USGS development, and is in the public domain. Since the government paid for the data fusion development at Coleman, the government and their contractors have access to the data fusion technology in this hydrogeologic package for certain computer platforms, but would probably have to hire FACT (Fusion and Control Technology, Inc.,) and/or HydroGeoLogic for some level of software and services. Further discussion in this report will concentrate on the hydrogeologic fusion module that is being sold as Hydro-FACT, which can be linked with MS-VMS.

  9. Diagnostics and data fusion of robotic sensors

    SciTech Connect

    Dhar, M.; Bardsley, S; Cowper, L.; Hamm, R.; Jammu, V.; Wagner, J.

    1996-12-31

    Robotic systems for remediation of hazardous waste sites must be highly reliable to avoid equipment failures and subsequent possible exposure of personnel to hazardous environments. Safe, efficient cleanup operations also require accurate, complete knowledge of the task space. This paper presents progress made on a 18 month program to meet these needs. To enhance robot reliability, a conceptual design of a monitoring and diagnostic system is being developed to predict the onset of mechanical failure modes, provide maximum lead time to make operational changes or repairs, and minimize the occurrence of on-site breakdowns. To ensure safe operation, a comprehensive software package is being developed that will fuse data from multiple surface mapping sensors and poses so as to reduce the error effects in individual data points and provide accurate 3-D maps of a work space.

  10. Sensor fusion by pseudo information measure: a mobile robot application.

    PubMed

    Asharif, Mohammad Reza; Moshiri, Behzad; HoseinNezhad, Reza

    2002-07-01

    In any autonomous mobile robot, one of the most important issues to be designed and implemented is environment perception. In this paper, a new approach is formulated in order to perform sensory data integration for generation of an occupancy grid map of the environment. This method is an extended version of the Bayesian fusion method for independent sources of information. The performance of the proposed method of fusion and its sensitivity are discussed. Map building simulation for a cylindrical robot with eight ultrasonic sensors and mapping implementation for a Khepera robot have been separately tried in simulation and experimental works. A new neural structure is introduced for conversion of proximity data that are given by Khepera IR sensors to occupancy probabilities. Path planning experiments have also been applied to the resulting maps. For each map, two factors are considered and calculated: the fitness and the augmented occupancy of the map with respect to the ideal map. The length and the least distance to obstacles were the other two factors that were calculated for the routes that are resulted by path planning experiments. Experimental and simulation results show that by using the new fusion formulas, more informative maps of the environment are obtained. By these maps more appropriate routes could be achieved. Actually, there is a tradeoff between the length of the resulting routes and their safety and by choosing the proper fusion function, this tradeoff is suitably tuned for different map building applications.

  11. Sensor fusion by pseudo information measure: a mobile robot application.

    PubMed

    Asharif, Mohammad Reza; Moshiri, Behzad; HoseinNezhad, Reza

    2002-07-01

    In any autonomous mobile robot, one of the most important issues to be designed and implemented is environment perception. In this paper, a new approach is formulated in order to perform sensory data integration for generation of an occupancy grid map of the environment. This method is an extended version of the Bayesian fusion method for independent sources of information. The performance of the proposed method of fusion and its sensitivity are discussed. Map building simulation for a cylindrical robot with eight ultrasonic sensors and mapping implementation for a Khepera robot have been separately tried in simulation and experimental works. A new neural structure is introduced for conversion of proximity data that are given by Khepera IR sensors to occupancy probabilities. Path planning experiments have also been applied to the resulting maps. For each map, two factors are considered and calculated: the fitness and the augmented occupancy of the map with respect to the ideal map. The length and the least distance to obstacles were the other two factors that were calculated for the routes that are resulted by path planning experiments. Experimental and simulation results show that by using the new fusion formulas, more informative maps of the environment are obtained. By these maps more appropriate routes could be achieved. Actually, there is a tradeoff between the length of the resulting routes and their safety and by choosing the proper fusion function, this tradeoff is suitably tuned for different map building applications. PMID:12160343

  12. Spectral photoplethysmographic imaging sensor fusion for enhanced heart rate detection

    NASA Astrophysics Data System (ADS)

    Amelard, Robert; Clausi, David A.; Wong, Alexander

    2016-03-01

    Continuous heart rate monitoring can provide important context for quantitative clinical assessment in scenarios such as long-term health monitoring and disability prevention. Photoplethysmographic imaging (PPGI) systems are particularly useful for such monitoring scenarios as contact-based devices pose problems related to comfort and mobility. Each pixel can be regarded as a virtual PPG sensor, thus enabling simultaneous measurements of multiple skin sites. Existing PPGI systems analyze temporal PPGI sensor uctuations related to hemodynamic pulsations across a region of interest to extract the blood pulse signal. However, due to spatially varying optical properties of the skin, the blood pulse signal may not be consistent across all PPGI sensors, leading to inaccurate heart rate monitoring. To increase the hemodynamic signal-to-noise ratio (SNR), we propose a novel spectral PPGI sensor fusion method for enhanced estimation of the true blood pulse signal. Motivated by the observation that PPGI sensors with high hemodynamic SNR exhibit a spectral energy peak at the heart rate frequency, an entropy-based fusion model was formulated to combine PPGI sensors based on the sensors' spectral energy distribution. The optical PPGI device comprised a near infrared (NIR) sensitive camera and an 850 nm LED. Spatially uniform irradiance was achieved by placing optical elements along the LED beam, providing consistent illumination across the skin area. Dual-mode temporally coded illumination was used to negate the temporal effect of ambient illumination. Experimental results show that the spectrally weighted PPGI method can accurately and consistently extract heart rate information where traditional region-based averaging fails.

  13. A Survey on Optimal Signal Processing Techniques Applied to Improve the Performance of Mechanical Sensors in Automotive Applications

    PubMed Central

    Hernandez, Wilmar

    2007-01-01

    In this paper a survey on recent applications of optimal signal processing techniques to improve the performance of mechanical sensors is made. Here, a comparison between classical filters and optimal filters for automotive sensors is made, and the current state of the art of the application of robust and optimal control and signal processing techniques to the design of the intelligent (or smart) sensors that today's cars need is presented through several experimental results that show that the fusion of intelligent sensors and optimal signal processing techniques is the clear way to go. However, the switch between the traditional methods of designing automotive sensors and the new ones cannot be done overnight because there are some open research issues that have to be solved. This paper draws attention to one of the open research issues and tries to arouse researcher's interest in the fusion of intelligent sensors and optimal signal processing techniques.

  14. Energy optimization in mobile sensor networks

    NASA Astrophysics Data System (ADS)

    Yu, Shengwei

    Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while

  15. Inertial Sensor Error Reduction through Calibration and Sensor Fusion.

    PubMed

    Lambrecht, Stefan; Nogueira, Samuel L; Bortole, Magdo; Siqueira, Adriano A G; Terra, Marco H; Rocon, Eduardo; Pons, José L

    2016-01-01

    This paper presents the comparison between cooperative and local Kalman Filters (KF) for estimating the absolute segment angle, under two calibration conditions. A simplified calibration, that can be replicated in most laboratories; and a complex calibration, similar to that applied by commercial vendors. The cooperative filters use information from either all inertial sensors attached to the body, Matricial KF; or use information from the inertial sensors and the potentiometers of an exoskeleton, Markovian KF. A one minute walking trial of a subject walking with a 6-DoF exoskeleton was used to assess the absolute segment angle of the trunk, thigh, shank, and foot. The results indicate that regardless of the segment and filter applied, the more complex calibration always results in a significantly better performance compared to the simplified calibration. The interaction between filter and calibration suggests that when the quality of the calibration is unknown the Markovian KF is recommended. Applying the complex calibration, the Matricial and Markovian KF perform similarly, with average RMSE below 1.22 degrees. Cooperative KFs perform better or at least equally good as Local KF, we therefore recommend to use cooperative KFs instead of local KFs for control or analysis of walking. PMID:26901198

  16. Inertial Sensor Error Reduction through Calibration and Sensor Fusion

    PubMed Central

    Lambrecht, Stefan; Nogueira, Samuel L.; Bortole, Magdo; Siqueira, Adriano A. G.; Terra, Marco H.; Rocon, Eduardo; Pons, José L.

    2016-01-01

    This paper presents the comparison between cooperative and local Kalman Filters (KF) for estimating the absolute segment angle, under two calibration conditions. A simplified calibration, that can be replicated in most laboratories; and a complex calibration, similar to that applied by commercial vendors. The cooperative filters use information from either all inertial sensors attached to the body, Matricial KF; or use information from the inertial sensors and the potentiometers of an exoskeleton, Markovian KF. A one minute walking trial of a subject walking with a 6-DoF exoskeleton was used to assess the absolute segment angle of the trunk, thigh, shank, and foot. The results indicate that regardless of the segment and filter applied, the more complex calibration always results in a significantly better performance compared to the simplified calibration. The interaction between filter and calibration suggests that when the quality of the calibration is unknown the Markovian KF is recommended. Applying the complex calibration, the Matricial and Markovian KF perform similarly, with average RMSE below 1.22 degrees. Cooperative KFs perform better or at least equally good as Local KF, we therefore recommend to use cooperative KFs instead of local KFs for control or analysis of walking. PMID:26901198

  17. Neural network fusion and inversion model for NDIR sensor measurement

    NASA Astrophysics Data System (ADS)

    Cieszczyk, Sławomir; Komada, Paweł

    2015-12-01

    This article presents the problem of the impact of environmental disturbances on the determination of information from measurements. As an example, NDIR sensor is studied, which can measure industrial or environmental gases of varying temperature. The issue of changes of influence quantities value appears in many industrial measurements. Developing of appropriate algorithms resistant to conditions changes is key problem. In the resulting mathematical model of inverse problem additional input variables appears. Due to the difficulties in the mathematical description of inverse model neural networks have been applied. They do not require initial assumptions about the structure of the created model. They provide correction of sensor non-linearity as well as correction of influence of interfering quantity. The analyzed issue requires additional measurement of disturbing quantity and its connection with measurement of primary quantity. Combining this information with the use of neural networks belongs to the class of sensor fusion algorithm.

  18. Sensor fusion using neural network in the robotic welding

    SciTech Connect

    Ohshima, Kenji; Yabe, Masaaki; Akita, Kazuya; Kugai, Katsuya; Yamane, Satoshi; Kubota, Takefumi

    1995-12-31

    It is important to realize intelligent welding robots to obtain a good quality of the welding results. For this purpose, it is required to detect the torch height, the torch attitude, the deviation from the center of the gap. In order to simultaneously detect those, the authors propose the sensor fusion by using the neural network, i.e., the information concerning the welding torch is detected by using both the welding current and the welding voltage. First, the authors deal with the welding phenomena as the melting phenomena in the electrode wire of the MIG welding and the CO{sub 2} short circuiting welding. Next, the training data of the neutral networks are made from the numerical simulations. The neuro arc sensor is trained so as to get the desired performance of the sensor. By using it, the seam tracking is carried out in the T-joint.

  19. Multi-Sensor Fusion of Landsat 8 Thermal Infrared (TIR) and Panchromatic (PAN) Images

    PubMed Central

    Jung, Hyung-Sup; Park, Sung-Whan

    2014-01-01

    Data fusion is defined as the combination of data from multiple sensors such that the resulting information is better than would be possible when the sensors are used individually. The multi-sensor fusion of panchromatic (PAN) and thermal infrared (TIR) images is a good example of this data fusion. While a PAN image has higher spatial resolution, a TIR one has lower spatial resolution. In this study, we have proposed an efficient method to fuse Landsat 8 PAN and TIR images using an optimal scaling factor in order to control the trade-off between the spatial details and the thermal information. We have compared the fused images created from different scaling factors and then tested the performance of the proposed method at urban and rural test areas. The test results show that the proposed method merges the spatial resolution of PAN image and the temperature information of TIR image efficiently. The proposed method may be applied to detect lava flows of volcanic activity, radioactive exposure of nuclear power plants, and surface temperature change with respect to land-use change. PMID:25529207

  20. Discrete Kalman Filter based Sensor Fusion for Robust Accessibility Interfaces

    NASA Astrophysics Data System (ADS)

    Ghersi, I.; Mariño, M.; Miralles, M. T.

    2016-04-01

    Human-machine interfaces have evolved, benefiting from the growing access to devices with superior, embedded signal-processing capabilities, as well as through new sensors that allow the estimation of movements and gestures, resulting in increasingly intuitive interfaces. In this context, sensor fusion for the estimation of the spatial orientation of body segments allows to achieve more robust solutions, overcoming specific disadvantages derived from the use of isolated sensors, such as the sensitivity of magnetic-field sensors to external influences, when used in uncontrolled environments. In this work, a method for the combination of image-processing data and angular-velocity registers from a 3D MEMS gyroscope, through a Discrete-time Kalman Filter, is proposed and deployed as an alternate user interface for mobile devices, in which an on-screen pointer is controlled with head movements. Results concerning general performance of the method are presented, as well as a comparative analysis, under a dedicated test application, with results from a previous version of this system, in which the relative-orientation information was acquired directly from MEMS sensors (3D magnetometer-accelerometer). These results show an improved response for this new version of the pointer, both in terms of precision and response time, while keeping many of the benefits that were highlighted for its predecessor, giving place to a complementary method for signal acquisition that can be used as an alternative-input device, as well as for accessibility solutions.

  1. Optimal sensor placement in structural health monitoring using discrete optimization

    NASA Astrophysics Data System (ADS)

    Sun, Hao; Büyüköztürk, Oral

    2015-12-01

    The objective of optimal sensor placement (OSP) is to obtain a sensor layout that gives as much information of the dynamic system as possible in structural health monitoring (SHM). The process of OSP can be formulated as a discrete minimization (or maximization) problem with the sensor locations as the design variables, conditional on the constraint of a given sensor number. In this paper, we propose a discrete optimization scheme based on the artificial bee colony algorithm to solve the OSP problem after first transforming it into an integer optimization problem. A modal assurance criterion-oriented objective function is investigated to measure the utility of a sensor configuration in the optimization process based on the modal characteristics of a reduced order model. The reduced order model is obtained using an iterated improved reduced system technique. The constraint is handled by a penalty term added to the objective function. Three examples, including a 27 bar truss bridge, a 21-storey building at the MIT campus and the 610 m high Canton Tower, are investigated to test the applicability of the proposed algorithm to OSP. In addition, the proposed OSP algorithm is experimentally validated on a physical laboratory structure which is a three-story two-bay steel frame instrumented with triaxial accelerometers. Results indicate that the proposed method is efficient and can be potentially used in OSP in practical SHM.

  2. Distributed fusion and automated sensor tasking in ISR systems

    NASA Astrophysics Data System (ADS)

    Preden, Jurgo; Pahtma, Raido; Astapov, Sergei; Ehala, Johannes; Riid, Andri; Motus, Leo

    2014-06-01

    Modern Intelligence, Surveillance and Reconnaissance (ISR) systems are increasingly being assembled from autonomous systems, so the resulting ISR system is a System of Systems (SoS). In order to take full advantage of the capabilities of the ISR SoS, the architecture and the design of these SoS should be able to facilitate the benefits inherent in a SoS approach - high resilience, higher level of adaptability and higher diversity, enabling on-demand system composition. The tasks performed by ISR SoS can well go beyond basic data acquisition, conditioning and communication as data processing can be easily integrated in the SoS. Such an ISR SoS can perform data fusion, classification and tracking (and conditional sensor tasking for additional data acquisition), these are extremely challenging tasks in this context, especially if the fusion is performed in a distributed manner. Our premise for the ISR SoS design and deployment is that the system is not designed as a complete system, where the capabilities of individual data providers are considered and the interaction paths, including communication channel capabilities, are specified at design time. Instead, we assume a loosely coupled SoS, where the data needs for a specific fusion task are described at a high level at design time and data providers (i.e., sensor systems) required for a specific fusion task are discovered dynamically at run time, the selection criteria for the data providers being the type and properties of data that can be provided by the specific data provider. The paper describes some of the aspects of a distributed ISR SoS design and implementation, bringing examples on both architectural design as well as on algorithm implementations.

  3. Fusion of radar and optical sensors for space robotic vision

    NASA Technical Reports Server (NTRS)

    Shaw, Scott W.; Defigueiredo, Rui J. P.; Krishen, Kumar

    1988-01-01

    Returned radar power estimates are used in an iterative procedure which generates successive approximations to the target shape in order to determine the shape of a 3-D surface. A simulation is shown which involves the reconstruction of an edge of a flat plate. Although this is a somewhat artificial example, it addresses the real problem of recovering edges of space objects lost in shadow or against a dark background. The results indicate that a microwave/optical sensor fusion system is possible, given sufficient computing power and accurate radar cross section measuring systems.

  4. Distributed data fusion across multiple hard and soft mobile sensor platforms

    NASA Astrophysics Data System (ADS)

    Sinsley, Gregory

    One of the biggest challenges currently facing the robotics field is sensor data fusion. Unmanned robots carry many sophisticated sensors including visual and infrared cameras, radar, laser range finders, chemical sensors, accelerometers, gyros, and global positioning systems. By effectively fusing the data from these sensors, a robot would be able to form a coherent view of its world that could then be used to facilitate both autonomous and intelligent operation. Another distinct fusion problem is that of fusing data from teammates with data from onboard sensors. If an entire team of vehicles has the same worldview they will be able to cooperate much more effectively. Sharing worldviews is made even more difficult if the teammates have different sensor types. The final fusion challenge the robotics field faces is that of fusing data gathered by robots with data gathered by human teammates (soft sensors). Humans sense the world completely differently from robots, which makes this problem particularly difficult. The advantage of fusing data from humans is that it makes more information available to the entire team, thus helping each agent to make the best possible decisions. This thesis presents a system for fusing data from multiple unmanned aerial vehicles, unmanned ground vehicles, and human observers. The first issue this thesis addresses is that of centralized data fusion. This is a foundational data fusion issue, which has been very well studied. Important issues in centralized fusion include data association, classification, tracking, and robotics problems. Because these problems are so well studied, this thesis does not make any major contributions in this area, but does review it for completeness. The chapter on centralized fusion concludes with an example unmanned aerial vehicle surveillance problem that demonstrates many of the traditional fusion methods. The second problem this thesis addresses is that of distributed data fusion. Distributed data fusion

  5. Convolutional neural network based sensor fusion for forward looking ground penetrating radar

    NASA Astrophysics Data System (ADS)

    Sakaguchi, Rayn; Crosskey, Miles; Chen, David; Walenz, Brett; Morton, Kenneth

    2016-05-01

    Forward looking ground penetrating radar (FLGPR) is an alternative buried threat sensing technology designed to offer additional standoff compared to downward looking GPR systems. Due to additional flexibility in antenna configurations, FLGPR systems can accommodate multiple sensor modalities on the same platform that can provide complimentary information. The different sensor modalities present challenges in both developing informative feature extraction methods, and fusing sensor information in order to obtain the best discrimination performance. This work uses convolutional neural networks in order to jointly learn features across two sensor modalities and fuse the information in order to distinguish between target and non-target regions. This joint optimization is possible by modifying the traditional image-based convolutional neural network configuration to extract data from multiple sources. The filters generated by this process create a learned feature extraction method that is optimized to provide the best discrimination performance when fused. This paper presents the results of applying convolutional neural networks and compares these results to the use of fusion performed with a linear classifier. This paper also compares performance between convolutional neural networks architectures to show the benefit of fusing the sensor information in different ways.

  6. Hand-writing motion tracking with vision-inertial sensor fusion: calibration and error correction.

    PubMed

    Zhou, Shengli; Fei, Fei; Zhang, Guanglie; Liu, Yunhui; Li, Wen J

    2014-08-25

    The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model.

  7. Sensor data fusion of optical and active radar data

    NASA Astrophysics Data System (ADS)

    Schultz, Johan; Gustafsson, Ulf; Crona, Torbjorn

    2004-08-01

    In this paper two different methods for fusing data from optical and active radar sensors are studied. The first method fuses data prior to feature extraction and the second method fuses data, in a more traditional way, after feature extraction. The advantage of fusing before feature extraction is that no information is lost prior to the fusion. The sensor data share one common dimension, namely azimuth, but the radar suffers from lower resolution. The algorithms are tested on real measurements from Ku- and millimeter wave radar combined with infrared or TV-camera. The study is in its initial phase and the two methods studied are simple in nature. The study aims to reveal differences between a raw data method and a feature-based method and should later result in a more complex and robust method.

  8. Information fusion based optimal control for large civil aircraft system.

    PubMed

    Zhen, Ziyang; Jiang, Ju; Wang, Xinhua; Gao, Chen

    2015-03-01

    Wind disturbance has a great influence on landing security of Large Civil Aircraft. Through simulation research and engineering experience, it can be found that PID control is not good enough to solve the problem of restraining the wind disturbance. This paper focuses on anti-wind attitude control for Large Civil Aircraft in landing phase. In order to improve the riding comfort and the flight security, an information fusion based optimal control strategy is presented to restrain the wind in landing phase for maintaining attitudes and airspeed. Data of Boeing707 is used to establish a nonlinear mode with total variables of Large Civil Aircraft, and then two linear models are obtained which are divided into longitudinal and lateral equations. Based on engineering experience, the longitudinal channel adopts PID control and C inner control to keep longitudinal attitude constant, and applies autothrottle system for keeping airspeed constant, while an information fusion based optimal regulator in the lateral control channel is designed to achieve lateral attitude holding. According to information fusion estimation, by fusing hard constraint information of system dynamic equations and the soft constraint information of performance index function, optimal estimation of the control sequence is derived. Based on this, an information fusion state regulator is deduced for discrete time linear system with disturbance. The simulation results of nonlinear model of aircraft indicate that the information fusion optimal control is better than traditional PID control, LQR control and LQR control with integral action, in anti-wind disturbance performance in the landing phase.

  9. Sensor fusion for the detection of land mines

    NASA Astrophysics Data System (ADS)

    Fritzsche, Martin; Loehlein, Otto

    1999-10-01

    The detection of buried anti-personnel mines (APMs) is widely considered as a problem which may only be solved with a combination of two or more complementary sensors. We present processing and fusion results obtained from a multisensor data set, acquired with a pulse induction metal detector (MD), a pulsed ultra wide band ground penetrating radar (GPR) and a 3 - 5 (mu) thermal IR camera. Metal detector and GPR sensors were mounted on a rig for optimum control. Various types of soils, clutter objects and burial conditions were recorded. Anti personnel mines included minimum metal mines as well as mines with a significant metal content. We use a special projection to map a 3D GPR data cube, with time or depth as vertical coordinate, into a horizontal plane view 2D image. Object contours are then derived, based on an edge extraction method, followed by an automatic detection of circular shapes with a Hough-transform. In the association step, the stand-off IR image, the metal detector and GPR images and related detections are mapped onto a common cartesian grid on the ground surface. Detection results are fused on a decision level, using a Bayesian approach. Our results indicate that the GPR performance approximately matches that of the metal detector. With both sensors all metallic mines and around 60% of the minimum metal mines were detected. In the case of two false alarms per square meter combined detection probability clearly exceeds single sensor performance and reaches around 80%. Our fusion demonstrator, which incorporates all elements of the processing chain, has been implemented on the basis of MATLABTM.

  10. Sensor fusion methodology for remote detection of buried land mines

    SciTech Connect

    Del Grande, N.

    1990-04-01

    We are investigation a sensor fusion methodology for remote detection of buried land mines. Our primary approach is sensor intrafusion. Our dual-channel passive IR methodology decouples true (corrected) surface temperature variations of 0.2{degree}C from spatially dependent surface emissivity noise. It produces surface temperature maps showing patterns of conducted heat from buried objects which heat and cool differently from their surroundings. Our methodology exploits Planck's radiation law. It produces separate maps of surface emissivity variations which allow us to reduce false alarms. Our secondary approach is sensor interfusion using other methodologies. For example, an active IR CO{sub 2} laser reflectance channel helps distinguish surface targets unrelated to buried land mines at night when photographic methods are ineffective. Also, the interfusion of ground penetrating radar provides depth information for confirming the site of buried objects. Together with EG G in Las Vegas, we flew a mission at Nellis AFB using the Daedalus dual-channel (5 and 10 micron) IR scanner mounted on a helicopter platform at an elevation of 60 m above the desert sand. We detected surface temperature patterns associated with buried (inert) land mines covered by as much as 10 cm of dry sand. The respective spatial, spectral, thermal, emissivity and temporal signatures associated with buried targets differed from those associated with surface vegetation, rocks and manmade objects. Our results were consistent with predictions based on the annual Temperature Wave Model.They were confirmed by field measurements. The dual-channel sensor fusion methodology is expected to enhance the capabilities of the military and industrial community for standoff mine detection. Other important potential applications are open skies, drug traffic control and environmental restoration at waste burial sites. 11 figs.

  11. Optimizing Retransmission Threshold in Wireless Sensor Networks.

    PubMed

    Bi, Ran; Li, Yingshu; Tan, Guozhen; Sun, Liang

    2016-01-01

    The retransmission threshold in wireless sensor networks is critical to the latency of data delivery in the networks. However, existing works on data transmission in sensor networks did not consider the optimization of the retransmission threshold, and they simply set the same retransmission threshold for all sensor nodes in advance. The method did not take link quality and delay requirement into account, which decreases the probability of a packet passing its delivery path within a given deadline. This paper investigates the problem of finding optimal retransmission thresholds for relay nodes along a delivery path in a sensor network. The object of optimizing retransmission thresholds is to maximize the summation of the probability of the packet being successfully delivered to the next relay node or destination node in time. A dynamic programming-based distributed algorithm for finding optimal retransmission thresholds for relay nodes along a delivery path in the sensor network is proposed. The time complexity is O n Δ · max 1 ≤ i ≤ n { u i } , where u i is the given upper bound of the retransmission threshold of sensor node i in a given delivery path, n is the length of the delivery path and Δ is the given upper bound of the transmission delay of the delivery path. If Δ is greater than the polynomial, to reduce the time complexity, a linear programming-based ( 1 + p m i n ) -approximation algorithm is proposed. Furthermore, when the ranges of the upper and lower bounds of retransmission thresholds are big enough, a Lagrange multiplier-based distributed O ( 1 ) -approximation algorithm with time complexity O ( 1 ) is proposed. Experimental results show that the proposed algorithms have better performance. PMID:27171092

  12. Optimizing Retransmission Threshold in Wireless Sensor Networks

    PubMed Central

    Bi, Ran; Li, Yingshu; Tan, Guozhen; Sun, Liang

    2016-01-01

    The retransmission threshold in wireless sensor networks is critical to the latency of data delivery in the networks. However, existing works on data transmission in sensor networks did not consider the optimization of the retransmission threshold, and they simply set the same retransmission threshold for all sensor nodes in advance. The method did not take link quality and delay requirement into account, which decreases the probability of a packet passing its delivery path within a given deadline. This paper investigates the problem of finding optimal retransmission thresholds for relay nodes along a delivery path in a sensor network. The object of optimizing retransmission thresholds is to maximize the summation of the probability of the packet being successfully delivered to the next relay node or destination node in time. A dynamic programming-based distributed algorithm for finding optimal retransmission thresholds for relay nodes along a delivery path in the sensor network is proposed. The time complexity is OnΔ·max1≤i≤n{ui}, where ui is the given upper bound of the retransmission threshold of sensor node i in a given delivery path, n is the length of the delivery path and Δ is the given upper bound of the transmission delay of the delivery path. If Δ is greater than the polynomial, to reduce the time complexity, a linear programming-based (1+pmin)-approximation algorithm is proposed. Furthermore, when the ranges of the upper and lower bounds of retransmission thresholds are big enough, a Lagrange multiplier-based distributed O(1)-approximation algorithm with time complexity O(1) is proposed. Experimental results show that the proposed algorithms have better performance. PMID:27171092

  13. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    PubMed Central

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-01-01

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  14. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection.

    PubMed

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-01-01

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  15. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection.

    PubMed

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-07-19

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  16. Multi-sensor fusion techniques for state estimation of micro air vehicles

    NASA Astrophysics Data System (ADS)

    Donavanik, Daniel; Hardt-Stremayr, Alexander; Gremillion, Gregory; Weiss, Stephan; Nothwang, William

    2016-05-01

    Aggressive flight of micro air vehicles (MAVs) in unstructured, GPS-denied environments poses unique challenges for estimation of vehicle pose and velocity due to the noise, delay, and drift in individual sensor measurements. Maneuvering flight at speeds in excess of 5 m/s poses additional challenges even for active range sensors; in the case of LIDAR, an assembled scan of the vehicles environment will in most cases be obsolete by the time it is processed. Multi-sensor fusion techniques which combine inertial measurements with passive vision techniques and/or LIDAR have achieved breakthroughs in the ability to maintain accurate state estimates without the use of external positioning sensors. In this paper, we survey algorithmic approaches to exploiting sensors with a wide range of nonlinear dynamics using filter and bundle-adjustment based approaches for state estimation and optimal control. From this foundation, we propose a biologically-inspired framework for incorporating the human operator in the loop as a privileged sensor in a combined human/autonomy paradigm.

  17. Context-Aided Sensor Fusion for Enhanced Urban Navigation

    PubMed Central

    Martí, Enrique David; Martín, David; García, Jesús; de la Escalera, Arturo; Molina, José Manuel; Armingol, José María

    2012-01-01

    The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments. PMID:23223080

  18. Context-aided sensor fusion for enhanced urban navigation.

    PubMed

    Martí, Enrique David; Martín, David; García, Jesús; de la Escalera, Arturo; Molina, José Manuel; Armingol, José María

    2012-01-01

     The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments.

  19. The optimal algorithm for Multi-source RS image fusion.

    PubMed

    Fu, Wei; Huang, Shui-Guang; Li, Zeng-Shun; Shen, Hao; Li, Jun-Shuai; Wang, Peng-Yuan

    2016-01-01

    In order to solve the issue which the fusion rules cannot be self-adaptively adjusted by using available fusion methods according to the subsequent processing requirements of Remote Sensing (RS) image, this paper puts forward GSDA (genetic-iterative self-organizing data analysis algorithm) by integrating the merit of genetic arithmetic together with the advantage of iterative self-organizing data analysis algorithm for multi-source RS image fusion. The proposed algorithm considers the wavelet transform of the translation invariance as the model operator, also regards the contrast pyramid conversion as the observed operator. The algorithm then designs the objective function by taking use of the weighted sum of evaluation indices, and optimizes the objective function by employing GSDA so as to get a higher resolution of RS image. As discussed above, the bullet points of the text are summarized as follows.•The contribution proposes the iterative self-organizing data analysis algorithm for multi-source RS image fusion.•This article presents GSDA algorithm for the self-adaptively adjustment of the fusion rules.•This text comes up with the model operator and the observed operator as the fusion scheme of RS image based on GSDA. The proposed algorithm opens up a novel algorithmic pathway for multi-source RS image fusion by means of GSDA. PMID:27408827

  20. The optimal algorithm for Multi-source RS image fusion.

    PubMed

    Fu, Wei; Huang, Shui-Guang; Li, Zeng-Shun; Shen, Hao; Li, Jun-Shuai; Wang, Peng-Yuan

    2016-01-01

    In order to solve the issue which the fusion rules cannot be self-adaptively adjusted by using available fusion methods according to the subsequent processing requirements of Remote Sensing (RS) image, this paper puts forward GSDA (genetic-iterative self-organizing data analysis algorithm) by integrating the merit of genetic arithmetic together with the advantage of iterative self-organizing data analysis algorithm for multi-source RS image fusion. The proposed algorithm considers the wavelet transform of the translation invariance as the model operator, also regards the contrast pyramid conversion as the observed operator. The algorithm then designs the objective function by taking use of the weighted sum of evaluation indices, and optimizes the objective function by employing GSDA so as to get a higher resolution of RS image. As discussed above, the bullet points of the text are summarized as follows.•The contribution proposes the iterative self-organizing data analysis algorithm for multi-source RS image fusion.•This article presents GSDA algorithm for the self-adaptively adjustment of the fusion rules.•This text comes up with the model operator and the observed operator as the fusion scheme of RS image based on GSDA. The proposed algorithm opens up a novel algorithmic pathway for multi-source RS image fusion by means of GSDA.

  1. Optimal Sensor Selection for Health Monitoring Systems

    NASA Technical Reports Server (NTRS)

    Santi, L. Michael; Sowers, T. Shane; Aguilar, Robert B.

    2005-01-01

    Sensor data are the basis for performance and health assessment of most complex systems. Careful selection and implementation of sensors is critical to enable high fidelity system health assessment. A model-based procedure that systematically selects an optimal sensor suite for overall health assessment of a designated host system is described. This procedure, termed the Systematic Sensor Selection Strategy (S4), was developed at NASA John H. Glenn Research Center in order to enhance design phase planning and preparations for in-space propulsion health management systems (HMS). Information and capabilities required to utilize the S4 approach in support of design phase development of robust health diagnostics are outlined. A merit metric that quantifies diagnostic performance and overall risk reduction potential of individual sensor suites is introduced. The conceptual foundation for this merit metric is presented and the algorithmic organization of the S4 optimization process is described. Representative results from S4 analyses of a boost stage rocket engine previously under development as part of NASA's Next Generation Launch Technology (NGLT) program are presented.

  2. Optimal topologies for wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Tillett, Jason C.; Yang, Shanchieh J.; Rao, Raghuveer M.; Sahin, Ferat

    2004-11-01

    Since untethered sensor nodes operate on battery, and because they must communicate through a multi-hop network, it is vital to optimally configure the transmit power of the nodes both to conserve power and optimize spatial reuse of a shared channel. Current topology control algorithms try to minimize radio power while ensuring connectivity of the network. We propose that another important metric for a sensor network topology will involve consideration of hidden nodes and asymmetric links. Minimizing the number of hidden nodes and asymmetric links at the expense of increasing the transmit power of a subset of the nodes may in fact increase the longevity of the sensor network. In this paper we explore a distributed evolutionary approach to optimizing this new metric. Inspiration from the Particle Swarm Optimization technique motivates a distributed version of the algorithm. We generate topologies with fewer hidden nodes and asymmetric links than a comparable algorithm and present some results that indicate that our topologies deliver more data and last longer.

  3. An Approach to Optimize the Fusion Coefficients for Land Cover Information Enhancement with Multisensor Data

    NASA Astrophysics Data System (ADS)

    Garg, Akanksha; Brodu, Nicolas; Yahia, Hussein; Singh, Dharmendra

    2016-04-01

    This paper explores a novel data fusion method with the application of Machine Learning approach for optimal weighted fusion of multisensor data. It will help to get the maximum information of any land cover. Considerable amount of research work has been carried out on multisensor data fusion but getting an optimal fusion for enhancement of land cover information using random weights is still ambiguous. Therefore, there is a need of such land cover monitoring system which can provide the maximum information of the land cover, generally which is not possible with the help of single sensor data. There is a necessity to develop such techniques by which information of multisensor data can be utilized optimally. Machine learning is one of the best way to optimize this type of information. So, in this paper, the weights of each sensor data have been critically analyzed which is required for the fusion, and observed that weights are quite sensitive in fusion. Therefore, different combinations of weights have been tested exhaustively in the direction to develop a relationship between weights and classification accuracy of the fused data. This relationship can be optimized through machine learning techniques like SVM (Support Vector Machine). In the present study, this experiment has been carried out for PALSAR (Phased Array L-Band Synthetic Aperture RADAR) and MODIS (Moderate Resolution Imaging Spectroradiometer) data. PALSAR is a fully polarimetric data with HH, HV and VV polarizations at good spatial resolution (25m), and NDVI (Normalized Difference Vegetation Index) is a good indicator of vegetation, utilizing different bands (Red and NIR) of freely available MODIS data at 250m resolution. First of all, resolution of NDVI has been enhanced from 250m to 25m (10 times) using modified DWT (Modified Discrete Wavelet Transform) to bring it on the same scale as that of PALSAR. Now, different polarized PALSAR data (HH, HV, VV) have been fused with resolution enhanced NDVI

  4. Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

    NASA Technical Reports Server (NTRS)

    Schenker, Paul S. (Editor)

    1991-01-01

    The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

  5. Fusion of magnetometer and gradiometer sensors of MEG in the presence of multiplicative error.

    PubMed

    Mohseni, Hamid R; Woolrich, Mark W; Kringelbach, Morten L; Luckhoo, Henry; Smith, Penny Probert; Aziz, Tipu Z

    2012-07-01

    Novel neuroimaging techniques have provided unprecedented information on the structure and function of the living human brain. Multimodal fusion of data from different sensors promises to radically improve this understanding, yet optimal methods have not been developed. Here, we demonstrate a novel method for combining multichannel signals. We show how this method can be used to fuse signals from the magnetometer and gradiometer sensors used in magnetoencephalography (MEG), and through extensive experiments using simulation, head phantom and real MEG data, show that it is both robust and accurate. This new approach works by assuming that the lead fields have multiplicative error. The criterion to estimate the error is given within a spatial filter framework such that the estimated power is minimized in the worst case scenario. The method is compared to, and found better than, existing approaches. The closed-form solution and the conditions under which the multiplicative error can be optimally estimated are provided. This novel approach can also be employed for multimodal fusion of other multichannel signals such as MEG and EEG. Although the multiplicative error is estimated based on beamforming, other methods for source analysis can equally be used after the lead-field modification.

  6. Prospects of steady state magnetic diagnostic of fusion reactors based on metallic Hall sensors

    NASA Astrophysics Data System (ADS)

    Ďuran, I.; Sentkerestiová, J.; Kovařík, K.; Viererbl, L.

    2012-06-01

    Employment of sensors based on Hall effect (Hall sensors) is one of the candidate approaches to detection of almost steady state magnetic fields in future fusion reactors based on magnetic confinement (tokamaks, stellarators etc.), and also in possible fusion-fission hybrid systems having these fusion reactors as a neutron source and driver. This contribution reviews the initial considerations concerning application of metallic Hall sensors in fusion reactor harsh environment that include high neutron loads (>1018 cm-2) and elevated temperatures (>200°C). In particular, the candidate sensing materials, candidate technologies for sensors production, initial analysis of activation and transmutation of sensors under reactor relevant neutron loads and the tests of the the first samples of copper Hall sensors are presented.

  7. Improvement of KinectTM Sensor Capabilities by Fusion with Laser Sensing Data Using Octree

    PubMed Central

    Chávez, Alfredo; Karstoft, Henrik

    2012-01-01

    To enhance sensor capabilities, sensor data readings from different modalities must be fused. The main contribution of this paper is to present a sensor data fusion approach that can reduce KinectTM sensor limitations. This approach involves combining laser with KinectTM sensors. Sensor data is modelled in a 3D environment based on octrees using a probabilistic occupancy estimation. The Bayesian method, which takes into account the uncertainty inherent in the sensor measurements, is used to fuse the sensor information and update the 3D octree map. The sensor fusion yields a significant increase of the field of view of the KinectTM sensor that can be used for robot tasks. PMID:22666006

  8. Designing Sensor Networks by a Generalized Highly Optimized Tolerance Model

    NASA Astrophysics Data System (ADS)

    Miyano, Takaya; Yamakoshi, Miyuki; Higashino, Sadanori; Tsutsui, Takako

    A variant of the highly optimized tolerance model is applied to a toy problem of bioterrorism to determine the optimal arrangement of hypothetical bio-sensors to avert epidemic outbreak. Nonlinear loss function is utilized in searching the optimal structure of the sensor network. The proposed method successfully averts disastrously large events, which can not be achieved by the original highly optimized tolerance model.

  9. Optimizing Voided Piezoelectric Polymers For Acoustic Sensors

    NASA Astrophysics Data System (ADS)

    Arvelo, Juan I.

    2009-07-01

    Polymer piezoelectric materials offer lower density and more flexibility than piezoelectric ceramics for applications where rugged and lightweight acoustic sensors are required. This paper discusses constraints imposed by material stiffness and dielectric constants and aims to derive a generalized closed-form solution for optimizing charged foamed polymers. Optimized solutions are reached in the limits of very large and small void fraction and permittivity ratio. The permittivity ratio is the ratio of the dielectric constants of the polymer and the material that fills the voids. Demonstrations indicate that, in the oblique asymptote, the optimized void fraction becomes equivalent to the permittivity ratio. This effort was conducted under the auspices of the Undersea Warfare Business Area (UWBA) Independent Research & Development (IRAD) Board of the Johns Hopkins University Applied Physics Laboratory (JHU/APL).

  10. Knowledge assistant: A sensor fusion framework for robotic environmental characterization

    SciTech Connect

    Feddema, J.T.; Rivera, J.J.; Tucker, S.D.

    1996-12-01

    A prototype sensor fusion framework called the {open_quotes}Knowledge Assistant{close_quotes} has been developed and tested on a gantry robot at Sandia National Laboratories. This Knowledge Assistant guides the robot operator during the planning, execution, and post analysis stages of the characterization process. During the planning stage, the Knowledge Assistant suggests robot paths and speeds based on knowledge of sensors available and their physical characteristics. During execution, the Knowledge Assistant coordinates the collection of data through a data acquisition {open_quotes}specialist.{close_quotes} During execution and post analysis, the Knowledge Assistant sends raw data to other {open_quotes}specialists,{close_quotes} which include statistical pattern recognition software, a neural network, and model-based search software. After the specialists return their results, the Knowledge Assistant consolidates the information and returns a report to the robot control system where the sensed objects and their attributes (e.g. estimated dimensions, weight, material composition, etc.) are displayed in the world model. This paper highlights the major components of this system.

  11. Optimization of wireless Bluetooth sensor systems.

    PubMed

    Lonnblad, J; Castano, J; Ekstrom, M; Linden, M; Backlund, Y

    2004-01-01

    Within this study, three different Bluetooth sensor systems, replacing cables for transmission of biomedical sensor data, have been designed and evaluated. The three sensor architectures are built on 1-, 2- and 3-chip solutions and depending on the monitoring situation and signal character, different solutions are optimal. Essential parameters for all systems have been low physical weight and small size, resistance to interference and interoperability with other technologies as global- or local networks, PC's and mobile phones. Two different biomedical input signals, ECG and PPG (photoplethysmography), have been used to evaluate the three solutions. The study shows that it is possibly to continuously transmit an analogue signal. At low sampling rates and slowly varying parameters, as monitoring the heart rate with PPG, the 1-chip solution is the most suitable, offering low power consumption and thus a longer battery lifetime or a smaller battery, minimizing the weight of the sensor system. On the other hand, when a higher sampling rate is required, as an ECG, the 3-chip architecture, with a FPGA or micro-controller, offers the best solution and performance. Our conclusion is that Bluetooth might be useful in replacing cables of medical monitoring systems.

  12. An approach to optimal hyperspectral and multispectral signature and image fusion for detecting hidden targets on shorelines

    NASA Astrophysics Data System (ADS)

    Bostater, Charles R.

    2015-10-01

    Hyperspectral and multispectral imagery of shorelines collected from airborne and shipborne platforms are used following pushbroom imagery corrections using inertial motion motions units and augmented global positioning data and Kalman filtering. Corrected radiance or reflectance images are then used to optimize synthetic high spatial resolution spectral signatures resulting from an optimized data fusion process. The process demonstrated utilizes littoral zone features from imagery acquired in the Gulf of Mexico region. Shoreline imagery along the Banana River, Florida, is presented that utilizes a technique that makes use of numerically embedded targets in both higher spatial resolution multispectral images and lower spatial resolution hyperspectral imagery. The fusion process developed utilizes optimization procedures that include random selection of regions and pixels in the imagery, and minimizing the difference between the synthetic signatures and observed signatures. The optimized data fusion approach allows detection of spectral anomalies in the resolution enhanced data cubes. Spectral-spatial anomaly detection is demonstrated using numerically embedded line targets within actual imagery. The approach allows one to test spectral signature anomaly detection and to identify features and targets. The optimized data fusion techniques and software allows one to perform sensitivity analysis and optimization in the singular value decomposition model building process and the 2-D Butterworth cutoff frequency and order numerical selection process. The data fusion "synthetic imagery" forms a basis for spectral-spatial resolution enhancement for optimal band selection and remote sensing algorithm development within "spectral anomaly areas". Sensitivity analysis demonstrates the data fusion methodology is most sensitive to (a) the pixels and features used in the SVD model building process and (b) the 2-D Butterworth cutoff frequency optimized by application of K

  13. Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

    NASA Technical Reports Server (NTRS)

    Schenker, Paul S. (Editor)

    1992-01-01

    Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

  14. Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

    NASA Astrophysics Data System (ADS)

    Schenker, Paul S.

    1992-11-01

    Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

  15. A Method for Improving the Pose Accuracy of a Robot Manipulator Based on Multi-Sensor Combined Measurement and Data Fusion

    PubMed Central

    Liu, Bailing; Zhang, Fumin; Qu, Xinghua

    2015-01-01

    An improvement method for the pose accuracy of a robot manipulator by using a multiple-sensor combination measuring system (MCMS) is presented. It is composed of a visual sensor, an angle sensor and a series robot. The visual sensor is utilized to measure the position of the manipulator in real time, and the angle sensor is rigidly attached to the manipulator to obtain its orientation. Due to the higher accuracy of the multi-sensor, two efficient data fusion approaches, the Kalman filter (KF) and multi-sensor optimal information fusion algorithm (MOIFA), are used to fuse the position and orientation of the manipulator. The simulation and experimental results show that the pose accuracy of the robot manipulator is improved dramatically by 38%∼78% with the multi-sensor data fusion. Comparing with reported pose accuracy improvement methods, the primary advantage of this method is that it does not require the complex solution of the kinematics parameter equations, increase of the motion constraints and the complicated procedures of the traditional vision-based methods. It makes the robot processing more autonomous and accurate. To improve the reliability and accuracy of the pose measurements of MCMS, the visual sensor repeatability is experimentally studied. An optimal range of 1 × 0.8 × 1 ∼ 2 × 0.8 × 1 m in the field of view (FOV) is indicated by the experimental results. PMID:25850067

  16. A method for improving the pose accuracy of a robot manipulator based on multi-sensor combined measurement and data fusion.

    PubMed

    Liu, Bailing; Zhang, Fumin; Qu, Xinghua

    2015-01-01

    An improvement method for the pose accuracy of a robot manipulator by using a multiple-sensor combination measuring system (MCMS) is presented. It is composed of a visual sensor, an angle sensor and a series robot. The visual sensor is utilized to measure the position of the manipulator in real time, and the angle sensor is rigidly attached to the manipulator to obtain its orientation. Due to the higher accuracy of the multi-sensor, two efficient data fusion approaches, the Kalman filter (KF) and multi-sensor optimal information fusion algorithm (MOIFA), are used to fuse the position and orientation of the manipulator. The simulation and experimental results show that the pose accuracy of the robot manipulator is improved dramatically by 38%~78% with the multi-sensor data fusion. Comparing with reported pose accuracy improvement methods, the primary advantage of this method is that it does not require the complex solution of the kinematics parameter equations, increase of the motion constraints and the complicated procedures of the traditional vision-based methods. It makes the robot processing more autonomous and accurate. To improve the reliability and accuracy of the pose measurements of MCMS, the visual sensor repeatability is experimentally studied. An optimal range of 1 x 0.8 x 1 ~ 2 x 0.8 x 1 m in the field of view (FOV) is indicated by the experimental results.

  17. Optimal Sensor Locations for Structural Identification

    NASA Technical Reports Server (NTRS)

    Udwadia, F. E.; Garba, J.

    1985-01-01

    The optimum sensor location problem, OSLP, may be thought of in terms of the set of systems, S, the class of input time functions, I, and the identification algorithm (estimator) used, E. Thus, for a given time history of input, the technique of determining the OSL requires, in general, the solution of the optimization and the identification problems simultaneously. A technique which uncouples the two problems is introduced. This is done by means of the concept of an efficient estimator for which the covariance of the parameter estimates is inversely proportional to the Fisher Information Matrix.

  18. Belief Function Based Decision Fusion for Decentralized Target Classification in Wireless Sensor Networks

    PubMed Central

    Zhang, Wenyu; Zhang, Zhenjiang

    2015-01-01

    Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective decision fusion rule based on belief function theory is proposed. Unlike existing belief function based decision fusion schemes, the proposed approach is compatible with any type of classifier because the basic belief assignments (BBAs) of each sensor are constructed on the basis of the classifier’s training output confusion matrix and real-time observations. We also derive explicit global BBA in the fusion center under Dempster’s combinational rule, making the decision making operation in the fusion center greatly simplified. Also, sending the whole BBA structure to the fusion center is avoided. Experimental results demonstrate that the proposed fusion rule has better performance in fusion accuracy compared with the naïve Bayes rule and weighted majority voting rule. PMID:26295399

  19. Sensor fusion for the localisation of birds in flight

    NASA Astrophysics Data System (ADS)

    Millikin, Rhonda Lorraine

    Tracking and identification of birds in flight remains a goal of aviation safety worldwide and conservation in North America. Marine surveillance radar, tracking radar and more recently weather radar have been used to monitor mass movements of birds. The emphasis has been on prediction of migration fronts where thousands of birds follow weather patterns across a large geographic area. Microphones have been stationed over wide areas to receive calls of these birds and help catalogue the diversity of species comprising these migrations. A most critical feature of landbird migration is where the birds land to rest and feed. These habitats are not known and therefore cannot effectively be protected. For effective management of landbird migrants (nocturnal migrant birds), short-range flight behaviour (100--300 m above ground) is the critical air space to monitor. To ensure conservation efforts are focused on endangered species and species truly at risk, species of individual birds must be identified. Short-range monitoring of individual birds is also important for aviation safety. Up to 75% of bird-aircraft collisions occur within 500 ft (153 m) above the runway. Identification of each bird will help predict its flight path, a critical factor in the prevention of a collision. This thesis focuses on short-range identification of individual birds to localise birds in flight. This goal is achieved through fusing data from two sensor systems, radar and acoustic. This fusion provides more accurate tracking of birds in the lower airspace and allows for the identification of species of interest. In the fall of 1999, an experiment was conducted at Prince Edward Point, a southern projection of land on the north shore of Lake Ontario, to prove that the fusion of radar and acoustic sensors enhances the detection, location and tracking of nocturnal migrant birds. As these birds migrate at night, they are difficult to track visually. However, they are detectable with X

  20. Estimating orientation using magnetic and inertial sensors and different sensor fusion approaches: accuracy assessment in manual and locomotion tasks.

    PubMed

    Bergamini, Elena; Ligorio, Gabriele; Summa, Aurora; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

    2014-10-09

    Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under different experimental conditions. Manual and locomotion tasks, differing in time duration, measurement volume, presence/absence of static phases, and out-of-plane movements, were performed by six subjects, and recorded by one unit located on the forearm or the lower trunk, respectively. Two sensor fusion methods, representative of the stochastic (Extended Kalman Filter) and complementary (Non-linear observer) filtering, were selected, and their accuracy was assessed in terms of attitude (pitch and roll angles) and heading (yaw angle) errors using stereophotogrammetric data as a reference. The sensor fusion approaches provided significantly more accurate results than gyroscope data integration. Accuracy improved mostly for heading and when the movement exhibited stationary phases, evenly distributed 3D rotations, it occurred in a small volume, and its duration was greater than approximately 20 s. These results were independent from the specific sensor fusion method used. Practice guidelines for improving the outcome accuracy are provided.

  1. Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks

    PubMed Central

    Bergamini, Elena; Ligorio, Gabriele; Summa, Aurora; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

    2014-01-01

    Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under different experimental conditions. Manual and locomotion tasks, differing in time duration, measurement volume, presence/absence of static phases, and out-of-plane movements, were performed by six subjects, and recorded by one unit located on the forearm or the lower trunk, respectively. Two sensor fusion methods, representative of the stochastic (Extended Kalman Filter) and complementary (Non-linear observer) filtering, were selected, and their accuracy was assessed in terms of attitude (pitch and roll angles) and heading (yaw angle) errors using stereophotogrammetric data as a reference. The sensor fusion approaches provided significantly more accurate results than gyroscope data integration. Accuracy improved mostly for heading and when the movement exhibited stationary phases, evenly distributed 3D rotations, it occurred in a small volume, and its duration was greater than approximately 20 s. These results were independent from the specific sensor fusion method used. Practice guidelines for improving the outcome accuracy are provided. PMID:25302810

  2. Optimization of Microelectronic Devices for Sensor Applications

    NASA Technical Reports Server (NTRS)

    Cwik, Tom; Klimeck, Gerhard

    2000-01-01

    The NASA/JPL goal to reduce payload in future space missions while increasing mission capability demands miniaturization of active and passive sensors, analytical instruments and communication systems among others. Currently, typical system requirements include the detection of particular spectral lines, associated data processing, and communication of the acquired data to other systems. Advances in lithography and deposition methods result in more advanced devices for space application, while the sub-micron resolution currently available opens a vast design space. Though an experimental exploration of this widening design space-searching for optimized performance by repeated fabrication efforts-is unfeasible, it does motivate the development of reliable software design tools. These tools necessitate models based on fundamental physics and mathematics of the device to accurately model effects such as diffraction and scattering in opto-electronic devices, or bandstructure and scattering in heterostructure devices. The software tools must have convenient turn-around times and interfaces that allow effective usage. The first issue is addressed by the application of high-performance computers and the second by the development of graphical user interfaces driven by properly developed data structures. These tools can then be integrated into an optimization environment, and with the available memory capacity and computational speed of high performance parallel platforms, simulation of optimized components can proceed. In this paper, specific applications of the electromagnetic modeling of infrared filtering, as well as heterostructure device design will be presented using genetic algorithm global optimization methods.

  3. Study of data fusion algorithms applied to unattended ground sensor network

    NASA Astrophysics Data System (ADS)

    Pannetier, B.; Moras, J.; Dezert, Jean; Sella, G.

    2014-06-01

    In this paper, data obtained from wireless unattended ground sensor network are used for tracking multiple ground targets (vehicles, pedestrians and animals) moving on and off the road network. The goal of the study is to evaluate several data fusion algorithms to select the best approach to establish the tactical situational awareness. The ground sensor network is composed of heterogeneous sensors (optronic, radar, seismic, acoustic, magnetic sensors) and data fusion nodes. The fusion nodes are small hardware platforms placed on the surveillance area that communicate together. In order to satisfy operational needs and the limited communication bandwidth between the nodes, we study several data fusion algorithms to track and classify targets in real time. A multiple targets tracking (MTT) algorithm is integrated in each data fusion node taking into account embedded constraint. The choice of the MTT algorithm is motivated by the limit of the chosen technology. In the fusion nodes, the distributed MTT algorithm exploits the road network information in order to constrain the multiple dynamic models. Then, a variable structure interacting multiple model (VS-IMM) is adapted with the road network topology. This algorithm is well-known in centralized architecture, but it implies a modification of other data fusion algorithms to preserve the performances of the tracking under constraints. Based on such VS-IMM MTT algorithm, we adapt classical data fusion techniques to make it working in three architectures: centralized, distributed and hierarchical. The sensors measurements are considered asynchronous, but the fusion steps are synchronized on all sensors. Performances of data fusion algorithms are evaluated using simulated data and also validated on real data. The scenarios under analysis contain multiple targets with close and crossing trajectories involving data association uncertainties.

  4. Distributed data fusion across multiple hard and soft mobile sensor platforms

    NASA Astrophysics Data System (ADS)

    Sinsley, Gregory

    One of the biggest challenges currently facing the robotics field is sensor data fusion. Unmanned robots carry many sophisticated sensors including visual and infrared cameras, radar, laser range finders, chemical sensors, accelerometers, gyros, and global positioning systems. By effectively fusing the data from these sensors, a robot would be able to form a coherent view of its world that could then be used to facilitate both autonomous and intelligent operation. Another distinct fusion problem is that of fusing data from teammates with data from onboard sensors. If an entire team of vehicles has the same worldview they will be able to cooperate much more effectively. Sharing worldviews is made even more difficult if the teammates have different sensor types. The final fusion challenge the robotics field faces is that of fusing data gathered by robots with data gathered by human teammates (soft sensors). Humans sense the world completely differently from robots, which makes this problem particularly difficult. The advantage of fusing data from humans is that it makes more information available to the entire team, thus helping each agent to make the best possible decisions. This thesis presents a system for fusing data from multiple unmanned aerial vehicles, unmanned ground vehicles, and human observers. The first issue this thesis addresses is that of centralized data fusion. This is a foundational data fusion issue, which has been very well studied. Important issues in centralized fusion include data association, classification, tracking, and robotics problems. Because these problems are so well studied, this thesis does not make any major contributions in this area, but does review it for completeness. The chapter on centralized fusion concludes with an example unmanned aerial vehicle surveillance problem that demonstrates many of the traditional fusion methods. The second problem this thesis addresses is that of distributed data fusion. Distributed data fusion

  5. Dynamic reweighting of three modalities for sensor fusion.

    PubMed

    Hwang, Sungjae; Agada, Peter; Kiemel, Tim; Jeka, John J

    2014-01-01

    We simultaneously perturbed visual, vestibular and proprioceptive modalities to understand how sensory feedback is re-weighted so that overall feedback remains suited to stabilizing upright stance. Ten healthy young subjects received an 80 Hz vibratory stimulus to their bilateral Achilles tendons (stimulus turns on-off at 0.28 Hz), a ± 1 mA binaural monopolar galvanic vestibular stimulus at 0.36 Hz, and a visual stimulus at 0.2 Hz during standing. The visual stimulus was presented at different amplitudes (0.2, 0.8 deg rotation about ankle axis) to measure: the change in gain (weighting) to vision, an intramodal effect; and a change in gain to vibration and galvanic vestibular stimulation, both intermodal effects. The results showed a clear intramodal visual effect, indicating a de-emphasis on vision when the amplitude of visual stimulus increased. At the same time, an intermodal visual-proprioceptive reweighting effect was observed with the addition of vibration, which is thought to change proprioceptive inputs at the ankles, forcing the nervous system to rely more on vision and vestibular modalities. Similar intermodal effects for visual-vestibular reweighting were observed, suggesting that vestibular information is not a "fixed" reference, but is dynamically adjusted in the sensor fusion process. This is the first time, to our knowledge, that the interplay between the three primary modalities for postural control has been clearly delineated, illustrating a central process that fuses these modalities for accurate estimates of self-motion.

  6. A Radiosonde Using a Humidity Sensor Array with a Platinum Resistance Heater and Multi-Sensor Data Fusion

    PubMed Central

    Shi, Yunbo; Luo, Yi; Zhao, Wenjie; Shang, Chunxue; Wang, Yadong; Chen, Yinsheng

    2013-01-01

    This paper describes the design and implementation of a radiosonde which can measure the meteorological temperature, humidity, pressure, and other atmospheric data. The system is composed of a CPU, microwave module, temperature sensor, pressure sensor and humidity sensor array. In order to effectively solve the humidity sensor condensation problem due to the low temperatures in the high altitude environment, a capacitive humidity sensor including four humidity sensors to collect meteorological humidity and a platinum resistance heater was developed using micro-electro-mechanical-system (MEMS) technology. A platinum resistance wire with 99.999% purity and 0.023 mm in diameter was used to obtain the meteorological temperature. A multi-sensor data fusion technique was applied to process the atmospheric data. Static and dynamic experimental results show that the designed humidity sensor with platinum resistance heater can effectively tackle the sensor condensation problem, shorten response times and enhance sensitivity. The humidity sensor array can improve measurement accuracy and obtain a reliable initial meteorological humidity data, while the multi-sensor data fusion technique eliminates the uncertainty in the measurement. The radiosonde can accurately reflect the meteorological changes. PMID:23857263

  7. Optimal Sensor Allocation for Fault Detection and Isolation

    NASA Technical Reports Server (NTRS)

    Azam, Mohammad; Pattipati, Krishna; Patterson-Hine, Ann

    2004-01-01

    Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosibility, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems. Keywords: sensor allocation, multiple fault diagnosis, Lagrangian relaxation, approximate belief revision, multidimensional knapsack problem.

  8. Robust interacting multiple model algorithms based on multi-sensor fusion criteria

    NASA Astrophysics Data System (ADS)

    Zhou, Weidong; Liu, Mengmeng

    2016-01-01

    This paper is concerned with the state estimation problem for a class of Markov jump linear discrete-time stochastic systems. Three novel interacting multiple model (IMM) algorithms are proposed based on the H∞ technique, the correlation among estimation errors of mode-conditioned filters and the multi-sensor optimal information fusion criteria. Mode probabilities in the novel algorithms are derived based on the error cross-covariances instead of likelihood functions. The H∞ technique taking the place of Kalman filtering is applied to enhance the robustness of the new approaches. Theoretical analysis and Monte Carlo simulation results indicate that the proposed algorithms are effective and have an obvious advantage in velocity estimation when tracking a maneuvering target.

  9. Single-sensor processing and sensor fusion for GPR and EMI data

    NASA Astrophysics Data System (ADS)

    Collins, Leslie M.; Huettel, Lisa G.

    2001-10-01

    As in many areas, performance of landmine detection algorithms is judged in terms of detection and false alarm rates. For the landmine detection problem, it is often the case that detectors satisfy one requirement at the cost of poor performance with regard to the other. It is widely accepted that single sensors cannot simultaneously achieve both high detection rates and low false alarm rates, since every sensor has its advantages and disadvantages when dealing with a large variety of landmines, from large metal-cased mines to small plastic-cased mines. Thus, in this paper we consider two types of sensors, EMI and GPR. In its most common instantiation, time-domain EMI is essentially a metal detector and thus detects mines with high metal content as well as metal debris in the environment. More advanced EMI systems have begun to show potential for the discrimination of such debris from mines. GPR is also used for landmine detection since it can detect and identify low-metallic subsurface anomalies. In our previous work, we have shown that Bayesian detection approach can be applied to EMI data and provide promising results. In this paper, we present results that indicate that statistical signal processing technique applied to GPR data can also yield performance improvements. Theoretical results are verified by data collected with a developmental mine-detection system, which consists of co-located metal detectors and GPR sensors. Thus, in addition to discussing individual sensor data processing, we also present result of data fusion of both the EMI and the GPR data using the detection system.

  10. Sensor fusion with passive millimeter-wave and laser radar for target detection

    NASA Astrophysics Data System (ADS)

    Lin, Chun-Shin; Amphay, Sengvieng A.; Sundstrom, Bryce M.

    1999-07-01

    Advanced sensors and guidance techniques are required in killing mobile offensive and defensive systems. Many different sensors such as radar, video camera, laser radar (LADAR), millimeter wave systems, infrared imagers, acoustic sensors, etc. are available for such usage. However, no single sensor provides completely satisfactory capabilities. Since some sensors have complementary capabilities, integration of multiple sensors for kill can relax the task difficulty and provide more reliable results. The use of multiple sensors can also reduce the possibility of being defeated by countermeasures. In this study, we investigated the framework and investigated potential techniques for integration and fusion of information from passive millimeter wave (PMMW) and LADAR systems. The focus has been on target detection. The PMMW is used to detect metal objects and the LADAR examines those regions of interest for other evidence of existence of a target. Advances obtained by integrating these two sensors include reduction of task complexity and improvement of reliability, both due to efficient localization of regions of interest from the PMMW. Since PMMW possesses weather penetration capabilities through fog, cloud, smoke, etc., the combined system has a near-all-weather capability. A LADAR provides 3D information, and it should be used as the primary sensor for target acquisition upon target detection. The framework of the fusion is based on the Dempster-Shafer decision method. The fusion may be done in the algorithm level and sensor level. With the Dempster-Shafer method as the framework, new sensors or new decision components can be easily integrated.

  11. Staggered scheduling of sensor estimation and fusion for tracking over long-haul links

    DOE PAGES

    Liu, Qiang; Rao, Nageswara S. V.; Wang, Xin

    2016-08-01

    Networked sensing can be found in a multitude of real-world applications. Here, we focus on the communication-and computation-constrained long-haul sensor networks, where sensors are remotely deployed over a vast geographical area to perform certain tasks. Of special interest is a class of such networks where sensors take measurements of one or more dynamic targets and send their state estimates to a remote fusion center via long-haul satellite links. The severe loss and delay over such links can easily reduce the amount of sensor data received by the fusion center, thereby limiting the potential information fusion gain and resulting in suboptimalmore » tracking performance. In this paper, starting with the temporal-domain staggered estimation for an individual sensor, we explore the impact of the so-called intra-state prediction and retrodiction on estimation errors. We then investigate the effect of such estimation scheduling across different sensors on the spatial-domain fusion performance, where the sensing time epochs across sensors are scheduled in an asynchronous and staggered manner. In particular, the impact of communication delay and loss as well as sensor bias on such scheduling is explored by means of numerical and simulation studies that demonstrate the validity of our analysis.« less

  12. Optimizing the configuration patterns for heterogeneous distributed sensor fields

    NASA Astrophysics Data System (ADS)

    Wettergren, Thomas A.; Costa, Russell

    2012-06-01

    When unmanned distributed sensor fields are developed for rapid deployment in hostile areas, the deployment may consist of multiple sensor types. This occurs because of the variations in expected threats and uncertainties about the details of the local environmental conditions. As more detailed information is available at deployment, the quantity and types of sensors are given and fixed, yet the specific pattern for the configuration of their deployment is still variable. We develop a new optimization approach for planning these configurations for this resource constrained sensor application. Our approach takes into account the variety of sensors available and their respective expected performance in the environment, as well as the target uncertainty. Due to the large dimensionality of the design space for this unmanned sensor planning problem, heuristic-based optimizations will provide very sub-optimal solutions and gradient-based methods lack a good quality initialization. Instead, we utilize a robust optimization procedure that combines genetic algorithms with nonlinear programming techniques to create numerical solutions for determining the optimal spatial distribution of sensing effort for each type of sensor. We illustrate the effectiveness of the approach on numerical examples, and also illustrate the qualitative difference in the optimal patterns as a function of the relative numbers of available sensors of each type. We conclude by using the optimization results to discuss the benefits of interspersing the different sensor types, as opposed to creating area sub-segmentations for each type.

  13. Statistical sensor fusion of ECG data using automotive-grade sensors

    NASA Astrophysics Data System (ADS)

    Koenig, A.; Rehg, T.; Rasshofer, R.

    2015-11-01

    Driver states such as fatigue, stress, aggression, distraction or even medical emergencies continue to be yield to severe mistakes in driving and promote accidents. A pathway towards improving driver state assessment can be found in psycho-physiological measures to directly quantify the driver's state from physiological recordings. Although heart rate is a well-established physiological variable that reflects cognitive stress, obtaining heart rate contactless and reliably is a challenging task in an automotive environment. Our aim was to investigate, how sensory fusion of two automotive grade sensors would influence the accuracy of automatic classification of cognitive stress levels. We induced cognitive stress in subjects and estimated levels from their heart rate signals, acquired from automotive ready ECG sensors. Using signal quality indices and Kalman filters, we were able to decrease Root Mean Squared Error (RMSE) of heart rate recordings by 10 beats per minute. We then trained a neural network to classify the cognitive workload state of subjects from heart rate and compared classification performance for ground truth, the individual sensors and the fused heart rate signal. We obtained an increase of 5 % higher correct classification by fusing signals as compared to individual sensors, staying only 4 % below the maximally possible classification accuracy from ground truth. These results are a first step towards real world applications of psycho-physiological measurements in vehicle settings. Future implementations of driver state modeling will be able to draw from a larger pool of data sources, such as additional physiological values or vehicle related data, which can be expected to drive classification to significantly higher values.

  14. Phase 1 report on sensor technology, data fusion and data interpretation for site characterization

    SciTech Connect

    Beckerman, M.

    1991-10-01

    In this report we discuss sensor technology, data fusion and data interpretation approaches of possible maximal usefulness for subsurface imaging and characterization of land-fill waste sites. Two sensor technologies, terrain conductivity using electromagnetic induction and ground penetrating radar, are described and the literature on the subject is reviewed. We identify the maximum entropy stochastic method as one providing a rigorously justifiable framework for fusing the sensor data, briefly summarize work done by us in this area, and examine some of the outstanding issues with regard to data fusion and interpretation. 25 refs., 17 figs.

  15. Fusion of threshold rules for target detection in wireless sensor networks

    SciTech Connect

    Zhu, Mengxia; Ding, Shi-You; Brooks, Richard R; Wu, Qishi; Rao, Nageswara S

    2010-03-01

    We propose a binary decision fusion rule that reaches a global decision on the presence of a target by integrating local decisions made by multiple sensors. Without requiring a priori probability of target presence, the fusion threshold bounds derived using Chebyshev's inequality ensure a higher hit rate and lower false alarm rate compared to the weighted averages of individual sensors. The Monte Carlo-based simulation results show that the proposed approach significantly improves target detection performance, and can also be used to guide the actual threshold selection in practical sensor network implementation under certain error rate constraints.

  16. The research of auto-focusing method for the image mosaic and fusion system with multi-sensor

    NASA Astrophysics Data System (ADS)

    Pang, Ke; Yao, Suying; Shi, Zaifeng; Xu, Jiangtao; Liu, Jiangming

    2013-09-01

    In modern image processing, due to the development of digital image processing, the focus of the sensor can be automatically set by the digital processing system through computation. In the other hand, the auto-focusing synchronously and consistently is one of the most important factors for image mosaic and fusion processing, especially for the system with multi-sensor which are put on one line in order to gain the wide angle video information. Different images sampled by the sensors with different focal length values will always increase the complexity of the affine matrix of the image mosaic and fusion in next, which potentially reducing the efficiency of the system and consuming more power. Here, a new fast evaluation method based on the gray value variance of the image pixel is proposed to find the common focal length value for all sensors to achieve the better image sharpness. For the multi-frame pictures that are sampled from different sensors that have been adjusted and been regarded as time synchronization, the gray value variances of the adjacent pixels are determined to generate one curve. This curve is the focus measure function which describes the relationship between the image sharpness and the focal length value of the sensor. On the basis of all focus measure functions of all sensors in the image processing system, this paper uses least square method to carry out the data fitting to imitate the disperse curves and give one objective function for the multi-sensor system, and then find the optimal solution corresponding to the extreme value of the image sharpness according to the evaluation of the objective function. This optimal focal length value is the common parameter for all sensors in this system. By setting the common focal length value, in the premise of ensuring the image sharpness, the computing of the affine matrix which is the core processing of the image mosaic and fusion which stitching all those pictures into one wide angle image will be

  17. Remote Sensing Image Fusion Using Ica and Optimized Wavelet Transform

    NASA Astrophysics Data System (ADS)

    Hnatushenko, V. V.; Vasyliev, V. V.

    2016-06-01

    In remote-sensing image processing, fusion (pan-sharpening) is a process of merging high-resolution panchromatic and lower resolution multispectral (MS) imagery to create a single high-resolution color image. Many methods exist to produce data fusion results with the best possible spatial and spectral characteristics, and a number have been commercially implemented. However, the pan-sharpening image produced by these methods gets the high color distortion of spectral information. In this paper, to minimize the spectral distortion we propose a remote sensing image fusion method which combines the Independent Component Analysis (ICA) and optimization wavelet transform. The proposed method is based on selection of multiscale components obtained after the ICA of images on the base of their wavelet decomposition and formation of linear forms detailing coefficients of the wavelet decomposition of images brightness distributions by spectral channels with iteratively adjusted weights. These coefficients are determined as a result of solving an optimization problem for the criterion of maximization of information entropy of the synthesized images formed by means of wavelet reconstruction. Further, reconstruction of the images of spectral channels is done by the reverse wavelet transform and formation of the resulting image by superposition of the obtained images. To verify the validity, the new proposed method is compared with several techniques using WorldView-2 satellite data in subjective and objective aspects. In experiments we demonstrated that our scheme provides good spectral quality and efficiency. Spectral and spatial quality metrics in terms of RASE, RMSE, CC, ERGAS and SSIM are used in our experiments. These synthesized MS images differ by showing a better contrast and clarity on the boundaries of the "object of interest - the background". The results show that the proposed approach performs better than some compared methods according to the performance metrics.

  18. Multi-sensor fusion system using wavelet-based detection algorithm applied to physiological monitoring under high-G environment

    NASA Astrophysics Data System (ADS)

    Ryoo, Han Chool

    2000-06-01

    A significant problem in physiological state monitoring systems with single data channels is high rates of false alarm. In order to reduce false alarm probability, several data channels can be integrated to enhance system performance. In this work, we have investigated a sensor fusion methodology applicable to physiological state monitoring, which combines local decisions made from dispersed detectors. Difficulties in biophysical signal processing are associated with nonstationary signal patterns and individual characteristics of human physiology resulting in nonidentical observation statistics. Thus a two compartment design, a modified version of well established fusion theory in communication systems, is presented and applied to biological signal processing where we combine discrete wavelet transforms (DWT) with sensor fusion theory. The signals were decomposed in time-frequency domain by discrete wavelet transform (DWT) to capture localized transient features. Local decisions by wavelet power analysis are followed by global decisions at the data fusion center operating under an optimization criterion, i.e., minimum error criterion (MEC). We used three signals acquired from human volunteers exposed to high-G forces at the human centrifuge/dynamic flight simulator facility in Warminster, PA. The subjects performed anti-G straining maneuvers to protect them from the adverse effects of high-G forces. These maneuvers require muscular tensing and altered breathing patterns. We attempted to determine the subject's state by detecting the presence or absence of the voluntary anti-G straining maneuvers (AGSM). During the exposure to high G force the respiratory patterns, blood pressure and electroencephalogram (EEG) were measured to determine changes in the subject's state. Experimental results show that the probability of false alarm under MEC can be significantly reduced by applying the same rule found at local thresholds to all subjects, and MEC can be employed as a

  19. Assessing the Performance of Sensor Fusion Methods: Application to Magnetic-Inertial-Based Human Body Tracking.

    PubMed

    Ligorio, Gabriele; Bergamini, Elena; Pasciuto, Ilaria; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

    2016-01-26

    Information from complementary and redundant sensors are often combined within sensor fusion algorithms to obtain a single accurate observation of the system at hand. However, measurements from each sensor are characterized by uncertainties. When multiple data are fused, it is often unclear how all these uncertainties interact and influence the overall performance of the sensor fusion algorithm. To address this issue, a benchmarking procedure is presented, where simulated and real data are combined in different scenarios in order to quantify how each sensor's uncertainties influence the accuracy of the final result. The proposed procedure was applied to the estimation of the pelvis orientation using a waist-worn magnetic-inertial measurement unit. Ground-truth data were obtained from a stereophotogrammetric system and used to obtain simulated data. Two Kalman-based sensor fusion algorithms were submitted to the proposed benchmarking procedure. For the considered application, gyroscope uncertainties proved to be the main error source in orientation estimation accuracy for both tested algorithms. Moreover, although different performances were obtained using simulated data, these differences became negligible when real data were considered. The outcome of this evaluation may be useful both to improve the design of new sensor fusion methods and to drive the algorithm tuning process.

  20. Assessing the Performance of Sensor Fusion Methods: Application to Magnetic-Inertial-Based Human Body Tracking.

    PubMed

    Ligorio, Gabriele; Bergamini, Elena; Pasciuto, Ilaria; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

    2016-01-01

    Information from complementary and redundant sensors are often combined within sensor fusion algorithms to obtain a single accurate observation of the system at hand. However, measurements from each sensor are characterized by uncertainties. When multiple data are fused, it is often unclear how all these uncertainties interact and influence the overall performance of the sensor fusion algorithm. To address this issue, a benchmarking procedure is presented, where simulated and real data are combined in different scenarios in order to quantify how each sensor's uncertainties influence the accuracy of the final result. The proposed procedure was applied to the estimation of the pelvis orientation using a waist-worn magnetic-inertial measurement unit. Ground-truth data were obtained from a stereophotogrammetric system and used to obtain simulated data. Two Kalman-based sensor fusion algorithms were submitted to the proposed benchmarking procedure. For the considered application, gyroscope uncertainties proved to be the main error source in orientation estimation accuracy for both tested algorithms. Moreover, although different performances were obtained using simulated data, these differences became negligible when real data were considered. The outcome of this evaluation may be useful both to improve the design of new sensor fusion methods and to drive the algorithm tuning process. PMID:26821027

  1. Optimal Sensor Selection for Classifying a Set of Ginsengs Using Metal-Oxide Sensors.

    PubMed

    Miao, Jiacheng; Zhang, Tinglin; Wang, You; Li, Guang

    2015-07-03

    The sensor selection problem was investigated for the application of classification of a set of ginsengs using a metal-oxide sensor-based homemade electronic nose with linear discriminant analysis. Samples (315) were measured for nine kinds of ginsengs using 12 sensors. We investigated the classification performances of combinations of 12 sensors for the overall discrimination of combinations of nine ginsengs. The minimum numbers of sensors for discriminating each sample set to obtain an optimal classification performance were defined. The relation of the minimum numbers of sensors with number of samples in the sample set was revealed. The results showed that as the number of samples increased, the average minimum number of sensors increased, while the increment decreased gradually and the average optimal classification rate decreased gradually. Moreover, a new approach of sensor selection was proposed to estimate and compare the effective information capacity of each sensor.

  2. Sensor Fusion Based Fault-Tolerant Attitude Estimation Solutions for Small Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Gross, Jason Nicholas

    Navigation-grade inertial sensors are often too expensive and too heavy for use in most Small Unmanned Aerial Vehicle (SUAV) systems. Low-cost Micro-Electrical-Mechanical-Systems (MEMS) inertial sensors provide an attractive alternative, but currently do not provide an adequate navigation solution alone due to the presence of sensor bias. Toward addressing this problem, this research focuses on the development and experimental evaluation of sensor fusion algorithms to combine partially redundant information from low-cost sensor to achieve accurate SUAV attitude estimation. To conduct this research, several sets of SUAVs flight data that include measurements from a low-cost MEMS based Inertial Measurement Unit, a Global Positioning System receiver, and a set of low-grade tri-axial magnetometers are used to evaluate a variety of algorithms. In order to provide a baseline for performance evaluation, attitude measurements obtained directly with a high-quality mechanical vertical gyroscope are used as an independent attitude 'truth'. In addition, as a part of this project, a custom SUAV avionics system was developed to provide a platform for fault-tolerant flight control research. The overall goal of this research is to provide high-accuracy attitude estimation during nominal sensor performance conditions and in the event of sensors failures, while using only low-cost components. To achieve this goal, this study is carried out in three phases. The specific aim of the first phase is to obtain high-accuracy under nominal sensor conditions. During this phase, two different nonlinear Kalman filtering methods are applied to various sensor fusion formulations and evaluated with respect to estimation accuracy over diverse sets of flight data. Next, during the second phase, sensor fusion based calibration techniques are explored to further enhance estimation accuracy. Finally, the third phase of the study considers the design of a sensor fusion attitude estimation architecture

  3. Information Fusion in Ad hoc Wireless Sensor Networks for Aircraft Health Monitoring

    NASA Astrophysics Data System (ADS)

    Fragoulis, Nikos; Tsagaris, Vassilis; Anastassopoulos, Vassilis

    In this paper the use of an ad hoc wireless sensor network for implementing a structural health monitoring system is discussed. The network is consisted of sensors deployed throughout the aircraft. These sensors being in the form of a microelectronic chip and consisted of sensing, data processing and communicating components could be easily embedded in any mechanical aircraft component. The established sensor network, due to its ad hoc nature is easily scalable, allowing adding or removing any number of sensors. The position of the sensor nodes need not necessarily to be engineered or predetermined, giving this way the ability to be deployed in inaccessible points. Information collected from various sensors of different modalities throughout the aircraft is then fused in order to provide a more comprehensive image of the aircraft structural health. Sensor level fusion along with decision quality information is used, in order to enhance detection performance.

  4. Double cluster heads model for secure and accurate data fusion in wireless sensor networks.

    PubMed

    Fu, Jun-Song; Liu, Yun

    2015-01-19

    Secure and accurate data fusion is an important issue in wireless sensor networks (WSNs) and has been extensively researched in the literature. In this paper, by combining clustering techniques, reputation and trust systems, and data fusion algorithms, we propose a novel cluster-based data fusion model called Double Cluster Heads Model (DCHM) for secure and accurate data fusion in WSNs. Different from traditional clustering models in WSNs, two cluster heads are selected after clustering for each cluster based on the reputation and trust system and they perform data fusion independently of each other. Then, the results are sent to the base station where the dissimilarity coefficient is computed. If the dissimilarity coefficient of the two data fusion results exceeds the threshold preset by the users, the cluster heads will be added to blacklist, and the cluster heads must be reelected by the sensor nodes in a cluster. Meanwhile, feedback is sent from the base station to the reputation and trust system, which can help us to identify and delete the compromised sensor nodes in time. Through a series of extensive simulations, we found that the DCHM performed very well in data fusion security and accuracy.

  5. Hybrid intelligent control concepts for optimal data fusion

    NASA Astrophysics Data System (ADS)

    Llinas, James

    1994-02-01

    In the post-Cold War era, Naval surface ship operations will be largely conducted in littoral waters to support regional military missions of all types, including humanitarian and evacuation activities, and amphibious mission execution. Under these conditions, surface ships will be much more isolated and vulnerable to a variety of threats, including maneuvering antiship missiles. To deal with these threats, the optimal employment of multiple shipborne sensors for maximum vigilance is paramount. This paper characterizes the sensor management problem as one of intelligent control, identifies some of the key issues in controller design, and presents one approach to controller design which is soon to be implemented and evaluated. It is argued that the complexity and hierarchical nature of problem formulation demands a hybrid combination of knowledge-based methods and scheduling techniques from 'hard' real-time systems theory for its solution.

  6. Rider trunk and bicycle pose estimation with fusion of force/inertial sensors.

    PubMed

    Zhang, Yizhai; Chen, Kuo; Yi, Jingang

    2013-09-01

    Estimation of human pose in physical human-machine interactions such as bicycling is challenging because of highly-dimensional human motion and lack of inexpensive, effective motion sensors. In this paper, we present a computational scheme to estimate both the rider trunk pose and the bicycle roll angle using only inertial and force sensors. The estimation scheme is built on a rider-bicycle dynamic model and the fusion of the wearable inertial sensors and the bicycle force sensors. We take advantages of the attractive properties of the robust force measurements and the motion-sensitive inertial measurements. The rider-bicycle dynamic model provides the underlying relationship between the force and the inertial measurements. The extended Kalman filter-based sensor fusion design fully incorporates the dynamic effects of the force measurements. The performance of the estimation scheme is demonstrated through extensive indoor and outdoor riding experiments. PMID:23629841

  7. Sensor Data Fusion with Z-Numbers and Its Application in Fault Diagnosis

    PubMed Central

    Jiang, Wen; Xie, Chunhe; Zhuang, Miaoyan; Shou, Yehang; Tang, Yongchuan

    2016-01-01

    Sensor data fusion technology is widely employed in fault diagnosis. The information in a sensor data fusion system is characterized by not only fuzziness, but also partial reliability. Uncertain information of sensors, including randomness, fuzziness, etc., has been extensively studied recently. However, the reliability of a sensor is often overlooked or cannot be analyzed adequately. A Z-number, Z = (A, B), can represent the fuzziness and the reliability of information simultaneously, where the first component A represents a fuzzy restriction on the values of uncertain variables and the second component B is a measure of the reliability of A. In order to model and process the uncertainties in a sensor data fusion system reasonably, in this paper, a novel method combining the Z-number and Dempster–Shafer (D-S) evidence theory is proposed, where the Z-number is used to model the fuzziness and reliability of the sensor data and the D-S evidence theory is used to fuse the uncertain information of Z-numbers. The main advantages of the proposed method are that it provides a more robust measure of reliability to the sensor data, and the complementary information of multi-sensors reduces the uncertainty of the fault recognition, thus enhancing the reliability of fault detection. PMID:27649193

  8. Sensor Data Fusion with Z-Numbers and Its Application in Fault Diagnosis.

    PubMed

    Jiang, Wen; Xie, Chunhe; Zhuang, Miaoyan; Shou, Yehang; Tang, Yongchuan

    2016-09-15

    Sensor data fusion technology is widely employed in fault diagnosis. The information in a sensor data fusion system is characterized by not only fuzziness, but also partial reliability. Uncertain information of sensors, including randomness, fuzziness, etc., has been extensively studied recently. However, the reliability of a sensor is often overlooked or cannot be analyzed adequately. A Z-number, Z = (A, B), can represent the fuzziness and the reliability of information simultaneously, where the first component A represents a fuzzy restriction on the values of uncertain variables and the second component B is a measure of the reliability of A. In order to model and process the uncertainties in a sensor data fusion system reasonably, in this paper, a novel method combining the Z-number and Dempster-Shafer (D-S) evidence theory is proposed, where the Z-number is used to model the fuzziness and reliability of the sensor data and the D-S evidence theory is used to fuse the uncertain information of Z-numbers. The main advantages of the proposed method are that it provides a more robust measure of reliability to the sensor data, and the complementary information of multi-sensors reduces the uncertainty of the fault recognition, thus enhancing the reliability of fault detection.

  9. Sensor Data Fusion with Z-Numbers and Its Application in Fault Diagnosis.

    PubMed

    Jiang, Wen; Xie, Chunhe; Zhuang, Miaoyan; Shou, Yehang; Tang, Yongchuan

    2016-01-01

    Sensor data fusion technology is widely employed in fault diagnosis. The information in a sensor data fusion system is characterized by not only fuzziness, but also partial reliability. Uncertain information of sensors, including randomness, fuzziness, etc., has been extensively studied recently. However, the reliability of a sensor is often overlooked or cannot be analyzed adequately. A Z-number, Z = (A, B), can represent the fuzziness and the reliability of information simultaneously, where the first component A represents a fuzzy restriction on the values of uncertain variables and the second component B is a measure of the reliability of A. In order to model and process the uncertainties in a sensor data fusion system reasonably, in this paper, a novel method combining the Z-number and Dempster-Shafer (D-S) evidence theory is proposed, where the Z-number is used to model the fuzziness and reliability of the sensor data and the D-S evidence theory is used to fuse the uncertain information of Z-numbers. The main advantages of the proposed method are that it provides a more robust measure of reliability to the sensor data, and the complementary information of multi-sensors reduces the uncertainty of the fault recognition, thus enhancing the reliability of fault detection. PMID:27649193

  10. Assessing the Performance of Sensor Fusion Methods: Application to Magnetic-Inertial-Based Human Body Tracking

    PubMed Central

    Ligorio, Gabriele; Bergamini, Elena; Pasciuto, Ilaria; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

    2016-01-01

    Information from complementary and redundant sensors are often combined within sensor fusion algorithms to obtain a single accurate observation of the system at hand. However, measurements from each sensor are characterized by uncertainties. When multiple data are fused, it is often unclear how all these uncertainties interact and influence the overall performance of the sensor fusion algorithm. To address this issue, a benchmarking procedure is presented, where simulated and real data are combined in different scenarios in order to quantify how each sensor’s uncertainties influence the accuracy of the final result. The proposed procedure was applied to the estimation of the pelvis orientation using a waist-worn magnetic-inertial measurement unit. Ground-truth data were obtained from a stereophotogrammetric system and used to obtain simulated data. Two Kalman-based sensor fusion algorithms were submitted to the proposed benchmarking procedure. For the considered application, gyroscope uncertainties proved to be the main error source in orientation estimation accuracy for both tested algorithms. Moreover, although different performances were obtained using simulated data, these differences became negligible when real data were considered. The outcome of this evaluation may be useful both to improve the design of new sensor fusion methods and to drive the algorithm tuning process. PMID:26821027

  11. A novel tiered sensor fusion approach for terrain characterization and safe landing assessment

    NASA Technical Reports Server (NTRS)

    Serrano, Navid; Bajracharya, Max; Howard, Ayanna; Seraji, Homayoun

    2005-01-01

    This paper presents a novel tiered sensor fusion methodology for real-time terrain safety assessment. A combination of active and passive sensors, specifically, radar, lidar, and camera, operate in three tiers according to their inherent ranges of operation. Low-level terrain features (e.g. slope, roughness) and high-level terrain features (e.g. hills, craters) are integrated using principles of reasoning under uncertainty. Three methodologies are used to infer landing safety: Fuzzy Reasoning, Probabilistic Reasoning, and Evidential Reasoning. The safe landing predictions from the three fusion engines are consolidated in a subsequent decision fusion stage aimed at combining the strengths of each fusion methodology. Results from simulated spacecraft descents are presented and discussed.

  12. Optimal placement of sensors and actuators for modal identification

    NASA Astrophysics Data System (ADS)

    Bedrossian, Herand

    1998-12-01

    This thesis describes a methodology for optimal placement of combined sensors and actuators for the purpose of structural modal identification. It is important that sensors (accelerometers) be optimally placed to identify the frequencies and mode shapes, and validate the mathematical models used to predict the loads and dynamic response. Due to cost, installation, and data management issues, only a limited number of sensors will be available for placement. This dissertation also examines a number of global stochastic search techniques including Evolution System (ES), Adaptive Random Search (ARS), Adaptive Simulated Annealing (ASA), and Genetic Algorithm (GA). The performance of these algorithms for large scale parameter optimization is investigated using a large set of test suites. The performance of GA hybrids that use local search to solve global optimization problems are shown to provide superior performance compared to other randomized search techniques. GA hybrids using local search (GA-LS hybrids) are motivated by the apparent need to employ both a global and local search strategy to provide an effective global optimization method. When compared to Adaptive Simulated Annealing, Adaptive Random Search and Evolution Systems, GA-LS hybrids not only find better solutions than the GA, but also optimize more efficiently. An integer based GA-LS hybrid algorithm is then developed for use in sensor and actuator placement problem. This dissertation explores the optimal combined placement of sensors and actuators for modal identification of large structures where a large number of sensors and actuators are typically used. The sensors and actuators are placed to minimize the sum of the Hankel Singular Values (HSV's) of a balanced system that includes a measure of both the controllability and observability of the system. By combining an efficient randomized search technique based on Hybrid-GA with a metric for sensor and actuator placement problem such as HSV's, a robust

  13. Reliability estimates for selected sensors in fusion applications

    SciTech Connect

    Cadwallader, L.C.

    1996-09-01

    This report presents the results of a study to define several types of sensors in use, the qualitative reliability (failure modes) and quantitative reliability (average failure rates) for these types of process sensors. Temperature, pressure, flow, and level sensors are discussed for water coolant and for cryogenic coolants. The failure rates that have been found are useful for risk assessment and safety analysis. Repair times and calibration intervals are also given when found in the literature. All of these values can also be useful to plant operators and maintenance personnel. Designers may be able to make use of these data when planning systems. The final chapter in this report discusses failure rates for several types of personnel safety sensors, including ionizing radiation monitors, toxic and combustible gas detectors, humidity sensors, and magnetic field sensors. These data could be useful to industrial hygienists and other safety professionals when designing or auditing for personnel safety.

  14. Complexity reducing algorithm for near optimal fusion (CRANOF) with application to tracking and information fusion

    NASA Astrophysics Data System (ADS)

    Bamber, D.; Goodman, I. R.; Torrez, William C.; Nguyen, H. T.

    2001-08-01

    Conditional probability logics (CPL's), such as Adams', while producing many satisfactory results, do not agree with commonsense reasoning for a number of key entailment schemes, including transitivity and contraposition. Also, CPL's and bayesian techniques, often: (1) use restrictive independence/simplification assumptions; (2) lack a rationale behind choice of prior distribution; (3) require highly complex implementation calculations; (4) introduce ad hoc techniques. To address the above difficulties, a new CPL is being developed: CRANOF - Complexity Reducing Algorithm for Near Optimal Fusion -based upon three factors: (i) second order probability logic (SOPL), i.e., probability of probabilities within a bayesian framework; (ii) justified use of Dirichlet family priors, based on an extension of Lukacs' characterization theorem; and (iii) replacement of the theoretical optimal solution by a near optimal one where the complexity of computations is reduced significantly. A fundamental application of CRANOF to correlation and tracking is provided here through a generic example in a form similar to transitivity: two track histories are to be merged or left alone, based upon observed kinematic and non-kinematic attribute information and conditional probabilities connecting the observed data to the degrees of matching of attributes, as well as relating the matching of prescribed groups of attributes from each track history to the correlation level between the histories.

  15. Wireless Sensor Network Optimization: Multi-Objective Paradigm.

    PubMed

    Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

    2015-07-20

    Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

  16. Wireless Sensor Network Optimization: Multi-Objective Paradigm

    PubMed Central

    Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

    2015-01-01

    Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

  17. Extended Logic Intelligent Processing System for a Sensor Fusion Processor Hardware

    NASA Technical Reports Server (NTRS)

    Stoica, Adrian; Thomas, Tyson; Li, Wei-Te; Daud, Taher; Fabunmi, James

    2000-01-01

    The paper presents the hardware implementation and initial tests from a low-power, highspeed reconfigurable sensor fusion processor. The Extended Logic Intelligent Processing System (ELIPS) is described, which combines rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor signals in compact low power VLSI. The development of the ELIPS concept is being done to demonstrate the interceptor functionality which particularly underlines the high speed and low power requirements. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Processing speeds of microseconds have been demonstrated using our test hardware.

  18. Autonomous navigation vehicle system based on robot vision and multi-sensor fusion

    NASA Astrophysics Data System (ADS)

    Wu, Lihong; Chen, Yingsong; Cui, Zhouping

    2011-12-01

    The architecture of autonomous navigation vehicle based on robot vision and multi-sensor fusion technology is expatiated in this paper. In order to acquire more intelligence and robustness, accurate real-time collection and processing of information are realized by using this technology. The method to achieve robot vision and multi-sensor fusion is discussed in detail. The results simulated in several operating modes show that this intelligent vehicle has better effects in barrier identification and avoidance and path planning. And this can provide higher reliability during vehicle running.

  19. LinkMind: link optimization in swarming mobile sensor networks.

    PubMed

    Ngo, Trung Dung

    2011-01-01

    A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation. PMID:22164070

  20. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    PubMed Central

    Ngo, Trung Dung

    2011-01-01

    A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation. PMID:22164070

  1. LinkMind: link optimization in swarming mobile sensor networks.

    PubMed

    Ngo, Trung Dung

    2011-01-01

    A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.

  2. Sensor Fusion of Gaussian Mixtures for Ballistic Target Tracking in the Re-Entry Phase.

    PubMed

    Lu, Kelin; Zhou, Rui

    2016-01-01

    A sensor fusion methodology for the Gaussian mixtures model is proposed for ballistic target tracking with unknown ballistic coefficients. To improve the estimation accuracy, a track-to-track fusion architecture is proposed to fuse tracks provided by the local interacting multiple model filters. During the fusion process, the duplicate information is removed by considering the first order redundant information between the local tracks. With extensive simulations, we show that the proposed algorithm improves the tracking accuracy in ballistic target tracking in the re-entry phase applications. PMID:27537883

  3. Sensor Fusion of Gaussian Mixtures for Ballistic Target Tracking in the Re-Entry Phase

    PubMed Central

    Lu, Kelin; Zhou, Rui

    2016-01-01

    A sensor fusion methodology for the Gaussian mixtures model is proposed for ballistic target tracking with unknown ballistic coefficients. To improve the estimation accuracy, a track-to-track fusion architecture is proposed to fuse tracks provided by the local interacting multiple model filters. During the fusion process, the duplicate information is removed by considering the first order redundant information between the local tracks. With extensive simulations, we show that the proposed algorithm improves the tracking accuracy in ballistic target tracking in the re-entry phase applications. PMID:27537883

  4. Optimization of Surface Acoustic Wave-Based Rate Sensors

    PubMed Central

    Xu, Fangqian; Wang, Wen; Shao, Xiuting; Liu, Xinlu; Liang, Yong

    2015-01-01

    The optimization of an surface acoustic wave (SAW)-based rate sensor incorporating metallic dot arrays was performed by using the approach of partial-wave analysis in layered media. The optimal sensor chip designs, including the material choice of piezoelectric crystals and metallic dots, dot thickness, and sensor operation frequency were determined theoretically. The theoretical predictions were confirmed experimentally by using the developed SAW sensor composed of differential delay line-oscillators and a metallic dot array deposited along the acoustic wave propagation path of the SAW delay lines. A significant improvement in sensor sensitivity was achieved in the case of 128° YX LiNbO3, and a thicker Au dot array, and low operation frequency were used to structure the sensor. PMID:26473865

  5. Data fusion on a distributed heterogeneous sensor network.

    SciTech Connect

    Lamborn, Peter; Williams, Pamela J.

    2006-02-01

    Alarm-based sensor systems are being explored as a tool to expand perimeter security for facilities and force protection. However, the collection of increased sensor data has resulted in an insufficient solution that includes faulty data points. Data analysis is needed to reduce nuisance and false alarms, which will improve officials decision making and confidence levels in the system's alarms. Moreover, operational costs can be allayed and losses mitigated if authorities are alerted only when a real threat is detected. In the current system, heuristics such as persistence of alarm and type of sensor that detected an event are used to guide officials responses. We hypothesize that fusing data from heterogeneous sensors in the sensor field can provide more complete situational awareness than looking at individual sensor data. We propose a two stage approach to reduce false alarms. First, we use self organizing maps to cluster sensors based on global positioning coordinates and then train classifiers on the within cluster data to obtain a local view of the event. Next, we train a classifier on the local results to compute a global solution. We investigate the use of machine learning techniques, such as k-nearest neighbor, neural networks, and support vector machines to improve alarm accuracy. On simulated sensor data, the proposed approach identifies false alarms with greater accuracy than a weighted voting algorithm.

  6. Advanced data visualization and sensor fusion: Conversion of techniques from medical imaging to Earth science

    NASA Technical Reports Server (NTRS)

    Savage, Richard C.; Chen, Chin-Tu; Pelizzari, Charles; Ramanathan, Veerabhadran

    1993-01-01

    Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES (Geostationary Operational Environmental Satellite), AVHRR (Advanced Very High Resolution Radiometer), and SSM/I (Special Sensor Microwave Imager) sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS (Earth Observation SystemData/Information System) prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.

  7. Helmet-mounted sensor fusion ATR for the dismounted soldier

    NASA Astrophysics Data System (ADS)

    Topiwala, Pankaj N.; Casasent, David

    2004-09-01

    Computer vision capabilities have long been available to advanced sensor systems such as those on aircraft, UAVs, helicopters, and ground scout vehicles; but to date, they have not been available to the dismounted soldier. This is understandable since the size/weight/cost metrics of carrying sensors and the image processing, interaction, and display capabilities, not to mention the power supply, have been prohibitive. But recent advances in uncooled IR sensors (up to QVGA), coupled with the steady advances in EO sensors (VGA+) and in microelectronics, are now making the prospect of computer vision for the foot soldier feasible for the first time. In this paper, we develop our initial approaches to all aspects of this problem: (a) sensor system integration, (b) image processing algorithms and initial hardware vision, and (c) display and interaction. As a prototype compute/display platform, we do initial development based on a lightweight commercial wearable computer and helmet-mounted display.

  8. Optimal geometry for a quartz multipurpose SPM sensor.

    PubMed

    Stirling, Julian

    2013-01-01

    We propose a geometry for a piezoelectric SPM sensor that can be used for combined AFM/LFM/STM. The sensor utilises symmetry to provide a lateral mode without the need to excite torsional modes. The symmetry allows normal and lateral motion to be completely isolated, even when introducing large tips to tune the dynamic properties to optimal values.

  9. Optimal geometry for a quartz multipurpose SPM sensor

    PubMed Central

    2013-01-01

    Summary We propose a geometry for a piezoelectric SPM sensor that can be used for combined AFM/LFM/STM. The sensor utilises symmetry to provide a lateral mode without the need to excite torsional modes. The symmetry allows normal and lateral motion to be completely isolated, even when introducing large tips to tune the dynamic properties to optimal values. PMID:23844342

  10. Scalable sensor management for automated fusion and tactical reconnaissance

    NASA Astrophysics Data System (ADS)

    Walls, Thomas J.; Wilson, Michael L.; Partridge, Darin C.; Haws, Jonathan R.; Jensen, Mark D.; Johnson, Troy R.; Petersen, Brad D.; Sullivan, Stephanie W.

    2013-05-01

    The capabilities of tactical intelligence, surveillance, and reconnaissance (ISR) payloads are expanding from single sensor imagers to integrated systems-of-systems architectures. Increasingly, these systems-of-systems include multiple sensing modalities that can act as force multipliers for the intelligence analyst. Currently, the separate sensing modalities operate largely independent of one another, providing a selection of operating modes but not an integrated intelligence product. We describe here a Sensor Management System (SMS) designed to provide a small, compact processing unit capable of managing multiple collaborative sensor systems on-board an aircraft. Its purpose is to increase sensor cooperation and collaboration to achieve intelligent data collection and exploitation. The SMS architecture is designed to be largely sensor and data agnostic and provide flexible networked access for both data providers and data consumers. It supports pre-planned and ad-hoc missions, with provisions for on-demand tasking and updates from users connected via data links. Management of sensors and user agents takes place over standard network protocols such that any number and combination of sensors and user agents, either on the local network or connected via data link, can register with the SMS at any time during the mission. The SMS provides control over sensor data collection to handle logging and routing of data products to subscribing user agents. It also supports the addition of algorithmic data processing agents for feature/target extraction and provides for subsequent cueing from one sensor to another. The SMS architecture was designed to scale from a small UAV carrying a limited number of payloads to an aircraft carrying a large number of payloads. The SMS system is STANAG 4575 compliant as a removable memory module (RMM) and can act as a vehicle specific module (VSM) to provide STANAG 4586 compliance (level-3 interoperability) to a non-compliant sensor system

  11. Optimal Magnetic Sensor Vests for Cardiac Source Imaging.

    PubMed

    Lau, Stephan; Petković, Bojana; Haueisen, Jens

    2016-01-01

    Magnetocardiography (MCG) non-invasively provides functional information about the heart. New room-temperature magnetic field sensors, specifically magnetoresistive and optically pumped magnetometers, have reached sensitivities in the ultra-low range of cardiac fields while allowing for free placement around the human torso. Our aim is to optimize positions and orientations of such magnetic sensors in a vest-like arrangement for robust reconstruction of the electric current distributions in the heart. We optimized a set of 32 sensors on the surface of a torso model with respect to a 13-dipole cardiac source model under noise-free conditions. The reconstruction robustness was estimated by the condition of the lead field matrix. Optimization improved the condition of the lead field matrix by approximately two orders of magnitude compared to a regular array at the front of the torso. Optimized setups exhibited distributions of sensors over the whole torso with denser sampling above the heart at the front and back of the torso. Sensors close to the heart were arranged predominantly tangential to the body surface. The optimized sensor setup could facilitate the definition of a standard for sensor placement in MCG and the development of a wearable MCG vest for clinical diagnostics. PMID:27231910

  12. Optimal Magnetic Sensor Vests for Cardiac Source Imaging

    PubMed Central

    Lau, Stephan; Petković, Bojana; Haueisen, Jens

    2016-01-01

    Magnetocardiography (MCG) non-invasively provides functional information about the heart. New room-temperature magnetic field sensors, specifically magnetoresistive and optically pumped magnetometers, have reached sensitivities in the ultra-low range of cardiac fields while allowing for free placement around the human torso. Our aim is to optimize positions and orientations of such magnetic sensors in a vest-like arrangement for robust reconstruction of the electric current distributions in the heart. We optimized a set of 32 sensors on the surface of a torso model with respect to a 13-dipole cardiac source model under noise-free conditions. The reconstruction robustness was estimated by the condition of the lead field matrix. Optimization improved the condition of the lead field matrix by approximately two orders of magnitude compared to a regular array at the front of the torso. Optimized setups exhibited distributions of sensors over the whole torso with denser sampling above the heart at the front and back of the torso. Sensors close to the heart were arranged predominantly tangential to the body surface. The optimized sensor setup could facilitate the definition of a standard for sensor placement in MCG and the development of a wearable MCG vest for clinical diagnostics. PMID:27231910

  13. Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device.

    PubMed

    He, Xiang; Aloi, Daniel N; Li, Jia

    2015-01-01

    Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design. PMID:26694387

  14. Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device

    PubMed Central

    He, Xiang; Aloi, Daniel N.; Li, Jia

    2015-01-01

    Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design. PMID:26694387

  15. Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device.

    PubMed

    He, Xiang; Aloi, Daniel N; Li, Jia

    2015-12-14

    Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design.

  16. Computer vision and sensor fusion for detecting buried objects

    SciTech Connect

    Clark, G.A.; Hernandez, J.E.; Sengupta, S.K.; Sherwood, R.J.; Schaich, P.C.; Buhl, M.R.; Kane, R.J.; DelGrande, N.K.

    1992-10-01

    Given multiple images of the surface of the earth from dual-band infrared sensors, our system fuses information from the sensors to reduce the effects of clutter and improve the ability to detect buried or surface target sites. Supervised learning pattern classifiers (including neural networks,) are used. We present results of experiments to detect buried land mines from real data, and evaluate the usefulness of fusing information from multiple sensor types. The novelty of the work lies mostly in the combination of the algorithms and their application to the very important and currently unsolved problem of detecting buried land mines from an airborne standoff platform.

  17. Neural network implementations of data association algorithms for sensor fusion

    NASA Technical Reports Server (NTRS)

    Brown, Donald E.; Pittard, Clarence L.; Martin, Worthy N.

    1989-01-01

    The paper is concerned with locating a time varying set of entities in a fixed field when the entities are sensed at discrete time instances. At a given time instant a collection of bivariate Gaussian sensor reports is produced, and these reports estimate the location of a subset of the entities present in the field. A database of reports is maintained, which ideally should contain one report for each entity sensed. Whenever a collection of sensor reports is received, the database must be updated to reflect the new information. This updating requires association processing between the database reports and the new sensor reports to determine which pairs of sensor and database reports correspond to the same entity. Algorithms for performing this association processing are presented. Neural network implementation of the algorithms, along with simulation results comparing the approaches are provided.

  18. Geometrical optimization of a local ballistic magnetic sensor

    SciTech Connect

    Kanda, Yuhsuke; Hara, Masahiro; Nomura, Tatsuya; Kimura, Takashi

    2014-04-07

    We have developed a highly sensitive local magnetic sensor by using a ballistic transport property in a two-dimensional conductor. A semiclassical simulation reveals that the sensitivity increases when the geometry of the sensor and the spatial distribution of the local field are optimized. We have also experimentally demonstrated a clear observation of a magnetization process in a permalloy dot whose size is much smaller than the size of an optimized ballistic magnetic sensor fabricated from a GaAs/AlGaAs two-dimensional electron gas.

  19. Effect of retransmission and retrodiction on estimation and fusion in long-haul sensor networks

    DOE PAGES

    Liu, Qiang; Wang, Xin; Rao, Nageswara S. V.; Brigham, Katharine; Vijaya Kumar, B. V. K.

    2016-02-01

    In a long-haul sensor network, sensors are remotely deployed over a large geographical area to perform certain tasks, such as target tracking. In this work, we study the scenario where sensors take measurements of one or more dynamic targets and send state estimates of the targets to a fusion center via satellite links. The severe loss and delay inherent over the satellite channels reduce the number of estimates successfully arriving at the fusion center, thereby limiting the potential fusion gain and resulting in suboptimal accuracy performance of the fused estimates. In addition, the errors in target-sensor data association can alsomore » degrade the estimation performance. To mitigate the effect of imperfect communications on state estimation and fusion, we consider retransmission and retrodiction. The system adopts certain retransmission-based transport protocols so that lost messages can be recovered over time. Besides, retrodiction/smoothing techniques are applied so that the chances of incurring excess delay due to retransmission are greatly reduced. We analyze the extent to which retransmission and retrodiction can improve the performance of delay-sensitive target tracking tasks under variable communication loss and delay conditions. Lastly, simulation results of a ballistic target tracking application are shown in the end to demonstrate the validity of our analysis.« less

  20. Sensor fusion-based security concept on airports with a rotating millimetre wave person scanner

    NASA Astrophysics Data System (ADS)

    Hantscher, Sebastian; Lang, Stefan; Hägelen, Manfred; Essen, Helmut; Tessmann, Axel

    2010-10-01

    This paper gives an overview about a new security concept on airports. Because single systems have not often the desired reliability, the concept is based on the fusion of different sensors. Moreover, first measurements of a 94 GHz person scanner with circular synthetic aperture are presented showing the capability to detect metallic as well as nonmetallic objects without violating the personal privacy.

  1. Recent results and challenges in development of metallic Hall sensors for fusion reactors

    SciTech Connect

    Ďuran, Ivan; Mušálek, Radek; Kovařík, Karel; Sentkerestiová, Jana; Kohout, Michal

    2014-08-21

    Reliable and precise diagnostic of local magnetic field is crucial for successful operation of future thermonuclear fusion reactors based on magnetic confinement. Magnetic sensors at these devices will experience an extremely demanding operational environment with large radiation and thermal loads in combination with required long term, reliable, and service-free performance. Neither present day commercial nor laboratory measurement systems comply with these requirements. Metallic Hall sensors based on e.g. copper or bismuth could potentially satisfy these needs. We present the technology for manufacturing of such sensors and some initial results on characterization of their properties.

  2. Embedded Relative Navigation Sensor Fusion Algorithms for Autonomous Rendezvous and Docking Missions

    NASA Technical Reports Server (NTRS)

    DeKock, Brandon K.; Betts, Kevin M.; McDuffie, James H.; Dreas, Christine B.

    2008-01-01

    bd Systems (a subsidiary of SAIC) has developed a suite of embedded relative navigation sensor fusion algorithms to enable NASA autonomous rendezvous and docking (AR&D) missions. Translational and rotational Extended Kalman Filters (EKFs) were developed for integrating measurements based on the vehicles' orbital mechanics and high-fidelity sensor error models and provide a solution with increased accuracy and robustness relative to any single relative navigation sensor. The filters were tested tinough stand-alone covariance analysis, closed-loop testing with a high-fidelity multi-body orbital simulation, and hardware-in-the-loop (HWIL) testing in the Marshall Space Flight Center (MSFC) Flight Robotics Laboratory (FRL).

  3. Fusion: ultra-high-speed and IR image sensors

    NASA Astrophysics Data System (ADS)

    Etoh, T. Goji; Dao, V. T. S.; Nguyen, Quang A.; Kimata, M.

    2015-08-01

    Most targets of ultra-high-speed video cameras operating at more than 1 Mfps, such as combustion, crack propagation, collision, plasma, spark discharge, an air bag at a car accident and a tire under a sudden brake, generate sudden heat. Researchers in these fields require tools to measure the high-speed motion and heat simultaneously. Ultra-high frame rate imaging is achieved by an in-situ storage image sensor. Each pixel of the sensor is equipped with multiple memory elements to record a series of image signals simultaneously at all pixels. Image signals stored in each pixel are read out after an image capturing operation. In 2002, we developed an in-situ storage image sensor operating at 1 Mfps 1). However, the fill factor of the sensor was only 15% due to a light shield covering the wide in-situ storage area. Therefore, in 2011, we developed a backside illuminated (BSI) in-situ storage image sensor to increase the sensitivity with 100% fill factor and a very high quantum efficiency 2). The sensor also achieved a much higher frame rate,16.7 Mfps, thanks to the wiring on the front side with more freedom 3). The BSI structure has another advantage that it has less difficulties in attaching an additional layer on the backside, such as scintillators. This paper proposes development of an ultra-high-speed IR image sensor in combination of advanced nano-technologies for IR imaging and the in-situ storage technology for ultra-highspeed imaging with discussion on issues in the integration.

  4. Visual sensor fusion for active security in robotic industrial environments

    NASA Astrophysics Data System (ADS)

    Robla, Sandra; Llata, Jose R.; Torre-Ferrero, Carlos; Sarabia, Esther G.; Becerra, Victor; Perez-Oria, Juan

    2014-12-01

    This work presents a method of information fusion involving data captured by both a standard charge-coupled device (CCD) camera and a time-of-flight (ToF) camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time-of-flight information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time, this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localisation. Further development of these methods will make it possible to identify objects and their position in the real world and to use this information to prevent possible collisions between the robot and such objects.

  5. Optimization of Strip Isolation for Silicon Sensors

    NASA Astrophysics Data System (ADS)

    Valentan, M.; Bergauer, T.; Dragicevic, M.; Friedl, M.; Irmler, C.; Huemer, E.; Treberspurg, W.

    Precision machines like electron-positron-colliders and b-factories demand for low material budget and high position resolution when it comes to particle tracking. A low material budget can be achieved by using thin double-sided silicon detectors (DSSDs) and lightweight construction. Since thin sensors give low signals, one has to be very careful to achieve high charge collection efficiency, which requires an appropriate sensor design. In this paper we present a detailed investigation of different p-stop patterns used for strip isolation on the n-side of double-sided microstrip sensors with n-type bulk. We designed test sensors featuring the common p-stop, the atoll p-stop and a combined p-stop pattern, and for every pattern four different geometric layouts were considered. These sensors were tested at the Super Proton Synchrotron (SPS) at CERN (Geneva, Switzerland) in a 120 GeV/c hadron beam. Then they were irradiated to 700 kGy with a 60Co source and subsequently tested in the same beam as before. One geometric layout of the atoll p-stop pattern turned out to perform best, both before and after irradiation. The conclusions of these tests will be applied to the design of DSSDs for the Belle II experiment at KEK (Tsukuba, Japan).

  6. Naval target classification by fusion of IR and EO sensors

    NASA Astrophysics Data System (ADS)

    Giompapa, S.; Croci, R.; Di Stefano, R.; Farina, A.; Gini, F.; Graziano, A.; Lapierre, F.

    2007-10-01

    This paper describes the classification function of naval targets performed by an infrared camera (IR) and an electro-optical camera (EO) that operate in a more complex multisensor system for the surveillance of a coastal region. The following naval targets are considered: high speed dinghy, motor boat, fishing boat, oil tanker. Target classification is automatically performed by exploiting the knowledge of the sensor confusion matrix (CM). The CM is analytically computed as a function of the sensor noise features, the sensor resolution, and the dimension of the involved image database. For both the sensors, a database of images is generated exploiting a three-dimensional (3D) Computer Aided Design (CAD) of the target, for the four types of ship mentioned above. For the EO camera, the image generation is simply obtained by the projection of the 3D CAD on the camera focal plane. For the IR images simulation, firstly the surface temperatures are computed using an Open-source Software for Modelling and Simulation of Infrared Signatures (OSMOSIS) that efficiently integrates the dependence of the emissivity upon the surface temperature, the wavelength, and the elevation angle. The software is applicable to realistic ship geometries. Secondly, these temperatures and the environment features are used to predict realistic IR images. The local decisions on the class are made using the elements of the confusion matrix of each sensor and they are fused according to a maximum likelihood (ML) rule. The global performance of the classification process is measured in terms of the global confusion matrix of the integrated system. This analytical approach can effectively reduce the computational load of a Monte Carlo simulation, when the sensors described here are introduced in a more complex multisensor system for the maritime surveillance.

  7. Advanced data visualization and sensor fusion: Conversion of techniques from medical imaging to Earth science

    NASA Technical Reports Server (NTRS)

    Savage, Richard C.; Chen, Chin-Tu; Pelizzari, Charles; Ramanathan, Veerabhadran

    1992-01-01

    Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES, AVHRR, and SSM/I sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.

  8. All-IP-Ethernet architecture for real-time sensor-fusion processing

    NASA Astrophysics Data System (ADS)

    Hiraki, Kei; Inaba, Mary; Tezuka, Hiroshi; Tomari, Hisanobu; Koizumi, Kenichi; Kondo, Shuya

    2016-03-01

    Serendipter is a device that distinguishes and selects very rare particles and cells from huge amount of population. We are currently designing and constructing information processing system for a Serendipter. The information processing system for Serendipter is a kind of sensor-fusion system but with much more difficulties: To fulfill these requirements, we adopt All IP based architecture: All IP-Ethernet based data processing system consists of (1) sensor/detector directly output data as IP-Ethernet packet stream, (2) single Ethernet/TCP/IP streams by a L2 100Gbps Ethernet switch, (3) An FPGA board with 100Gbps Ethernet I/F connected to the switch and a Xeon based server. Circuits in the FPGA include 100Gbps Ethernet MAC, buffers and preprocessing, and real-time Deep learning circuits using multi-layer neural networks. Proposed All-IP architecture solves existing problem to construct large-scale sensor-fusion systems.

  9. Multi-sensor fusion with interacting multiple model filter for improved aircraft position accuracy.

    PubMed

    Cho, Taehwan; Lee, Changho; Choi, Sangbang

    2013-01-01

    The International Civil Aviation Organization (ICAO) has decided to adopt Communications, Navigation, and Surveillance/Air Traffic Management (CNS/ATM) as the 21st century standard for navigation. Accordingly, ICAO members have provided an impetus to develop related technology and build sufficient infrastructure. For aviation surveillance with CNS/ATM, Ground-Based Augmentation System (GBAS), Automatic Dependent Surveillance-Broadcast (ADS-B), multilateration (MLAT) and wide-area multilateration (WAM) systems are being established. These sensors can track aircraft positions more accurately than existing radar and can compensate for the blind spots in aircraft surveillance. In this paper, we applied a novel sensor fusion method with Interacting Multiple Model (IMM) filter to GBAS, ADS-B, MLAT, and WAM data in order to improve the reliability of the aircraft position. Results of performance analysis show that the position accuracy is improved by the proposed sensor fusion method with the IMM filter.

  10. Efficient Sensor Placement Optimization Using Gradient Descent and Probabilistic Coverage

    PubMed Central

    Akbarzadeh, Vahab; Lévesque, Julien-Charles; Gagné, Christian; Parizeau, Marc

    2014-01-01

    We are proposing an adaptation of the gradient descent method to optimize the position and orientation of sensors for the sensor placement problem. The novelty of the proposed method lies in the combination of gradient descent optimization with a realistic model, which considers both the topography of the environment and a set of sensors with directional probabilistic sensing. The performance of this approach is compared with two other black box optimization methods over area coverage and processing time. Results show that our proposed method produces competitive results on smaller maps and superior results on larger maps, while requiring much less computation than the other optimization methods to which it has been compared. PMID:25196164

  11. Sensor fusion for assured vision in space applications

    NASA Technical Reports Server (NTRS)

    Collin, Marie-France; Krishen, Kumar

    1993-01-01

    By using emittance and reflectance radiation models, the effects of angle of observation, polarization, and spectral content are analyzed to characterize the geometrical and physical properties--reflectivity, emissivity, orientation, dielectric properties, and roughness--of a sensed surface. Based on this analysis, the use of microwave, infrared, and optical sensing is investigated to assure the perception of surfaces on a typical lunar outpost. Also, the concept of employing several sensors on a lunar outpost is explored. An approach for efficient hardware implementation of the fused sensor systems is discussed.

  12. Report of the Fusion Energy Sciences Advisory Committee. Panel on Integrated Simulation and Optimization of Magnetic Fusion Systems

    SciTech Connect

    Dahlburg, Jill; Corones, James; Batchelor, Donald; Bramley, Randall; Greenwald, Martin; Jardin, Stephen; Krasheninnikov, Sergei; Laub, Alan; Leboeuf, Jean-Noel; Lindl, John; Lokke, William; Rosenbluth, Marshall; Ross, David; Schnack, Dalton

    2002-11-01

    Fusion is potentially an inexhaustible energy source whose exploitation requires a basic understanding of high-temperature plasmas. The development of a science-based predictive capability for fusion-relevant plasmas is a challenge central to fusion energy science, in which numerical modeling has played a vital role for more than four decades. A combination of the very wide range in temporal and spatial scales, extreme anisotropy, the importance of geometric detail, and the requirement of causality which makes it impossible to parallelize over time, makes this problem one of the most challenging in computational physics. Sophisticated computational models are under development for many individual features of magnetically confined plasmas and increases in the scope and reliability of feasible simulations have been enabled by increased scientific understanding and improvements in computer technology. However, full predictive modeling of fusion plasmas will require qualitative improvements and innovations to enable cross coupling of a wider variety of physical processes and to allow solution over a larger range of space and time scales. The exponential growth of computer speed, coupled with the high cost of large-scale experimental facilities, makes an integrated fusion simulation initiative a timely and cost-effective opportunity. Worldwide progress in laboratory fusion experiments provides the basis for a recent FESAC recommendation to proceed with a burning plasma experiment (see FESAC Review of Burning Plasma Physics Report, September 2001). Such an experiment, at the frontier of the physics of complex systems, would be a huge step in establishing the potential of magnetic fusion energy to contribute to the world’s energy security. An integrated simulation capability would dramatically enhance the utilization of such a facility and lead to optimization of toroidal fusion plasmas in general. This science-based predictive capability, which was cited in the FESAC

  13. Field of view selection for optimal airborne imaging sensor performance

    NASA Astrophysics Data System (ADS)

    Goss, Tristan M.; Barnard, P. Werner; Fildis, Halidun; Erbudak, Mustafa; Senger, Tolga; Alpman, Mehmet E.

    2014-05-01

    The choice of the Field of View (FOV) of imaging sensors used in airborne targeting applications has major impact on the overall performance of the system. Conducting a market survey from published data on sensors used in stabilized airborne targeting systems shows a trend of ever narrowing FOVs housed in smaller and lighter volumes. This approach promotes the ever increasing geometric resolution provided by narrower FOVs, while it seemingly ignores the influences the FOV selection has on the sensor's sensitivity, the effects of diffraction, the influences of sight line jitter and collectively the overall system performance. This paper presents a trade-off methodology to select the optimal FOV for an imaging sensor that is limited in aperture diameter by mechanical constraints (such as space/volume available and window size) by balancing the influences FOV has on sensitivity and resolution and thereby optimizing the system's performance. The methodology may be applied to staring array based imaging sensors across all wavebands from visible/day cameras through to long wave infrared thermal imagers. Some examples of sensor analysis applying the trade-off methodology are given that highlights the performance advantages that can be gained by maximizing the aperture diameters and choosing the optimal FOV for an imaging sensor used in airborne targeting applications.

  14. Wireless sensor fusion approach for monitoring chemical mechanical planarization (CMP) process

    NASA Astrophysics Data System (ADS)

    Ohri, Amit

    Chemical mechanical planarization (CMP) is used in the microelectronics and optical industries for local as well as global planarity and for producing mirror finished surfaces. Roughness (Ra), within-non-uniformity (WIWNU), and material removal rate (MRR) are the major performance variables in polishing. CMP is a complex process involving some 36 input variables. Analysis of the review of the literatures showed that static models that use process parameters are inadequate for estimating and monitoring the performance variables in the CMP process. Pad-level interactions play a major role in polishing. Sensor based monitoring techniques enables monitoring of the CMP process. Additionally, sensor fusion techniques may facilitate in improving the robustness and monitoring the process beyond using one sensor. In this work, wireless vibration (Z-axis) and temperature sensors mounted on a bench top polisher (ECOMET polisher from Buehler) are used to monitor the material removal rate (MRR) and surface finish (Ra). The wireless sensor platform has a sampling rate of 500 Hz for the vibration sensor and 4 Hz for the temperature sensor. Alumina-based alkaline slurry is used in polishing process. The process conditions include two loading conditions (10 lb and 5 lb) and two rotational speeds (500 rpm and 300 rpm). The polishing studies were conducted on a 1.6" copper samples and Microcloth pad (from Buehler). The overall approach used involves relating the various sensors signal features to MRR and Ra from the CMP process. The vibration features were extracted using statistical, frequency, and RQA (non-linear) analysis techniques. The vibration features were combined with temperature features to build multiple linear regression models. The regression fitting accuracy for the roughness model is ˜ 93% using the statistical features, such as maximum and kurtosis, time-frequency features, such as energy, nonlinear features such as LAM and Lmax and thermal features such as net

  15. Monitoring soil health with a sensor fusion approach

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sensor-based approaches to assessment and quantification of soil health are important to facilitate cost-effective, site-specific soil management. While traditional laboratory analysis is effective for assessing soil health (or soil quality) at a few sites, such an approach quickly becomes infeasibl...

  16. Fusion of smartphone motion sensors for physical activity recognition.

    PubMed

    Shoaib, Muhammad; Bosch, Stephan; Incel, Ozlem Durmaz; Scholten, Hans; Havinga, Paul J M

    2014-06-10

    For physical activity recognition, smartphone sensors, such as an accelerometer and a gyroscope, are being utilized in many research studies. So far, particularly, the accelerometer has been extensively studied. In a few recent studies, a combination of a gyroscope, a magnetometer (in a supporting role) and an accelerometer (in a lead role) has been used with the aim to improve the recognition performance. How and when are various motion sensors, which are available on a smartphone, best used for better recognition performance, either individually or in combination? This is yet to be explored. In order to investigate this question, in this paper, we explore how these various motion sensors behave in different situations in the activity recognition process. For this purpose, we designed a data collection experiment where ten participants performed seven different activities carrying smart phones at different positions. Based on the analysis of this data set, we show that these sensors, except the magnetometer, are each capable of taking the lead roles individually, depending on the type of activity being recognized, the body position, the used data features and the classification method employed (personalized or generalized). We also show that their combination only improves the overall recognition performance when their individual performances are not very high, so that there is room for performance improvement. We have made our data set and our data collection application publicly available, thereby making our experiments reproducible.

  17. Statistical methods of combining information: Applications to sensor data fusion

    SciTech Connect

    Burr, T.

    1996-12-31

    This paper reviews some statistical approaches to combining information from multiple sources. Promising new approaches will be described, and potential applications to combining not-so-different data sources such as sensor data will be discussed. Experiences with one real data set are described.

  18. Optimal flow sensor placement on wastewater treatment plants.

    PubMed

    Villez, Kris; Vanrolleghem, Peter A; Corominas, Lluís

    2016-09-15

    Obtaining high quality data collected on wastewater treatment plants is gaining increasing attention in the wastewater engineering literature. Typical studies focus on recognition of faulty data with a given set of installed sensors on a wastewater treatment plant. Little attention is however given to how one can install sensors in such a way that fault detection and identification can be improved. In this work, we develop a method to obtain Pareto optimal sensor layouts in terms of cost, observability, and redundancy. Most importantly, the resulting method allows reducing the large set of possibilities to a minimal set of sensor layouts efficiently for any wastewater treatment plant on the basis of structural criteria only, with limited sensor information, and without prior data collection. In addition, the developed optimization scheme is fast. Practically important is that the number of sensors needed for both observability of all flows and redundancy of all flow sensors is only one more compared to the number of sensors needed for observability of all flows in the studied wastewater treatment plant configurations.

  19. Optimal flow sensor placement on wastewater treatment plants.

    PubMed

    Villez, Kris; Vanrolleghem, Peter A; Corominas, Lluís

    2016-09-15

    Obtaining high quality data collected on wastewater treatment plants is gaining increasing attention in the wastewater engineering literature. Typical studies focus on recognition of faulty data with a given set of installed sensors on a wastewater treatment plant. Little attention is however given to how one can install sensors in such a way that fault detection and identification can be improved. In this work, we develop a method to obtain Pareto optimal sensor layouts in terms of cost, observability, and redundancy. Most importantly, the resulting method allows reducing the large set of possibilities to a minimal set of sensor layouts efficiently for any wastewater treatment plant on the basis of structural criteria only, with limited sensor information, and without prior data collection. In addition, the developed optimization scheme is fast. Practically important is that the number of sensors needed for both observability of all flows and redundancy of all flow sensors is only one more compared to the number of sensors needed for observability of all flows in the studied wastewater treatment plant configurations. PMID:27258618

  20. Three-band MRI image fusion utilizing the wavelet-based method optimized with two quantitative fusion metrics

    NASA Astrophysics Data System (ADS)

    Zheng, Yufeng; Elmaghraby, Adel S.; Frigui, Hichem

    2006-03-01

    In magnetic resonance imaging (MRI), there are three bands of images ("MRI triplet") available, which are T1-, T2- and PD-weighted images. The three images of a MRI triplet provide complementary structure information and therefore it is useful for diagnosis and subsequent analysis to combine three-band images into one. We propose an advanced discrete wavelet transform (αDWT) for three-band MRI image fusion and the αDWT algorithm is further optimized utilizing two quantitative fusion metrics - the image quality index (IQI) and ratio spatial frequency error (rSFe). In the aDWT method, principle component analysis (PCA) and morphological processing are incorporated into a regular DWT fusion algorithm. Furthermore, the αDWT has two adjustable parameters - the level of DWT decomposition (L d) and the length of the selected wavelet (L w) that determinately affect the fusion result. The fused image quality can be quantitatively measured with the established metrics - IQI and rSFe. Varying the control parameters (L d and L w), an iterative fusion procedure can be implemented and running until an optimized fusion is achieved. We fused and analyzed several MRI triplets from the Visible Human Project ® female dataset. From the quantitative and qualitative evaluations of fused images, we found that (1) the αDWTi-IQI algorithm produces a smoothed image whereas the αDWTi-rSFe algorithm yields a sharpened image, (2) fused image "T1+T2" is the most informative one in comparison with other two-in-one fusions (PD+T1 and PD+T2), (3) for three-in-one fusions, no significant difference is observed among the three fusions of (PD+T1)+T2, (PD+T2)+T1 and (T1+T2)+PD, thus the order of fusion does not play an important role. The fused images can significantly benefit medical diagnosis and also the further image processing such as multi-modality image fusion (with CT images), visualization (colorization), segmentation, classification and computer-aided diagnosis (CAD).

  1. Particle swarm optimization for the clustering of wireless sensors

    NASA Astrophysics Data System (ADS)

    Tillett, Jason C.; Rao, Raghuveer M.; Sahin, Ferat; Rao, T. M.

    2003-07-01

    Clustering is necessary for data aggregation, hierarchical routing, optimizing sleep patterns, election of extremal sensors, optimizing coverage and resource allocation, reuse of frequency bands and codes, and conserving energy. Optimal clustering is typically an NP-hard problem. Solutions to NP-hard problems involve searches through vast spaces of possible solutions. Evolutionary algorithms have been applied successfully to a variety of NP-hard problems. We explore one such approach, Particle Swarm Optimization (PSO), an evolutionary programming technique where a 'swarm' of test solutions, analogous to a natural swarm of bees, ants or termites, is allowed to interact and cooperate to find the best solution to the given problem. We use the PSO approach to cluster sensors in a sensor network. The energy efficiency of our clustering in a data-aggregation type sensor network deployment is tested using a modified LEACH-C code. The PSO technique with a recursive bisection algorithm is tested against random search and simulated annealing; the PSO technique is shown to be robust. We further investigate developing a distributed version of the PSO algorithm for clustering optimally a wireless sensor network.

  2. Optimal weighted suprathreshold stochastic resonance with multigroup saturating sensors

    NASA Astrophysics Data System (ADS)

    Xu, Liyan; Duan, Fabing; Abbott, Derek; McDonnell, Mark D.

    2016-09-01

    Suprathreshold stochastic resonance (SSR) describes a noise-enhanced effect that occurs, not in a single element, but rather in an array of nonlinear elements when the signal is no longer subthreshold. Within the context of SSR, we investigate the optimization problem of signal recovery through an array of saturating sensors where the response of each element can be optimally weighted prior to summation, with a performance measure of mean square error (MSE). We consider groups of sensors. Individual sensors within each group have identical parameters, but each group has distinct parameters. We find that optimally weighting the sensor responses provides a lower MSE in comparison with the unweighted case for weak and moderate noise intensities. Moreover, as the slope parameter of the nonlinear sensors increases, the MSE superiority of the optimally weighted array shows a peak, and then tends to a fixed value. These results indicate that SSR with optimal weights, as a general mechanism of enhancement by noise, is of potential interest to signal recovery.

  3. Multi-sensor data fusion for measurement of complex freeform surfaces

    NASA Astrophysics Data System (ADS)

    Ren, M. J.; Liu, M. Y.; Cheung, C. F.; Yin, Y. H.

    2016-01-01

    Along with the rapid development of the science and technology in fields such as space optics, multi-scale enriched freeform surfaces are widely used to enhance the performance of the optical systems in both functionality and size reduction. Multi-sensor technology is considered as one of the promising methods to measure and characterize these surfaces at multiple scales. This paper presents a multi-sensor data fusion based measurement method to purposely extract the geometric information of the components with different scales which is used to establish a holistic geometry of the surface via data fusion. To address the key problems of multi-sensor data fusion, an intrinsic feature pattern based surface registration method is developed to transform the measured datasets to a common coordinate frame. Gaussian zero-order regression filter is then used to separate each measured data in different scales, and the datasets are fused based on an edge intensity data fusion algorithm within the same wavelength. The fused data at different scales is then merged to form a new surface with holistic multiscale information. Experimental study is presented to verify the effectiveness of the proposed method.

  4. Multi-Sensor Data Fusion Using a Relevance Vector Machine Based on an Ant Colony for Gearbox Fault Detection.

    PubMed

    Liu, Zhiwen; Guo, Wei; Tang, Zhangchun; Chen, Yongqiang

    2015-08-31

    Sensors play an important role in the modern manufacturing and industrial processes. Their reliability is vital to ensure reliable and accurate information for condition based maintenance. For the gearbox, the critical machine component in the rotating machinery, the vibration signals collected by sensors are usually noisy. At the same time, the fault detection results based on the vibration signals from a single sensor may be unreliable and unstable. To solve this problem, this paper proposes an intelligent multi-sensor data fusion method using the relevance vector machine (RVM) based on an ant colony optimization algorithm (ACO-RVM) for gearboxes' fault detection. RVM is a sparse probability model based on support vector machine (SVM). RVM not only has higher detection accuracy, but also better real-time accuracy compared with SVM. The ACO algorithm is used to determine kernel parameters of RVM. Moreover, the ensemble empirical mode decomposition (EEMD) is applied to preprocess the raw vibration signals to eliminate the influence caused by noise and other unrelated signals. The distance evaluation technique (DET) is employed to select dominant features as input of the ACO-RVM, so that the redundancy and inference in a large amount of features can be removed. Two gearboxes are used to demonstrate the performance of the proposed method. The experimental results show that the ACO-RVM has higher fault detection accuracy than the RVM with normal the cross-validation (CV).

  5. Multi-Sensor Data Fusion Using a Relevance Vector Machine Based on an Ant Colony for Gearbox Fault Detection

    PubMed Central

    Liu, Zhiwen; Guo, Wei; Tang, Zhangchun; Chen, Yongqiang

    2015-01-01

    Sensors play an important role in the modern manufacturing and industrial processes. Their reliability is vital to ensure reliable and accurate information for condition based maintenance. For the gearbox, the critical machine component in the rotating machinery, the vibration signals collected by sensors are usually noisy. At the same time, the fault detection results based on the vibration signals from a single sensor may be unreliable and unstable. To solve this problem, this paper proposes an intelligent multi-sensor data fusion method using the relevance vector machine (RVM) based on an ant colony optimization algorithm (ACO-RVM) for gearboxes’ fault detection. RVM is a sparse probability model based on support vector machine (SVM). RVM not only has higher detection accuracy, but also better real-time accuracy compared with SVM. The ACO algorithm is used to determine kernel parameters of RVM. Moreover, the ensemble empirical mode decomposition (EEMD) is applied to preprocess the raw vibration signals to eliminate the influence caused by noise and other unrelated signals. The distance evaluation technique (DET) is employed to select dominant features as input of the ACO-RVM, so that the redundancy and inference in a large amount of features can be removed. Two gearboxes are used to demonstrate the performance of the proposed method. The experimental results show that the ACO-RVM has higher fault detection accuracy than the RVM with normal the cross-validation (CV). PMID:26334280

  6. A Simulation Environment for Benchmarking Sensor Fusion-Based Pose Estimators

    PubMed Central

    Ligorio, Gabriele; Sabatini, Angelo Maria

    2015-01-01

    In-depth analysis and performance evaluation of sensor fusion-based estimators may be critical when performed using real-world sensor data. For this reason, simulation is widely recognized as one of the most powerful tools for algorithm benchmarking. In this paper, we present a simulation framework suitable for assessing the performance of sensor fusion-based pose estimators. The systems used for implementing the framework were magnetic/inertial measurement units (MIMUs) and a camera, although the addition of further sensing modalities is straightforward. Typical nuisance factors were also included for each sensor. The proposed simulation environment was validated using real-life sensor data employed for motion tracking. The higher mismatch between real and simulated sensors was about 5% of the measured quantity (for the camera simulation), whereas a lower correlation was found for an axis of the gyroscope (0.90). In addition, a real benchmarking example of an extended Kalman filter for pose estimation from MIMU and camera data is presented. PMID:26703603

  7. A Simulation Environment for Benchmarking Sensor Fusion-Based Pose Estimators.

    PubMed

    Ligorio, Gabriele; Sabatini, Angelo Maria

    2015-01-01

    In-depth analysis and performance evaluation of sensor fusion-based estimators may be critical when performed using real-world sensor data. For this reason, simulation is widely recognized as one of the most powerful tools for algorithm benchmarking. In this paper, we present a simulation framework suitable for assessing the performance of sensor fusion-based pose estimators. The systems used for implementing the framework were magnetic/inertial measurement units (MIMUs) and a camera, although the addition of further sensing modalities is straightforward. Typical nuisance factors were also included for each sensor. The proposed simulation environment was validated using real-life sensor data employed for motion tracking. The higher mismatch between real and simulated sensors was about 5% of the measured quantity (for the camera simulation), whereas a lower correlation was found for an axis of the gyroscope (0.90). In addition, a real benchmarking example of an extended Kalman filter for pose estimation from MIMU and camera data is presented. PMID:26703603

  8. Optimal scheduling of multiple sensors in continuous time.

    PubMed

    Wu, Xiang; Zhang, Kanjian; Sun, Changyin

    2014-05-01

    This paper considers an optimal sensor scheduling problem in continuous time. In order to make the model more close to the practical problems, suppose that the following conditions are satisfied: only one sensor may be active at any one time; an admissible sensor schedule is a piecewise constant function with a finite number of switches; and each sensor either doesn't operate or operates for a minimum non-negligible amount of time. However, the switching times are unknown, and the feasible region isn't connected. Thus, it's difficult to solve the problem by conventional optimization techniques. To overcome this difficulty, by combining a binary relaxation, a time-scaling transformation and an exact penalty function, an algorithm is developed for solving this problem. Numerical results show that the algorithm is effective.

  9. Optimal sensor location for parameter identification in soft clay

    NASA Astrophysics Data System (ADS)

    Hölter, R.; Mahmoudi, E.; Schanz, T.

    2015-10-01

    Performing parameter identification for model calibration prior to numerical simulation is an essential task in geotechnical engineering. However, it has to be kept in mind that the accuracy of the obtained parameter is closely related to the chosen experimental set-up, such as the number of sensors as well as their location. A well considered position of sensors can increase the quality of the measurement and reduce the number of monitoring points. This paper illustrates this concept by means of a loading device that is used to identify the stiffness and permeability factor of soft clays. With an initial set-up of the measurement devices the pore water pressure and the vertical displacements are recorded and used to identify the aforementioned parameters. Starting from these identified parameters, the optimal measurement set-up is investigated with a method based on global sensitivity analysis. This method shows an optimal sensor location assuming three sensors for each measured quantity.

  10. Software for multimodal battlefield signal modeling and optimal sensor placement

    NASA Astrophysics Data System (ADS)

    Yamamoto, Kenneth K.; Vecherin, Sergey N.; Wilson, D. Keith; Borden, Christian T.; Bettencourt, Elizabeth; Pettit, Chris L.

    2012-05-01

    Effective use of passive and active sensors for surveillance, security, and intelligence must consider terrain and atmospheric effects on the sensor performance. Several years ago, U.S. Army ERDC undertook development of software for modeling environmental effects on target signatures, signal propagation, and battlefield sensors for many signal modalities (e.g., optical, acoustic, seismic, magnetic, radio-frequency, chemical, biological, and nuclear). Since its inception, the software, called Environmental Awareness for Sensor and Emitter Employment (EASEE), has matured and evolved significantly for simulating a broad spectrum of signal-transmission and sensing scenarios. The underlying software design involves a flexible, object-oriented approach to the various stages of signal modeling from emission through processing into inferences. A sensor placement algorithm has also been built in for optimizing sensor selections and placements based on specification of sensor supply limitations, coverage priorities, and wireless sensor communication requirements. Some recent and ongoing enhancements are described, including modeling of active sensing scenarios and signal reflections, directivity of signal emissions and sensors, improved handling of signal feature dependencies, extensions to realistically model additional signal modalities such as infrared and RF, and XML-based communication with other calculation and display engines.

  11. Towards an Optimal Energy Consumption for Unattended Mobile Sensor Networks through Autonomous Sensor Redeployment

    PubMed Central

    Jia, Jie; Wen, Yingyou; Zhao, Dazhe

    2014-01-01

    Energy hole is an inherent problem caused by heavier traffic loads of sensor nodes nearer the sink because of more frequent data transmission, which is strongly dependent on the topology induced by the sensor deployment. In this paper, we propose an autonomous sensor redeployment algorithm to balance energy consumption and mitigate energy hole for unattended mobile sensor networks. First, with the target area divided into several equal width coronas, we present a mathematical problem modeling sensor node layout as well as transmission pattern to maximize network coverage and reduce communication cost. And then, by calculating the optimal node density for each corona to avoid energy hole, a fully distributed movement algorithm is proposed, which can achieve an optimal distribution quickly only by pushing or pulling its one-hop neighbors. The simulation results demonstrate that our algorithm achieves a much smaller average moving distance and a much longer network lifetime than existing algorithms and can eliminate the energy hole problem effectively. PMID:24949494

  12. Inertial and optical sensor fusion to compensate for partial occlusions in surgical tracking systems

    NASA Astrophysics Data System (ADS)

    He, Changyu; Liu, Yue

    2015-08-01

    To solve the occlusion problem in optical tracking system (OTS) for surgical navigation, this paper proposes a sensor fusion approach and an adaptive display method to handle cases where partial or total occlusion occurs. In the sensor fusion approach, the full 6D pose information provided by the optical tracker is used to estimate the bias of the inertial sensors when all of the markers are visible. When partial occlusion occurs, the optical system can track the position of at least one marker which can be combined with the orientation estimated from the inertial measurements to recover the full 6D pose information. When all the markers are invisible, the position tracking will be realized based on outputs of the Inertial Measurement Unit (IMU) which may generate increasing drifting error. To alert the user when the drifting error is great enough to influence the navigation, the images adaptive to the drifting error are displayed in the field of the user's view. The experiments are performed with an augmented reality HMD which displays the AR images and the hybrid tracking system (HTS) which consists of an OTS and an IMU. Experimental result shows that with proposed sensor fusion approach the 6D pose of the head with respect to the reference frame can be estimated even under partial occlusion conditions. With the help of the proposed adaptive display method, the users can recover the scene of markers when the error is considered to be relatively high.

  13. Steam distribution and energy delivery optimization using wireless sensors

    NASA Astrophysics Data System (ADS)

    Olama, Mohammed M.; Allgood, Glenn O.; Kuruganti, Teja P.; Sukumar, Sreenivas R.; Djouadi, Seddik M.; Lake, Joe E.

    2011-05-01

    The Extreme Measurement Communications Center at Oak Ridge National Laboratory (ORNL) explores the deployment of a wireless sensor system with a real-time measurement-based energy efficiency optimization framework in the ORNL campus. With particular focus on the 12-mile long steam distribution network in our campus, we propose an integrated system-level approach to optimize the energy delivery within the steam distribution system. We address the goal of achieving significant energy-saving in steam lines by monitoring and acting on leaking steam valves/traps. Our approach leverages an integrated wireless sensor and real-time monitoring capabilities. We make assessments on the real-time status of the distribution system by mounting acoustic sensors on the steam pipes/traps/valves and observe the state measurements of these sensors. Our assessments are based on analysis of the wireless sensor measurements. We describe Fourier-spectrum based algorithms that interpret acoustic vibration sensor data to characterize flows and classify the steam system status. We are able to present the sensor readings, steam flow, steam trap status and the assessed alerts as an interactive overlay within a web-based Google Earth geographic platform that enables decision makers to take remedial action. We believe our demonstration serves as an instantiation of a platform that extends implementation to include newer modalities to manage water flow, sewage and energy consumption.

  14. Steam distribution and energy delivery optimization using wireless sensors

    SciTech Connect

    Olama, Mohammed M; Allgood, Glenn O; Kuruganti, Phani Teja; Sukumar, Sreenivas R; Djouadi, Seddik M; Lake, Joe E

    2011-01-01

    The Extreme Measurement Communications Center at Oak Ridge National Laboratory (ORNL) explores the deployment of a wireless sensor system with a real-time measurement-based energy efficiency optimization framework in the ORNL campus. With particular focus on the 12-mile long steam distribution network in our campus, we propose an integrated system-level approach to optimize the energy delivery within the steam distribution system. We address the goal of achieving significant energy-saving in steam lines by monitoring and acting on leaking steam valves/traps. Our approach leverages an integrated wireless sensor and real-time monitoring capabilities. We make assessments on the real-time status of the distribution system by mounting acoustic sensors on the steam pipes/traps/valves and observe the state measurements of these sensors. Our assessments are based on analysis of the wireless sensor measurements. We describe Fourier-spectrum based algorithms that interpret acoustic vibration sensor data to characterize flows and classify the steam system status. We are able to present the sensor readings, steam flow, steam trap status and the assessed alerts as an interactive overlay within a web-based Google Earth geographic platform that enables decision makers to take remedial action. We believe our demonstration serves as an instantiation of a platform that extends implementation to include newer modalities to manage water flow, sewage and energy consumption.

  15. Tools for multi-aspect data gathering and sensor fusion

    NASA Astrophysics Data System (ADS)

    Smith, Roderick A.; Emblen, Chris

    1997-07-01

    At long range, only the highlight echoes are available for classifying targets as minelike; their variation with aspect provides vital classification clues. Gathering this data with experimental equipment presents new challenges for planning, operation and post processing. The course of the ship varies from minute to minute, as it attempts to follow the tracks between waypoints. the sonar array orientation must compensate for the motion, to maintain the sonar footprint over the target. This task is relatively straight forward with the wide sector angels and large range extent of in-service minehunting sonars. Some experimental wide band sonar modules however only process a few tens of meters of range extent. Skilled operators, low seastage and graphic tools are then needed to acquire the target echo. DRA is writing software modules to visualize and plan the mine hunting strategy and fusion of data in such scenarios, aimed at trials planners, sonar operators, and processing engineers.

  16. Optimal configuration of redundant inertial sensors for navigation and FDI performance.

    PubMed

    Shim, Duk-Sun; Yang, Cheol-Kwan

    2010-01-01

    This paper considers the optimal sensor configuration for inertial navigation systems which have redundant inertial sensors such as gyroscopes and accelerometers. We suggest a method to determine the optimal sensor configuration which considers both the navigation and FDI performance. Monte Carlo simulations are performed to show the performance of the suggested optimal sensor configuration method.

  17. Optimizing Sensor and Actuator Arrays for ASAC Noise Control

    NASA Technical Reports Server (NTRS)

    Palumbo, Dan; Cabell, Ran

    2000-01-01

    This paper summarizes the development of an approach to optimizing the locations for arrays of sensors and actuators in active noise control systems. A type of directed combinatorial search, called Tabu Search, is used to select an optimal configuration from a much larger set of candidate locations. The benefit of using an optimized set is demonstrated. The importance of limiting actuator forces to realistic levels when evaluating the cost function is discussed. Results of flight testing an optimized system are presented. Although the technique has been applied primarily to Active Structural Acoustic Control systems, it can be adapted for use in other active noise control implementations.

  18. Sensor data fusion for mine detection from a vehicle-mounted system

    NASA Astrophysics Data System (ADS)

    Bhatia, Indar L.; Diehl, Vince E.; Moore, Tim; Marble, Jay A.; Tran, Ky; Bishop, Steven S.

    2000-08-01

    The MH/K) Close in Detector (CID) system employs ground penetrating radar (GPR), forward looking IR and metal detectors that are individually and collectively processed to generate automatic target detections. The detection preprocessing is initially being accomplished on a sensor by sensor basis. For the IR sensor, we apply digital filtering techniques and morphology to detect the mines and a separate filter to characterize the background level. For preprocessing the GPR returns, we apply an inverse Fourier transform to the complex frequency return signal to obtain depth information and apply digital filtering techniques to remove fixed pattern noise and provide contrast enhancement. Metal detector returns are preprocessed using a distance measure of the return compared with the averaged background. A representative data set is extracted from the preprocessed data for each of the sensor types. Other MH/K team efforts for ATR and fusion development include TRW, BAE and Sandia National Laboratories.

  19. Fast obstacle detection based on multi-sensor information fusion

    NASA Astrophysics Data System (ADS)

    Lu, Linli; Ying, Jie

    2014-11-01

    Obstacle detection is one of the key problems in areas such as driving assistance and mobile robot navigation, which cannot meet the actual demand by using a single sensor. A method is proposed to realize the real-time access to the information of the obstacle in front of the robot and calculating the real size of the obstacle area according to the mechanism of the triangle similarity in process of imaging by fusing datum from a camera and an ultrasonic sensor, which supports the local path planning decision. In the part of image analyzing, the obstacle detection region is limited according to complementary principle. We chose ultrasonic detection range as the region for obstacle detection when the obstacle is relatively near the robot, and the travelling road area in front of the robot is the region for a relatively-long-distance detection. The obstacle detection algorithm is adapted from a powerful background subtraction algorithm ViBe: Visual Background Extractor. We extracted an obstacle free region in front of the robot in the initial frame, this region provided a reference sample set of gray scale value for obstacle detection. Experiments of detecting different obstacles at different distances respectively, give the accuracy of the obstacle detection and the error percentage between the calculated size and the actual size of the detected obstacle. Experimental results show that the detection scheme can effectively detect obstacles in front of the robot and provide size of the obstacle with relatively high dimensional accuracy.

  20. Knowledge-based imaging-sensor fusion system

    NASA Technical Reports Server (NTRS)

    Westrom, George

    1989-01-01

    An imaging system which applies knowledge-based technology to supervise and control both sensor hardware and computation in the imaging system is described. It includes the development of an imaging system breadboard which brings together into one system work that we and others have pursued for LaRC for several years. The goal is to combine Digital Signal Processing (DSP) with Knowledge-Based Processing and also include Neural Net processing. The system is considered a smart camera. Imagine that there is a microgravity experiment on-board Space Station Freedom with a high frame rate, high resolution camera. All the data cannot possibly be acquired from a laboratory on Earth. In fact, only a small fraction of the data will be received. Again, imagine being responsible for some experiments on Mars with the Mars Rover: the data rate is a few kilobits per second for data from several sensors and instruments. Would it not be preferable to have a smart system which would have some human knowledge and yet follow some instructions and attempt to make the best use of the limited bandwidth for transmission. The system concept, current status of the breadboard system and some recent experiments at the Mars-like Amboy Lava Fields in California are discussed.

  1. The life and death of ATR/sensor fusion and the hope for resurrection

    NASA Astrophysics Data System (ADS)

    Rogers, Steven K.; Sadowski, Charles; Bauer, Kenneth W.; Oxley, Mark E.; Kabrisky, Matthew; Rogers, Adam; Mott, Stephen D.

    2008-04-01

    For over half a century, scientists and engineers have worked diligently to advance computational intelligence. One application of interest is how computational intelligence can bring value to our war fighters. Automatic Target Recognition (ATR) and sensor fusion efforts have fallen far short of the desired capabilities. In this article we review the capabilities requested by war fighters. When compared to our current capabilities, it is easy to conclude current Combat Identification (CID) as a Family of Systems (FoS) does a lousy job. The war fighter needed capable, operationalized ATR and sensor fusion systems ten years ago but it did not happen. The article reviews the war fighter needs and the current state of the art. The article then concludes by looking forward to where we are headed to provide the capabilities required.

  2. Sensor fusion IV: Control paradigms and data structures; Proceedings of the Meeting, Boston, MA, Nov. 12-15, 1991

    NASA Technical Reports Server (NTRS)

    Schenker, Paul S. (Editor)

    1992-01-01

    Various papers on control paradigms and data structures in sensor fusion are presented. The general topics addressed include: decision models and computational methods, sensor modeling and data representation, active sensing strategies, geometric planning and visualization, task-driven sensing, motion analysis, models motivated biology and psychology, decentralized detection and distributed decision, data fusion architectures, robust estimation of shapes and features, application and implementation. Some of the individual subjects considered are: the Firefly experiment on neural networks for distributed sensor data fusion, manifold traversing as a model for learning control of autonomous robots, choice of coordinate systems for multiple sensor fusion, continuous motion using task-directed stereo vision, interactive and cooperative sensing and control for advanced teleoperation, knowledge-based imaging for terrain analysis, physical and digital simulations for IVA robotics.

  3. Sensor Fusion of Position- and Micro-Sensors (MEMS) integrated in a Wireless Sensor Network for movement detection in landslide areas

    NASA Astrophysics Data System (ADS)

    Arnhardt, Christian; Fernández-Steeger, Tomas; Azzam, Rafig

    2010-05-01

    Monitoring systems in landslide areas are important elements of effective Early Warning structures. Data acquisition and retrieval allows the detection of movement processes and thus is essential to generate warnings in time. Apart from the precise measurement, the reliability of data is fundamental, because outliers can trigger false alarms and leads to the loss of acceptance of such systems. For the monitoring of mass movements and their risk it is important to know, if there is movement, how fast it is and how trustworthy is the information. The joint project "Sensorbased landslide early warning system" (SLEWS) deals with these questions, and tries to improve data quality and to reduce false alarm rates, due to the combination of sensor date (sensor fusion). The project concentrates on the development of a prototypic Alarm- and Early Warning system (EWS) for different types of landslides by using various low-cost sensors, integrated in a wireless sensor network (WSN). The network consists of numerous connection points (nodes) that transfer data directly or over other nodes (Multi-Hop) in real-time to a data collection point (gateway). From there all the data packages are transmitted to a spatial data infrastructure (SDI) for further processing, analyzing and visualizing with respect to end-user specifications. The ad-hoc characteristic of the network allows the autonomous crosslinking of the nodes according to existing connections and communication strength. Due to the independent finding of new or more stable connections (self healing) a breakdown of the whole system is avoided. The bidirectional data stream enables the receiving of data from the network but also allows the transfer of commands and pointed requests into the WSN. For the detection of surface deformations in landslide areas small low-cost Micro-Electro-Mechanical-Systems (MEMS) and positionsensors from the automobile industries, different industrial applications and from other measurement

  4. Wrap-Around Out-the-Window Sensor Fusion System

    NASA Technical Reports Server (NTRS)

    Fox, Jeffrey; Boe, Eric A.; Delgado, Francisco; Secor, James B.; Clark, Michael R.; Ehlinger, Kevin D.; Abernathy, Michael F.

    2009-01-01

    The Advanced Cockpit Evaluation System (ACES) includes communication, computing, and display subsystems, mounted in a van, that synthesize out-the-window views to approximate the views of the outside world as it would be seen from the cockpit of a crewed spacecraft, aircraft, or remote control of a ground vehicle or UAV (unmanned aerial vehicle). The system includes five flat-panel display units arranged approximately in a semicircle around an operator, like cockpit windows. The scene displayed on each panel represents the view through the corresponding cockpit window. Each display unit is driven by a personal computer equipped with a video-capture card that accepts live input from any of a variety of sensors (typically, visible and/or infrared video cameras). Software running in the computers blends the live video images with synthetic images that could be generated, for example, from heads-up-display outputs, waypoints, corridors, or from satellite photographs of the same geographic region. Data from a Global Positioning System receiver and an inertial navigation system aboard the remote vehicle are used by the ACES software to keep the synthetic and live views in registration. If the live image were to fail, the synthetic scenes could still be displayed to maintain situational awareness.

  5. Optimization of the SHX Fusion Powered Transatmospheric Propulsion Concept

    NASA Technical Reports Server (NTRS)

    Adams, Robert B.; Landrum, D. Brian

    2001-01-01

    Existing propulsion technology has not achieved cost effective payload delivery rates to low earth orbit. A fusion based propulsion system, denoted as the Simultaneous Heating and eXpansion (SHX) engine, has been proposed in earlier papers. The SHX couples energy generated by a fusion reactor to the engine flowpath by use of coherent beam emitters. A quasi-one-dimensional flow model was used to quantify the effects of area expansion and energy input on propulsive efficiency for several beam models. Entropy calculations were included to evaluate the lost work in the system.

  6. Optimization of floodplain monitoring sensors through an entropy approach

    NASA Astrophysics Data System (ADS)

    Ridolfi, E.; Yan, K.; Alfonso, L.; Di Baldassarre, G.; Napolitano, F.; Russo, F.; Bates, P. D.

    2012-04-01

    To support the decision making processes of flood risk management and long term floodplain planning, a significant issue is the availability of data to build appropriate and reliable models. Often the required data for model building, calibration and validation are not sufficient or available. A unique opportunity is offered nowadays by the globally available data, which can be freely downloaded from internet. However, there remains the question of what is the real potential of those global remote sensing data, characterized by different accuracies, for global inundation monitoring and how to integrate them with inundation models. In order to monitor a reach of the River Dee (UK), a network of cheap wireless sensors (GridStix) was deployed both in the channel and in the floodplain. These sensors measure the water depth, supplying the input data for flood mapping. Besides their accuracy and reliability, their location represents a big issue, having the purpose of providing as much information as possible and at the same time as low redundancy as possible. In order to update their layout, the initial number of six sensors has been increased up to create a redundant network over the area. Through an entropy approach, the most informative and the least redundant sensors have been chosen among all. First, a simple raster-based inundation model (LISFLOOD-FP) is used to generate a synthetic GridStix data set of water stages. The Digital Elevation Model (DEM) used for hydraulic model building is the globally and freely available SRTM DEM. Second, the information content of each sensor has been compared by evaluating their marginal entropy. Those with a low marginal entropy are excluded from the process because of their low capability to provide information. Then the number of sensors has been optimized considering a Multi-Objective Optimization Problem (MOOP) with two objectives, namely maximization of the joint entropy (a measure of the information content) and

  7. Optimal Sensor Layouts in Underwater Locomotory Systems

    NASA Astrophysics Data System (ADS)

    Colvert, Brendan; Kanso, Eva

    2015-11-01

    Retrieving and understanding global flow characteristics from local sensory measurements is a challenging but extremely relevant problem in fields such as defense, robotics, and biomimetics. It is an inverse problem in that the goal is to translate local information into global flow properties. In this talk we present techniques for optimization of sensory layouts within the context of an idealized underwater locomotory system. Using techniques from fluid mechanics and control theory, we show that, under certain conditions, local measurements can inform the submerged body about its orientation relative to the ambient flow, and allow it to recognize local properties of shear flows. We conclude by commenting on the relevance of these findings to underwater navigation in engineered systems and live organisms.

  8. An automatic fall detection framework using data fusion of Doppler radar and motion sensor network.

    PubMed

    Liu, Liang; Popescu, Mihail; Skubic, Marjorie; Rantz, Marilyn

    2014-01-01

    This paper describes the ongoing work of detecting falls in independent living senior apartments. We have developed a fall detection system with Doppler radar sensor and implemented ceiling radar in real senior apartments. However, the detection accuracy on real world data is affected by false alarms inherent in the real living environment, such as motions from visitors. To solve this issue, this paper proposes an improved framework by fusing the Doppler radar sensor result with a motion sensor network. As a result, performance is significantly improved after the data fusion by discarding the false alarms generated by visitors. The improvement of this new method is tested on one week of continuous data from an actual elderly person who frequently falls while living in her senior home. PMID:25571349

  9. An automatic fall detection framework using data fusion of Doppler radar and motion sensor network.

    PubMed

    Liu, Liang; Popescu, Mihail; Skubic, Marjorie; Rantz, Marilyn

    2014-01-01

    This paper describes the ongoing work of detecting falls in independent living senior apartments. We have developed a fall detection system with Doppler radar sensor and implemented ceiling radar in real senior apartments. However, the detection accuracy on real world data is affected by false alarms inherent in the real living environment, such as motions from visitors. To solve this issue, this paper proposes an improved framework by fusing the Doppler radar sensor result with a motion sensor network. As a result, performance is significantly improved after the data fusion by discarding the false alarms generated by visitors. The improvement of this new method is tested on one week of continuous data from an actual elderly person who frequently falls while living in her senior home.

  10. Geometry optimization for micro-pressure sensor considering dynamic interference.

    PubMed

    Yu, Zhongliang; Zhao, Yulong; Li, Lili; Tian, Bian; Li, Cun

    2014-09-01

    Presented is the geometry optimization for piezoresistive absolute micro-pressure sensor. A figure of merit called the performance factor (PF) is defined as a quantitative index to describe the comprehensive performances of a sensor including sensitivity, resonant frequency, and acceleration interference. Three geometries are proposed through introducing islands and sensitive beams into typical flat diaphragm. The stress distributions of sensitive elements are analyzed by finite element method. Multivariate fittings based on ANSYS simulation results are performed to establish the equations about surface stress, deflection, and resonant frequency. Optimization by MATLAB is carried out to determine the dimensions of the geometries. Convex corner undercutting is evaluated. Each PF of the three geometries with the determined dimensions is calculated and compared. Silicon bulk micromachining is utilized to fabricate the prototypes of the sensors. The outputs of the sensors under both static and dynamic conditions are tested. Experimental results demonstrate the rationality of the defined performance factor and reveal that the geometry with quad islands presents the highest PF of 210.947 Hz(1/4). The favorable overall performances enable the sensor more suitable for altimetry.

  11. Geometry optimization for micro-pressure sensor considering dynamic interference

    SciTech Connect

    Yu, Zhongliang; Zhao, Yulong Li, Lili; Tian, Bian; Li, Cun

    2014-09-15

    Presented is the geometry optimization for piezoresistive absolute micro-pressure sensor. A figure of merit called the performance factor (PF) is defined as a quantitative index to describe the comprehensive performances of a sensor including sensitivity, resonant frequency, and acceleration interference. Three geometries are proposed through introducing islands and sensitive beams into typical flat diaphragm. The stress distributions of sensitive elements are analyzed by finite element method. Multivariate fittings based on ANSYS simulation results are performed to establish the equations about surface stress, deflection, and resonant frequency. Optimization by MATLAB is carried out to determine the dimensions of the geometries. Convex corner undercutting is evaluated. Each PF of the three geometries with the determined dimensions is calculated and compared. Silicon bulk micromachining is utilized to fabricate the prototypes of the sensors. The outputs of the sensors under both static and dynamic conditions are tested. Experimental results demonstrate the rationality of the defined performance factor and reveal that the geometry with quad islands presents the highest PF of 210.947 Hz{sup 1/4}. The favorable overall performances enable the sensor more suitable for altimetry.

  12. Computer simulation of optimal sensor locations in loading identification

    NASA Astrophysics Data System (ADS)

    Li, Dong-Sheng; Li, Hong-Nan; Guo, Xing L.

    2003-07-01

    A method is presented for the selection of a set of sensor locations from a larger candidate sent for the purpose of structural loading identification. The method ranks the candidate sensor locations according to their effectiveness for identifying the given known loadings. Measurement locations that yield abnormal jumps in identification results or increase the condition number of the frequency response function are removed. The final sensor configuration tends to minimize the error of the loading identification results and the condition number of the frequency response function. The initial candidate set is selected based on the modal kinetic energy distribution that gives a measure of the dynamic contribution of each physical degree freedom to each of the target mode shapes of interest. In addition, excitation location is considered when selecting appropriate response measurement locations. This method was successfully applied to the optimal sensor location selection and loading identification of a uniform cantilever beam in experiment. It is shown that computer simulation is a good way to select the optimal sensor location for loading identification.

  13. Robust optimization of contaminant sensor placement for community water systems.

    SciTech Connect

    Konjevod, Goran; Carr, Robert D.; Greenberg, Harvey J.; Hart, William Eugene; Morrison, Tod; Phillips, Cynthia Ann; Lin, Henry; Lauer, Erik

    2004-09-01

    We present a series of related robust optimization models for placing sensors in municipal water networks to detect contaminants that are maliciously or accidentally injected.We formulate sensor placement problems as mixed-integer programs, for which the objective coefficients are not known with certainty. We consider a restricted absolute robustness criteria that is motivated by natural restrictions on the uncertain data, and we define three robust optimization models that differ in how the coefficients in the objective vary. Under one set of assumptions there exists a sensor placement that is optimal for all admissible realizations of the coefficients. Under other assumptions, we can apply sorting to solve each worst-case realization efficiently, or we can apply duality to integrate the worst-case outcome and have one integer program. The most difficult case is where the objective parameters are bilinear, and we prove its complexity is NP-hard even under simplifying assumptions. We consider a relaxation that provides an approximation, giving an overall guarantee of nearoptimality when used with branch-and-bound search. We present preliminary computational experiments that illustrate the computational complexity of solving these robust formulations on sensor placement applications.

  14. Optimization of fingernail sensor design based on fingernail imaging

    NASA Astrophysics Data System (ADS)

    Abu-Khalaf, Jumana M.; Mascaro, Stephen A.

    2010-08-01

    This paper describes the optimization of fingernail sensors for measuring fingertip touch forces for human-computer interaction. The fingernail sensor uses optical reflectance photoplethysmography to measure the change in blood perfusion in the fingernail bed when the fingerpad touches a surface with various forces. In the original fingernail sensor, color changes observed through the fingernail have been measured by mounting an array of six LEDs (Light Emitting Diodes) and eight photodetectors on the fingernail in a laterally symmetric configuration. The optical components were located such that each photodiode had at least one neighboring LED. The role of each of the photodetectors was investigated in terms of the effect of removing one or more photodetectors on force prediction estimation. The analysis suggested designing the next generation of fingernail sensors with less than eight photodetectors. This paper proposes an optimal redesign by analyzing a photographic catalog composed of six different force poses, representing average fingernail coloration patterns of fifteen human subjects. It also introduces an optical model that describes light transmission between an LED and a photodiode, and predicts the optimal locations of the optoelectronic devices in the fingernail area.

  15. Joint UK-Australian Space Surveillance Target Tracking, Cueing and Sensor Data Fusion Experiment

    NASA Astrophysics Data System (ADS)

    Donnelly, P.; Harwood, N.; Ash, A.; Eastment, J.; Ladd, D.; Walden, C.; Bennett, J.; Smith, C.; Ritchie, I.; Rutten, M.; Gordon, N.

    2014-09-01

    In February 2014 the UK and Australia carried out a joint space surveillance target tracking, cueing, and sensor data fusion experiment. Four organisations were involved, these being the UK Defence Science and Technology Laboratory (DSTL) and Science and Technology Facilities Council (STFC) with the Defence Science and Technology Organisation (DSTO) and Electro Optic Systems (EOS) of Australia. The experiment utilised the UK STFC CAMRa radar located at Chilbolton in southern England and an Australian optical camera and laser system owned and operated by EOS and located at Mount Stromlo near Canberra, Australia. An additional experimental camera owned and operated by DSTO and located at Adelaide, Australia also contributed. Three initial objectives of the experiment were all achieved, these being: 1) Use multiple CAMRa orbit passes to cue EOS optical sensor; 2) Use single CAMRa passes constrained by TLEs to cue EOS optical sensor; 3) Use EOS laser returns to provide an updated "reverse" cue for CAMRa radar. Due to the success of these three objectives, two additional objectives were also set during the trials, these being: 4) Use CAMRa orbits to cue DSTO experimental optical sensor; 5) Use CAMRa orbits to provide CAMRa self-cue. These objectives were also achieved. The experiments were performed over two one week periods with a one week separation between tracking campaigns. This paper describes the experimental programme from a top-level perspective and outlines the planning and execution of the experiment together with some initial analysis results. The main achievements and implications for use of dissimilar and geographically separated sensors for space situational awareness are highlighted. Two companion papers describe the sensor aspects of the experiment (Eastment et al.) and the data fusion aspects (Rutten et al.) respectively.

  16. Design and optimization of microstructured optical fiber sensors

    NASA Astrophysics Data System (ADS)

    Jewart, Charles Milford

    2011-12-01

    The integration of sensor networks into large civil and mechanical structures is becoming an important engineering practice to ensure the structural health of important infrastructure and power generation facilities. The temperature, pressure, and internal stress distribution within the structures are key parameters to monitor the structural health of a system. Optical fiber sensors are one of the most common sensing elements used in the structural health monitoring due to their compact size, low cost, electrical immunity, and multiplexing ability. In this dissertation, the design and optimization of air-hole microstructured optical fibers for use as application specific sensors is presented. Air hole matrices are used to design fiber cores with a large birefringence; while air hole arrays within the fiber cladding are studied and optimized to engineer unique geometries that can give desired sensitivity and directionality of the fiber sensors. A pure silica core microstructured photonic crystal fiber was designed for hydrostatic pressure sensing. The impact of the surrounding air-holes to the propagation mode profiles and indices were studied and improved. To improve directionality and sensitivity of fiber sensors, air holes in the fiber cladding were implemented and optimized in the design of the fiber. Finite element analysis simulations were performed to elicit the correlation between air-hole configuration and the fiber sensor's performance and impact of the fiber's opto-mechanic properties. To measure pressure and stress at high temperature, an ultrafast laser was used to inscribe type II gratings in two-hole microstructured optical fibers and suspended core fibers. The fiber Bragg grating resonance wavelength shift and peak splitting were studied as a function of external pressure, bending, and lateral compression. Fiber sensors in two-hole fibers show stable and reproducible operation above 800°C. Fiber grating sensor in suspended core fibers exhibits high

  17. Optimization of electrochemical aptamer-based sensors via optimization of probe packing density and surface chemistry.

    PubMed

    White, Ryan J; Phares, Noelle; Lubin, Arica A; Xiao, Yi; Plaxco, Kevin W

    2008-09-16

    Electrochemical, aptamer-based (E-AB) sensors, which are comprised of an electrode modified with surface immobilized, redox-tagged DNA aptamers, have emerged as a promising new biosensor platform. In order to further improve this technology we have systematically studied the effects of probe (aptamer) packing density, the AC frequency used to interrogate the sensor, and the nature of the self-assembled monolayer (SAM) used to passivate the electrode on the performance of representative E-AB sensors directed against the small molecule cocaine and the protein thrombin. We find that, by controlling the concentration of aptamer employed during sensor fabrication, we can control the density of probe DNA molecules on the electrode surface over an order of magnitude range. Over this range, the gain of the cocaine sensor varies from 60% to 200%, with maximum gain observed near the lowest probe densities. In contrast, over a similar range, the signal change of the thrombin sensor varies from 16% to 42% and optimal signaling is observed at intermediate densities. Above cut-offs at low hertz frequencies, neither sensor displays any significant dependence on the frequency of the alternating potential employed in their interrogation. Finally, we find that E-AB signal gain is sensitive to the nature of the alkanethiol SAM employed to passivate the interrogating electrode; while thinner SAMs lead to higher absolute sensor currents, reducing the length of the SAM from 6-carbons to 2-carbons reduces the observed signal gain of our cocaine sensor 10-fold. We demonstrate that fabrication and operational parameters can be varied to achieve optimal sensor performance and that these can serve as a basic outline for future sensor fabrication.

  18. Particle swarm optimization for optimal sensor placement in ultrasonic SHM systems

    NASA Astrophysics Data System (ADS)

    Blanloeuil, Philippe; Nurhazli, Nur A. E.; Veidt, Martin

    2016-04-01

    A Particle Swarm Optimization (PSO) algorithm is used to improve sensors placement in an ultrasonic Structural Health Monitoring (SHM) system where the detection is performed through the beam-forming imaging algorithm. The imaging algorithm reconstructs the defect image and estimates its location based on analytically generated signals, considering circular through hole damage in an aluminum plate as the tested structure. Then, the PSO algorithm changes the position of sensors to improve the accuracy of the detection. Thus, the two algorithms are working together iteratively to optimize the system configuration, taking into account a complete modeling of the SHM system. It is shown that this approach can provide good sensors placements for detection of multiple defects in the target area, and for different numbers of sensors.

  19. Selection of optimal sensors for predicting performance of polymer electrolyte membrane fuel cell

    NASA Astrophysics Data System (ADS)

    Mao, Lei; Jackson, Lisa

    2016-10-01

    In this paper, sensor selection algorithms are investigated based on a sensitivity analysis, and the capability of optimal sensors in predicting PEM fuel cell performance is also studied using test data. The fuel cell model is developed for generating the sensitivity matrix relating sensor measurements and fuel cell health parameters. From the sensitivity matrix, two sensor selection approaches, including the largest gap method, and exhaustive brute force searching technique, are applied to find the optimal sensors providing reliable predictions. Based on the results, a sensor selection approach considering both sensor sensitivity and noise resistance is proposed to find the optimal sensor set with minimum size. Furthermore, the performance of the optimal sensor set is studied to predict fuel cell performance using test data from a PEM fuel cell system. Results demonstrate that with optimal sensors, the performance of PEM fuel cell can be predicted with good quality.

  20. Fusion of WiFi, smartphone sensors and landmarks using the Kalman filter for indoor localization.

    PubMed

    Chen, Zhenghua; Zou, Han; Jiang, Hao; Zhu, Qingchang; Soh, Yeng Chai; Xie, Lihua

    2015-01-01

    Location-based services (LBS) have attracted a great deal of attention recently. Outdoor localization can be solved by the GPS technique, but how to accurately and efficiently localize pedestrians in indoor environments is still a challenging problem. Recent techniques based on WiFi or pedestrian dead reckoning (PDR) have several limiting problems, such as the variation of WiFi signals and the drift of PDR. An auxiliary tool for indoor localization is landmarks, which can be easily identified based on specific sensor patterns in the environment, and this will be exploited in our proposed approach. In this work, we propose a sensor fusion framework for combining WiFi, PDR and landmarks. Since the whole system is running on a smartphone, which is resource limited, we formulate the sensor fusion problem in a linear perspective, then a Kalman filter is applied instead of a particle filter, which is widely used in the literature. Furthermore, novel techniques to enhance the accuracy of individual approaches are adopted. In the experiments, an Android app is developed for real-time indoor localization and navigation. A comparison has been made between our proposed approach and individual approaches. The results show significant improvement using our proposed framework. Our proposed system can provide an average localization accuracy of 1 m. PMID:25569750

  1. Fusion of WiFi, Smartphone Sensors and Landmarks Using the Kalman Filter for Indoor Localization

    PubMed Central

    Chen, Zhenghua; Zou, Han; Jiang, Hao; Zhu, Qingchang; Soh, Yeng Chai; Xie, Lihua

    2015-01-01

    Location-based services (LBS) have attracted a great deal of attention recently. Outdoor localization can be solved by the GPS technique, but how to accurately and efficiently localize pedestrians in indoor environments is still a challenging problem. Recent techniques based on WiFi or pedestrian dead reckoning (PDR) have several limiting problems, such as the variation of WiFi signals and the drift of PDR. An auxiliary tool for indoor localization is landmarks, which can be easily identified based on specific sensor patterns in the environment, and this will be exploited in our proposed approach. In this work, we propose a sensor fusion framework for combining WiFi, PDR and landmarks. Since the whole system is running on a smartphone, which is resource limited, we formulate the sensor fusion problem in a linear perspective, then a Kalman filter is applied instead of a particle filter, which is widely used in the literature. Furthermore, novel techniques to enhance the accuracy of individual approaches are adopted. In the experiments, an Android app is developed for real-time indoor localization and navigation. A comparison has been made between our proposed approach and individual approaches. The results show significant improvement using our proposed framework. Our proposed system can provide an average localization accuracy of 1 m. PMID:25569750

  2. Fusion of WiFi, smartphone sensors and landmarks using the Kalman filter for indoor localization.

    PubMed

    Chen, Zhenghua; Zou, Han; Jiang, Hao; Zhu, Qingchang; Soh, Yeng Chai; Xie, Lihua

    2015-01-05

    Location-based services (LBS) have attracted a great deal of attention recently. Outdoor localization can be solved by the GPS technique, but how to accurately and efficiently localize pedestrians in indoor environments is still a challenging problem. Recent techniques based on WiFi or pedestrian dead reckoning (PDR) have several limiting problems, such as the variation of WiFi signals and the drift of PDR. An auxiliary tool for indoor localization is landmarks, which can be easily identified based on specific sensor patterns in the environment, and this will be exploited in our proposed approach. In this work, we propose a sensor fusion framework for combining WiFi, PDR and landmarks. Since the whole system is running on a smartphone, which is resource limited, we formulate the sensor fusion problem in a linear perspective, then a Kalman filter is applied instead of a particle filter, which is widely used in the literature. Furthermore, novel techniques to enhance the accuracy of individual approaches are adopted. In the experiments, an Android app is developed for real-time indoor localization and navigation. A comparison has been made between our proposed approach and individual approaches. The results show significant improvement using our proposed framework. Our proposed system can provide an average localization accuracy of 1 m.

  3. On the use of sensor fusion to reduce the impact of rotational and additive noise in human activity recognition.

    PubMed

    Banos, Oresti; Damas, Miguel; Pomares, Hector; Rojas, Ignacio

    2012-01-01

    The main objective of fusion mechanisms is to increase the individual reliability of the systems through the use of the collectivity knowledge. Moreover, fusion models are also intended to guarantee a certain level of robustness. This is particularly required for problems such as human activity recognition where runtime changes in the sensor setup seriously disturb the reliability of the initial deployed systems. For commonly used recognition systems based on inertial sensors, these changes are primarily characterized as sensor rotations, displacements or faults related to the batteries or calibration. In this work we show the robustness capabilities of a sensor-weighted fusion model when dealing with such disturbances under different circumstances. Using the proposed method, up to 60% outperformance is obtained when a minority of the sensors are artificially rotated or degraded, independent of the level of disturbance (noise) imposed. These robustness capabilities also apply for any number of sensors affected by a low to moderate noise level. The presented fusion mechanism compensates the poor performance that otherwise would be obtained when just a single sensor is considered.

  4. On the Use of Sensor Fusion to Reduce the Impact of Rotational and Additive Noise in Human Activity Recognition

    PubMed Central

    Banos, Oresti; Damas, Miguel; Pomares, Hector; Rojas, Ignacio

    2012-01-01

    The main objective of fusion mechanisms is to increase the individual reliability of the systems through the use of the collectivity knowledge. Moreover, fusion models are also intended to guarantee a certain level of robustness. This is particularly required for problems such as human activity recognition where runtime changes in the sensor setup seriously disturb the reliability of the initial deployed systems. For commonly used recognition systems based on inertial sensors, these changes are primarily characterized as sensor rotations, displacements or faults related to the batteries or calibration. In this work we show the robustness capabilities of a sensor-weighted fusion model when dealing with such disturbances under different circumstances. Using the proposed method, up to 60% outperformance is obtained when a minority of the sensors are artificially rotated or degraded, independent of the level of disturbance (noise) imposed. These robustness capabilities also apply for any number of sensors affected by a low to moderate noise level. The presented fusion mechanism compensates the poor performance that otherwise would be obtained when just a single sensor is considered. PMID:22969386

  5. Identifying and Tracking Pedestrians Based on Sensor Fusion and Motion Stability Predictions

    PubMed Central

    Musleh, Basam; García, Fernando; Otamendi, Javier; Armingol, José Mª; de la Escalera, Arturo

    2010-01-01

    The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS) applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem) and dense disparity maps and u-v disparity (vision subsystem). Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle. PMID:22163639

  6. Design of 3D measurement system based on multi-sensor data fusion technique

    NASA Astrophysics Data System (ADS)

    Zhang, Weiguang; Han, Jun; Yu, Xun

    2009-05-01

    With the rapid development of shape measurement technique, multi-sensor approach becomes one of valid way to improve the accuracy, to expend measuring range, to reduce occlusion, to realize multi-resolution measurement, and to increase measuring speed simultaneously. Sensors in multi-sensor system can have different system parameters, and they may have different measuring range and different precision. Light sectioning method is one of useful measurement technique for 3D profile measurement. It is insensitive to the surface optical property of 3D object, has scarcely any demand on surrounding. A multi-sensor system scheme, which uses light sectioning method and multi-sensor data fusion techniques, is presented for blade of aviation engine and spiral bevel gear measurement. The system model is developed to build the relationship between measuring range & precision and system parameters. The system parameters were set according to system error analysis, measuring range and precision. The result shows that the system is more universal than it's ancestor, and that the accuracy of the system is about 0.05mm for the 60× 60mm2 measuring range, and that the system is successful for the aero-dynamical data curve of blade of aviation engine and tooth profile of spiral bevel gear measurement with 3600 multi-resolution measuring character.

  7. Identifying and tracking pedestrians based on sensor fusion and motion stability predictions.

    PubMed

    Musleh, Basam; García, Fernando; Otamendi, Javier; Armingol, José Maria; de la Escalera, Arturo

    2010-01-01

    The lack of trustworthy sensors makes development of Advanced Driver Assistance System (ADAS) applications a tough task. It is necessary to develop intelligent systems by combining reliable sensors and real-time algorithms to send the proper, accurate messages to the drivers. In this article, an application to detect and predict the movement of pedestrians in order to prevent an imminent collision has been developed and tested under real conditions. The proposed application, first, accurately measures the position of obstacles using a two-sensor hybrid fusion approach: a stereo camera vision system and a laser scanner. Second, it correctly identifies pedestrians using intelligent algorithms based on polylines and pattern recognition related to leg positions (laser subsystem) and dense disparity maps and u-v disparity (vision subsystem). Third, it uses statistical validation gates and confidence regions to track the pedestrian within the detection zones of the sensors and predict their position in the upcoming frames. The intelligent sensor application has been experimentally tested with success while tracking pedestrians that cross and move in zigzag fashion in front of a vehicle.

  8. Hydrogeologic Data Fusion. Industry Programs/Characterization, Monitoring, and Sensor Technology Crosscut Program. OST Reference #2944

    SciTech Connect

    None, None

    1999-09-01

    Problem: The fate and transport of contaminants in the subsurface requires knowledge of the hydrogeologic system. Site characterization typically involves the collection of various data sets needed to create a conceptual model that represents what’s known about contaminant migration in the subsurface at a particular site. How Hydrogeologic Data Fusion Works Hydrogeologic Data Fusion is a mathematical tool that can be used to combine various types of geophysical, geologic, and hydrologic data from different types of sensors to estimate geologic and hydrogeologic properties. It can be especially useful at hazardous waste sites where the hydrology, geology, or contaminant distribution is significantly complex such that groundwater modeling is required to enable a reasonable and accurate prediction of subsurface conditions.

  9. Genetic algorithm parameter optimization: applied to sensor coverage

    NASA Astrophysics Data System (ADS)

    Sahin, Ferat; Abbate, Giuseppe

    2004-08-01

    Genetic Algorithms are powerful tools, which when set upon a solution space will search for the optimal answer. These algorithms though have some associated problems, which are inherent to the method such as pre-mature convergence and lack of population diversity. These problems can be controlled with changes to certain parameters such as crossover, selection, and mutation. This paper attempts to tackle these problems in GA by having another GA controlling these parameters. The values for crossover parameter are: one point, two point, and uniform. The values for selection parameters are: best, worst, roulette wheel, inside 50%, outside 50%. The values for the mutation parameter are: random and swap. The system will include a control GA whose population will consist of different parameters settings. While this GA is attempting to find the best parameters it will be advancing into the search space of the problem and refining the population. As the population changes due to the search so will the optimal parameters. For every control GA generation each of the individuals in the population will be tested for fitness by being run through the problem GA with the assigned parameters. During these runs the population used in the next control generation is compiled. Thus, both the issue of finding the best parameters and the solution to the problem are attacked at the same time. The goal is to optimize the sensor coverage in a square field. The test case used was a 30 by 30 unit field with 100 sensor nodes. Each sensor node had a coverage area of 3 by 3 units. The algorithm attempts to optimize the sensor coverage in the field by moving the nodes. The results show that the control GA will provide better results when compared to a system with no parameter changes.

  10. Optimizing quantum efficiency in a stacked CMOS sensor

    NASA Astrophysics Data System (ADS)

    Hannebauer, Rob; Yoo, Sang Keun; Gilblom, David L.; Gilblom, Alexander D.

    2011-03-01

    Optimizing quantum efficiency of image sensors, whether CCD or CMOS, has usually required backside thinning to bring the photon receiving surface close to the charge generation elements. A new CMOS sensor architecture has been developed that permits high-fill-factor photodiodes to be placed at the silicon surface without the need for backside thinning. The photodiode access provided by this architecture permits application of highly-effective anti-reflection coatings on the input surface and construction of a mirror inside the silicon below the photodiodes to effectively double the optical thickness of the silicon charge generation volume. Secondary benefits of this architecture include prevention of light from reaching the CMOS circuitry under the photodiodes, improvement of near-infrared quantum efficiency, and reduction in optical artifacts caused by reflections from the sensor surface. Utilizing these techniques, a sensor is being constructed with 4096 x 4096 pixels 4.8 μm square with 95% fill factor backed by a mirror tuned to the 400-700 nm visible band and a front-surface anti-reflectance coating. The quantum efficiency is expected to exceed 80% through the visible and the global shutter extinction ratio should exceed 106:1. The sensors have been fabricated and first test data is due in February 2011.

  11. Analysis of LPFG sensor systems for aircraft wing drag optimization

    NASA Astrophysics Data System (ADS)

    Kazemi, Alex A.; Ishihara, Abe

    2014-09-01

    In normal fiber, the refractive indices of the core and cladding do not change along the length of the fiber; however, by inducing a periodic modulation of refractive index along the length in the core of the optical fiber, the optical fiber grating is produced. This exhibits very interesting spectral properties and for this reason we propose to develop and integrate a distributed sensor network based on long period fiber gratings (LPFGs) technology which has grating periods on the order of 100 μm to 1 mm to be embedded in the wing section of aircraft to measure bending and torsion in real-time in order to measure wing deformation of commercial airplanes resulting in extensive benefits such as reduced structural weight, mitigation of induced drag and lower fuel consumption which is fifty percent of total cost of operation for airline industry. Fiber optic sensors measurement capabilities are as vital as they are for other sensing technologies, but optical measurements differ in important ways. In this paper we focus on the testing and aviation requirements for LPFG sensors. We discuss the bases of aviation standards for fiber optic sensor measurements, and the quantities that are measured. Our main objective is to optimize the design for material, mechanical, optical and environmental requirements. We discuss the analysis and evaluation of extensive testing of LPFG sensor systems such as attenuation, environmental, humidity, fluid immersion, temperature cycling, aging, smoke, flammability, impact resistance, flexure endurance, tensile, vitiation and shock.

  12. Optimizing electromagnetic induction sensors for dynamic munitions classification surveys

    NASA Astrophysics Data System (ADS)

    Miller, Jonathan S.; Keranen, Joe; Schultz, Gregory

    2014-06-01

    Standard protocol for detection and classification of Unexploded Ordnance (UXO) comprises a two-step process that includes an initial digital geophysical mapping (DGM) survey to detect magnetic field anomalies followed by a cued survey at each anomaly location that enables classification of these anomalies. The initial DGM survey is typically performed using a low resolution single axis electromagnetic induction (EMI) sensor while the follow-up cued survey requires revisiting each anomaly location with a multi-axis high resolution EMI sensor. The DGM survey comprises data collection in tightly spaced transects over the entire survey area. Once data collection in this area is complete, a threshold analysis is applied to the resulting magnetic field anomaly map to identify anomalies corresponding to potential targets of interest (TOI). The cued sensor is deployed in static mode where this higher resolution sensor is placed over the location of each anomaly to record a number of soundings that may be stacked and averaged to produce low noise data. These data are of sufficient quality to subsequently classify the object as either TOI or clutter. While this approach has demonstrated success in producing effective classification of UXO, conducting successive surveys is time consuming. Additionally, the low resolution of the initial DGM survey often produces errors in the target picking process that results in poor placement of the cued sensor and often requires several revisits to the anomaly location to ensure adequate characterization of the target space. We present data and test results from an advanced multi-axis EMI sensor optimized to provide both detection and classification from a single survey. We demonstrate how the large volume of data from this sensor may be used to produce effective detection and classification decisions while only requiring one survey of the munitions response area.

  13. Calibration of laser scanner and camera fusion system for intelligent vehicles using Nelder-Mead optimization

    NASA Astrophysics Data System (ADS)

    Osgood, Thomas J.; Huang, Yingping

    2013-03-01

    A novel method is presented here for the calibration of a sensor fusion system for intelligent vehicles. In this example, the sensors are a camera and a laser scanner which observe the same scene from different viewpoints. The method employs the Nelder-Mead direct search algorithm to minimize the sum of squared errors between the image coordinates and the re-projected laser data by iteratively adjusting and improving the calibration parameters. The method is applied to a real set of data collected from a test vehicle. Using only 11 well-spaced target points observable by each sensor, 12 intrinsic and extrinsic parameters indicating the position relationship between the sensors can be estimated to give an accurate projection. Experiments show that the method can project the laser points onto the image plane with an average error of 1.01 pixels (1.51 pixels worst case).

  14. Optimizing High-Z Coatings for Inertial Fusion Energy Shells

    SciTech Connect

    Stephens, Elizabeth H.; Nikroo, Abbas; Goodin, Daniel T.; Petzoldt, Ronald W.

    2003-05-15

    Inertial fusion energy (IFE) reactors require shells with a high-Z coating that is both permeable, for timely filling with deuterium-tritium, and reflective, for survival in the chamber. Previously, gold was deposited on shells while they were agitated to obtain uniform, reproducible coatings. However, these coatings were rather impermeable, resulting in unacceptably long fill times. We report here on an initial study on Pd coatings on shells in the same manner. We have found that these palladium-coated shells are substantially more permeable than gold. Pd coatings on shells remained stable on exposure to deuterium. Pd coatings had lower reflectivity compared to gold that leads to a lower working temperature, and efficiency, of the proposed fusion reactor. Seeking to combine the permeability of Pd coatings and high reflectivity of gold, AuPd-alloy coatings were produced using a cosputtering technique. These alloys demonstrated higher permeability than Au and higher reflectivity than Pd. However, these coatings were still less reflective than the gold coatings. To improve the permeability of gold's coatings, permeation experiments were performed at higher temperatures. With the parameters of composition, thickness, and temperature, we have the ability to comply with a large target design window.

  15. Sensor fusion with on-line gas emission multisensor arrays and standard process measuring devices in baker's yeast manufacturing process.

    PubMed

    Mandenius, C F; Eklöv, T; Lundström, I

    1997-07-20

    The use of a multisensor array for measuring the emission from a production-scale baker's yeast manufacturing process is reported. The sensor array, containing 14 different gas-sensitive semiconductor devices and an infrared gas sensor, was used to monitor the gas emission from a yeast culture bioreactor during fed-batch operation. The signal pattern from the sensors was evaluated in relation to two key process variables, the cell mass and the ethanol concentrations. Fusion with the on-line sensor signals for reactor weight and aeration rate made it possible to estimate cell mass and ethanol concentration using computation with backpropagating artificial neural nets. Identification of process states with the same fusion of sensor signals was realized using principal component analysis. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 55: 427-438, 1997.

  16. Anchor node localization for wireless sensor networks using video and compass information fusion.

    PubMed

    Pescaru, Dan; Curiac, Daniel-Ioan

    2014-01-01

    Distributed sensing, computing and communication capabilities of wireless sensor networks require, in most situations, an efficient node localization procedure. In the case of random deployments in harsh or hostile environments, a general localization process within global coordinates is based on a set of anchor nodes able to determine their own position using GPS receivers. In this paper we propose another anchor node localization technique that can be used when GPS devices cannot accomplish their mission or are considered to be too expensive. This novel technique is based on the fusion of video and compass data acquired by the anchor nodes and is especially suitable for video- or multimedia-based wireless sensor networks. For these types of wireless networks the presence of video cameras is intrinsic, while the presence of digital compasses is also required for identifying the cameras' orientations. PMID:24594614

  17. Anchor Node Localization for Wireless Sensor Networks Using Video and Compass Information Fusion

    PubMed Central

    Pescaru, Dan; Curiac, Daniel-Ioan

    2014-01-01

    Distributed sensing, computing and communication capabilities of wireless sensor networks require, in most situations, an efficient node localization procedure. In the case of random deployments in harsh or hostile environments, a general localization process within global coordinates is based on a set of anchor nodes able to determine their own position using GPS receivers. In this paper we propose another anchor node localization technique that can be used when GPS devices cannot accomplish their mission or are considered to be too expensive. This novel technique is based on the fusion of video and compass data acquired by the anchor nodes and is especially suitable for video- or multimedia-based wireless sensor networks. For these types of wireless networks the presence of video cameras is intrinsic, while the presence of digital compasses is also required for identifying the cameras' orientations. PMID:24594614

  18. Integrated multi-sensor fusion for mapping and localization in outdoor environments for mobile robots

    NASA Astrophysics Data System (ADS)

    Emter, Thomas; Petereit, Janko

    2014-05-01

    An integrated multi-sensor fusion framework for localization and mapping for autonomous navigation in unstructured outdoor environments based on extended Kalman filters (EKF) is presented. The sensors for localization include an inertial measurement unit, a GPS, a fiber optic gyroscope, and wheel odometry. Additionally a 3D LIDAR is used for simultaneous localization and mapping (SLAM). A 3D map is built while concurrently a localization in a so far established 2D map is estimated with the current scan of the LIDAR. Despite of longer run-time of the SLAM algorithm compared to the EKF update, a high update rate is still guaranteed by sophisticatedly joining and synchronizing two parallel localization estimators.

  19. Sensor fusion performance gain for buried mine/UXO detection using GPR, EMI, and MAG sensors

    NASA Astrophysics Data System (ADS)

    Marble, Jay A.; Ackenhusen, John G.; Wegrzyn, John W.; Mancuso, Joseph; Dwan, Chris M.

    2000-08-01

    In this presentation, we compare the gain in performance offered by combing the result of a ground-penetrating radar, an electromagnetic induction metal detector, and a magnetometer (MAG) against the performance offered by any one of these sensors alone on the problem of buried mine and unexploded ordnance detection. Using the community-wide DARPA background clutter data set, we characterize the single-channel performance of each of these detectors, describing the preprocessing and detection processing used for each. We then combine the sensor results, using a variety of binary decision-level Boolean methods. A performance gain was observed as a two-to-threefold reduction in the false alarm rate, operating at an 80 percent probability of detection, for 'majority voting', which was the best of the combining methods.

  20. Optimization of parasitic isolators in laser fusion systems

    SciTech Connect

    Figueira, J.F.; Phipps, C.R. Jr.

    1980-01-01

    The results of model calculations for the optimization of the efficiency of high-gain amplifier systems stabilized by saturable absorbers are described. It is shown that the isolator performance can be characterized by a convenient figure of merit.

  1. An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation

    PubMed Central

    He, Changyu; Kazanzides, Peter; Sen, Hasan Tutkun; Kim, Sungmin; Liu, Yue

    2015-01-01

    Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight between the camera and the markers, which may be difficult to maintain in actual applications. In contrast, inertial sensing does not require line-of-sight but is subject to drift, which may cause large cumulative errors, especially during the measurement of position. To handle cases where some or all of the markers are occluded, this paper proposes an inertial and optical sensor fusion approach in which the bias of the inertial sensors is estimated when the optical tracker provides full six degree-of-freedom (6-DOF) pose information. As long as the position of at least one marker can be tracked by the optical system, the 3-DOF position can be combined with the orientation estimated from the inertial measurements to recover the full 6-DOF pose information. When all the markers are occluded, the position tracking relies on the inertial sensors that are bias-corrected by the optical tracking system. Experiments are performed with an augmented reality head-mounted display (ARHMD) that integrates an optical tracking system (OTS) and inertial measurement unit (IMU). Experimental results show that under partial occlusion conditions, the root mean square errors (RMSE) of orientation and position are 0.04° and 0.134 mm, and under total occlusion conditions for 1 s, the orientation and position RMSE are 0.022° and 0.22 mm, respectively. Thus, the proposed sensor fusion approach can provide reliable 6-DOF pose under long-term partial occlusion and short-term total occlusion conditions. PMID:26184191

  2. An Inertial and Optical Sensor Fusion Approach for Six Degree-of-Freedom Pose Estimation.

    PubMed

    He, Changyu; Kazanzides, Peter; Sen, Hasan Tutkun; Kim, Sungmin; Liu, Yue

    2015-01-01

    Optical tracking provides relatively high accuracy over a large workspace but requires line-of-sight between the camera and the markers, which may be difficult to maintain in actual applications. In contrast, inertial sensing does not require line-of-sight but is subject to drift, which may cause large cumulative errors, especially during the measurement of position. To handle cases where some or all of the markers are occluded, this paper proposes an inertial and optical sensor fusion approach in which the bias of the inertial sensors is estimated when the optical tracker provides full six degree-of-freedom (6-DOF) pose information. As long as the position of at least one marker can be tracked by the optical system, the 3-DOF position can be combined with the orientation estimated from the inertial measurements to recover the full 6-DOF pose information. When all the markers are occluded, the position tracking relies on the inertial sensors that are bias-corrected by the optical tracking system. Experiments are performed with an augmented reality head-mounted display (ARHMD) that integrates an optical tracking system (OTS) and inertial measurement unit (IMU). Experimental results show that under partial occlusion conditions, the root mean square errors (RMSE) of orientation and position are 0.04° and 0.134 mm, and under total occlusion conditions for 1 s, the orientation and position RMSE are 0.022° and 0.22 mm, respectively. Thus, the proposed sensor fusion approach can provide reliable 6-DOF pose under long-term partial occlusion and short-term total occlusion conditions.

  3. Optimizing probe design for an implantable perfusion and oxygenation sensor

    SciTech Connect

    Akl, Tony; Long, Ruiqi; McShane, Michael J.; Ericson, Milton Nance; Wilson, Mark A.; Cote, Gerard L.

    2011-01-01

    In an effort to develop an implantable optical perfusion and oxygenation sensor, based on multiwavelength reflectance pulse oximetry, we investigate the effect of source detector separation and other source-detector characteristics to optimize the sensor s signal to background ratio using Monte Carlo (MC) based simulations and in vitro phantom studies. Separations in the range 0.45 to 1.25 mm were found to be optimal in the case of a point source. The numerical aperture (NA) of the source had no effect on the collected signal while the widening of the source spatial profile caused a shift in the optimal source-detector separation. Specifically, for a 4.5 mm flat beam and a 2.4 mm 2.5 mm photodetector, the optimal performance was found to be when the source and detector are adjacent to each other. These modeling results were confirmed by data collected from in vitro experiments on a liver phantom perfused with dye solutions mimicking the absorption properties of hemoglobin for different oxygenation states.

  4. A Method Based on Multi-Sensor Data Fusion for Fault Detection of Planetary Gearboxes

    PubMed Central

    Lei, Yaguo; Lin, Jing; He, Zhengjia; Kong, Detong

    2012-01-01

    Studies on fault detection and diagnosis of planetary gearboxes are quite limited compared with those of fixed-axis gearboxes. Different from fixed-axis gearboxes, planetary gearboxes exhibit unique behaviors, which invalidate fault diagnosis methods that work well for fixed-axis gearboxes. It is a fact that for systems as complex as planetary gearboxes, multiple sensors mounted on different locations provide complementary information on the health condition of the systems. On this basis, a fault detection method based on multi-sensor data fusion is introduced in this paper. In this method, two features developed for planetary gearboxes are used to characterize the gear health conditions, and an adaptive neuro-fuzzy inference system (ANFIS) is utilized to fuse all features from different sensors. In order to demonstrate the effectiveness of the proposed method, experiments are carried out on a planetary gearbox test rig, on which multiple accelerometers are mounted for data collection. The comparisons between the proposed method and the methods based on individual sensors show that the former achieves much higher accuracies in detecting planetary gearbox faults. PMID:22438750

  5. A method based on multi-sensor data fusion for fault detection of planetary gearboxes.

    PubMed

    Lei, Yaguo; Lin, Jing; He, Zhengjia; Kong, Detong

    2012-01-01

    Studies on fault detection and diagnosis of planetary gearboxes are quite limited compared with those of fixed-axis gearboxes. Different from fixed-axis gearboxes, planetary gearboxes exhibit unique behaviors, which invalidate fault diagnosis methods that work well for fixed-axis gearboxes. It is a fact that for systems as complex as planetary gearboxes, multiple sensors mounted on different locations provide complementary information on the health condition of the systems. On this basis, a fault detection method based on multi-sensor data fusion is introduced in this paper. In this method, two features developed for planetary gearboxes are used to characterize the gear health conditions, and an adaptive neuro-fuzzy inference system (ANFIS) is utilized to fuse all features from different sensors. In order to demonstrate the effectiveness of the proposed method, experiments are carried out on a planetary gearbox test rig, on which multiple accelerometers are mounted for data collection. The comparisons between the proposed method and the methods based on individual sensors show that the former achieves much higher accuracies in detecting planetary gearbox faults.

  6. Sensor fusion: lane marking detection and autonomous intelligent cruise control system

    NASA Astrophysics Data System (ADS)

    Baret, Marc; Baillarin, S.; Calesse, C.; Martin, Lionel

    1995-12-01

    In the past few years MATRA and RENAULT have developed an Autonomous Intelligent Cruise Control (AICC) system based on a LIDAR sensor. This sensor incorporating a charge coupled device was designed to acquire pulsed laser diode emission reflected by standard car reflectors. The absence of moving mechanical parts, the large field of view, the high measurement rate and the very good accuracy for distance range and angular position of targets make this sensor very interesting. It provides the equipped car with the distance and the relative speed of other vehicles enabling the safety distance to be controlled by acting on the throttle and the automatic gear box. Experiments in various real traffic situations have shown the limitations of this kind of system especially on bends. All AICC sensors are unable to distinguish between a bend and a change of lane. This is easily understood if we consider a road without lane markings. This fact has led MATRA to improve its AICC system by providing the lane marking information. Also in the scope of the EUREKA PROMETHEUS project, MATRA and RENAULT have developed a lane keeping system in order to warn of the drivers lack of vigilance. Thus, MATRA have spread this system to far field lane marking detection and have coupled it with the AICC system. Experiments will be carried out on roads to estimate the gain in performance and comfort due to this fusion.

  7. Exploiting node mobility for energy optimization in wireless sensor networks

    NASA Astrophysics Data System (ADS)

    El-Moukaddem, Fatme Mohammad

    Wireless Sensor Networks (WSNs) have become increasingly available for data-intensive applications such as micro-climate monitoring, precision agriculture, and audio/video surveillance. A key challenge faced by data-intensive WSNs is to transmit the sheer amount of data generated within an application's lifetime to the base station despite the fact that sensor nodes have limited power supplies such as batteries or small solar panels. The availability of numerous low-cost robotic units (e.g. Robomote and Khepera) has made it possible to construct sensor networks consisting of mobile sensor nodes. It has been shown that the controlled mobility offered by mobile sensors can be exploited to improve the energy efficiency of a network. In this thesis, we propose schemes that use mobile sensor nodes to reduce the energy consumption of data-intensive WSNs. Our approaches differ from previous work in two main aspects. First, our approaches do not require complex motion planning of mobile nodes, and hence can be implemented on a number of low-cost mobile sensor platforms. Second, we integrate the energy consumption due to both mobility and wireless communications into a holistic optimization framework. We consider three problems arising from the limited energy in the sensor nodes. In the first problem, the network consists of mostly static nodes and contains only a few mobile nodes. In the second and third problems, we assume essentially that all nodes in the WSN are mobile. We first study a new problem called max-data mobile relay configuration (MMRC ) that finds the positions of a set of mobile sensors, referred to as relays, that maximize the total amount of data gathered by the network during its lifetime. We show that the MMRC problem is surprisingly complex even for a trivial network topology due to the joint consideration of the energy consumption of both wireless communication and mechanical locomotion. We present optimal MMRC algorithms and practical distributed

  8. Discrete-Time ARMAv Model-Based Optimal Sensor Placement

    SciTech Connect

    Song Wei; Dyke, Shirley J.

    2008-07-08

    This paper concentrates on the optimal sensor placement problem in ambient vibration based structural health monitoring. More specifically, the paper examines the covariance of estimated parameters during system identification using auto-regressive and moving average vector (ARMAv) model. By utilizing the discrete-time steady state Kalman filter, this paper realizes the structure's finite element (FE) model under broad-band white noise excitations using an ARMAv model. Based on the asymptotic distribution of the parameter estimates of the ARMAv model, both a theoretical closed form and a numerical estimate form of the covariance of the estimates are obtained. Introducing the information entropy (differential entropy) measure, as well as various matrix norms, this paper attempts to find a reasonable measure to the uncertainties embedded in the ARMAv model estimates. Thus, it is possible to select the optimal sensor placement that would lead to the smallest uncertainties during the ARMAv identification process. Two numerical examples are provided to demonstrate the methodology and compare the sensor placement results upon various measures.

  9. Gyro Drift Correction for An Indirect Kalman Filter Based Sensor Fusion Driver.

    PubMed

    Lee, Chan-Gun; Dao, Nhu-Ngoc; Jang, Seonmin; Kim, Deokhwan; Kim, Yonghun; Cho, Sungrae

    2016-01-01

    Sensor fusion techniques have made a significant contribution to the success of the recently emerging mobile applications era because a variety of mobile applications operate based on multi-sensing information from the surrounding environment, such as navigation systems, fitness trackers, interactive virtual reality games, etc. For these applications, the accuracy of sensing information plays an important role to improve the user experience (UX) quality, especially with gyroscopes and accelerometers. Therefore, in this paper, we proposed a novel mechanism to resolve the gyro drift problem, which negatively affects the accuracy of orientation computations in the indirect Kalman filter based sensor fusion. Our mechanism focuses on addressing the issues of external feedback loops and non-gyro error elements contained in the state vectors of an indirect Kalman filter. Moreover, the mechanism is implemented in the device-driver layer, providing lower process latency and transparency capabilities for the upper applications. These advances are relevant to millions of legacy applications since utilizing our mechanism does not require the existing applications to be re-programmed. The experimental results show that the root mean square errors (RMSE) before and after applying our mechanism are significantly reduced from 6.3 × 10(-1) to 5.3 × 10(-7), respectively. PMID:27294941

  10. Gyro Drift Correction for An Indirect Kalman Filter Based Sensor Fusion Driver

    PubMed Central

    Lee, Chan-Gun; Dao, Nhu-Ngoc; Jang, Seonmin; Kim, Deokhwan; Kim, Yonghun; Cho, Sungrae

    2016-01-01

    Sensor fusion techniques have made a significant contribution to the success of the recently emerging mobile applications era because a variety of mobile applications operate based on multi-sensing information from the surrounding environment, such as navigation systems, fitness trackers, interactive virtual reality games, etc. For these applications, the accuracy of sensing information plays an important role to improve the user experience (UX) quality, especially with gyroscopes and accelerometers. Therefore, in this paper, we proposed a novel mechanism to resolve the gyro drift problem, which negatively affects the accuracy of orientation computations in the indirect Kalman filter based sensor fusion. Our mechanism focuses on addressing the issues of external feedback loops and non-gyro error elements contained in the state vectors of an indirect Kalman filter. Moreover, the mechanism is implemented in the device-driver layer, providing lower process latency and transparency capabilities for the upper applications. These advances are relevant to millions of legacy applications since utilizing our mechanism does not require the existing applications to be re-programmed. The experimental results show that the root mean square errors (RMSE) before and after applying our mechanism are significantly reduced from 6.3×10-1 to 5.3×10-7, respectively. PMID:27294941

  11. Gyro Drift Correction for An Indirect Kalman Filter Based Sensor Fusion Driver.

    PubMed

    Lee, Chan-Gun; Dao, Nhu-Ngoc; Jang, Seonmin; Kim, Deokhwan; Kim, Yonghun; Cho, Sungrae

    2016-06-11

    Sensor fusion techniques have made a significant contribution to the success of the recently emerging mobile applications era because a variety of mobile applications operate based on multi-sensing information from the surrounding environment, such as navigation systems, fitness trackers, interactive virtual reality games, etc. For these applications, the accuracy of sensing information plays an important role to improve the user experience (UX) quality, especially with gyroscopes and accelerometers. Therefore, in this paper, we proposed a novel mechanism to resolve the gyro drift problem, which negatively affects the accuracy of orientation computations in the indirect Kalman filter based sensor fusion. Our mechanism focuses on addressing the issues of external feedback loops and non-gyro error elements contained in the state vectors of an indirect Kalman filter. Moreover, the mechanism is implemented in the device-driver layer, providing lower process latency and transparency capabilities for the upper applications. These advances are relevant to millions of legacy applications since utilizing our mechanism does not require the existing applications to be re-programmed. The experimental results show that the root mean square errors (RMSE) before and after applying our mechanism are significantly reduced from 6.3 × 10(-1) to 5.3 × 10(-7), respectively.

  12. Real-time Enhancement, Registration, and Fusion for a Multi-Sensor Enhanced Vision System

    NASA Technical Reports Server (NTRS)

    Hines, Glenn D.; Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

    2006-01-01

    Over the last few years NASA Langley Research Center (LaRC) has been developing an Enhanced Vision System (EVS) to aid pilots while flying in poor visibility conditions. The EVS captures imagery using two infrared video cameras. The cameras are placed in an enclosure that is mounted and flown forward-looking underneath the NASA LaRC ARIES 757 aircraft. The data streams from the cameras are processed in real-time and displayed on monitors on-board the aircraft. With proper processing the camera system can provide better-than- human-observed imagery particularly during poor visibility conditions. However, to obtain this goal requires several different stages of processing including enhancement, registration, and fusion, and specialized processing hardware for real-time performance. We are using a real-time implementation of the Retinex algorithm for image enhancement, affine transformations for registration, and weighted sums to perform fusion. All of the algorithms are executed on a single TI DM642 digital signal processor (DSP) clocked at 720 MHz. The image processing components were added to the EVS system, tested, and demonstrated during flight tests in August and September of 2005. In this paper we briefly discuss the EVS image processing hardware and algorithms. We then discuss implementation issues and show examples of the results obtained during flight tests. Keywords: enhanced vision system, image enhancement, retinex, digital signal processing, sensor fusion

  13. Hybrid swarm intelligence optimization approach for optimal data storage position identification in wireless sensor networks.

    PubMed

    Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

    2015-01-01

    The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches.

  14. Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

    PubMed Central

    Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

    2015-01-01

    The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches. PMID:25734182

  15. Nuclear performance optimization of the molten-salt fusion breeder

    SciTech Connect

    Lee, J.D.; Bandini, B.R.

    1986-06-05

    Improved nuclear analysis, including the treatment of resonance and spatial self-shielding, coupled with an optimization procedure, has resulted in an improved performance estimate for the molten salt blanket. Net U-233 breeding ratio ranges between 0.58 and 0.63, and blanket energy multiplication ranges between 1.8 and 1.9.

  16. The Optimized Block-Regression Fusion Algorithm for Pansharpening of Very High Resolution Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Zhang, J. X.; Yang, J. H.; Reinartz, P.

    2016-06-01

    Pan-sharpening of very high resolution remotely sensed imagery need enhancing spatial details while preserving spectral characteristics, and adjusting the sharpened results to realize the different emphases between the two abilities. In order to meet the requirements, this paper is aimed at providing an innovative solution. The block-regression-based algorithm (BR), which was previously presented for fusion of SAR and optical imagery, is firstly applied to sharpen the very high resolution satellite imagery, and the important parameter for adjustment of fusion result, i.e., block size, is optimized according to the two experiments for Worldview-2 and QuickBird datasets in which the optimal block size is selected through the quantitative comparison of the fusion results of different block sizes. Compared to five fusion algorithms (i.e., PC, CN, AWT, Ehlers, BDF) in fusion effects by means of quantitative analysis, BR is reliable for different data sources and can maximize enhancement of spatial details at the expense of a minimum spectral distortion.

  17. Fusion

    NASA Astrophysics Data System (ADS)

    Herman, Robin

    1990-10-01

    The book abounds with fascinating anecdotes about fusion's rocky path: the spurious claim by Argentine dictator Juan Peron in 1951 that his country had built a working fusion reactor, the rush by the United States to drop secrecy and publicize its fusion work as a propaganda offensive after the Russian success with Sputnik; the fortune Penthouse magazine publisher Bob Guccione sank into an unconventional fusion device, the skepticism that met an assertion by two University of Utah chemists in 1989 that they had created "cold fusion" in a bottle. Aimed at a general audience, the book describes the scientific basis of controlled fusion--the fusing of atomic nuclei, under conditions hotter than the sun, to release energy. Using personal recollections of scientists involved, it traces the history of this little-known international race that began during the Cold War in secret laboratories in the United States, Great Britain and the Soviet Union, and evolved into an astonishingly open collaboration between East and West.

  18. Application of Multi-Sensor Fusion to the Aerosol Forecasting Problem

    NASA Astrophysics Data System (ADS)

    Reid, J. S.; Zhang, J.; Hsu, C.; Christopher, S. A.; Hyer, E. J.; Kuciaskas, A. P.; Westphal, D. L.; Kahn, R. A.; Hansen, J. A.

    2007-12-01

    The current Earth observing satellite constellation is at a pinnacle, and the near-future schedule suggests that a host of environmental monitoring capabilities will likely be lost over the next five to ten years. The MODIS carrying satellites are nearing the end of their design life, and the NPOESS satellites have been de-scoped and delayed. Many A-Train products, currently taken for granted, will simply not exist to support continuing operational aerosol missions. This situation places the aerosol forecasting community in a particularly difficult position. For air quality systems, the utilization of multiple satellite products and sensors in a data assimilation framework will become a necessity. In this talk we give a brief overview of current capabilities and challenges based on existing sensor products. This includes not only those pertaining to aerosol particle retrievals, but related environmental products that have great potential in improving simulations of 4-dimensional aerosol fields. However, we also show that situations can arise where multi-product fusion and assimilation can actually be detrimental if not interpreted carefully. Given future sensor efficacy and mission plans, possible solutions will then be given on how to maintain our current capabilities into the future. Potential exists not only for fusion of level 2 or 3 products, but also for incorporating numerous level 1b products in single retrievals. Similarly, model results should influence the retrieval process, whether through external meteorological and ensemble input, iterative product data assimilation, or ultimately, radiance assimilation. We see hope for consistency through the Deep Blue algorithm or through combined polar orbiter/geostationary products such as the proposed multi-angle spectropolarimetric imager (MSPI) with GOES-R.

  19. Motion-sensor fusion-based gesture recognition and its VLSI architecture design for mobile devices

    NASA Astrophysics Data System (ADS)

    Zhu, Wenping; Liu, Leibo; Yin, Shouyi; Hu, Siqi; Tang, Eugene Y.; Wei, Shaojun

    2014-05-01

    With the rapid proliferation of smartphones and tablets, various embedded sensors are incorporated into these platforms to enable multimodal human-computer interfaces. Gesture recognition, as an intuitive interaction approach, has been extensively explored in the mobile computing community. However, most gesture recognition implementations by now are all user-dependent and only rely on accelerometer. In order to achieve competitive accuracy, users are required to hold the devices in predefined manner during the operation. In this paper, a high-accuracy human gesture recognition system is proposed based on multiple motion sensor fusion. Furthermore, to reduce the energy overhead resulted from frequent sensor sampling and data processing, a high energy-efficient VLSI architecture implemented on a Xilinx Virtex-5 FPGA board is also proposed. Compared with the pure software implementation, approximately 45 times speed-up is achieved while operating at 20 MHz. The experiments show that the average accuracy for 10 gestures achieves 93.98% for user-independent case and 96.14% for user-dependent case when subjects hold the device randomly during completing the specified gestures. Although a few percent lower than the conventional best result, it still provides competitive accuracy acceptable for practical usage. Most importantly, the proposed system allows users to hold the device randomly during operating the predefined gestures, which substantially enhances the user experience.

  20. Multi sensor fusion framework for indoor-outdoor localization of limited resource mobile robots.

    PubMed

    Marín, Leonardo; Vallés, Marina; Soriano, Ángel; Valera, Ángel; Albertos, Pedro

    2013-10-21

    This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments.

  1. Multi sensor fusion framework for indoor-outdoor localization of limited resource mobile robots.

    PubMed

    Marín, Leonardo; Vallés, Marina; Soriano, Ángel; Valera, Ángel; Albertos, Pedro

    2013-01-01

    This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments. PMID:24152933

  2. Fusion of Haptic and Gesture Sensors for Rehabilitation of Bimanual Coordination and Dexterous Manipulation

    PubMed Central

    Yu, Ningbo; Xu, Chang; Li, Huanshuai; Wang, Kui; Wang, Liancheng; Liu, Jingtai

    2016-01-01

    Disabilities after neural injury, such as stroke, bring tremendous burden to patients, families and society. Besides the conventional constrained-induced training with a paretic arm, bilateral rehabilitation training involves both the ipsilateral and contralateral sides of the neural injury, fitting well with the fact that both arms are needed in common activities of daily living (ADLs), and can promote good functional recovery. In this work, the fusion of a gesture sensor and a haptic sensor with force feedback capabilities has enabled a bilateral rehabilitation training therapy. The Leap Motion gesture sensor detects the motion of the healthy hand, and the omega.7 device can detect and assist the paretic hand, according to the designed cooperative task paradigm, as much as needed, with active force feedback to accomplish the manipulation task. A virtual scenario has been built up, and the motion and force data facilitate instantaneous visual and audio feedback, as well as further analysis of the functional capabilities of the patient. This task-oriented bimanual training paradigm recruits the sensory, motor and cognitive aspects of the patient into one loop, encourages the active involvement of the patients into rehabilitation training, strengthens the cooperation of both the healthy and impaired hands, challenges the dexterous manipulation capability of the paretic hand, suits easy of use at home or centralized institutions and, thus, promises effective potentials for rehabilitation training. PMID:26999149

  3. Sensor Fusion of Cameras and a Laser for City-Scale 3D Reconstruction

    PubMed Central

    Bok, Yunsu; Choi, Dong-Geol; Kweon, In So

    2014-01-01

    This paper presents a sensor fusion system of cameras and a 2D laser sensor for large-scale 3D reconstruction. The proposed system is designed to capture data on a fast-moving ground vehicle. The system consists of six cameras and one 2D laser sensor, and they are synchronized by a hardware trigger. Reconstruction of 3D structures is done by estimating frame-by-frame motion and accumulating vertical laser scans, as in previous works. However, our approach does not assume near 2D motion, but estimates free motion (including absolute scale) in 3D space using both laser data and image features. In order to avoid the degeneration associated with typical three-point algorithms, we present a new algorithm that selects 3D points from two frames captured by multiple cameras. The problem of error accumulation is solved by loop closing, not by GPS. The experimental results show that the estimated path is successfully overlaid on the satellite images, such that the reconstruction result is very accurate. PMID:25375758

  4. Multi Sensor Fusion Framework for Indoor-Outdoor Localization of Limited Resource Mobile Robots

    PubMed Central

    Marín, Leonardo; Vallés, Marina; Soriano, Ángel; Valera, Ángel; Albertos, Pedro

    2013-01-01

    This paper presents a sensor fusion framework that improves the localization of mobile robots with limited computational resources. It employs an event based Kalman Filter to combine the measurements of a global sensor and an inertial measurement unit (IMU) on an event based schedule, using fewer resources (execution time and bandwidth) but with similar performance when compared to the traditional methods. The event is defined to reflect the necessity of the global information, when the estimation error covariance exceeds a predefined limit. The proposed experimental platforms are based on the LEGO Mindstorm NXT, and consist of a differential wheel mobile robot navigating indoors with a zenithal camera as global sensor, and an Ackermann steering mobile robot navigating outdoors with a SBG Systems GPS accessed through an IGEP board that also serves as datalogger. The IMU in both robots is built using the NXT motor encoders along with one gyroscope, one compass and two accelerometers from Hitecnic, placed according to a particle based dynamic model of the robots. The tests performed reflect the correct performance and low execution time of the proposed framework. The robustness and stability is observed during a long walk test in both indoors and outdoors environments. PMID:24152933

  5. Genetic Algorithm Application in Optimization of Wireless Sensor Networks

    PubMed Central

    Norouzi, Ali; Zaim, A. Halim

    2014-01-01

    There are several applications known for wireless sensor networks (WSN), and such variety demands improvement of the currently available protocols and the specific parameters. Some notable parameters are lifetime of network and energy consumption for routing which play key role in every application. Genetic algorithm is one of the nonlinear optimization methods and relatively better option thanks to its efficiency for large scale applications and that the final formula can be modified by operators. The present survey tries to exert a comprehensive improvement in all operational stages of a WSN including node placement, network coverage, clustering, and data aggregation and achieve an ideal set of parameters of routing and application based WSN. Using genetic algorithm and based on the results of simulations in NS, a specific fitness function was achieved, optimized, and customized for all the operational stages of WSNs. PMID:24693235

  6. Optimal sensor placement for modal testing on wind turbines

    NASA Astrophysics Data System (ADS)

    Schulze, Andreas; Zierath, János; Rosenow, Sven-Erik; Bockhahn, Reik; Rachholz, Roman; Woernle, Christoph

    2016-09-01

    The mechanical design of wind turbines requires a profound understanding of the dynamic behaviour. Even though highly detailed simulation models are already in use to support wind turbine design, modal testing on a real prototype is irreplaceable to identify site-specific conditions such as the stiffness of the tower foundation. Correct identification of the mode shapes of a complex mechanical structure much depends on the placement of the sensors. For operational modal analysis of a 3 MW wind turbine with a 120 m rotor on a 100 m tower developed by W2E Wind to Energy, algorithms for optimal placement of acceleration sensors are applied. The mode shapes used for the optimisation are calculated by means of a detailed flexible multibody model of the wind turbine. Among the three algorithms in this study, the genetic algorithm with weighted off-diagonal criterion yields the sensor configuration with the highest quality. The ongoing measurements on the prototype will be the basis for the development of optimised wind turbine designs.

  7. Optimization design of the coil of the eddy current sensor

    NASA Astrophysics Data System (ADS)

    Pu, Tiecheng; Fan, Shangchun

    2006-11-01

    An eddy current sensor is usually used to measure the departure of a shaft from its axes, in order to avoid destroying the system because of collision. The design of the coil as the sense organ of an eddy current sensor is to search a set of proper sizes (includes the outer radius, the inner radius and tallness of the coil) in which the quality factor and the grads of magnetic field strength is great as soon as possible but the length of the lead is not much long. So an optimization function is introduced here for efficient design. This function is direct ratio with the quality factor of the core and the magnetic grads product by the coil and inverse ratio with the lead length. The proportions of three parameters can be changed according to the instance. When the value of the function reaches the maximum, the sizes of coil are the anticipant optimal sizes and the integration capability of the coil is at the high-point. To search the maximum of the function, the genetic algorithm is adopted. The simulation result by Matlab proves the practicability of the method.

  8. Optimizing probe design for an implantable perfusion and oxygenation sensor

    PubMed Central

    Akl, Tony J.; Long, Ruiqi; McShane, Michael J.; Ericson, M. Nance; Wilson, Mark A.; Coté, Gerard L.

    2011-01-01

    In an effort to develop an implantable optical perfusion and oxygenation sensor, based on multiwavelength reflectance pulse oximetry, we investigate the effect of source–detector separation and other source-detector characteristics to optimize the sensor’s signal to background ratio using Monte Carlo (MC) based simulations and in vitro phantom studies. Separations in the range 0.45 to 1.25 mm were found to be optimal in the case of a point source. The numerical aperture (NA) of the source had no effect on the collected signal while the widening of the source spatial profile caused a shift in the optimal source-detector separation. Specifically, for a 4.5 mm flat beam and a 2.4 mm × 2.5 mm photodetector, the optimal performance was found to be when the source and detector are adjacent to each other. These modeling results were confirmed by data collected from in vitro experiments on a liver phantom perfused with dye solutions mimicking the absorption properties of hemoglobin for different oxygenation states. PMID:21833350

  9. Improvement of force-sensor-based heart rate estimation using multichannel data fusion.

    PubMed

    Bruser, Christoph; Kortelainen, Juha M; Winter, Stefan; Tenhunen, Mirja; Parkka, Juha; Leonhardt, Steffen

    2015-01-01

    The aim of this paper is to present and evaluate algorithms for heartbeat interval estimation from multiple spatially distributed force sensors integrated into a bed. Moreover, the benefit of using multichannel systems as opposed to a single sensor is investigated. While it might seem intuitive that multiple channels are superior to a single channel, the main challenge lies in finding suitable methods to actually leverage this potential. To this end, two algorithms for heart rate estimation from multichannel vibration signals are presented and compared against a single-channel sensing solution. The first method operates by analyzing the cepstrum computed from the average spectra of the individual channels, while the second method applies Bayesian fusion to three interval estimators, such as the autocorrelation, which are applied to each channel. This evaluation is based on 28 night-long sleep lab recordings during which an eight-channel polyvinylidene fluoride-based sensor array was used to acquire cardiac vibration signals. The recruited patients suffered from different sleep disorders of varying severity. From the sensor array data, a virtual single-channel signal was also derived for comparison by averaging the channels. The single-channel results achieved a beat-to-beat interval error of 2.2% with a coverage (i.e., percentage of the recording which could be analyzed) of 68.7%. In comparison, the best multichannel results attained a mean error and coverage of 1.0% and 81.0%, respectively. These results present statistically significant improvements of both metrics over the single-channel results (p < 0.05).

  10. A data fusion algorithm for multi-sensor microburst hazard assessment

    NASA Technical Reports Server (NTRS)

    Wanke, Craig R.; Hansman, R. John

    1994-01-01

    A recursive model-based data fusion algorithm for multi-sensor microburst hazard assessment is described. An analytical microburst model is used to approximate the actual windfield, and a set of 'best' model parameters are estimated from measured winds. The winds corresponding to the best parameter set can then be used to compute alerting factors such as microburst position, extent, and intensity. The estimation algorithm is based on an iterated extended Kalman filter which uses the microburst model parameters as state variables. Microburst state dynamic and process noise parameters are chosen based on measured microburst statistics. The estimation method is applied to data from a time-varying computational simulation of a historical microburst event to demonstrate its capabilities and limitations. Selection of filter parameters and initial conditions is discussed. Computational requirements and datalink bandwidth considerations are also addressed.

  11. Context-Aware Personal Navigation Using Embedded Sensor Fusion in Smartphones

    PubMed Central

    Saeedi, Sara; Moussa, Adel; El-Sheimy, Naser

    2014-01-01

    Context-awareness is an interesting topic in mobile navigation scenarios where the context of the application is highly dynamic. Using context-aware computing, navigation services consider the situation of user, not only in the design process, but in real time while the device is in use. The basic idea is that mobile navigation services can provide different services based on different contexts—where contexts are related to the user's activity and the device placement. Context-aware systems are concerned with the following challenges which are addressed in this paper: context acquisition, context understanding, and context-aware application adaptation. The proposed approach in this paper is using low-cost sensors in a multi-level fusion scheme to improve the accuracy and robustness of context-aware navigation system. The experimental results demonstrate the capabilities of the context-aware Personal Navigation Systems (PNS) for outdoor personal navigation using a smartphone. PMID:24670715

  12. Real-time classification and sensor fusion with a spiking deep belief network

    PubMed Central

    O'Connor, Peter; Neil, Daniel; Liu, Shih-Chii; Delbruck, Tobi; Pfeiffer, Michael

    2013-01-01

    Deep Belief Networks (DBNs) have recently shown impressive performance on a broad range of classification problems. Their generative properties allow better understanding of the performance, and provide a simpler solution for sensor fusion tasks. However, because of their inherent need for feedback and parallel update of large numbers of units, DBNs are expensive to implement on serial computers. This paper proposes a method based on the Siegert approximation for Integrate-and-Fire neurons to map an offline-trained DBN onto an efficient event-driven spiking neural network suitable for hardware implementation. The method is demonstrated in simulation and by a real-time implementation of a 3-layer network with 2694 neurons used for visual classification of MNIST handwritten digits with input from a 128 × 128 Dynamic Vision Sensor (DVS) silicon retina, and sensory-fusion using additional input from a 64-channel AER-EAR silicon cochlea. The system is implemented through the open-source software in the jAER project and runs in real-time on a laptop computer. It is demonstrated that the system can recognize digits in the presence of distractions, noise, scaling, translation and rotation, and that the degradation of recognition performance by using an event-based approach is less than 1%. Recognition is achieved in an average of 5.8 ms after the onset of the presentation of a digit. By cue integration from both silicon retina and cochlea outputs we show that the system can be biased to select the correct digit from otherwise ambiguous input. PMID:24115919

  13. Real-time classification and sensor fusion with a spiking deep belief network.

    PubMed

    O'Connor, Peter; Neil, Daniel; Liu, Shih-Chii; Delbruck, Tobi; Pfeiffer, Michael

    2013-01-01

    Deep Belief Networks (DBNs) have recently shown impressive performance on a broad range of classification problems. Their generative properties allow better understanding of the performance, and provide a simpler solution for sensor fusion tasks. However, because of their inherent need for feedback and parallel update of large numbers of units, DBNs are expensive to implement on serial computers. This paper proposes a method based on the Siegert approximation for Integrate-and-Fire neurons to map an offline-trained DBN onto an efficient event-driven spiking neural network suitable for hardware implementation. The method is demonstrated in simulation and by a real-time implementation of a 3-layer network with 2694 neurons used for visual classification of MNIST handwritten digits with input from a 128 × 128 Dynamic Vision Sensor (DVS) silicon retina, and sensory-fusion using additional input from a 64-channel AER-EAR silicon cochlea. The system is implemented through the open-source software in the jAER project and runs in real-time on a laptop computer. It is demonstrated that the system can recognize digits in the presence of distractions, noise, scaling, translation and rotation, and that the degradation of recognition performance by using an event-based approach is less than 1%. Recognition is achieved in an average of 5.8 ms after the onset of the presentation of a digit. By cue integration from both silicon retina and cochlea outputs we show that the system can be biased to select the correct digit from otherwise ambiguous input. PMID:24115919

  14. Multiple sensor detection of process phenomena in laser powder bed fusion

    NASA Astrophysics Data System (ADS)

    Lane, Brandon; Whitenton, Eric; Moylan, Shawn

    2016-05-01

    Laser powder bed fusion (LPBF) is an additive manufacturing (AM) process in which a high power laser melts metal powder layers into complex, three-dimensional shapes. LPBF parts are known to exhibit relatively high residual stresses, anisotropic microstructure, and a variety of defects. To mitigate these issues, in-situ measurements of the melt-pool phenomena may illustrate relationships between part quality and process signatures. However, phenomena such as spatter, plume formation, laser modulation, and melt-pool oscillations may require data acquisition rates exceeding 10 kHz. This hinders use of relatively data-intensive, streaming imaging sensors in a real-time monitoring and feedback control system. Single-point sensors such as photodiodes provide the temporal bandwidth to capture process signatures, while providing little spatial information. This paper presents results from experiments conducted on a commercial LPBF machine which incorporated synchronized, in-situ acquisition of a thermal camera, high-speed visible camera, photodiode, and laser modulation signal during fabrication of a nickel alloy 625 AM part with an overhang geometry. Data from the thermal camera provides temperature information, the visible camera provides observation of spatter, and the photodiode signal provides high temporal bandwidth relative brightness stemming from the melt pool region. In addition, joint-time frequency analysis (JTFA) was performed on the photodiode signal. JTFA results indicate what digital filtering and signal processing are required to highlight particular signatures. Image fusion of the synchronized data obtained over multiple build layers allows visual comparison between the photodiode signal and relating phenomena observed in the imaging detectors.

  15. Some aspects of optimal human-computer symbiosis in multisensor geospatial data fusion

    NASA Astrophysics Data System (ADS)

    Levin, E.; Sergeyev, A.

    Nowadays vast amount of the available geospatial data provides additional opportunities for the targeting accuracy increase due to possibility of geospatial data fusion. One of the most obvious operations is determining of the targets 3D shapes and geospatial positions based on overlapped 2D imagery and sensor modeling. 3D models allows for the extraction of such information about targets, which cannot be measured directly based on single non-fused imagery. Paper describes ongoing research effort at Michigan Tech attempting to combine advantages of human analysts and computer automated processing for efficient human computer symbiosis for geospatial data fusion. Specifically, capabilities provided by integration into geospatial targeting interfaces novel human-computer interaction method such as eye-tracking and EEG was explored. Paper describes research performed and results in more details.

  16. Spatial Aspects of Multi-Sensor Data Fusion: Aerosol Optical Thickness

    NASA Technical Reports Server (NTRS)

    Leptoukh, Gregory; Zubko, V.; Gopalan, A.

    2007-01-01

    The Goddard Earth Sciences Data and Information Services Center (GES DISC) investigated the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the multitude of NASA remote sensing data sets, and as part of a larger effort to integrate this capability in the GES-DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni). This initial study focused on merging daily mean Aerosol Optical Thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood technique to merge the pixel values where available. The algorithm was applied to two regional AOT subsets (with mostly regular and irregular gaps, respectively) and a set of AOT fields that differed only in the size and location of artificially created gaps. The Cumulative Semivariogram (CSV) was found to be sensitive to the spatial distribution of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.

  17. The application of machine learning in multi sensor data fusion for activity recognition in mobile device space

    NASA Astrophysics Data System (ADS)

    Marhoubi, Asmaa H.; Saravi, Sara; Edirisinghe, Eran A.

    2015-05-01

    The present generation of mobile handheld devices comes equipped with a large number of sensors. The key sensors include the Ambient Light Sensor, Proximity Sensor, Gyroscope, Compass and the Accelerometer. Many mobile applications are driven based on the readings obtained from either one or two of these sensors. However the presence of multiple-sensors will enable the determination of more detailed activities that are carried out by the user of a mobile device, thus enabling smarter mobile applications to be developed that responds more appropriately to user behavior and device usage. In the proposed research we use recent advances in machine learning to fuse together the data obtained from all key sensors of a mobile device. We investigate the possible use of single and ensemble classifier based approaches to identify a mobile device's behavior in the space it is present. Feature selection algorithms are used to remove non-discriminant features that often lead to poor classifier performance. As the sensor readings are noisy and include a significant proportion of missing values and outliers, we use machine learning based approaches to clean the raw data obtained from the sensors, before use. Based on selected practical case studies, we demonstrate the ability to accurately recognize device behavior based on multi-sensor data fusion.

  18. A millimeter wave image fusion algorithm design and optimization based on CDF97 wavelet transform

    NASA Astrophysics Data System (ADS)

    Yu, Jian-cheng; Chen, Bo-yang; Xia, A.-lin; Liu, Xin-guang

    2011-08-01

    region. Based on this assumption, a new fusion rule is proposed here. Firstly, get the low-frequency part of the selection matrix according to the comparison regional low-frequency energy matrix of the two images. Then, taking into account the consistency and continuity of low-frequency detail, high frequency and low frequency selection matrix can be the same. And this can ensure a better fusion of the edge of the image characteristics. Simulation results show that this algorithm's performance is much better compared to traditional energy-weighted and average method, though less quantitative comparison point compared to the region based method, yet, the difference is small according to the visible evaluation. This algorithm is tested in the self-developed image processing platform based on DM642. By using the optimization strategy, the speed of 256 × 256 dual-channel image fusion can be more than 28 F/S. Therefore, the proposed fusion algorithm can meet the system performance and application requirements.

  19. A sensor fusion method for tracking vertical velocity and height based on inertial and barometric altimeter measurements.

    PubMed

    Sabatini, Angelo Maria; Genovese, Vincenzo

    2014-07-24

    A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04-0.24 m/s; height RMSE was in the range 5-68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions.

  20. A Sensor Fusion Method for Tracking Vertical Velocity and Height Based on Inertial and Barometric Altimeter Measurements

    PubMed Central

    Sabatini, Angelo Maria; Genovese, Vincenzo

    2014-01-01

    A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04–0.24 m/s; height RMSE was in the range 5–68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions. PMID:25061835

  1. A sensor fusion method for tracking vertical velocity and height based on inertial and barometric altimeter measurements.

    PubMed

    Sabatini, Angelo Maria; Genovese, Vincenzo

    2014-01-01

    A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04-0.24 m/s; height RMSE was in the range 5-68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions. PMID:25061835

  2. Flux Tensor Constrained Geodesic Active Contours with Sensor Fusion for Persistent Object Tracking

    PubMed Central

    Bunyak, Filiz; Palaniappan, Kannappan; Nath, Sumit Kumar; Seetharaman, Gunasekaran

    2007-01-01

    This paper makes new contributions in motion detection, object segmentation and trajectory estimation to create a successful object tracking system. A new efficient motion detection algorithm referred to as the flux tensor is used to detect moving objects in infrared video without requiring background modeling or contour extraction. The flux tensor-based motion detector when applied to infrared video is more accurate than thresholding ”hot-spots”, and is insensitive to shadows as well as illumination changes in the visible channel. In real world monitoring tasks fusing scene information from multiple sensors and sources is a useful core mechanism to deal with complex scenes, lighting conditions and environmental variables. The object segmentation algorithm uses level set-based geodesic active contour evolution that incorporates the fusion of visible color and infrared edge informations in a novel manner. Touching or overlapping objects are further refined during the segmentation process using an appropriate shape-based model. Multiple object tracking using correspondence graphs is extended to handle groups of objects and occlusion events by Kalman filter-based cluster trajectory analysis and watershed segmentation. The proposed object tracking algorithm was successfully tested on several difficult outdoor multispectral videos from stationary sensors and is not confounded by shadows or illumination variations. PMID:19096530

  3. Sensor fusion of cameras and a laser for city-scale 3D reconstruction.

    PubMed

    Bok, Yunsu; Choi, Dong-Geol; Kweon, In So

    2014-01-01

    This paper presents a sensor fusion system of cameras and a 2D laser sensorfor large-scale 3D reconstruction. The proposed system is designed to capture data on afast-moving ground vehicle. The system consists of six cameras and one 2D laser sensor,and they are synchronized by a hardware trigger. Reconstruction of 3D structures is doneby estimating frame-by-frame motion and accumulating vertical laser scans, as in previousworks. However, our approach does not assume near 2D motion, but estimates free motion(including absolute scale) in 3D space using both laser data and image features. In orderto avoid the degeneration associated with typical three-point algorithms, we present a newalgorithm that selects 3D points from two frames captured by multiple cameras. The problemof error accumulation is solved by loop closing, not by GPS. The experimental resultsshow that the estimated path is successfully overlaid on the satellite images, such that thereconstruction result is very accurate. PMID:25375758

  4. Robust and reliable banknote authentification and print flaw detection with opto-acoustical sensor fusion methods

    NASA Astrophysics Data System (ADS)

    Lohweg, Volker; Schaede, Johannes; Türke, Thomas

    2006-02-01

    The authenticity checking and inspection of bank notes is a high labour intensive process where traditionally every note on every sheet is inspected manually. However with the advent of more and more sophisticated security features, both visible and invisible, and the requirement of cost reduction in the printing process, it is clear that automation is required. As more and more print techniques and new security features will be established, total quality security, authenticity and bank note printing must be assured. Therefore, this factor necessitates amplification of a sensorial concept in general. We propose a concept for both authenticity checking and inspection methods for pattern recognition and classification for securities and banknotes, which is based on the concept of sensor fusion and fuzzy interpretation of data measures. In the approach different methods of authenticity analysis and print flaw detection are combined, which can be used for vending or sorting machines, as well as for printing machines. Usually only the existence or appearance of colours and their textures are checked by cameras. Our method combines the visible camera images with IR-spectral sensitive sensors, acoustical and other measurements like temperature and pressure of printing machines.

  5. Optimization of beam configuration in laser fusion based on the laser beam pattern

    SciTech Connect

    Xu, Teng; Xu, Lixin; Wang, Anting; Gu, Chun; Wang, Shengbo; Liu, Jing; Wei, Ankun

    2013-12-15

    A simple method based on the laser beam pattern is proposed and numerically demonstrated to optimize a beam configuration for direct drive laser fusion. In this method, both the geometrical factor G{sub l} and the single beam factor B{sub l} are considered. By diminishing the product of B{sub l}·G{sub l}, the irradiation nonuniformity can be decreased to the order of 10{sup −5}. This optimization method can be applied on the design of irradiation systems for an arbitrary number of beams and any axially symmetric beam patterns.

  6. Developing Fast Fluorescent Protein Voltage Sensors by Optimizing FRET Interactions

    PubMed Central

    Sung, Uhna; Sepehri-Rad, Masoud; Piao, Hong Hua; Jin, Lei; Hughes, Thomas; Cohen, Lawrence B.; Baker, Bradley J.

    2015-01-01

    FRET (Förster Resonance Energy Transfer)-based protein voltage sensors can be useful for monitoring neuronal activity in vivo because the ratio of signals between the donor and acceptor pair reduces common sources of noise such as heart beat artifacts. We improved the performance of FRET based genetically encoded Fluorescent Protein (FP) voltage sensors by optimizing the location of donor and acceptor FPs flanking the voltage sensitive domain of the Ciona intestinalis voltage sensitive phosphatase. First, we created 39 different “Nabi1” constructs by positioning the donor FP, UKG, at 8 different locations downstream of the voltage-sensing domain and the acceptor FP, mKO, at 6 positions upstream. Several of these combinations resulted in large voltage dependent signals and relatively fast kinetics. Nabi1 probes responded with signal size up to 11% ΔF/F for a 100 mV depolarization and fast response time constants both for signal activation (~2 ms) and signal decay (~3 ms). We improved expression in neuronal cells by replacing the mKO and UKG FRET pair with Clover (donor FP) and mRuby2 (acceptor FP) to create Nabi2 probes. Nabi2 probes also had large signals and relatively fast time constants in HEK293 cells. In primary neuronal culture, a Nabi2 probe was able to differentiate individual action potentials at 45 Hz. PMID:26587834

  7. Developing Fast Fluorescent Protein Voltage Sensors by Optimizing FRET Interactions.

    PubMed

    Sung, Uhna; Sepehri-Rad, Masoud; Piao, Hong Hua; Jin, Lei; Hughes, Thomas; Cohen, Lawrence B; Baker, Bradley J

    2015-01-01

    FRET (Förster Resonance Energy Transfer)-based protein voltage sensors can be useful for monitoring neuronal activity in vivo because the ratio of signals between the donor and acceptor pair reduces common sources of noise such as heart beat artifacts. We improved the performance of FRET based genetically encoded Fluorescent Protein (FP) voltage sensors by optimizing the location of donor and acceptor FPs flanking the voltage sensitive domain of the Ciona intestinalis voltage sensitive phosphatase. First, we created 39 different "Nabi1" constructs by positioning the donor FP, UKG, at 8 different locations downstream of the voltage-sensing domain and the acceptor FP, mKO, at 6 positions upstream. Several of these combinations resulted in large voltage dependent signals and relatively fast kinetics. Nabi1 probes responded with signal size up to 11% ΔF/F for a 100 mV depolarization and fast response time constants both for signal activation (~2 ms) and signal decay (~3 ms). We improved expression in neuronal cells by replacing the mKO and UKG FRET pair with Clover (donor FP) and mRuby2 (acceptor FP) to create Nabi2 probes. Nabi2 probes also had large signals and relatively fast time constants in HEK293 cells. In primary neuronal culture, a Nabi2 probe was able to differentiate individual action potentials at 45 Hz. PMID:26587834

  8. Cost optimization of a sky surveillance visual sensor network

    NASA Astrophysics Data System (ADS)

    Ahmad, Naeem; Khursheed, Khursheed; Imran, Muhammad; Lawal, Najeem; O'Nils, Mattias

    2012-06-01

    A Visual Sensor Network (VSN) is a network of spatially distributed cameras. The primary difference between VSN and other type of sensor networks is the nature and volume of information. A VSN generally consists of cameras, communication, storage and central computer, where image data from multiple cameras is processed and fused. In this paper, we use optimization techniques to reduce the cost as derived by a model of a VSN to track large birds, such as Golden Eagle, in the sky. The core idea is to divide a given monitoring range of altitudes into a number of sub-ranges of altitudes. The sub-ranges of altitudes are monitored by individual VSNs, VSN1 monitors lower range, VSN2 monitors next higher and so on, such that a minimum cost is used to monitor a given area. The VSNs may use similar or different types of cameras but different optical components, thus, forming a heterogeneous network. We have calculated the cost required to cover a given area by considering an altitudes range as single element and also by dividing it into sub-ranges. To cover a given area with given altitudes range, with a single VSN requires 694 camera nodes in comparison to dividing this range into sub-ranges of altitudes, which requires only 88 nodes, which is 87% reduction in the cost.

  9. Data dimensionality reduction and data fusion for fast characterization of green coffee samples using hyperspectral sensors.

    PubMed

    Calvini, Rosalba; Foca, Giorgia; Ulrici, Alessandro

    2016-10-01

    Hyperspectral sensors represent a powerful tool for chemical mapping of solid-state samples, since they provide spectral information localized in the image domain in very short times and without the need of sample pretreatment. However, due to the large data size of each hyperspectral image, data dimensionality reduction (DR) is necessary in order to develop hyperspectral sensors for real-time monitoring of large sets of samples with different characteristics. In particular, in this work, we focused on DR methods to convert the three-dimensional data array corresponding to each hyperspectral image into a one-dimensional signal (1D-DR), which retains spectral and/or spatial information. In this way, large datasets of hyperspectral images can be converted into matrices of signals, which in turn can be easily processed using suitable multivariate statistical methods. Obviously, different 1D-DR methods highlight different aspects of the hyperspectral image dataset. Therefore, in order to investigate their advantages and disadvantages, in this work, we compared three different 1D-DR methods: average spectrum (AS), single space hyperspectrogram (SSH) and common space hyperspectrogram (CSH). In particular, we have considered 370 NIR-hyperspectral images of a set of green coffee samples, and the three 1D-DR methods were tested for their effectiveness in sensor fault detection, data structure exploration and sample classification according to coffee variety and to coffee processing method. Principal component analysis and partial least squares-discriminant analysis were used to compare the three separate DR methods. Furthermore, low-level and mid-level data fusion was also employed to test the advantages of using AS, SSH and CSH altogether. Graphical Abstract Key steps in hyperspectral data dimenionality reduction.

  10. Data dimensionality reduction and data fusion for fast characterization of green coffee samples using hyperspectral sensors.

    PubMed

    Calvini, Rosalba; Foca, Giorgia; Ulrici, Alessandro

    2016-10-01

    Hyperspectral sensors represent a powerful tool for chemical mapping of solid-state samples, since they provide spectral information localized in the image domain in very short times and without the need of sample pretreatment. However, due to the large data size of each hyperspectral image, data dimensionality reduction (DR) is necessary in order to develop hyperspectral sensors for real-time monitoring of large sets of samples with different characteristics. In particular, in this work, we focused on DR methods to convert the three-dimensional data array corresponding to each hyperspectral image into a one-dimensional signal (1D-DR), which retains spectral and/or spatial information. In this way, large datasets of hyperspectral images can be converted into matrices of signals, which in turn can be easily processed using suitable multivariate statistical methods. Obviously, different 1D-DR methods highlight different aspects of the hyperspectral image dataset. Therefore, in order to investigate their advantages and disadvantages, in this work, we compared three different 1D-DR methods: average spectrum (AS), single space hyperspectrogram (SSH) and common space hyperspectrogram (CSH). In particular, we have considered 370 NIR-hyperspectral images of a set of green coffee samples, and the three 1D-DR methods were tested for their effectiveness in sensor fault detection, data structure exploration and sample classification according to coffee variety and to coffee processing method. Principal component analysis and partial least squares-discriminant analysis were used to compare the three separate DR methods. Furthermore, low-level and mid-level data fusion was also employed to test the advantages of using AS, SSH and CSH altogether. Graphical Abstract Key steps in hyperspectral data dimenionality reduction. PMID:27342797

  11. Optimization of tritium breeding and shielding analysis to plasma in ITER fusion reactor

    NASA Astrophysics Data System (ADS)

    Indah Rosidah, M.; Suud, Zaki; Yazid, Putranto Ilham

    2015-09-01

    The development of fusion energy is one of the important International energy strategies with the important milestone is ITER (International Thermonuclear Experimental Reactor) project, initiated by many countries, such as: America, Europe, and Japan who agreed to set up TOKAMAK type fusion reactor in France. In ideal fusion reactor the fuel is purely deuterium, but it need higher temperature of reactor. In ITER project the fuels are deuterium and tritium which need lower temperature of the reactor. In this study tritium for fusion reactor can be produced by using reaction of lithium with neutron in the blanket region. With the tritium breeding blanket which react between Li-6 in the blanket with neutron resulted from the plasma region. In this research the material used in each layer surrounding the plasma in the reactor is optimized. Moreover, achieving self-sufficiency condition in the reactor in order tritium has enough availability to be consumed for a long time. In order to optimize Tritium Breeding Ratio (TBR) value in the fusion reactor, there are several strategies considered here. The first requirement is making variation in Li-6 enrichment to be 60%, 70%, and 90%. But, the result of that condition can not reach TBR value better than with no enrichment. Because there is reduction of Li-7 percent when increasing Li-6 percent. The other way is converting neutron multiplier material with Pb. From this, we get TBR value better with the Be as neutron multiplier. Beside of TBR value, fusion reactor can analyze the distribution of neutron flux and dose rate of neutron to know the change of neutron concentration for each layer in reactor. From the simulation in this study, 97% neutron concentration can be absorbed by material in reactor, so it is good enough. In addition, it is required to analyze spectrum neutron energy in many layers in the fusion reactor such as in blanket, coolant, and divertor. Actually material in that layer can resist in high temperature

  12. Optimization of tritium breeding and shielding analysis to plasma in ITER fusion reactor

    SciTech Connect

    Indah Rosidah, M. Suud, Zaki; Yazid, Putranto Ilham

    2015-09-30

    The development of fusion energy is one of the important International energy strategies with the important milestone is ITER (International Thermonuclear Experimental Reactor) project, initiated by many countries, such as: America, Europe, and Japan who agreed to set up TOKAMAK type fusion reactor in France. In ideal fusion reactor the fuel is purely deuterium, but it need higher temperature of reactor. In ITER project the fuels are deuterium and tritium which need lower temperature of the reactor. In this study tritium for fusion reactor can be produced by using reaction of lithium with neutron in the blanket region. With the tritium breeding blanket which react between Li-6 in the blanket with neutron resulted from the plasma region. In this research the material used in each layer surrounding the plasma in the reactor is optimized. Moreover, achieving self-sufficiency condition in the reactor in order tritium has enough availability to be consumed for a long time. In order to optimize Tritium Breeding Ratio (TBR) value in the fusion reactor, there are several strategies considered here. The first requirement is making variation in Li-6 enrichment to be 60%, 70%, and 90%. But, the result of that condition can not reach TBR value better than with no enrichment. Because there is reduction of Li-7 percent when increasing Li-6 percent. The other way is converting neutron multiplier material with Pb. From this, we get TBR value better with the Be as neutron multiplier. Beside of TBR value, fusion reactor can analyze the distribution of neutron flux and dose rate of neutron to know the change of neutron concentration for each layer in reactor. From the simulation in this study, 97% neutron concentration can be absorbed by material in reactor, so it is good enough. In addition, it is required to analyze spectrum neutron energy in many layers in the fusion reactor such as in blanket, coolant, and divertor. Actually material in that layer can resist in high temperature

  13. Optimal periodic cooperative spectrum sensing based on weight fusion in cognitive radio networks.

    PubMed

    Liu, Xin; Jia, Min; Gu, Xuemai; Tan, Xuezhi

    2013-01-01

    The performance of cooperative spectrum sensing in cognitive radio (CR) networks depends on the sensing mode, the sensing time and the number of cooperative users. In order to improve the sensing performance and reduce the interference to the primary user (PU), a periodic cooperative spectrum sensing model based on weight fusion is proposed in this paper. Moreover, the sensing period, the sensing time and the searching time are optimized, respectively. Firstly the sensing period is optimized to improve the spectrum utilization and reduce the interference, then the joint optimization algorithm of the local sensing time and the number of cooperative users, is proposed to obtain the optimal sensing time for improving the throughput of the cognitive radio user (CRU) during each period, and finally the water-filling principle is applied to optimize the searching time in order to make the CRU find an idle channel within the shortest time. The simulation results show that compared with the previous algorithms, the optimal sensing period can improve the spectrum utilization of the CRU and decrease the interference to the PU significantly, the optimal sensing time can make the CRU achieve the largest throughput, and the optimal searching time can make the CRU find an idle channel with the least time. PMID:23604027

  14. Design And Implementation Of A Multi-Sensor Fusion Algorithm On A Hypercube Computer Architecture

    NASA Astrophysics Data System (ADS)

    Glover, Charles W.

    1990-03-01

    A multi-sensor integration (MSI) algorithm written for sequential single processor computer architecture has been transformed into a concurrent algorithm and implemented in parallel on a multi-processor hypercube computer architecture. This paper will present the philosophy and methodologies used in the decomposition of the sequential MSI algorithm, and its transformation into a parallel MSI algorithm. The parallel MSI algorithm was implemented on a NCUBETM hypercube computer. The performance of the parallel MSI algorithm has been measured and compared against its sequential counterpart by running test case scenarios through a simulation program. The simulation program allows the user to define the trajectories of all players in the scenario, and to pick the sensor suites of the players and their operating characteristics. For example, an air-to-air engagement scenario was used as one of the test cases. In this scenario, two friend aircrafts were being attacked by six foe aircraft in a pincer maneuver. Both the friend and foe aircrafts launch missiles at several different time points in the engagement. The sensor suites on each aircraft are dual mode RADAR, dual mode IRST, and ESM sensors. The modes of the sensors are switched as needed throughout the scenario. The RADAR sensor is used only intermittently, thus most of the MSI information is obtained from passive sensing. The maneuvers in this scenario caused aircraft and missile to constantly fly in and out of sensors field-of-view (F0V). This resulted in the MSI algorithm to constantly reacquire, initiate, and delete new tracks as it tracked all objects in the scenario. The objective was to determine performance of the parallel MSI algorithm in such a complex environment, and to determine how many multi-processors (nodes) of the hypercube could be effectively used by an aircraft in such an environment. For the scenario just discussed, a 4-node hypercube was found to be the optimal size and a factor two in speedup

  15. Infrared/laser multi-sensor fusion and tracking based on the multi-scale model

    NASA Astrophysics Data System (ADS)

    Wang, Bingjian; Hao, Jingya; Yi, Xiang; Wu, Feihong; Li, Min; Qin, Hanlin; Huang, Hanqiao

    2016-03-01

    The state estimation problem of targets detected by infrared/laser composite detection system with different sampling rates was studied in this paper. An effective state estimation algorithm based on data fusion is presented. Because sampling rate of infrared detection system is much higher than that of the laser detection system, the theory of multi-scale analysis is used to establish multi-scale model in this algorithm. At the fine scale, angle information provided by infrared detection system is used to estimate the target state through the unscented Kalman filter. It makes full use of the high frequency characteristic of infrared detection system to improve target state estimation accuracy. At the coarse scale, due to the sampling ratio of infrared and laser detection systems is an integer multiple, the angle information can be fused directly with the distance information of laser detection system to determine the target location. The fused information is served as observation, while the converted measurement Kalman filter (CMKF) is used to estimate the target state, which greatly reduces the complexity of filtering process and gets the optimal fusion estimation. The simulation results of tracking a target in 3-D space by infrared and laser detection systems demonstrate that the proposed algorithm in this paper is efficient and can obtain better performance than traditional algorithm.

  16. Generic Sensor Data Fusion Services for Web-enabled Environmental Risk Management and Decision-Support Systems

    NASA Astrophysics Data System (ADS)

    Sabeur, Zoheir; Middleton, Stuart; Veres, Galina; Zlatev, Zlatko; Salvo, Nicola

    2010-05-01

    The advancement of smart sensor technology in the last few years has led to an increase in the deployment of affordable sensors for monitoring the environment around Europe. This is generating large amounts of sensor observation information and inevitably leading to problems about how to manage large volumes of data as well as making sense out the data for decision-making. In addition, the various European Directives (Water Framework Diectives, Bathing Water Directives, Habitat Directives, etc.. ) which regulate human activities in the environment and the INSPIRE Directive on spatial information management regulations have implicitely led the designated European Member States environment agencies and authorities to put in place new sensor monitoring infrastructure and share information about environmental regions under their statutory responsibilities. They will need to work cross border and collectively reach environmental quality standards. They will also need to regularly report to the EC on the quality of the environments of which they are responsible and make such information accessible to the members of the public. In recent years, early pioneering work on the design of service oriented architecture using sensor networks has been achieved. Information web-services infrastructure using existing data catalogues and web-GIS map services can now be enriched with the deployment of new sensor observation and data fusion and modelling services using OGC standards. The deployment of the new services which describe sensor observations and intelligent data-processing using data fusion techniques can now be implemented and provide added value information with spatial-temporal uncertainties to the next generation of decision support service systems. The new decision support service systems have become key to implement across Europe in order to comply with EU environmental regulations and INSPIRE. In this paper, data fusion services using OGC standards with sensor

  17. Optimal fusion of antibody binding domains resulted in higher affinity and wider specificity.

    PubMed

    Dong, Jinhua; Kojima, Tomoki; Ohashi, Hiroyuki; Ueda, Hiroshi

    2015-11-01

    Antibody is a very important protein in biotechnological and biomedical fields because of its high affinity and specificity to various antigens. Due to the rise of human antibody therapeutics, its cost-effective purification is an urgent issue for bio-industry. In this study, we made novel fusion proteins PAxPG with a flexible (DDAKK)n linker between the two Ig binding domains derived from Staphylococcus protein A and Streptococcus protein G. The fusion proteins bound human and mouse IgGs and their fragments with up to 58-times higher affinity and wider specificity than the parental binding domains. Interestingly, the optimal linker for human Fab fragment was n = 4, which was close to the modeled distance between the termini of domains bound to heavy chain, implying increased avidity as a possible mechanism. For binding to Fc, the longest n=6 linker gave the highest affinity, implying longer interchain distance between the two binding sites. The novel fusion protein with optimized interdomain linker length will be a useful tool for the purification and detection of various IgGs including mouse IgG1 that binds only weakly to natural protein A. PMID:25910963

  18. Vis-NIRS sensor fusion for local, regional and global calibrations of SOC content

    NASA Astrophysics Data System (ADS)

    Knadel, M.; Deng, F.; Thomsen, A.; Greve, M. H.

    2012-04-01

    The considerable potential of sensor fusion has been recognised and is finding application in soil mapping. Visible-near-infrared (Vis-NIR) diffuse reflectance spectroscopy (DRS) has proven to be an efficient method for measuring soil physical, chemical and biological properties. The objective of this study was to determine whether a Danish national soil spectral library spiked with local samples can give better SOC predictions than the regional or local calibrations alone. It was also investigated if the national library developed using a laboratory sensor can be used to predict field-generated data by the mobile sensor platform (MSP). Local and regional SOC models were based on data obtained from individual fields and from the compilation of the data obtained from six fields in one model, respectively. The prerequisite for using vis-NIR for soil analysis is the development of a soil spectral library. Such library should be based on representative samples for the future application. We selected 2851 samples from a diverse archive of Danish soils and perform a global calibration. Additionally, the national spectral library was spiked with some local samples obtained from the fields under study. Local, regional and global spiked SOC models were compared. The best results from the partial least squares regression (PLSR) were obtained for the regional calibration (RMSEP=0.39, r2=0.93 and RPD=4), followed by the calibrations from the library spiked with local MSP measurements (RMSEP=0.38, r2=0.84, RPD=2.5). Finally, kriging maps of SOC content were validated. The highest root mean square error of prediction (5.4) was generated by the map based on the regional calibration model. The lowest RMSEP (4.1), however, was found for the map generated from the global library spiked with the local samples acquired by MSP. The results from this study show that the national spectral library established using a laboratory sensor can deliver good predictive abilities of SOC on field

  19. Optimized sensor location for estimating story-drift angle for tall buildings subject to earthquakes

    NASA Astrophysics Data System (ADS)

    Ozawa, Sayuki; Mita, Akira

    2016-04-01

    Structural Health Monitoring (SHM) is a technology that can evaluate the extent of the deterioration or the damage of the building quantitatively. Most SHM systems utilize only a few sensors and the sensors are placed equally including the roof. However, the location of the sensors has not been verified. Therefore, in this study, the optimal location of the sensors is studied for estimating the inter-story drift angle which is used in immediate diagnosis after an earthquake. This study proposes a practical optimal sensor location method after testing all the possible sensor location combinations. From the simulation results of all location patterns, it was proved that placing the sensor on the roof is not always optimal. This result is practically useful as it is difficult to place the sensor on the roof in most cases. Modal Assurance Criterion (MAC) is one of the practical optimal sensor location methods. I proposed MASS Modal Assurance Criterion (MAC*) which incorporate the mass matrix of the building into the MAC. Either the mass matrix or the stiffness matrix needs to be considered for the orthogonality of the mode vectors, normal MAC does not consider this condition. The location of sensors determined by MAC* was superior to the previous method, MAC. In this study, an important knowledge of the location of sensors was provided for implementing SHM systems.

  20. Human Arm Motion Tracking by Orientation-Based Fusion of Inertial Sensors and Kinect Using Unscented Kalman Filter.

    PubMed

    Atrsaei, Arash; Salarieh, Hassan; Alasty, Aria

    2016-09-01

    Due to various applications of human motion capture techniques, developing low-cost methods that would be applicable in nonlaboratory environments is under consideration. MEMS inertial sensors and Kinect are two low-cost devices that can be utilized in home-based motion capture systems, e.g., home-based rehabilitation. In this work, an unscented Kalman filter approach was developed based on the complementary properties of Kinect and the inertial sensors to fuse the orientation data of these two devices for human arm motion tracking during both stationary shoulder joint position and human body movement. A new measurement model of the fusion algorithm was obtained that can compensate for the inertial sensors drift problem in high dynamic motions and also joints occlusion in Kinect. The efficiency of the proposed algorithm was evaluated by an optical motion tracker system. The errors were reduced by almost 50% compared to cases when either inertial sensor or Kinect measurements were utilized. PMID:27428461

  1. Human Arm Motion Tracking by Orientation-Based Fusion of Inertial Sensors and Kinect Using Unscented Kalman Filter.

    PubMed

    Atrsaei, Arash; Salarieh, Hassan; Alasty, Aria

    2016-09-01

    Due to various applications of human motion capture techniques, developing low-cost methods that would be applicable in nonlaboratory environments is under consideration. MEMS inertial sensors and Kinect are two low-cost devices that can be utilized in home-based motion capture systems, e.g., home-based rehabilitation. In this work, an unscented Kalman filter approach was developed based on the complementary properties of Kinect and the inertial sensors to fuse the orientation data of these two devices for human arm motion tracking during both stationary shoulder joint position and human body movement. A new measurement model of the fusion algorithm was obtained that can compensate for the inertial sensors drift problem in high dynamic motions and also joints occlusion in Kinect. The efficiency of the proposed algorithm was evaluated by an optical motion tracker system. The errors were reduced by almost 50% compared to cases when either inertial sensor or Kinect measurements were utilized.

  2. Optimized swimmer tracking system by a dynamic fusion of correlation and color histogram techniques

    NASA Astrophysics Data System (ADS)

    Benarab, D.; Napoléon, T.; Alfalou, A.; Verney, A.; Hellard, P.

    2015-12-01

    To design a robust swimmer tracking system, we took into account two well-known tracking techniques: the nonlinear joint transform correlation (NL-JTC) and the color histogram. The two techniques perform comparably well, yet they both have substantial limitations. Interestingly, they also seem to show some complementarity. The correlation technique yields accurate detection but is sensitive to rotation, scale and contour deformation, whereas the color histogram technique is robust for rotation and contour deformation but shows low accuracy and is highly sensitive to luminosity and confusing background colors. These observations suggested the possibility of a dynamic fusion of the correlation plane and the color scores map. Before this fusion, two steps are required. First is the extraction of a sub-plane of correlation that describes the similarity between the reference and target images. This sub-plane has the same size as the color scores map but they have different interval values. Thus, the second step is required which is the normalization of the planes in the same interval so they can be fused. In order to determine the benefits of this fusion technique, first, we tested it on a synthetic image containing different forms with different colors. We thus were able to optimize the correlation plane and color histogram techniques before applying our fusion technique to real videos of swimmers in international competitions. Last, a comparative study of the dynamic fusion technique and the two classical techniques was carried out to demonstrate the efficacy of the proposed technique. The criteria of comparison were the tracking percentage, the peak to correlation energy (PCE), which evaluated the sharpness of the peak (accuracy), and the local standard deviation (Local-STD), which assessed the noise in the planes (robustness).

  3. Sensors Fusion based Online Mapping and Features Extraction of Mobile Robot in the Road Following and Roundabout

    NASA Astrophysics Data System (ADS)

    Ali, Mohammed A. H.; Mailah, Musa; Yussof, Wan Azhar B.; Hamedon, Zamzuri B.; Yussof, Zulkifli B.; Majeed, Anwar P. P.

    2016-02-01

    A road feature extraction based mapping system using a sensor fusion technique for mobile robot navigation in road environments is presented in this paper. The online mapping of mobile robot is performed continuously in the road environments to find the road properties that enable the robot to move from a certain start position to pre-determined goal while discovering and detecting the roundabout. The sensors fusion involving laser range finder, camera and odometry which are installed in a new platform, are used to find the path of the robot and localize it within its environments. The local maps are developed using camera and laser range finder to recognize the roads borders parameters such as road width, curbs and roundabout. Results show the capability of the robot with the proposed algorithms to effectively identify the road environments and build a local mapping for road following and roundabout.

  4. Fusion of Optimized Indicators from Advanced Driver Assistance Systems (ADAS) for Driver Drowsiness Detection

    PubMed Central

    Daza, Iván G.; Bergasa, Luis M.; Bronte, Sebastián; Yebes, J. Javier; Almazán, Javier; Arroyo, Roberto

    2014-01-01

    This paper presents a non-intrusive approach for monitoring driver drowsiness using the fusion of several optimized indicators based on driver physical and driving performance measures, obtained from ADAS (Advanced Driver Assistant Systems) in simulated conditions. The paper is focused on real-time drowsiness detection technology rather than on long-term sleep/awake regulation prediction technology. We have developed our own vision system in order to obtain robust and optimized driver indicators able to be used in simulators and future real environments. These indicators are principally based on driver physical and driving performance skills. The fusion of several indicators, proposed in the literature, is evaluated using a neural network and a stochastic optimization method to obtain the best combination. We propose a new method for ground-truth generation based on a supervised Karolinska Sleepiness Scale (KSS). An extensive evaluation of indicators, derived from trials over a third generation simulator with several test subjects during different driving sessions, was performed. The main conclusions about the performance of single indicators and the best combinations of them are included, as well as the future works derived from this study. PMID:24412904

  5. Fusion of optimized indicators from Advanced Driver Assistance Systems (ADAS) for driver drowsiness detection.

    PubMed

    Daza, Iván García; Bergasa, Luis Miguel; Bronte, Sebastián; Yebes, Jose Javier; Almazán, Javier; Arroyo, Roberto

    2014-01-09

    This paper presents a non-intrusive approach for monitoring driver drowsiness using the fusion of several optimized indicators based on driver physical and driving performance measures, obtained from ADAS (Advanced Driver Assistant Systems) in simulated conditions. The paper is focused on real-time drowsiness detection technology rather than on long-term sleep/awake regulation prediction technology. We have developed our own vision system in order to obtain robust and optimized driver indicators able to be used in simulators and future real environments. These indicators are principally based on driver physical and driving performance skills. The fusion of several indicators, proposed in the literature, is evaluated using a neural network and a stochastic optimization method to obtain the best combination. We propose a new method for ground-truth generation based on a supervised Karolinska Sleepiness Scale (KSS). An extensive evaluation of indicators, derived from trials over a third generation simulator with several test subjects during different driving sessions, was performed. The main conclusions about the performance of single indicators and the best combinations of them are included, as well as the future works derived from this study.

  6. Targeted codon optimization improves translational fidelity for an Fc fusion protein.

    PubMed

    Hutterer, Katariina M; Zhang, Zhongqi; Michaels, Mark Leo; Belouski, Ed; Hong, Robert W; Shah, Bhavana; Berge, Mark; Barkhordarian, Hedieh; Le, Eleanor; Smith, Steve; Winters, Dwight; Abroson, Frank; Hecht, Randy; Liu, Jennifer

    2012-11-01

    High levels of translational errors, both truncation and misincorporation in an Fc-fusion protein were observed. Here, we demonstrate the impact of several commercially available codon optimization services, and compare to a targeted strategy. Using the targeted strategy, only codons known to have translational errors are modified. For an Fc-fusion protein expressed in Escherichia coli, the targeted strategy, in combination with appropriate fermentation conditions, virtually eliminated misincorporation (proteins produced with a wrong amino acid sequence), and reduced the level of truncation. The use of full optimization using commercially available strategies reduced the initial errors, but introduced different misincorporations. However, truncation was higher using the targeted strategy than for most of the full optimization strategies. This targeted approach, along with monitoring of translation fidelity and careful attention to fermentation conditions is key to minimizing translational error and ensuring high-quality expression. These findings should be useful for other biopharmaceutical products, as well as any other transgenic constructs where protein quality is important.

  7. Interactive Scene Analysis Module - A sensor-database fusion system for telerobotic environments

    NASA Technical Reports Server (NTRS)

    Cooper, Eric G.; Vazquez, Sixto L.; Goode, Plesent W.

    1992-01-01

    Accomplishing a task with telerobotics typically involves a combination of operator control/supervision and a 'script' of preprogrammed commands. These commands usually assume that the location of various objects in the task space conform to some internal representation (database) of that task space. The ability to quickly and accurately verify the task environment against the internal database would improve the robustness of these preprogrammed commands. In addition, the on-line initialization and maintenance of a task space database is difficult for operators using Cartesian coordinates alone. This paper describes the Interactive Scene' Analysis Module (ISAM) developed to provide taskspace database initialization and verification utilizing 3-D graphic overlay modelling, video imaging, and laser radar based range imaging. Through the fusion of taskspace database information and image sensor data, a verifiable taskspace model is generated providing location and orientation data for objects in a task space. This paper also describes applications of the ISAM in the Intelligent Systems Research Laboratory (ISRL) at NASA Langley Research Center, and discusses its performance relative to representation accuracy and operator interface efficiency.

  8. A Locomotion Intent Prediction System Based on Multi-Sensor Fusion

    PubMed Central

    Chen, Baojun; Zheng, Enhao; Wang, Qining

    2014-01-01

    Locomotion intent prediction is essential for the control of powered lower-limb prostheses to realize smooth locomotion transitions. In this research, we develop a multi-sensor fusion based locomotion intent prediction system, which can recognize current locomotion mode and detect locomotion transitions in advance. Seven able-bodied subjects were recruited for this research. Signals from two foot pressure insoles and three inertial measurement units (one on the thigh, one on the shank and the other on the foot) are measured. A two-level recognition strategy is used for the recognition with linear discriminate classifier. Six kinds of locomotion modes and ten kinds of locomotion transitions are tested in this study. Recognition accuracy during steady locomotion periods (i.e., no locomotion transitions) is 99.71% ± 0.05% for seven able-bodied subjects. During locomotion transition periods, all the transitions are correctly detected and most of them can be detected before transiting to new locomotion modes. No significant deterioration in recognition performance is observed in the following five hours after the system is trained, and small number of experiment trials are required to train reliable classifiers. PMID:25014097

  9. The Study of Cross-layer Optimization for Wireless Rechargeable Sensor Networks Implemented in Coal Mines.

    PubMed

    Ding, Xu; Shi, Lei; Han, Jianghong; Lu, Jingting

    2016-01-28

    Wireless sensor networks deployed in coal mines could help companies provide workers working in coal mines with more qualified working conditions. With the underground information collected by sensor nodes at hand, the underground working conditions could be evaluated more precisely. However, sensor nodes may tend to malfunction due to their limited energy supply. In this paper, we study the cross-layer optimization problem for wireless rechargeable sensor networks implemented in coal mines, of which the energy could be replenished through the newly-brewed wireless energy transfer technique. The main results of this article are two-fold: firstly, we obtain the optimal relay nodes' placement according to the minimum overall energy consumption criterion through the Lagrange dual problem and KKT conditions; secondly, the optimal strategies for recharging locomotives and wireless sensor networks are acquired by solving a cross-layer optimization problem. The cyclic nature of these strategies is also manifested through simulations in this paper.

  10. The Study of Cross-layer Optimization for Wireless Rechargeable Sensor Networks Implemented in Coal Mines

    PubMed Central

    Ding, Xu; Shi, Lei; Han, Jianghong; Lu, Jingting

    2016-01-01

    Wireless sensor networks deployed in coal mines could help companies provide workers working in coal mines with more qualified working conditions. With the underground information collected by sensor nodes at hand, the underground working conditions could be evaluated more precisely. However, sensor nodes may tend to malfunction due to their limited energy supply. In this paper, we study the cross-layer optimization problem for wireless rechargeable sensor networks implemented in coal mines, of which the energy could be replenished through the newly-brewed wireless energy transfer technique. The main results of this article are two-fold: firstly, we obtain the optimal relay nodes’ placement according to the minimum overall energy consumption criterion through the Lagrange dual problem and KKT conditions; secondly, the optimal strategies for recharging locomotives and wireless sensor networks are acquired by solving a cross-layer optimization problem. The cyclic nature of these strategies is also manifested through simulations in this paper. PMID:26828500

  11. Novel free-form hohlraum shape design and optimization for laser-driven inertial confinement fusion

    SciTech Connect

    Jiang, Shaoen; Jing, Longfei Ding, Yongkun; Huang, Yunbao

    2014-10-15

    The hohlraum shape attracts considerable attention because there is no successful ignition method for laser-driven inertial confinement fusion at the National Ignition Facility. The available hohlraums are typically designed with simple conic curves, including ellipses, parabolas, arcs, or Lame curves, which allow only a few design parameters for the shape optimization, making it difficult to improve the performance, e.g., the energy coupling efficiency or radiation drive symmetry. A novel free-form hohlraum design and optimization approach based on the non-uniform rational basis spline (NURBS) model is proposed. In the present study, (1) all kinds of hohlraum shapes can be uniformly represented using NURBS, which is greatly beneficial for obtaining the optimal available hohlraum shapes, and (2) such free-form uniform representation enables us to obtain an optimal shape over a large design domain for the hohlraum with a more uniform radiation and higher drive temperature of the fuel capsule. Finally, a hohlraum is optimized and evaluated with respect to the drive temperature and symmetry at the Shenguang III laser facility in China. The drive temperature and symmetry results indicate that such a free-form representation is advantageous over available hohlraum shapes because it can substantially expand the shape design domain so as to obtain an optimal hohlraum with high performance.

  12. Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

    NASA Astrophysics Data System (ADS)

    Wilson, Brian; Manipon, Gerald; Hua, Hook; Fetzer, Eric

    2014-05-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map-reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in a hybrid Cloud (private eucalyptus & public Amazon). Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Multi-year datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will present the architecture of SciReduce, describe the

  13. Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

    NASA Astrophysics Data System (ADS)

    Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

    2015-12-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, MODIS, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. HySDS is a Hybrid-Cloud Science Data System that has been developed and applied under NASA AIST, MEaSUREs, and ACCESS grants. HySDS uses the SciFlow workflow engine to partition analysis workflows into parallel tasks (e.g. segmenting by time or space) that are pushed into a durable job queue. The tasks are "pulled" from the queue by worker Virtual Machines (VM's) and executed in an on-premise Cloud (Eucalyptus or OpenStack) or at Amazon in the public Cloud or govCloud. In this way, years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the transferred data. We are using HySDS to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a MEASURES grant. We will present the architecture of HySDS, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. Our system demonstrates how one can pull A-Train variables (Levels 2 & 3) on-demand into the Amazon Cloud, and cache only those variables that are heavily used, so that any number of compute jobs can be

  14. Development and Application of Non-Linear Image Enhancement and Multi-Sensor Fusion Techniques for Hazy and Dark Imaging

    NASA Technical Reports Server (NTRS)

    Rahman, Zia-ur

    2005-01-01

    The purpose of this research was to develop enhancement and multi-sensor fusion algorithms and techniques to make it safer for the pilot to fly in what would normally be considered Instrument Flight Rules (IFR) conditions, where pilot visibility is severely restricted due to fog, haze or other weather phenomenon. We proposed to use the non-linear Multiscale Retinex (MSR) as the basic driver for developing an integrated enhancement and fusion engine. When we started this research, the MSR was being applied primarily to grayscale imagery such as medical images, or to three-band color imagery, such as that produced in consumer photography: it was not, however, being applied to other imagery such as that produced by infrared image sources. However, we felt that it was possible by using the MSR algorithm in conjunction with multiple imaging modalities such as long-wave infrared (LWIR), short-wave infrared (SWIR), and visible spectrum (VIS), we could substantially improve over the then state-of-the-art enhancement algorithms, especially in poor visibility conditions. We proposed the following tasks: 1) Investigate the effects of applying the MSR to LWIR and SWIR images. This consisted of optimizing the algorithm in terms of surround scales, and weights for these spectral bands; 2) Fusing the LWIR and SWIR images with the VIS images using the MSR framework to determine the best possible representation of the desired features; 3) Evaluating different mixes of LWIR, SWIR and VIS bands for maximum fog and haze reduction, and low light level compensation; 4) Modifying the existing algorithms to work with video sequences. Over the course of the 3 year research period, we were able to accomplish these tasks and report on them at various internal presentations at NASA Langley Research Center, and in presentations and publications elsewhere. A description of the work performed under the tasks is provided in Section 2. The complete list of relevant publications during the research

  15. Respiratory syncytial virus fusion inhibitors. Part 4: optimization for oral bioavailability.

    PubMed

    Yu, Kuo-Long; Sin, Ny; Civiello, Rita L; Wang, X Alan; Combrink, Keith D; Gulgeze, H Belgin; Venables, Brian L; Wright, J J Kim; Dalterio, Richard A; Zadjura, Lisa; Marino, Anthony; Dando, Sandra; D'Arienzo, Celia; Kadow, Kathleen F; Cianci, Christopher W; Li, Zhufang; Clarke, Junius; Genovesi, Eugene V; Medina, Ivette; Lamb, Lucinda; Colonno, Richard J; Yang, Zheng; Krystal, Mark; Meanwell, Nicholas A

    2007-02-15

    A series of benzimidazole-based inhibitors of respiratory syncytial virus (RSV) fusion were optimized for antiviral potency, membrane permeability and metabolic stability in human liver microsomes. 1-Cyclopropyl-1,3-dihydro-3-[[1-(4-hydroxybutyl)-1H-benzimidazol-2-yl]methyl]-2H-imidazo[4,5-c]pyridin-2-one (6m, BMS-433771) was identified as a potent RSV inhibitor demonstrating good bioavailability in the mouse, rat, dog and cynomolgus monkey that demonstrated antiviral activity in the BALB/c and cotton rat models of infection following oral administration.

  16. Development of a Pedestrian Indoor Navigation System Based on Multi-Sensor Fusion and Fuzzy Logic Estimation Algorithms

    NASA Astrophysics Data System (ADS)

    Lai, Y. C.; Chang, C. C.; Tsai, C. M.; Lin, S. Y.; Huang, S. C.

    2015-05-01

    This paper presents a pedestrian indoor navigation system based on the multi-sensor fusion and fuzzy logic estimation algorithms. The proposed navigation system is a self-contained dead reckoning navigation that means no other outside signal is demanded. In order to achieve the self-contained capability, a portable and wearable inertial measure unit (IMU) has been developed. Its adopted sensors are the low-cost inertial sensors, accelerometer and gyroscope, based on the micro electro-mechanical system (MEMS). There are two types of the IMU modules, handheld and waist-mounted. The low-cost MEMS sensors suffer from various errors due to the results of manufacturing imperfections and other effects. Therefore, a sensor calibration procedure based on the scalar calibration and the least squares methods has been induced in this study to improve the accuracy of the inertial sensors. With the calibrated data acquired from the inertial sensors, the step length and strength of the pedestrian are estimated by multi-sensor fusion and fuzzy logic estimation algorithms. The developed multi-sensor fusion algorithm provides the amount of the walking steps and the strength of each steps in real-time. Consequently, the estimated walking amount and strength per step are taken into the proposed fuzzy logic estimation algorithm to estimates the step lengths of the user. Since the walking length and direction are both the required information of the dead reckoning navigation, the walking direction is calculated by integrating the angular rate acquired by the gyroscope of the developed IMU module. Both the walking length and direction are calculated on the IMU module and transmit to a smartphone with Bluetooth to perform the dead reckoning navigation which is run on a self-developed APP. Due to the error accumulating of dead reckoning navigation, a particle filter and a pre-loaded map of indoor environment have been applied to the APP of the proposed navigation system to extend its

  17. Optimal Sensor Location Design for Reliable Fault Detection in Presence of False Alarms

    PubMed Central

    Yang, Fan; Xiao, Deyun; Shah, Sirish L.

    2009-01-01

    To improve fault detection reliability, sensor location should be designed according to an optimization criterion with constraints imposed by issues of detectability and identifiability. Reliability requires the minimization of undetectability and false alarm probability due to random factors on sensor readings, which is not only related with sensor readings but also affected by fault propagation. This paper introduces the reliability criteria expression based on the missed/false alarm probability of each sensor and system topology or connectivity derived from the directed graph. The algorithm for the optimization problem is presented as a heuristic procedure. Finally, a boiler system is illustrated using the proposed method. PMID:22291524

  18. An Optimized PatchMatch for multi-scale and multi-feature label fusion.

    PubMed

    Giraud, Rémi; Ta, Vinh-Thong; Papadakis, Nicolas; Manjón, José V; Collins, D Louis; Coupé, Pierrick

    2016-01-01

    Automatic segmentation methods are important tools for quantitative analysis of Magnetic Resonance Images (MRI). Recently, patch-based label fusion approaches have demonstrated state-of-the-art segmentation accuracy. In this paper, we introduce a new patch-based label fusion framework to perform segmentation of anatomical structures. The proposed approach uses an Optimized PAtchMatch Label fusion (OPAL) strategy that drastically reduces the computation time required for the search of similar patches. The reduced computation time of OPAL opens the way for new strategies and facilitates processing on large databases. In this paper, we investigate new perspectives offered by OPAL, by introducing a new multi-scale and multi-feature framework. During our validation on hippocampus segmentation we use two datasets: young adults in the ICBM cohort and elderly adults in the EADC-ADNI dataset. For both, OPAL is compared to state-of-the-art methods. Results show that OPAL obtained the highest median Dice coefficient (89.9% for ICBM and 90.1% for EADC-ADNI). Moreover, in both cases, OPAL produced a segmentation accuracy similar to inter-expert variability. On the EADC-ADNI dataset, we compare the hippocampal volumes obtained by manual and automatic segmentation. The volumes appear to be highly correlated that enables to perform more accurate separation of pathological populations. PMID:26244277

  19. Leveraging Data Fusion Strategies in Multireceptor Lead Optimization MM/GBSA End-Point Methods.

    PubMed

    Knight, Jennifer L; Krilov, Goran; Borrelli, Kenneth W; Williams, Joshua; Gunn, John R; Clowes, Alec; Cheng, Luciano; Friesner, Richard A; Abel, Robert

    2014-08-12

    Accurate and efficient affinity calculations are critical to enhancing the contribution of in silico modeling during the lead optimization phase of a drug discovery campaign. Here, we present a large-scale study of the efficacy of data fusion strategies to leverage results from end-point MM/GBSA calculations in multiple receptors to identify potent inhibitors among an ensemble of congeneric ligands. The retrospective analysis of 13 congeneric ligand series curated from publicly available data across seven biological targets demonstrates that in 90% of the individual receptor structures MM/GBSA scores successfully identify subsets of inhibitors that are more potent than a random selection, and data fusion strategies that combine MM/GBSA scores from each of the receptors significantly increase the robustness of the predictions. Among nine different data fusion metrics based on consensus scores or receptor rankings, the SumZScore (i.e., converting MM/GBSA scores into standardized Z-Scores within a receptor and computing the sum of the Z-Scores for a given ligand across the ensemble of receptors) is found to be a robust and physically meaningful metric for combining results across multiple receptors. Perhaps most surprisingly, even with relatively low to modest overall correlations between SumZScore and experimental binding affinities, SumZScore tends to reliably prioritize subsets of inhibitors that are at least as potent as those that are prioritized from a "best" single receptor identified from known compounds within the congeneric series. PMID:26588291

  20. Theoretical model and optimization of a novel temperature sensor based on quartz tuning fork resonators

    NASA Astrophysics Data System (ADS)

    Jun, Xu; Bo, You; Xin, Li; Juan, Cui

    2007-12-01

    To accurately measure temperatures, a novel temperature sensor based on a quartz tuning fork resonator has been designed. The principle of the quartz tuning fork temperature sensor is that the resonant frequency of the quartz resonator changes with the variation in temperature. This type of tuning fork resonator has been designed with a new doubly rotated cut work at flexural vibration mode as temperature sensor. The characteristics of the temperature sensor were evaluated and the results sufficiently met the target of development for temperature sensor. The theoretical model for temperature sensing has been developed and built. The sensor structure was analysed by finite element method (FEM) and optimized, including tuning fork geometry, tine electrode pattern and the sensor's elements size. The performance curve of output versus measured temperature is given. The results from theoretical analysis and experiments indicate that the sensor's sensitivity can reach 60 ppm °C-1 with the measured temperature range varying from 0 to 100 °C.

  1. Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations

    PubMed Central

    Kim, Dong Hyun; Lee, Sang Wook; Park, Hyung-Soon

    2016-01-01

    Bending sensors enable compact, wearable designs when used for measuring hand configurations in data gloves. While existing data gloves can accurately measure angular displacement of the finger and distal thumb joints, accurate measurement of thumb carpometacarpal (CMC) joint movements remains challenging due to crosstalk between the multi-sensor outputs required to measure the degrees of freedom (DOF). To properly measure CMC-joint configurations, sensor locations that minimize sensor crosstalk must be identified. This paper presents a novel approach to identifying optimal sensor locations. Three-dimensional hand surface data from ten subjects was collected in multiple thumb postures with varied CMC-joint flexion and abduction angles. For each posture, scanned CMC-joint contours were used to estimate CMC-joint flexion and abduction angles by varying the positions and orientations of two bending sensors. Optimal sensor locations were estimated by the least squares method, which minimized the difference between the true CMC-joint angles and the joint angle estimates. Finally, the resultant optimal sensor locations were experimentally validated. Placing sensors at the optimal locations, CMC-joint angle measurement accuracies improved (flexion, 2.8° ± 1.9°; abduction, 1.9° ± 1.2°). The proposed method for improving the accuracy of the sensing system can be extended to other types of soft wearable measurement devices. PMID:27240364

  2. Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations.

    PubMed

    Kim, Dong Hyun; Lee, Sang Wook; Park, Hyung-Soon

    2016-05-26

    Bending sensors enable compact, wearable designs when used for measuring hand configurations in data gloves. While existing data gloves can accurately measure angular displacement of the finger and distal thumb joints, accurate measurement of thumb carpometacarpal (CMC) joint movements remains challenging due to crosstalk between the multi-sensor outputs required to measure the degrees of freedom (DOF). To properly measure CMC-joint configurations, sensor locations that minimize sensor crosstalk must be identified. This paper presents a novel approach to identifying optimal sensor locations. Three-dimensional hand surface data from ten subjects was collected in multiple thumb postures with varied CMC-joint flexion and abduction angles. For each posture, scanned CMC-joint contours were used to estimate CMC-joint flexion and abduction angles by varying the positions and orientations of two bending sensors. Optimal sensor locations were estimated by the least squares method, which minimized the difference between the true CMC-joint angles and the joint angle estimates. Finally, the resultant optimal sensor locations were experimentally validated. Placing sensors at the optimal locations, CMC-joint angle measurement accuracies improved (flexion, 2.8° ± 1.9°; abduction, 1.9° ± 1.2°). The proposed method for improving the accuracy of the sensing system can be extended to other types of soft wearable measurement devices.

  3. Data fusion for reconstruction algorithms via different sensors in geophysical sensing

    NASA Astrophysics Data System (ADS)

    Nordebo, Sven; Gustafsson, Mats; Soldovieri, Francesco

    2010-05-01

    A unified approach to sensitivity analysis and data fusion for multi-physics inverse scattering problems will be presented which is based on Fisher information analysis for distributed parameter systems, cf., [4]. This approach is particularly useful when there is a diversity of measurement sensors having varying noise spectral content and signal to noise ratios, such as with information fusion with multi-physics data. Here, the Fisher information analysis yields a systematic procedure to incorporate a statistically based weighting of the measurements. The forward operator is the mapping that takes the unknown material parameters of interest to the measurement data. It will be shown that the Fisher information analysis is equivalent to performing a Singular Value Decomposition (SVD) analysis of the linearized forward operator [1,2,5], provided that the measurement noise is Gaussian distributed and that the appropriate scalar product is chosen for the space of measurement data. Hence, the Fisher information concept provides a systematic means of choosing the scalar product for the related Hilbert space in a way that is statistically optimum. In particular, if J denotes the Jacobian, or the Fréchet derivative of the forward operator, then the Fisher information integral operator is given by I = 2J*J where J* is the Hilbert adjoint operator, see e.g., [3] for the finite-dimensional case. Hence, the truncated SVD algorithm [1,2,5] corresponds here to a regularized pseudo-inverse based on the Fisher information operator. Application examples using the truncated SVD algorithm [5] for multi-physics inverse problems in geophysical sensing will be considered. References [1] M. Bertero. Linear inverse and ill-posed problems. Advances in electronics and electron physics, 75, 1-120, 1989. [2] Q. Fang, P. M. Meaney, and K. D. Paulsen. Singular value analysis of the Jacobian matrix in microwave image reconstruction. IEEE Trans. Antennas Propagat., 54(8), 2371-2380, aug 2006. [3

  4. Characterization and optimization of an ultrasonic piezo-optical ring sensor

    NASA Astrophysics Data System (ADS)

    Frankforter, Erik; Lin, Bin; Giurgiutiu, Victor

    2016-04-01

    A resonant piezo-optical ring sensor with both piezoelectric and fiber Bragg grating (FBG) sensing elements was assessed for ultrasonic wave detection. The ring sensor is an existing device that has been shown experimentally to exhibit a number of sensing features: omnidirectionality, mode selectivity, and frequency tunability. The present study uses finite element modeling to understand these features as a means to characterize and optimize the sensor. A combined vibration-wave propagation modeling approach was used, where the vibrational modeling provided a basis for understanding sensing features, and the wave propagation modeling provided predictive power for sensor performance. The sensor features corresponded to the fundamental vibrational mode of the sensor, particularly to the base motion of this mode. The vibrational modeling was also used to guide sensor optimization, with an emphasis on the FBG and piezoelectric sensing elements. It was found that sensor symmetry and nodes of extraneous resonance modes could be exploited to provide a single-resonance response. A series of pitch-catch guided wave experiments were performed on a thin aluminum plate to assess the optimized sensor configuration. Tuning curves showed a single-frequency response to a Lamb wave and mechanical filtering away from the dominant frequency; the sensor capability for mechanical amplification of a Lamb wave and mechanical amplification of a pencil-lead-break acoustic emission event were also demonstrated.

  5. Road centerline extraction from airborne LiDAR point cloud based on hierarchical fusion and optimization

    NASA Astrophysics Data System (ADS)

    Hui, Zhenyang; Hu, Youjian; Jin, Shuanggen; Yevenyo, Yao Ziggah

    2016-08-01

    Road information acquisition is an important part of city informatization construction. Airborne LiDAR provides a new means of acquiring road information. However, the existing road extraction methods using LiDAR point clouds always decide the road intensity threshold based on experience, which cannot obtain the optimal threshold to extract a road point cloud. Moreover, these existing methods are deficient in removing the interference of narrow roads and several attached areas (e.g., parking lot and bare ground) to main roads extraction, thereby imparting low completeness and correctness to the city road network extraction result. Aiming at resolving the key technical issues of road extraction from airborne LiDAR point clouds, this paper proposes a novel method to extract road centerlines from airborne LiDAR point clouds. The proposed approach is mainly composed of three key algorithms, namely, Skewness balancing, Rotating neighborhood, and Hierarchical fusion and optimization (SRH). The skewness balancing algorithm used for the filtering was adopted as a new method for obtaining an optimal intensity threshold such that the "pure" road point cloud can be obtained. The rotating neighborhood algorithm on the other hand was developed to remove narrow roads (corridors leading to parking lots or sidewalks), which are not the main roads to be extracted. The proposed hierarchical fusion and optimization algorithm caused the road centerlines to be unaffected by certain attached areas and ensured the road integrity as much as possible. The proposed method was tested using the Vaihingen dataset. The results demonstrated that the proposed method can effectively extract road centerlines in a complex urban environment with 91.4% correctness and 80.4% completeness.

  6. Optimization and Validation of Rotating Current Excitation with GMR Array Sensors for Riveted Structures Inspection.

    PubMed

    Ye, Chaofeng; Udpa, Lalita; Udpa, Satish

    2016-09-16

    In eddy current non-destructive testing of a multi-layered riveted structure, rotating current excitation, generated by orthogonal coils, is advantageous in providing sensitivity to defects of all orientations. However, when used with linear array sensors, the exciting magnetic flux density ( B x ) of the orthogonal coils is not uniform over the sensor region, resulting in an output signal magnitude that depends on the relative location of the defect to the sensor array. In this paper, the rotating excitation coil is optimized to achieve a uniform B x field in the sensor array area and minimize the probe size. The current density distribution of the coil is optimized using the polynomial approximation method. A non-uniform coil design is derived from the optimized current density distribution. Simulation results, using both an optimized coil and a conventional coil, are generated using the finite element method (FEM) model. The signal magnitude for an optimized coil is seen to be more robust with respect to offset of defects from the coil center. A novel multilayer coil structure, fabricated on a multi-layer printed circuit board, is used to build the optimized coil. A prototype probe with the optimized coil and 32 giant magnetoresistive (GMR) sensors is built and tested on a two-layer riveted aluminum sample. Experimental results show that the optimized probe has better defect detection capability compared with a conventional non-optimized coil.

  7. Optimization and Validation of Rotating Current Excitation with GMR Array Sensors for Riveted Structures Inspection

    PubMed Central

    Ye, Chaofeng; Udpa, Lalita; Udpa, Satish

    2016-01-01

    In eddy current non-destructive testing of a multi-layered riveted structure, rotating current excitation, generated by orthogonal coils, is advantageous in providing sensitivity to defects of all orientations. However, when used with linear array sensors, the exciting magnetic flux density (Bx) of the orthogonal coils is not uniform over the sensor region, resulting in an output signal magnitude that depends on the relative location of the defect to the sensor array. In this paper, the rotating excitation coil is optimized to achieve a uniform Bx field in the sensor array area and minimize the probe size. The current density distribution of the coil is optimized using the polynomial approximation method. A non-uniform coil design is derived from the optimized current density distribution. Simulation results, using both an optimized coil and a conventional coil, are generated using the finite element method (FEM) model. The signal magnitude for an optimized coil is seen to be more robust with respect to offset of defects from the coil center. A novel multilayer coil structure, fabricated on a multi-layer printed circuit board, is used to build the optimized coil. A prototype probe with the optimized coil and 32 giant magnetoresistive (GMR) sensors is built and tested on a two-layer riveted aluminum sample. Experimental results show that the optimized probe has better defect detection capability compared with a conventional non-optimized coil. PMID:27649202

  8. Optimization and Validation of Rotating Current Excitation with GMR Array Sensors for Riveted Structures Inspection.

    PubMed

    Ye, Chaofeng; Udpa, Lalita; Udpa, Satish

    2016-01-01

    In eddy current non-destructive testing of a multi-layered riveted structure, rotating current excitation, generated by orthogonal coils, is advantageous in providing sensitivity to defects of all orientations. However, when used with linear array sensors, the exciting magnetic flux density ( B x ) of the orthogonal coils is not uniform over the sensor region, resulting in an output signal magnitude that depends on the relative location of the defect to the sensor array. In this paper, the rotating excitation coil is optimized to achieve a uniform B x field in the sensor array area and minimize the probe size. The current density distribution of the coil is optimized using the polynomial approximation method. A non-uniform coil design is derived from the optimized current density distribution. Simulation results, using both an optimized coil and a conventional coil, are generated using the finite element method (FEM) model. The signal magnitude for an optimized coil is seen to be more robust with respect to offset of defects from the coil center. A novel multilayer coil structure, fabricated on a multi-layer printed circuit board, is used to build the optimized coil. A prototype probe with the optimized coil and 32 giant magnetoresistive (GMR) sensors is built and tested on a two-layer riveted aluminum sample. Experimental results show that the optimized probe has better defect detection capability compared with a conventional non-optimized coil. PMID:27649202

  9. Optimal placement of actuators and sensors in control augmented structural optimization

    NASA Technical Reports Server (NTRS)

    Sepulveda, A. E.; Schmit, L. A., Jr.

    1990-01-01

    A control-augmented structural synthesis methodology is presented in which actuator and sensor placement is treated in terms of (0,1) variables. Structural member sizes and control variables are treated simultaneously as design variables. A multiobjective utopian approach is used to obtain a compromise solution for inherently conflicting objective functions such as strucutal mass control effort and number of actuators. Constraints are imposed on transient displacements, natural frequencies, actuator forces and dynamic stability as well as controllability and observability of the system. The combinatorial aspects of the mixed - (0,1) continuous variable design optimization problem are made tractable by combining approximation concepts with branch and bound techniques. Some numerical results for example problems are presented to illustrate the efficacy of the design procedure set forth.

  10. The monitoring of glacial migration in Greenland by multi sensor data fusion

    NASA Astrophysics Data System (ADS)

    Park, H.; Kim, J.; yun, H.; Choi, Y.

    2013-12-01

    The retreatment of ice sheet in Greenland by global warming is now firmly confirmed by variety of observations. However, the arguments about the melting speed of ice sheet is still undergoing owing to the absence of the quantitative measurement method to continuously trace the direction and the speed of icecap change. Thus, we tested a scheme to spatially and temporally monitor the migration of ice sheet with high accuracy employing multi sensor information and their data fusion. The target areas were established in Jakoshavm and Mittivakkat glaciers where the shrinking of glaciers has been obvious for the last one century. At first, in both well-known Greenland glaciers, Differential Interferometric SAR (DInSAR) campaigns which are highly useful to monitor the glacial retreat have been undertaking employing 30 European remote sensing satellite (ERS) and 15 Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) InSAR pairs. Since base DEM quality for DInSAR analysis is poor and InSAR pixels are frequently de-correlated over ice body, two pass DInSAR doesn't produce reliable outputs. Thus the time series analyses of Permanent Scatterer and Small Baseline Subset are expected to effectively trace the translation of the glaciers and employed as the main methodology of DInSAR. Although DInSAR time series analysis effectively reconstructed temporal change of glaciers, the extracted glacial movements are projected values into line of sight direction of the sensor. Therefore it might be better to interpret them together with the other remote sensed data set for the fulfilment of useful directional measurements. In terms of such data fusion aspect, we also employ Co-registration of Optically Sensed Images and Correlation (CoSi-CORR, Leprince et al., 2007) technique, which is known as a tool for 2D change tracing, with ALOS Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) to compensate for any line

  11. Sensor Fusion of Monocular Cameras and Laser Rangefinders for Line-Based Simultaneous Localization and Mapping (SLAM) Tasks in Autonomous Mobile Robots

    PubMed Central

    Zhang, Xinzheng; Rad, Ahmad B.; Wong, Yiu-Kwong

    2012-01-01

    This paper presents a sensor fusion strategy applied for Simultaneous Localization and Mapping (SLAM) in dynamic environments. The designed approach consists of two features: (i) the first one is a fusion module which synthesizes line segments obtained from laser rangefinder and line features extracted from monocular camera. This policy eliminates any pseudo segments that appear from any momentary pause of dynamic objects in laser data. (ii) The second characteristic is a modified multi-sensor point estimation fusion SLAM (MPEF-SLAM) that incorporates two individual Extended Kalman Filter (EKF) based SLAM algorithms: monocular and laser SLAM. The error of the localization in fused SLAM is reduced compared with those of individual SLAM. Additionally, a new data association technique based on the homography transformation matrix is developed for monocular SLAM. This data association method relaxes the pleonastic computation. The experimental results validate the performance of the proposed sensor fusion and data association method. PMID:22368478

  12. Sensor fusion of monocular cameras and laser rangefinders for line-based Simultaneous Localization and Mapping (SLAM) tasks in autonomous mobile robots.

    PubMed

    Zhang, Xinzheng; Rad, Ahmad B; Wong, Yiu-Kwong

    2012-01-01

    This paper presents a sensor fusion strategy applied for Simultaneous Localization and Mapping (SLAM) in dynamic environments. The designed approach consists of two features: (i) the first one is a fusion module which synthesizes line segments obtained from laser rangefinder and line features extracted from monocular camera. This policy eliminates any pseudo segments that appear from any momentary pause of dynamic objects in laser data. (ii) The second characteristic is a modified multi-sensor point estimation fusion SLAM (MPEF-SLAM) that incorporates two individual Extended Kalman Filter (EKF) based SLAM algorithms: monocular and laser SLAM. The error of the localization in fused SLAM is reduced compared with those of individual SLAM. Additionally, a new data association technique based on the homography transformation matrix is developed for monocular SLAM. This data association method relaxes the pleonastic computation. The experimental results validate the performance of the proposed sensor fusion and data association method.

  13. Sensor fusion of monocular cameras and laser rangefinders for line-based Simultaneous Localization and Mapping (SLAM) tasks in autonomous mobile robots.

    PubMed

    Zhang, Xinzheng; Rad, Ahmad B; Wong, Yiu-Kwong

    2012-01-01

    This paper presents a sensor fusion strategy applied for Simultaneous Localization and Mapping (SLAM) in dynamic environments. The designed approach consists of two features: (i) the first one is a fusion module which synthesizes line segments obtained from laser rangefinder and line features extracted from monocular camera. This policy eliminates any pseudo segments that appear from any momentary pause of dynamic objects in laser data. (ii) The second characteristic is a modified multi-sensor point estimation fusion SLAM (MPEF-SLAM) that incorporates two individual Extended Kalman Filter (EKF) based SLAM algorithms: monocular and laser SLAM. The error of the localization in fused SLAM is reduced compared with those of individual SLAM. Additionally, a new data association technique based on the homography transformation matrix is developed for monocular SLAM. This data association method relaxes the pleonastic computation. The experimental results validate the performance of the proposed sensor fusion and data association method. PMID:22368478

  14. New results and implications for lunar crustal iron distribution using sensor data fusion techniques

    NASA Astrophysics Data System (ADS)

    Clark, P. E.; McFadden, L. A.

    2000-02-01

    Remote measurements of the Moon have provided iron maps, and thus essential constraints for models of lunar crustal formation and mare basalt petrogenesis. A bulk crustal iron map was produced for the equatorial region from Apollo gamma-ray (AGR) spectrometer measurements, and a global iron variation map from recent Clementine spectral reflectance (CSR) measurements. Both iron maps show bimodal distribution, but have significantly different peak values and variations. In this paper, CSR data have been recalibrated to pyroxene in lunar landing site soils. A residual iron map is derived from the difference between AGR (bulk) and recalibrated CSR (pyroxene) iron abundances. The most likely interpretation is that the residual represents ferrous iron in olivine. This residual iron is anticorrelated to basin age, with older basins containing less olivine, suggesting segregation of basin basalt sources from a progressively fractionating underlying source region at the time of basin formation. Results presented here provide a quantitative basis for (1) establishing the relationship between direct geochemical (gamma-ray, X-ray) and mineralogical (near-IR) remote sensing data sets using sensor data fusion techniques to allow (2) simultaneous determination of elemental and mineralogical component distribution on remote targets and (3) meaningful interpretation of orbital and ground-based spectral reflectance measurements. When calibrated data from the Lunar Prospector mission are available, mapping of bulk crustal iron and iron-bearing soil components will be possible for the entire Moon. Similar analyses for data from the Near Earth Asteroid Rendezvous (NEAR) mission to asteroid 433 Eros will constrain models of asteroid formation.

  15. Optimization of sensor introduction into laminated composite materials

    NASA Astrophysics Data System (ADS)

    Schaaf, Kristin; Nemat-Nasser, Sia

    2008-03-01

    This work seeks to extend the functionality of the composite material beyond that of simply load-bearing and to enable in situ sensing, without compromising the structural integrity of the host composite material. Essential to the application of smart composites is the issue of the mechanical coupling of the sensor to the host material. Here we present various methods of embedding sensors within the host composite material. In this study, quasi-static three-point bending (short beam) and fatigue three-point bending (short beam) tests are conducted in order to characterize the effects of introducing the sensors into the host composite material. The sensors that are examined include three types of polyvinylidene fluoride (PVDF) thin film sensors: silver ink with a protective coating of urethane, silver ink without a protective coating, and nickel-copper alloy without a protective coating. The methods of sensor integration include placement at the midplane between the layers of prepreg material as well as a sandwich configuration in which a PVDF thin film sensor is placed between the first and second and nineteenth and twentieth layers of prepreg. Each PVDF sensor is continuous and occupies the entire layer, lying in the plane normal to the thickness direction in laminated composites. The work described here is part of an ongoing effort to understand the structural effects of integrating microsensor networks into a host composite material.

  16. Reliability of Measured Data for pH Sensor Arrays with Fault Diagnosis and Data Fusion Based on LabVIEW

    PubMed Central

    Liao, Yi-Hung; Chou, Jung-Chuan; Lin, Chin-Yi

    2013-01-01

    Fault diagnosis (FD) and data fusion (DF) technologies implemented in the LabVIEW program were used for a ruthenium dioxide pH sensor array. The purpose of the fault diagnosis and data fusion technologies is to increase the reliability of measured data. Data fusion is a very useful statistical method used for sensor arrays in many fields. Fault diagnosis is used to avoid sensor faults and to measure errors in the electrochemical measurement system, therefore, in this study, we use fault diagnosis to remove any faulty sensors in advance, and then proceed with data fusion in the sensor array. The average, self-adaptive and coefficient of variance data fusion methods are used in this study. The pH electrode is fabricated with ruthenium dioxide (RuO2) sensing membrane using a sputtering system to deposit it onto a silicon substrate, and eight RuO2 pH electrodes are fabricated to form a sensor array for this study. PMID:24351636

  17. Adapting computational optimization concepts from aeronautics to nuclear fusion reactor design

    NASA Astrophysics Data System (ADS)

    Dekeyser, W.; Reiter, D.; Baelmans, M.

    2012-10-01

    Even on the most powerful supercomputers available today, computational nuclear fusion reactor divertor design is extremely CPU demanding, not least due to the large number of design variables and the hybrid micro-macro character of the flows. Therefore, automated design methods based on optimization can greatly assist current reactor design studies. Over the past decades, "adjoint methods" for shape optimization have proven their virtue in the field of aerodynamics. Applications include drag reduction for wing and wing-body configurations. Here we demonstrate that also for divertor design, these optimization methods have a large potential. Specifically, we apply the continuous adjoint method to the optimization of the divertor geometry in a 2D poloidal cross section of an axisymmetric tokamak device (as, e.g., JET and ITER), using a simplified model for the plasma edge. The design objective is to spread the target material heat load as much as possible by controlling the shape of the divertor, while maintaining the full helium ash removal capabilities of the vacuum pumping system.

  18. New Optimal Sensor Suite for Ultrahigh Temperature Fossil Fuel Applications

    SciTech Connect

    John Coggin; Jonas Ivasauskas; Russell G. May; Michael B. Miller; Rena Wilson

    2006-09-30

    Accomplishments during Phase II of a program to develop and demonstrate photonic sensor technology for the instrumentation of advanced powerplants are described. The goal of this project is the research and development of advanced, robust photonic sensors based on improved sapphire optical waveguides, and the identification and demonstration of applications of the new sensors in advanced fossil fuel power plants, where the new technology will contribute to improvements in process control and monitoring. During this program work period, major progress has been experienced in the development of the sensor hardware, and the planning of the system installation and operation. The major focus of the next work period will be the installation of sensors in the Hamilton, Ohio power plant, and demonstration of high-temperature strain gages during mechanical testing of SOFC components.

  19. Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing

    NASA Astrophysics Data System (ADS)

    Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

    2013-12-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the 'A-Train' platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (MERRA), stratify the comparisons using a classification of the 'cloud scenes' from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically 'sharded' by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will

  20. Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing

    NASA Astrophysics Data System (ADS)

    Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E.

    2013-05-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will

  1. Results of the Development of Humanitarian Landmine Detection System by a Compact Fusion Neutron Source and Dual Sensors

    SciTech Connect

    Yoshikawa, Kiyoshi; Masuda, Kai; Takamatsu, Teruhisa; Yamamoto, Yasushi; Toku, Hisayuki; Fujimoto, Takashi; Hotta, Eiki; Yamauchi, Kunihito; Ohnishi, Masami; Osawa, Hodaka; Shiroya, Seiji; Misawa, Tsuyoshi; Takahashi, Yoshiyuki; Kubo, Yoshikazu; Doi, Toshiro

    2009-03-10

    A 5-year task is described on the research and development of the advanced humanitarian landmine detection system by using a compact discharge-type fusion neutron source called IECF (Inertial-Electrostatic Confinement Fusion) device and 3 dual sensors made of BGO and NaI(Tl). With 10{sup 7} D-D neutrons/s stably produced in steady-state mode, H-2.2 MeV, N-5.3, 10.8 MeV {gamma} rays from (n,{gamma}) reaction with hydrogen and nitrogen atoms in the explosives are measured for two kinds of explosives (TNT, RDX), under the conditions of three different buried depths, and soil moistures each. Final probabilities of detection for arid soil are found to be 100% in the present tests. The neutron backscattering method is also found to be efficient.

  2. Enhancing chemical identification efficiency by SAW sensor transients through a data enrichment and information fusion strategy—a simulation study

    NASA Astrophysics Data System (ADS)

    Singh, Prashant; Yadava, R. D. S.

    2013-05-01

    The paper proposes a new approach for improving the odor recognition efficiency of a surface acoustic wave (SAW) transient sensor system based on a single polymer coating. The vapor identity information is hidden in transient response shapes through dependences on specific vapor solvation and diffusion parameters in the polymer coating. The variations in the vapor exposure and purge durations and the sensor operating frequency have been used to create diversity in transient shapes via termination of the vapor-polymer equilibration process up to different stages. The transient signals were analyzed by the discrete wavelet transform using Daubechies-4 mother wavelet basis. The wavelet approximation coefficients were then processed by principal component analysis for creating feature space. The set of principal components define the vapor identity information. In an attempt to enhance vapor class separability we analyze two types of information fusion methods. In one, the sensor operation frequency is fixed and the sensing and purge durations are varied, and in the second, the sensing and purge durations are fixed and the sensor operating frequency is varied. The fusion is achieved by concatenation of discrete wavelet coefficients corresponding to various transients prior to the principal component analysis. The simulation experiments with polyisobutylene SAW sensor coating for operation frequencies over [55-160] MHz and sensing durations over [5-60] s were analyzed. The target vapors are seven volatile organics: chloroform, chlorobenzene, o-dichlorobenzene, n-heptane, toluene, n-hexane and n-octane whose concentrations were varied over [10-100] ppm. The simulation data were generated using a SAW sensor transient response model that incorporates the viscoelastic effects due to polymer coating and an additive noise source in the output. The analysis reveals that: (i) in single transient analysis the class separability increases with sensing duration for a given

  3. A novel optimal sensitivity design scheme for yarn tension sensor using surface acoustic wave device.

    PubMed

    Lei, Bingbing; Lu, Wenke; Zhu, Changchun; Liu, Qinghong; Zhang, Haoxin

    2014-08-01

    In this paper, we propose a novel optimal sensitivity design scheme for the yarn tension sensor using surface acoustic wave (SAW) device. In order to obtain the best sensitivity, the regression model between the size of the SAW yarn tension sensor substrate and the sensitivity of the SAW yarn tension sensor was established using the least square method. The model was validated too. Through analyzing the correspondence between the regression function monotonicity and its partial derivative sign, the effect of the SAW yarn tension sensor substrate size on the sensitivity of the SAW yarn tension sensor was investigated. Based on the regression model, a linear programming model was established to gain the optimal sensitivity of the SAW yarn tension sensor. The linear programming result shows that the maximum sensitivity will be achieved when the SAW yarn tension sensor substrate length is equal to 15 mm and its width is equal to 3mm within a fixed interval of the substrate size. An experiment of SAW yarn tension sensor about 15 mm long and 3mm wide was presented. Experimental results show that the maximum sensitivity 1982.39 Hz/g was accomplished, which confirms that the optimal sensitivity design scheme is useful and effective.

  4. An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network

    PubMed Central

    Vimalarani, C.; Subramanian, R.; Sivanandam, S. N.

    2016-01-01

    Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption. PMID:26881273

  5. An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network.

    PubMed

    Vimalarani, C; Subramanian, R; Sivanandam, S N

    2016-01-01

    Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption. PMID:26881273

  6. Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

    NASA Astrophysics Data System (ADS)

    Wilson, B. D.; Manipon, G.; Hua, H.

    2012-12-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within Sci

  7. Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

    NASA Astrophysics Data System (ADS)

    Wilson, B.; Manipon, G.; Hua, H.

    2012-04-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within Sci

  8. Optimal Sensor Placement for Measuring Physical Activity with a 3D Accelerometer

    PubMed Central

    Boerema, Simone T.; van Velsen, Lex; Schaake, Leendert; Tönis, Thijs M.; Hermens, Hermie J.

    2014-01-01

    Accelerometer-based activity monitors are popular for monitoring physical activity. In this study, we investigated optimal sensor placement for increasing the quality of studies that utilize accelerometer data to assess physical activity. We performed a two-staged study, focused on sensor location and type of mounting. Ten subjects walked at various walking speeds on a treadmill, performed a deskwork protocol, and walked on level ground, while simultaneously wearing five ProMove2 sensors with a snug fit on an elastic waist belt. We found that sensor location, type of activity, and their interaction-effect affected sensor output. The most lateral positions on the waist belt were the least sensitive for interference. The effect of mounting was explored, by making two subjects repeat the experimental protocol with sensors more loosely fitted to the elastic belt. The loose fit resulted in lower sensor output, except for the deskwork protocol, where output was higher. In order to increase the reliability and to reduce the variability of sensor output, researchers should place activity sensors on the most lateral position of a participant's waist belt. If the sensor hampers free movement, it may be positioned slightly more forward on the belt. Finally, sensors should be fitted tightly to the body. PMID:24553085

  9. Optimization of self-directed target coverage in wireless multimedia sensor network.

    PubMed

    Yang, Yang; Wang, Yufei; Pi, Dechang; Wang, Ruchuan

    2014-01-01

    Video and image sensors in wireless multimedia sensor networks (WMSNs) have directed view and limited sensing angle. So the methods to solve target coverage problem for traditional sensor networks, which use circle sensing model, are not suitable for WMSNs. Based on the FoV (field of view) sensing model and FoV disk model proposed, how expected multimedia sensor covers the target is defined by the deflection angle between target and the sensor's current orientation and the distance between target and the sensor. Then target coverage optimization algorithms based on expected coverage value are presented for single-sensor single-target, multisensor single-target, and single-sensor multitargets problems distinguishingly. Selecting the orientation that sensor rotated to cover every target falling in the FoV disk of that sensor for candidate orientations and using genetic algorithm to multisensor multitargets problem, which has NP-complete complexity, then result in the approximated minimum subset of sensors which covers all the targets in networks. Simulation results show the algorithm's performance and the effect of number of targets on the resulting subset. PMID:25136667

  10. The Homogeneity of Optimal Sensor Placement Across Multiple Winged Insect Species

    NASA Astrophysics Data System (ADS)

    Jenkins, Abigail L.

    Taking inspiration from biology, control algorithms can be implemented to imitate the naturally occurring control systems present in nature. This research is primarily concerned with insect flight and optimal wing sensor placement. Many winged insects with halteres are equipped with mechanoreceptors termed campaniform sensilla. Although the exact information these receptors provide to the insect's nervous system is unknown, it is thought to have the capability of measuring inertial rotation forces. During flight, when the wing bends, the information measured by the campaniform sensilla is received by the central nervous system, and provides the insect necessary data to control flight. This research compares three insect species - the hawkmoth Manduca sexta, the honeybee Apis mellifera, and the fruit fly Drosophila melanogaster. Using an observability-based sensor placement algorithm, the optimal sensor placement for these three species is determined. Simulations resolve if this optimal sensor placement corresponds to the insect's campaniform sensilla, as well as if placement is homogeneous across species.

  11. Spatiotemporal and geometric optimization of sensor arrays for detecting analytes in fluids

    DOEpatents

    Lewis, Nathan S.; Freund, Michael S.; Briglin, Shawn S.; Tokumaru, Phillip; Martin, Charles R.; Mitchell, David

    2009-09-29

    Sensor arrays and sensor array systems for detecting analytes in fluids. Sensors configured to generate a response upon introduction of a fluid containing one or more analytes can be located on one or more surfaces relative to one or more fluid channels in an array. Fluid channels can take the form of pores or holes in a substrate material. Fluid channels can be formed between one or more substrate plates. Sensor can be fabricated with substantially optimized sensor volumes to generate a response having a substantially maximized signal to noise ratio upon introduction of a fluid containing one or more target analytes. Methods of fabricating and using such sensor arrays and systems are also disclosed.

  12. Spatiotemporal and geometric optimization of sensor arrays for detecting analytes fluids

    DOEpatents

    Lewis, Nathan S.; Freund, Michael S.; Briglin, Shawn M.; Tokumaru, Phil; Martin, Charles R.; Mitchell, David T.

    2006-10-17

    Sensor arrays and sensor array systems for detecting analytes in fluids. Sensors configured to generate a response upon introduction of a fluid containing one or more analytes can be located on one or more surfaces relative to one or more fluid channels in an array. Fluid channels can take the form of pores or holes in a substrate material. Fluid channels can be formed between one or more substrate plates. Sensor can be fabricated with substantially optimized sensor volumes to generate a response having a substantially maximized signal to noise ratio upon introduction of a fluid containing one or more target analytes. Methods of fabricating and using such sensor arrays and systems are also disclosed.

  13. Deployment optimization of electro-optical sensor systems for naval missions

    NASA Astrophysics Data System (ADS)

    van Valkenburg-Haarst, Tanja Y. C.; van Norden, Wilbert L.; van der Meiden, Hilderick A.; ten Holter, Koen P. A.

    2010-10-01

    In today's naval missions, such as anti-piracy or counter-drugs operations, Electro-Optical (EO) sensors play an increasingly important role. In particular, these sensors are essential for classification and identification of targets. These tasks are traditionally performed by human operators, but because the complexity of today's missions, in combination with reduced manning, automating the information processing of EO sensors is increasingly necessary. This paper discusses the contribution of EO sensor systems to the picture compilation process, and how the deployment of EO sensors can be optimized for current naval missions. In particular, we discuss automation techniques for detection, classification and identification using EO sensors. Based on our findings, we give recommendations for future research.

  14. A UAV routing and sensor control optimization algorithm for target search

    NASA Astrophysics Data System (ADS)

    Collins, Gaemus E.; Riehl, James R.; Vegdahl, Philip S.

    2007-04-01

    An important problem in unmanned air vehicle (UAV) and UAV-mounted sensor control is the target search problem: locating target(s) in minimum time. Current methods solve the optimization of UAV routing control and sensor management independently. While this decoupled approach makes the target search problem computationally tractable, it is suboptimal. In this paper, we explore the target search and classification problems by formulating and solving a joint UAV routing and sensor control optimization problem. The routing problem is solved on a graph using receding horizon optimal control. The graph is dynamically adjusted based on the target probability distribution function (PDF). The objective function for the routing optimization is the solution of a sensor control optimization problem. An optimal sensor schedule (in the sense of maximizing the viewed target probability mass) is constructed for each candidate flight path in the routing control problem. The PDF of the target state is represented with a particle filter and an "occupancy map" for any undiscovered targets. The tradeoff between searching for undiscovered targets and locating tracks is handled automatically and dynamically by the use of an appropriate objective function. In particular, the objective function is based on the expected amount of target probability mass to be viewed.

  15. Sensor Selection and Optimization for Health Assessment of Aerospace Systems

    NASA Technical Reports Server (NTRS)

    Maul, William A.; Kopasakis, George; Santi, Louis M.; Sowers, Thomas S.; Chicatelli, Amy

    2008-01-01

    Aerospace systems are developed similarly to other large-scale systems through a series of reviews, where designs are modified as system requirements are refined. For space-based systems few are built and placed into service these research vehicles have limited historical experience to draw from and formidable reliability and safety requirements, due to the remote and severe environment of space. Aeronautical systems have similar reliability and safety requirements, and while these systems may have historical information to access, commercial and military systems require longevity under a range of operational conditions and applied loads. Historically, the design of aerospace systems, particularly the selection of sensors, is based on the requirements for control and performance rather than on health assessment needs. Furthermore, the safety and reliability requirements are met through sensor suite augmentation in an ad hoc, heuristic manner, rather than any systematic approach. A review of the current sensor selection practice within and outside of the aerospace community was conducted and a sensor selection architecture is proposed that will provide a justifiable, defendable sensor suite to address system health assessment requirements.

  16. Sensor Selection and Optimization for Health Assessment of Aerospace Systems

    NASA Technical Reports Server (NTRS)

    Maul, William A.; Kopasakis, George; Santi, Louis M.; Sowers, Thomas S.; Chicatelli, Amy

    2007-01-01

    Aerospace systems are developed similarly to other large-scale systems through a series of reviews, where designs are modified as system requirements are refined. For space-based systems few are built and placed into service. These research vehicles have limited historical experience to draw from and formidable reliability and safety requirements, due to the remote and severe environment of space. Aeronautical systems have similar reliability and safety requirements, and while these systems may have historical information to access, commercial and military systems require longevity under a range of operational conditions and applied loads. Historically, the design of aerospace systems, particularly the selection of sensors, is based on the requirements for control and performance rather than on health assessment needs. Furthermore, the safety and reliability requirements are met through sensor suite augmentation in an ad hoc, heuristic manner, rather than any systematic approach. A review of the current sensor selection practice within and outside of the aerospace community was conducted and a sensor selection architecture is proposed that will provide a justifiable, dependable sensor suite to address system health assessment requirements.

  17. Laser based microstructuring of polymer optical fibers for sensors optimization

    NASA Astrophysics Data System (ADS)

    Athanasekos, Loukas; Vasileiadis, Miltiadis; El Sachat, Alexandros; Vainos, Nikolaos A.; Riziotis, Christos

    2015-03-01

    Microstructuring of Polymer Optical Fibers-POF through surface modification with UV excimer laser radiation has been performed and studied. The laser modified surface cavities on fibers act as material receptors of exact volume allowing highly controllable and repeatable structures. The effect of Laser writing conditions on different etching characteristics of cladding and core materials of the fibres are presented. Ablated structures on the fibres are examined for optimised sensors' response characteristics. As a case study humidity and ammonia sensors are demonstrated by employing sensitive block copolymer materials on suitably micromachined segments of fibres.

  18. Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey

    PubMed Central

    Adnan, Md. Akhtaruzzaman; Razzaque, Mohammd Abdur; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

    2014-01-01

    For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted. PMID:24368702

  19. Bio-mimic optimization strategies in wireless sensor networks: a survey.

    PubMed

    Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

    2013-01-01

    For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted. PMID:24368702

  20. Bio-mimic optimization strategies in wireless sensor networks: a survey.

    PubMed

    Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

    2013-12-24

    For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.

  1. Robust optimal sensor placement for operational modal analysis based on maximum expected utility

    NASA Astrophysics Data System (ADS)

    Li, Binbin; Der Kiureghian, Armen

    2016-06-01

    Optimal sensor placement is essentially a decision problem under uncertainty. The maximum expected utility theory and a Bayesian linear model are used in this paper for robust sensor placement aimed at operational modal identification. To avoid nonlinear relations between modal parameters and measured responses, we choose to optimize the sensor locations relative to identifying modal responses. Since the modal responses contain all the information necessary to identify the modal parameters, the optimal sensor locations for modal response estimation provide at least a suboptimal solution for identification of modal parameters. First, a probabilistic model for sensor placement considering model uncertainty, load uncertainty and measurement error is proposed. The maximum expected utility theory is then applied with this model by considering utility functions based on three principles: quadratic loss, Shannon information, and K-L divergence. In addition, the prior covariance of modal responses under band-limited white-noise excitation is derived and the nearest Kronecker product approximation is employed to accelerate evaluation of the utility function. As demonstration and validation examples, sensor placements in a 16-degrees-of-freedom shear-type building and in Guangzhou TV Tower under ground motion and wind load are considered. Placements of individual displacement meter, velocimeter, accelerometer and placement of mixed sensors are illustrated.

  2. Optimized signal processing for FMCW interrogated reflective delay line-type SAW sensors.

    PubMed

    Viikari, Ville; Kokkonen, Kimmo; Meltaus, Johanna

    2008-11-01

    This correspondence presents an optimized frequency modulated continuous-wave (FMCW) interrogation procedure for reflective delay line-type SAW sensors. In this method, the time delays between reflections are obtained with Fourier transform from optimally windowed frequency response. Optimal window functions maximize the signal-tointerference ratio at chosen temporal points of interest. The method is experimentally verified and its accuracy is compared with that of a Fourier transform from Hamming-windowed frequency response. PMID:19049933

  3. Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors.

    PubMed

    Januszkiewicz, Łukasz; Di Barba, Paolo; Hausman, Sławomir

    2016-01-01

    We investigate a case of automated energy-budget-aware optimization of the physical position of nodes (sensors) in a Wireless Body Area Network (WBAN). This problem has not been presented in the literature yet, as opposed to antenna and routing optimization, which are relatively well-addressed. In our research, which was inspired by a safety-critical application for firefighters, the sensor network consists of three nodes located on the human body. The nodes communicate over a radio link operating in the 2.4 GHz or 5.8 GHz ISM frequency band. Two sensors have a fixed location: one on the head (earlobe pulse oximetry) and one on the arm (with accelerometers, temperature and humidity sensors, and a GPS receiver), while the position of the third sensor can be adjusted within a predefined region on the wearer's chest. The path loss between each node pair strongly depends on the location of the nodes and is difficult to predict without performing a full-wave electromagnetic simulation. Our optimization scheme employs evolutionary computing. The novelty of our approach lies not only in the formulation of the problem but also in linking a fully automated optimization procedure with an electromagnetic simulator and a simplified human body model. This combination turns out to be a computationally effective solution, which, depending on the initial placement, has a potential to improve performance of our example sensor network setup by up to about 20 dB with respect to the path loss between selected nodes. PMID:27196911

  4. On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks.

    PubMed

    Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon

    2015-01-01

    Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting-both in terms of data and energy-data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios. PMID:26270664

  5. On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks

    PubMed Central

    Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon

    2015-01-01

    Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting—both in terms of data and energy—data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios. PMID:26270664

  6. Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors.

    PubMed

    Januszkiewicz, Łukasz; Di Barba, Paolo; Hausman, Sławomir

    2016-05-17

    We investigate a case of automated energy-budget-aware optimization of the physical position of nodes (sensors) in a Wireless Body Area Network (WBAN). This problem has not been presented in the literature yet, as opposed to antenna and routing optimization, which are relatively well-addressed. In our research, which was inspired by a safety-critical application for firefighters, the sensor network consists of three nodes located on the human body. The nodes communicate over a radio link operating in the 2.4 GHz or 5.8 GHz ISM frequency band. Two sensors have a fixed location: one on the head (earlobe pulse oximetry) and one on the arm (with accelerometers, temperature and humidity sensors, and a GPS receiver), while the position of the third sensor can be adjusted within a predefined region on the wearer's chest. The path loss between each node pair strongly depends on the location of the nodes and is difficult to predict without performing a full-wave electromagnetic simulation. Our optimization scheme employs evolutionary computing. The novelty of our approach lies not only in the formulation of the problem but also in linking a fully automated optimization procedure with an electromagnetic simulator and a simplified human body model. This combination turns out to be a computationally effective solution, which, depending on the initial placement, has a potential to improve performance of our example sensor network setup by up to about 20 dB with respect to the path loss between selected nodes.

  7. On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks.

    PubMed

    Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon

    2015-08-11

    Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting-both in terms of data and energy-data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios.

  8. Image fusion

    NASA Technical Reports Server (NTRS)

    Pavel, M.

    1993-01-01

    The topics covered include the following: a system overview of the basic components of a system designed to improve the ability of a pilot to fly through low-visibility conditions such as fog; the role of visual sciences; fusion issues; sensor characterization; sources of information; image processing; and image fusion.

  9. Design optimization of high pressure and high temperature piezoresistive pressure sensor for high sensitivity

    NASA Astrophysics Data System (ADS)

    Niu, Zhe; Zhao, Yulong; Tian, Bian

    2014-01-01

    This paper describes a design method for optimizing sensitivity of piezoresistive pressure sensor in high-pressure and high-temperature environment. In order to prove the method, a piezoresistive pressure sensor (HPTSS) is designed. With the purpose of increasing sensitivity and to improve the measurement range, the piezoresistive sensor adopts rectangular membrane and thick film structure. The configuration of piezoresistors is arranged according to the characteristic of the rectangular membrane. The structure and configuration of the sensor chip are analyzed theoretically and simulated by the finite element method. This design enables the sensor chip to operate in high pressure condition (such as 150 MPa) with a high sensitivity and accuracy. The silicon on insulator wafer is selected to guarantee the thermo stability of the sensor chip. In order to optimize the fabrication and improve the yield of production, an electric conduction step is devised. Series of experiments demonstrates a favorable linearity of 0.13% and a high accuracy of 0.48%. And the sensitivity of HTPSS is about six times as high as a conventional square-membrane sensor chip in the experiment. Compared with the square-membrane pressure sensor and current production, the strength of HPTTS lies in sensitivity and measurement. The performance of the HPTSS indicates that it could be an ideal candidate for high-pressure and high-temperature sensing in real application.

  10. Design optimization of high pressure and high temperature piezoresistive pressure sensor for high sensitivity.

    PubMed

    Niu, Zhe; Zhao, Yulong; Tian, Bian

    2014-01-01

    This paper describes a design method for optimizing sensitivity of piezoresistive pressure sensor in high-pressure and high-temperature environment. In order to prove the method, a piezoresistive pressure sensor (HPTSS) is designed. With the purpose of increasing sensitivity and to improve the measurement range, the piezoresistive sensor adopts rectangular membrane and thick film structure. The configuration of piezoresistors is arranged according to the characteristic of the rectangular membrane. The structure and configuration of the sensor chip are analyzed theoretically and simulated by the finite element method. This design enables the sensor chip to operate in high pressure condition (such as 150 MPa) with a high sensitivity and accuracy. The silicon on insulator wafer is selected to guarantee the thermo stability of the sensor chip. In order to optimize the fabrication and improve the yield of production, an electric conduction step is devised. Series of experiments demonstrates a favorable linearity of 0.13% and a high accuracy of 0.48%. And the sensitivity of HTPSS is about six times as high as a conventional square-membrane sensor chip in the experiment. Compared with the square-membrane pressure sensor and current production, the strength of HPTTS lies in sensitivity and measurement. The performance of the HPTSS indicates that it could be an ideal candidate for high-pressure and high-temperature sensing in real application.

  11. Optimized beryllium target design for indirectly driven inertial confinement fusion experiments on the National Ignition Facility

    NASA Astrophysics Data System (ADS)

    Simakov, Andrei N.; Wilson, Douglas C.; Yi, Sunghwan A.; Kline, John L.; Clark, Daniel S.; Milovich, Jose L.; Salmonson, Jay D.; Batha, Steven H.

    2014-02-01

    For indirect drive inertial confinement fusion, Beryllium (Be) ablators offer a number of important advantages as compared with other ablator materials, e.g., plastic and high density carbon. In particular, the low opacity and relatively high density of Be lead to higher rocket efficiencies giving a higher fuel implosion velocity for a given X-ray drive; and to higher ablation velocities providing more ablative stabilization and reducing the effect of hydrodynamic instabilities on the implosion performance. Be ablator advantages provide a larger target design optimization space and can significantly improve the National Ignition Facility (NIF) [J. D. Lindl et al., Phys. Plasmas 11, 339 (2004)] ignition margin. Herein, we summarize the Be advantages, briefly review NIF Be target history, and present a modern, optimized, low adiabat, Revision 6 NIF Be target design. This design takes advantage of knowledge gained from recent NIF experiments, including more realistic levels of laser-plasma energy backscatter, degraded hohlraum-capsule coupling, and the presence of cross-beam energy transfer.

  12. Optimized beryllium target design for indirectly driven inertial confinement fusion experiments on the National Ignition Facility

    SciTech Connect

    Simakov, Andrei N. Wilson, Douglas C.; Yi, Sunghwan A.; Kline, John L.; Batha, Steven H.; Clark, Daniel S.; Milovich, Jose L.; Salmonson, Jay D.

    2014-02-15

    For indirect drive inertial confinement fusion, Beryllium (Be) ablators offer a number of important advantages as compared with other ablator materials, e.g., plastic and high density carbon. In particular, the low opacity and relatively high density of Be lead to higher rocket efficiencies giving a higher fuel implosion velocity for a given X-ray drive; and to higher ablation velocities providing more ablative stabilization and reducing the effect of hydrodynamic instabilities on the implosion performance. Be ablator advantages provide a larger target design optimization space and can significantly improve the National Ignition Facility (NIF) [J. D. Lindl et al., Phys. Plasmas 11, 339 (2004)] ignition margin. Herein, we summarize the Be advantages, briefly review NIF Be target history, and present a modern, optimized, low adiabat, Revision 6 NIF Be target design. This design takes advantage of knowledge gained from recent NIF experiments, including more realistic levels of laser-plasma energy backscatter, degraded hohlraum-capsule coupling, and the presence of cross-beam energy transfer.

  13. Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion

    PubMed Central

    Deng, Ning

    2014-01-01

    In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, andMMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity. PMID:24683317

  14. Efficient iris recognition based on optimal subfeature selection and weighted subregion fusion.

    PubMed

    Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; He, Fei; Wang, Hongye; Deng, Ning

    2014-01-01

    In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, and MMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity. PMID:24683317

  15. Sensor fusion of inertial-odometric navigation as a function of the actual manoeuvres of autonomous guided vehicles

    NASA Astrophysics Data System (ADS)

    DeCecco, Mariolino

    2003-05-01

    This paper presents a description of the 'sensor-fusion' algorithm for a navigation system suitable for autonomous guided vehicles that use two navigation systems: an odometric one which uses encoders mounted on the vehicle's wheels and an inertial one which uses a gyroscope. In the proposed algorithm the accuracy of both navigation systems is estimated as a function of the actual manoeuvre being carried out, which is identified by navigation data, and then the outputs of both sensors are fused taking into account the accuracy ratios. The method is explained starting from the measurement models and its calibration as a function of the different manoeuvres. Experimental calibration of the proposed algorithm was carried out using a scaled mock-up of an industrial robot. While the mean absolute value of the estimated error in distance over the path is 49 mm when using odometric navigation and 28 mm when using odometric plus inertial attitude navigation, it is only 15 mm when carrying out data fusion between the two measurement systems. A recursive method for estimating the evolution of spatial uncertainty, which also takes into account the systematic effects, is proposed.

  16. Multi-sensor fusion of electro-optic and infrared signals for high resolution visible images: part I

    NASA Astrophysics Data System (ADS)

    Huang, Xiaopeng; Netravali, Ravi; Man, Hong; Lawrence, Victor

    2013-06-01

    Electro-Optic (EO) image sensors exhibit the properties of high resolution and low noise level, but they cannot reflect information about the temperature of objects and do not work in dark environments. On the other hand, infrared (IR) image sensors exhibit the properties of low resolution and high noise level, but IR images can reflect information about the temperature of objects all the time. Therefore, in this paper, we propose a novel framework to enhance the resolution of EO images using the information (e.g., temperature) from IR images, which helps distinguish temperature variation of objects in the daytime via high-resolution EO images. The proposed novel framework involves four main steps: (1) select target objects with temperature variation in original IR images; (2) fuse original RGB color (EO) images and IR images based on image fusion algorithms; (3) blend the fused images of target objects in proportion with original gray-scale EO images; (4) superimpose the target objects' temperature information, onto original EO images via the modified NTSC color space transformation. Therein, the image fusion step will be conducted by qualitative (frame pipeline) approach. Revealing temperature information in EO images for the first time is the most significant contribution of this paper. Simulation results will show the transformed EO images with the targets' temperature information.

  17. Dual-Tree Complex Wavelet Transform and Image Block Residual-Based Multi-Focus Image Fusion in Visual Sensor Networks

    PubMed Central

    Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

    2014-01-01

    This paper presents a novel framework for the fusion of multi-focus images explicitly designed for visual sensor network (VSN) environments. Multi-scale based fusion methods can often obtain fused images with good visual effect. However, because of the defects of the fusion rules, it is almost impossible to completely avoid the loss of useful information in the thus obtained fused images. The proposed fusion scheme can be divided into two processes: initial fusion and final fusion. The initial fusion is based on a dual-tree complex wavelet transform (DTCWT). The Sum-Modified-Laplacian (SML)-based visual contrast and SML are employed to fuse the low- and high-frequency coefficients, respectively, and an initial composited image is obtained. In the final fusion process, the image block residuals technique and consistency verification are used to detect the focusing areas and then a decision map is obtained. The map is used to guide how to achieve the final fused image. The performance of the proposed method was extensively tested on a number of multi-focus images, including no-referenced images, referenced images, and images with different noise levels. The experimental results clearly indicate that the proposed method outperformed various state-of-the-art fusion methods, in terms of both subjective and objective evaluations, and is more suitable for VSNs. PMID:25587878

  18. Enhancing potency of siRNA targeting fusion genes by optimization outside of target sequence

    PubMed Central

    Gavrilov, Kseniya; Seo, Young-Eun; Tietjen, Gregory T.; Cui, Jiajia; Cheng, Christopher J.; Saltzman, W. Mark

    2015-01-01

    Canonical siRNA design algorithms have become remarkably effective at predicting favorable binding regions within a target mRNA, but in some cases (e.g., a fusion junction site) region choice is restricted. In these instances, alternative approaches are necessary to obtain a highly potent silencing molecule. Here we focus on strategies for rational optimization of two siRNAs that target the junction sites of fusion oncogenes BCR-ABL and TMPRSS2-ERG. We demonstrate that modifying the termini of these siRNAs with a terminal G-U wobble pair or a carefully selected pair of terminal asymmetry-enhancing mismatches can result in an increase in potency at low doses. Importantly, we observed that improvements in silencing at the mRNA level do not necessarily translate to reductions in protein level and/or cell death. Decline in protein level is also heavily influenced by targeted protein half-life, and delivery vehicle toxicity can confound measures of cell death due to silencing. Therefore, for BCR-ABL, which has a long protein half-life that is difficult to overcome using siRNA, we also developed a nontoxic transfection vector: poly(lactic-coglycolic acid) nanoparticles that release siRNA over many days. We show that this system can achieve effective killing of leukemic cells. These findings provide insights into the implications of siRNA sequence for potency and suggest strategies for the design of more effective therapeutic siRNA molecules. Furthermore, this work points to the importance of integrating studies of siRNA design and delivery, while heeding and addressing potential limitations such as restricted targetable mRNA regions, long protein half-lives, and nonspecific toxicities. PMID:26627251

  19. Performance optimization of high-order Lamb wave sensors based on silicon carbide substrates.

    PubMed

    Chen, Zhe; Fan, Li; Zhang, Shu-yi; Zhang, Hui

    2016-02-01

    Silicon carbide (SiC), as a new type of material for substrates in micro-electromechanical system (MEMS), was given high consideration in virtue of the properties of high acoustic velocity, low loss, chemical resistance, and etc. In this work, five performance parameters, which are electromechanical coupling coefficients, mass sensitivities, conductivity sensitivities, insert losses and minimum detectable masses, are theoretically investigated in Lamb wave chemical sensors for gas sensing based on SiC substrates. It is presented that higher performance can be achieved based on high-order modes other than fundamental modes, and the abovementioned five parameters can be simultaneously optimized. Then, according to the optimized operating conditions, operating parameters of the SiC-based high-order Lamb wave sensors are designed, which can be easily realized in MEMS technology. Finally, it is demonstrates that the SiC-based sensor exhibits better performance than that of the sensor with a conventional silicon substrate.

  20. Optimal design of a spectral readout type planar waveguide-mode sensor with a monolithic structure.

    PubMed

    Wang, Xiaomin; Fujimaki, Makoto; Kato, Takafumi; Nomura, Ken-Ichi; Awazu, Koichi; Ohki, Yoshimichi

    2011-10-10

    Optical planar waveguide-mode sensor is a promising candidate for highly sensitive biosensing techniques in fields such as protein adsorption, receptor-ligand interaction and surface bacteria adhesion. To make the waveguide-mode sensor system more realistic, a spectral readout type waveguide sensor is proposed to take advantage of its high speed, compactness and low cost. Based on our previously proposed monolithic waveguide-mode sensor composed of a SiO2 waveguide layer and a single crystalline Si layer [1], the mechanism for achieving high sensitivity is revealed by numerical simulations. The optimal achievable sensitivities for a series of waveguide structures are summarized in a contour map, and they are found to be better than those of previously reported angle-scan type waveguide sensors.

  1. Optimal sensor placement for maximum area coverage (MAC) for damage localization in composite structures

    NASA Astrophysics Data System (ADS)

    Thiene, M.; Sharif Khodaei, Z.; Aliabadi, M. H.

    2016-09-01

    In this paper an optimal sensor placement algorithm for attaining the maximum area coverage (MAC) within a sensor network is presented. The proposed novel approach takes into account physical properties of Lamb wave propagation (attenuation profile, direction dependant group velocity due to material anisotropy) and geometrical complexities (boundary reflections, presence of openings) of the structure. A feature of the proposed optimization approach lies in the fact that it is independent of characteristics of the damage detection algorithm (e.g. probability of detection) making it readily up-scalable to large complex composite structures such as aircraft stiffened composite panel. The proposed fitness function (MAC) is independent of damage parameters (type, severity, location). Statistical analysis carried out shows that the proposed optimum sensor network with MAC results in high probability of damage localization. Genetic algorithm is coupled with the fitness function to provide an efficient optimization strategy.

  2. Note: Optimization of piezoresistive response of pure carbon nanotubes networks as in-plane strain sensors

    NASA Astrophysics Data System (ADS)

    Miao, Yu; Chen, L.; Sammynaiken, R.; Lin, Y.; Zhang, W. J.

    2011-12-01

    The use of carbon nanotubes (CNT) for the application in in-plane strain detection is promising. In recent years, in-plane strain sensors constructed from CNT networks have been developed; however, few studied optimization of these sensors. In this paper, a study of the optimization of pure CNT networks in terms of piezoresistive response is reported. The so-called pure CNT networks are CNT networks free of surfactants. The performances of piezoresistive response are gauge factor (GF) and linearity. The variables are the number of layers of networks, concentration of CNT solution, and length of sonication time. As a result, the study concluded an optimal pure CNT networks sensor (GF: 2.59, linearity 0.98) with ten layers of networks, 0.8 mg/ml concentration, and 2 h of sonication time.

  3. Binary particle swarm optimization algorithm assisted to design of plasmonic nanospheres sensor

    NASA Astrophysics Data System (ADS)

    Kaboli, Milad; Akhlaghi, Majid; Shahmirzaee, Hossein

    2016-04-01

    In this study, a coherent perfect absorption (CPA)-type sensor based on plasmonic nanoparticles is proposed. It consists of a plasmonic nanospheres array on top of a quartz substrate. The refractive index changes above the sensor surface, which is due to the appearance of gas or the absorption of biomolecules, can be detected by measuring the resulting spectral shifts of the absorption coefficient. Since the CPA efficiency depends strongly on the number of plasmonic nanoparticles and the locations of nanoparticles, binary particle swarm optimization (BPSO) algorithm is used to design an optimized array of the plasmonic nanospheres. This optimized structure should be maximizing the absorption coefficient only in the one frequency. BPSO algorithm, a swarm of birds including a matrix with binary entries responsible for controlling nanospheres in the array, shows the presence with symbol of ('1') and the absence with ('0'). The sensor can be used for sensing both gas and low refractive index materials in an aqueous environment.

  4. Robust electromagnetically guided endoscopic procedure using enhanced particle swarm optimization for multimodal information fusion

    SciTech Connect

    Luo, Xiongbiao E-mail: Ying.Wan@student.uts.edu.au; Wan, Ying E-mail: Ying.Wan@student.uts.edu.au; He, Xiangjian

    2015-04-15

    Purpose: Electromagnetically guided endoscopic procedure, which aims at accurately and robustly localizing the endoscope, involves multimodal sensory information during interventions. However, it still remains challenging in how to integrate these information for precise and stable endoscopic guidance. To tackle such a challenge, this paper proposes a new framework on the basis of an enhanced particle swarm optimization method to effectively fuse these information for accurate and continuous endoscope localization. Methods: The authors use the particle swarm optimization method, which is one of stochastic evolutionary computation algorithms, to effectively fuse the multimodal information including preoperative information (i.e., computed tomography images) as a frame of reference, endoscopic camera videos, and positional sensor measurements (i.e., electromagnetic sensor outputs). Since the evolutionary computation method usually limits its possible premature convergence and evolutionary factors, the authors introduce the current (endoscopic camera and electromagnetic sensor’s) observation to boost the particle swarm optimization and also adaptively update evolutionary parameters in accordance with spatial constraints and the current observation, resulting in advantageous performance in the enhanced algorithm. Results: The experimental results demonstrate that the authors’ proposed method provides a more accurate and robust endoscopic guidance framework than state-of-the-art methods. The average guidance accuracy of the authors’ framework was about 3.0 mm and 5.6° while the previous methods show at least 3.9 mm and 7.0°. The average position and orientation smoothness of their method was 1.0 mm and 1.6°, which is significantly better than the other methods at least with (2.0 mm and 2.6°). Additionally, the average visual quality of the endoscopic guidance was improved to 0.29. Conclusions: A robust electromagnetically guided endoscopy framework was

  5. Distributed service-based approach for sensor data fusion in IoT environments.

    PubMed

    Rodríguez-Valenzuela, Sandra; Holgado-Terriza, Juan A; Gutiérrez-Guerrero, José M; Muros-Cobos, Jesús L

    2014-10-15

    The Internet of Things (IoT) enables the communication among smart objects promoting the pervasive presence around us of a variety of things or objects that are able to interact and cooperate jointly to reach common goals. IoT objects can obtain data from their context, such as the home, office, industry or body. These data can be combined to obtain new and more complex information applying data fusion processes. However, to apply data fusion algorithms in IoT environments, the full system must deal with distributed nodes, decentralized communication and support scalability and nodes dynamicity, among others restrictions. In this paper, a novel method to manage data acquisition and fusion based on a distributed service composition model is presented, improving the data treatment in IoT pervasive environments.

  6. Distributed Service-Based Approach for Sensor Data Fusion in IoT Environments

    PubMed Central

    Rodríguez-Valenzuela, Sandra; Holgado-Terriza, Juan A.; Gutiérrez-Guerrero, José M.; Muros-Cobos, Jesús L.

    2014-01-01

    The Internet of Things (IoT) enables the communication among smart objects promoting the pervasive presence around us of a variety of things or objects that are able to interact and cooperate jointly to reach common goals. IoT objects can obtain data from their context, such as the home, office, industry or body. These data can be combined to obtain new and more complex information applying data fusion processes. However, to apply data fusion algorithms in IoT environments, the full system must deal with distributed nodes, decentralized communication and support scalability and nodes dynamicity, among others restrictions. In this paper, a novel method to manage data acquisition and fusion based on a distributed service composition model is presented, improving the data treatment in IoT pervasive environments. PMID:25320907

  7. Front end optimization for the monolithic active pixel sensor of the ALICE Inner Tracking System upgrade

    NASA Astrophysics Data System (ADS)

    Kim, D.; Aglieri Rinella, G.; Cavicchioli, C.; Chanlek, N.; Collu, A.; Degerli, Y.; Dorokhov, A.; Flouzat, C.; Gajanana, D.; Gao, C.; Guilloux, F.; Hillemanns, H.; Hristozkov, S.; Junique, A.; Keil, M.; Kofarago, M.; Kugathasan, T.; Kwon, Y.; Lattuca, A.; Mager, M.; Sielewicz, K. M.; Marin Tobon, C. A.; Marras, D.; Martinengo, P.; Mazza, G.; Mugnier, H.; Musa, L.; Pham, T. H.; Puggioni, C.; Reidt, F.; Riedler, P.; Rousset, J.; Siddhanta, S.; Snoeys, W.; Song, M.; Usai, G.; Van Hoorne, J. W.; Yang, P.

    2016-02-01

    ALICE plans to replace its Inner Tracking System during the second long shut down of the LHC in 2019 with a new 10 m2 tracker constructed entirely with monolithic active pixel sensors. The TowerJazz 180 nm CMOS imaging Sensor process has been selected to produce the sensor as it offers a deep pwell allowing full CMOS in-pixel circuitry and different starting materials. First full-scale prototypes have been fabricated and tested. Radiation tolerance has also been verified. In this paper the development of the charge sensitive front end and in particular its optimization for uniformity of charge threshold and time response will be presented.

  8. Geometrical optimization of sensors for eddy currents nondestructive testing and evaluation

    SciTech Connect

    Thollon, F.; Burais, N.

    1995-05-01

    Design of Non Destructive Testing (NDT) and Non Destructive Evaluation (NDE) sensors is possible by solving Maxwell`s relations with FEM or BIM. But the large number of geometrical and electrical parameters of sensor and tested material implies many results that don`t give necessarily a well adapted sensor. The authors have used a genetic algorithm for automatic optimization. After having tested this algorithm with analytical solution of Maxwell`s relations for cladding thickness measurement, the method has been implemented in finite element package.

  9. Optimal sensor selection for noisy binary detection in stochastic pooling networks

    NASA Astrophysics Data System (ADS)

    McDonnell, Mark D.; Li, Feng; Amblard, P.-O.; Grant, Alex J.

    2013-08-01

    Stochastic Pooling Networks (SPNs) are a useful model for understanding and explaining how naturally occurring encoding of stochastic processes can occur in sensor systems ranging from macroscopic social networks to neuron populations and nanoscale electronics. Due to the interaction of nonlinearity, random noise, and redundancy, SPNs support various unexpected emergent features, such as suprathreshold stochastic resonance, but most existing mathematical results are restricted to the simplest case where all sensors in a network are identical. Nevertheless, numerical results on information transmission have shown that in the presence of independent noise, the optimal configuration of a SPN is such that there should be partial heterogeneity in sensor parameters, such that the optimal solution includes clusters of identical sensors, where each cluster has different parameter values. In this paper, we consider a SPN model of a binary hypothesis detection task and show mathematically that the optimal solution for a specific bound on detection performance is also given by clustered heterogeneity, such that measurements made by sensors with identical parameters either should all be excluded from the detection decision or all included. We also derive an algorithm for numerically finding the optimal solution and illustrate its utility with several examples, including a model of parallel sensory neurons with Poisson firing characteristics.

  10. Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter.

    PubMed

    Chowdhury, Amor; Sarjaš, Andrej

    2016-01-01

    The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation. PMID:27649197

  11. Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter

    PubMed Central

    Chowdhury, Amor; Sarjaš, Andrej

    2016-01-01

    The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation. PMID:27649197

  12. Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter.

    PubMed

    Chowdhury, Amor; Sarjaš, Andrej

    2016-09-15

    The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation.

  13. Design concept for an optimized earth radiation budget sensor

    NASA Technical Reports Server (NTRS)

    Carman, S. L.; Hansen, M. Z.; Arking, A.; Hoffman, J. W.

    1982-01-01

    The Earth Radiation Budget Program has the objective to measure and model the terrestrial radiation budget and obtain a better understanding of the climate and its changes. A multisensor, multisatellite system with high and midinclination orbits will be needed for implementing this program. Various approaches for conducting sensing operations have been evaluated. The present investigation considers a method of sampling with a unique multidirectional array mosaic sensor to fulfill the requirements of earth radiation budget measurements. Previous and present generation earth radiation budget (ERB) satellite instruments are discussed, and attention is given to instrument design tradeoffs and the baseline instrument concept.

  14. Microwave and video sensor fusion for the shape extraction of 3D space objects

    NASA Technical Reports Server (NTRS)

    Shaw, Scott W.; Defigueiredo, Rui J. P.; Krishen, Kumar

    1987-01-01

    A new system for the fusion of optical image data and polarized radar scattering cross-sections is presented. By considering the scattering data in conjunction with image data, the problem of ambiguity can be reduced. Only a small part of the surface needs to be reconstructed from the radar cross-sections; the remaining portion is constrained by the optical image.

  15. Optimal sensor configuration for flexible structures with multi-dimensional mode shapes

    NASA Astrophysics Data System (ADS)

    Chang, Minwoo; Pakzad, Shamim N.

    2015-05-01

    A framework for deciding the optimal sensor configuration is implemented for civil structures with multi-dimensional mode shapes, which enhances the applicability of structural health monitoring for existing structures. Optimal sensor placement (OSP) algorithms are used to determine the best sensor configuration for structures with a priori knowledge of modal information. The signal strength at each node is evaluated by effective independence and modified variance methods. Euclidean norm of signal strength indices associated with each node is used to expand OSP applicability into flexible structures. The number of sensors for each method is determined using the threshold for modal assurance criterion (MAC) between estimated (from a set of observations) and target mode shapes. Kriging is utilized to infer the modal estimates for unobserved locations with a weighted sum of known neighbors. A Kriging model can be expressed as a sum of linear regression and random error which is assumed as the realization of a stochastic process. This study presents the effects of Kriging parameters for the accurate estimation of mode shapes and the minimum number of sensors. The feasible ranges to satisfy MAC criteria are investigated and used to suggest the adequate searching bounds for associated parameters. The finite element model of a tall building is used to demonstrate the application of optimal sensor configuration. The dynamic modes of flexible structure at centroid are appropriately interpreted into the outermost sensor locations when OSP methods are implemented. Kriging is successfully used to interpolate the mode shapes from a set of sensors and to monitor structures associated with multi-dimensional mode shapes.

  16. Optimizing Cluster Heads for Energy Efficiency in Large-Scale Heterogeneous Wireless Sensor Networks

    DOE PAGES

    Gu, Yi; Wu, Qishi; Rao, Nageswara S. V.

    2010-01-01

    Many complex sensor network applications require deploying a large number of inexpensive and small sensors in a vast geographical region to achieve quality through quantity. Hierarchical clustering is generally considered as an efficient and scalable way to facilitate the management and operation of such large-scale networks and minimize the total energy consumption for prolonged lifetime. Judicious selection of cluster heads for data integration and communication is critical to the success of applications based on hierarchical sensor networks organized as layered clusters. We investigate the problem of selecting sensor nodes in a predeployed sensor network to be the cluster headsmore » to minimize the total energy needed for data gathering. We rigorously derive an analytical formula to optimize the number of cluster heads in sensor networks under uniform node distribution, and propose a Distance-based Crowdedness Clustering algorithm to determine the cluster heads in sensor networks under general node distribution. The results from an extensive set of experiments on a large number of simulated sensor networks illustrate the performance superiority of the proposed solution over the clustering schemes based on k -means algorithm.« less

  17. Integration of GPR and Laser Position Sensors for Real-Time 3D Data Fusion

    NASA Astrophysics Data System (ADS)

    Grasmueck, M.; Viggiano, D.

    2005-05-01

    Non-invasive 3D imaging visualizes anatomy and contents inside objects. Such tools are a commodity for medical doctors diagnosing a patient's health without scalpel and airport security staff inspecting the contents of baggage without opening. For geologists, hydrologists, archeologists and engineers wanting to see inside the shallow subsurface, such 3D tools are still a rarity. Theory and practice show that full-resolution 3D Ground Penetrating Radar (GPR) imaging requires unaliased recording of dipping reflections and diffractions. For a heterogeneous subsurface, minimum grid spacing of GPR measurements should be at least quarter wavelength or less in all directions. Consequently, positioning precision needs to be better than eighth wavelength for correct grid point assignment. Until now 3D GPR imaging has not been practical: data acquisition and processing took weeks to months, data analysis required geophysical training with no versatile 3D systems commercially available. We have integrated novel rotary laser positioning technology with GPR into a highly efficient and simple to use 3D imaging system. The laser positioning enables acquisition of centimeter accurate x, y, and z coordinates from multiple small detectors attached to moving GPR antennae. Positions streaming with 20 updates/second from each detector are fused in real-time with the GPR data. We developed software for automated data acquisition and real-time 3D GPR data quality control on slices at selected depths. Standard formatted (SEGY) data cubes and animations are generated within an hour after the last trace has been acquired. Examples can be seen at www.3dgpr.info. Such instant 3D GPR can be used as an on-site imaging tool supporting field work, hypothesis testing, and optimal sample collection. Rotary laser positioning has the flexibility to be integrated with multiple moving GPR antennae and other geophysical sensors enabling simple and efficient high resolution 3D data acquisition at

  18. Optimal waveforms design for ultra-wideband impulse radio sensors.

    PubMed

    Li, Bin; Zhou, Zheng; Zou, Weixia; Li, Dejian; Zhao, Chong

    2010-01-01

    Ultra-wideband impulse radio (UWB-IR) sensors should comply entirely with the regulatory spectral limits for elegant coexistence. Under this premise, it is desirable for UWB pulses to improve frequency utilization to guarantee the transmission reliability. Meanwhile, orthogonal waveform division multiple-access (WDMA) is significant to mitigate mutual interferences in UWB sensor networks. Motivated by the considerations, we suggest in this paper a low complexity pulse forming technique, and its efficient implementation on DSP is investigated. The UWB pulse is derived preliminarily with the objective of minimizing the mean square error (MSE) between designed power spectrum density (PSD) and the emission mask. Subsequently, this pulse is iteratively modified until its PSD completely conforms to spectral constraints. The orthogonal restriction is then analyzed and different algorithms have been presented. Simulation demonstrates that our technique can produce UWB waveforms with frequency utilization far surpassing the other existing signals under arbitrary spectral mask conditions. Compared to other orthogonality design schemes, the designed pulses can maintain mutual orthogonality without any penalty on frequency utilization, and hence, are much superior in a WDMA network, especially with synchronization deviations. PMID:22163511

  19. An analytical model for studying the structural effects and optimization of a capacitive tactile sensor array

    NASA Astrophysics Data System (ADS)

    Liang, Guanhao; Wang, Yancheng; Mei, Deqing; Xi, Kailun; Chen, Zichen

    2016-04-01

    This paper presents an analytical model to study the structural effects of a capacitive tactile sensor array on its capacitance changes and sensitivities. The tactile sensor array has 8  ×  8 sensor units, and each unit utilizes the truncated polydimethylsiloxane (PDMS) pyramid array structure as the dielectric layer to enhance the sensing performance. To predict the capacitance changes of the sensor unit, it is simplified into a two-layered structure: upper polyethylene terephthalate (PET) film and bottom truncated PDMS pyramid array. The upper PET is modeled by a displacement field function, while each of the truncated pyramids is analyzed to obtain its stress-strain relation. Using the Ritz method, the displacement field functions are solved. The deformation of the upper electrodes and the capacitance changes of the sensor unit can then be calculated. Using the developed model, the structural effects of the truncated PDMS pyramid array and the PDMS bump on the capacitance changes and sensitivities are studied. To achieve the largest capacitance changes, the dimensions have been optimized for the sensor unit. To verify the developed model, we have fabricated the sensor array, and the average sensitivities of the sensor unit to the x-, y-, and z-axes force are 0.49, 0.50, and 0.32% mN-1, respectively, while the model predicted values are 0.54, 0.54, and 0.35% mN-1. Results demonstrate that the developed model can accurately predict the sensing performance of the sensor array and could be utilized for structural optimization.

  20. Camera-based platform and sensor motion tracking for data fusion in a landmine detection system

    NASA Astrophysics Data System (ADS)

    van der Mark, Wannes; van den Heuvel, Johan C.; den Breejen, Eric; Groen, Frans C. A.

    2003-09-01

    Vehicles that serve in the role as landmine detection robots could be an important tool for demining former conflict areas. On the LOTUS platform for humanitarian demining, different sensors are used to detect a wide range of landmine types. Reliable and accurate detection depends on correctly combining the observations from the different sensors on the moving platform. Currently a method based on odometry is used to merge the readings from the sensors. In this paper a vision based approach is presented which can estimate the relative sensor pose and position together with the vehicle motion. To estimate the relative position and orientation of sensors, techniques from camera calibration are used. The platform motion is estimated from tracked features on the ground. A new approach is presented which can reduce the influence of tracking errors or other outliers on the accuracy of the ego-motion estimate. Overall, the new vision based approach for sensor localization leads to better estimates then the current odometry based method.

  1. Estimation of aboveground biomass in forests using multi-sensor (LIDAR, IFSAR, ETM+) fusion

    NASA Astrophysics Data System (ADS)

    Hyde, P.; Dubuyah, R.; Blair, B.; Hofton, M.; Hunsaker, C.; Pierce, L.; Walker, W.

    2002-05-01

    Aboveground biomass in forests, or the dry weight of standing trees, is a key ecosystem parameter for carbon dynamics, fire modeling, and biodiversity studies. Field-based assessments are expensive and methods to scale from field plots to landscapes are not generally accepted. Remote sensing potentially provides a cost-effective alternative, but no single sensor has yet to provide accurate, consistent estimates in all biomes. Passive optical sensors and synthetic aperture radar (SAR) have been proven effective only in young, structurally simple forests. Light detecting and ranging (LIDAR) has been effective in old-growth, structurally complex forests, but data are not widely available. Combining information from these sensors will leverage the high information content, high cost LIDAR data with lower cost, more widely available SAR and passive optical data. In this study, Landsat ETM+, x-band interferometric SAR, and airborne LIDAR from the Laser Vegetation Imaging Sensor (LVIS) were statistically fused using a decision tree classifier and compared to field-based estimates of biomass in Sierra National Forest, CA, USA. Biomass estimates derived from all sensors combined were more accurate than those derived from any single sensor.

  2. Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

    SciTech Connect

    Kumar, Rajeeva; Kumar, Aditya; Dai, Dan; Seenumani, Gayathri; Down, John; Lopez, Rodrigo

    2012-12-31

    This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developed will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve

  3. Deployment-based lifetime optimization model for homogeneous Wireless Sensor Network under retransmission.

    PubMed

    Li, Ruiying; Liu, Xiaoxi; Xie, Wei; Huang, Ning

    2014-12-10

    Sensor-deployment-based lifetime optimization is one of the most effective methods used to prolong the lifetime of Wireless Sensor Network (WSN) by reducing the distance-sensitive energy consumption. In this paper, data retransmission, a major consumption factor that is usually neglected in the previous work, is considered. For a homogeneous WSN, monitoring a circular target area with a centered base station, a sensor deployment model based on regular hexagonal grids is analyzed. To maximize the WSN lifetime, optimization models for both uniform and non-uniform deployment schemes are proposed by constraining on coverage, connectivity and success transmission rate. Based on the data transmission analysis in a data gathering cycle, the WSN lifetime in the model can be obtained through quantifying the energy consumption at each sensor location. The results of case studies show that it is meaningful to consider data retransmission in the lifetime optimization. In particular, our investigations indicate that, with the same lifetime requirement, the number of sensors needed in a non-uniform topology is much less than that in a uniform one. Finally, compared with a random scheme, simulation results further verify the advantage of our deployment model.

  4. Deployment-Based Lifetime Optimization Model for Homogeneous Wireless Sensor Network under Retransmission

    PubMed Central

    Li, Ruiying; Liu, Xiaoxi; Xie, Wei; Huang, Ning

    2014-01-01

    Sensor-deployment-based lifetime optimization is one of the most effective methods used to prolong the lifetime of Wireless Sensor Network (WSN) by reducing the distance-sensitive energy consumption. In this paper, data retransmission, a major consumption factor that is usually neglected in the previous work, is considered. For a homogeneous WSN, monitoring a circular target area with a centered base station, a sensor deployment model based on regular hexagonal grids is analyzed. To maximize the WSN lifetime, optimization models for both uniform and non-uniform deployment schemes are proposed by constraining on coverage, connectivity and success transmission rate. Based on the data transmission analysis in a data gathering cycle, the WSN lifetime in the model can be obtained through quantifying the energy consumption at each sensor location. The results of case studies show that it is meaningful to consider data retransmission in the lifetime optimization. In particular, our investigations indicate that, with the same lifetime requirement, the number of sensors needed in a non-uniform topology is much less than that in a uniform one. Finally, compared with a random scheme, simulation results further verify the advantage of our deployment model. PMID:25513822

  5. Star sensor baffle optimization: some helpful practical design rules

    NASA Astrophysics Data System (ADS)

    Arnoux, Jean-Jacques P.

    1996-11-01

    The performance of a star sensor is often limited by the stray light level on the detector and by non-uniformity and slopes of the corresponding irradiance. One of the major contributors to this unwanted noise is the baffle, which is frequently designed as a single equipment: its geometry is derived using simple rule to block first and second level scattering of stray light flux coming from external sources at off-axis positions defined by the mission. The geometry of the baffle is constrained by mechanical engineering requirements which confine its overall dimension. Better system performances are obtained when the early design of the baffle can take into account the angular response of the camera.

  6. On the Design of Smart Parking Networks in the Smart Cities: An Optimal Sensor Placement Model.

    PubMed

    Bagula, Antoine; Castelli, Lorenzo; Zennaro, Marco

    2015-06-30

    Smart parking is a typical IoT application that can benefit from advances in sensor, actuator and RFID technologies to provide many services to its users and parking owners of a smart city. This paper considers a smart parking infrastructure where sensors are laid down on the parking spots to detect car presence and RFID readers are embedded into parking gates to identify cars and help in the billing of the smart parking. Both types of devices are endowed with wired and wireless communication capabilities for reporting to a gateway where the situation recognition is performed. The sensor devices are tasked to play one of the three roles: (1) slave sensor nodes located on the parking spot to detect car presence/absence; (2) master nodes located at one of the edges of a parking lot to detect presence and collect the sensor readings from the slave nodes; and (3) repeater sensor nodes, also called "anchor" nodes, located strategically at specific locations in the parking lot to increase the coverage and connectivity of the wireless sensor network. While slave and master nodes are placed based on geographic constraints, the optimal placement of the relay/anchor sensor nodes in smart parking is an important parameter upon which the cost and efficiency of the parking system depends. We formulate the optimal placement of sensors in smart parking as an integer linear programming multi-objective problem optimizing the sensor network engineering efficiency in terms of coverage and lifetime maximization, as well as its economic gain in terms of the number of sensors deployed for a specific coverage and lifetime. We propose an exact solution to the node placement problem using single-step and two-step solutions implemented in the Mosel language based on the Xpress-MPsuite of libraries. Experimental results reveal the relative efficiency of the single-step compared to the two-step model on different performance parameters. These results are consolidated by simulation results

  7. On the Design of Smart Parking Networks in the Smart Cities: An Optimal Sensor Placement Model.

    PubMed

    Bagula, Antoine; Castelli, Lorenzo; Zennaro, Marco

    2015-01-01

    Smart parking is a typical IoT application that can benefit from advances in sensor, actuator and RFID technologies to provide many services to its users and parking owners of a smart city. This paper considers a smart parking infrastructure where sensors are laid down on the parking spots to detect car presence and RFID readers are embedded into parking gates to identify cars and help in the billing of the smart parking. Both types of devices are endowed with wired and wireless communication capabilities for reporting to a gateway where the situation recognition is performed. The sensor devices are tasked to play one of the three roles: (1) slave sensor nodes located on the parking spot to detect car presence/absence; (2) master nodes located at one of the edges of a parking lot to detect presence and collect the sensor readings from the slave nodes; and (3) repeater sensor nodes, also called "anchor" nodes, located strategically at specific locations in the parking lot to increase the coverage and connectivity of the wireless sensor network. While slave and master nodes are placed based on geographic constraints, the optimal placement of the relay/anchor sensor nodes in smart parking is an important parameter upon which the cost and efficiency of the parking system depends. We formulate the optimal placement of sensors in smart parking as an integer linear programming multi-objective problem optimizing the sensor network engineering efficiency in terms of coverage and lifetime maximization, as well as its economic gain in terms of the number of sensors deployed for a specific coverage and lifetime. We propose an exact solution to the node placement problem using single-step and two-step solutions implemented in the Mosel language based on the Xpress-MPsuite of libraries. Experimental results reveal the relative efficiency of the single-step compared to the two-step model on different performance parameters. These results are consolidated by simulation results

  8. On the Design of Smart Parking Networks in the Smart Cities: An Optimal Sensor Placement Model

    PubMed Central

    Bagula, Antoine; Castelli, Lorenzo; Zennaro, Marco

    2015-01-01

    Smart parking is a typical IoT application that can benefit from advances in sensor, actuator and RFID technologies to provide many services to its users and parking owners of a smart city. This paper considers a smart parking infrastructure where sensors are laid down on the parking spots to detect car presence and RFID readers are embedded into parking gates to identify cars and help in the billing of the smart parking. Both types of devices are endowed with wired and wireless communication capabilities for reporting to a gateway where the situation recognition is performed. The sensor devices are tasked to play one of the three roles: (1) slave sensor nodes located on the parking spot to detect car presence/absence; (2) master nodes located at one of the edges of a parking lot to detect presence and collect the sensor readings from the slave nodes; and (3) repeater sensor nodes, also called “anchor” nodes, located strategically at specific locations in the parking lot to increase the coverage and connectivity of the wireless sensor network. While slave and master nodes are placed based on geographic constraints, the optimal placement of the relay/anchor sensor nodes in smart parking is an important parameter upon which the cost and efficiency of the parking system depends. We formulate the optimal placement of sensors in smart parking as an integer linear programming multi-objective problem optimizing the sensor network engineering efficiency in terms of coverage and lifetime maximization, as well as its economic gain in terms of the number of sensors deployed for a specific coverage and lifetime. We propose an exact solution to the node placement problem using single-step and two-step solutions implemented in the Mosel language based on the Xpress-MPsuite of libraries. Experimental results reveal the relative efficiency of the single-step compared to the two-step model on different performance parameters. These results are consolidated by simulation results

  9. A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

    PubMed Central

    Lee, JongHyup; Pak, Dohyun

    2016-01-01

    For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

  10. A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks.

    PubMed

    Lee, JongHyup; Pak, Dohyun

    2016-01-01

    For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

  11. A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks.

    PubMed

    Lee, JongHyup; Pak, Dohyun

    2016-08-29

    For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections.

  12. Reliable Fusion of Stereo Matching and Depth Sensor for High Quality Dense Depth Maps

    PubMed Central

    Liu, Jing; Li, Chunpeng; Fan, Xuefeng; Wang, Zhaoqi

    2015-01-01

    Depth estimation is a classical problem in computer vision, which typically relies on either a depth sensor or stereo matching alone. The depth sensor provides real-time estimates in repetitive and textureless regions where stereo matching is not effective. However, stereo matching can obtain more accurate results in rich texture regions and object boundaries where the depth sensor often fails. We fuse stereo matching and the depth sensor using their complementary characteristics to improve the depth estimation. Here, texture information is incorporated as a constraint to restrict the pixel’s scope of potential disparities and to reduce noise in repetitive and textureless regions. Furthermore, a novel pseudo-two-layer model is used to represent the relationship between disparities in different pixels and segments. It is more robust to luminance variation by treating information obtained from a depth sensor as prior knowledge. Segmentation is viewed as a soft constraint to reduce ambiguities caused by under- or over-segmentation. Compared to the average error rate 3.27% of the previous state-of-the-art methods, our method provides an average error rate of 2.61% on the Middlebury datasets, which shows that our method performs almost 20% better than other “fused” algorithms in the aspect of precision. PMID:26308003

  13. Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors

    PubMed Central

    Januszkiewicz, Łukasz; Di Barba, Paolo; Hausman, Sławomir

    2016-01-01

    We investigate a case of automated energy-budget-aware optimization of the physical position of nodes (sensors) in a Wireless Body Area Network (WBAN). This problem has not been presented in the literature yet, as opposed to antenna and routing optimization, which are relatively well-addressed. In our research, which was inspired by a safety-critical application for firefighters, the sensor network consists of three nodes located on the human body. The nodes communicate over a radio link operating in the 2.4 GHz or 5.8 GHz ISM frequency band. Two sensors have a fixed location: one on the head (earlobe pulse oximetry) and one on the arm (with accelerometers, temperature and humidity sensors, and a GPS receiver), while the position of the third sensor can be adjusted within a predefined region on the wearer’s chest. The path loss between each node pair strongly depends on the location of the nodes and is difficult to predict without performing a full-wave electromagnetic simulation. Our optimization scheme employs evolutionary computing. The novelty of our approach lies not only in the formulation of the problem but also in linking a fully automated optimization procedure with an electromagnetic simulator and a simplified human body model. This combination turns out to be a computationally effective solution, which, depending on the initial placement, has a potential to improve performance of our example sensor network setup by up to about 20 dB with respect to the path loss between selected nodes. PMID:27196911

  14. FusionArc optimization: A hybrid volumetric modulated arc therapy (VMAT) and intensity modulated radiation therapy (IMRT) planning strategy

    SciTech Connect

    Matuszak, Martha M.; McShan, Daniel L.; Ten Haken, Randall K.; Steers, Jennifer M.; Long, Troy; Edwin Romeijn, H.; Fraass, Benedick A.

    2013-07-15

    Purpose: To introduce a hybrid volumetric modulated arc therapy/intensity modulated radiation therapy (VMAT/IMRT) optimization strategy called FusionArc that combines the delivery efficiency of single-arc VMAT with the potentially desirable intensity modulation possible with IMRT.Methods: A beamlet-based inverse planning system was enhanced to combine the advantages of VMAT and IMRT into one comprehensive technique. In the hybrid strategy, baseline single-arc VMAT plans are optimized and then the current cost function gradients with respect to the beamlets are used to define a metric for predicting which beam angles would benefit from further intensity modulation. Beams with the highest metric values (called the gradient factor) are converted from VMAT apertures to IMRT fluence, and the optimization proceeds with the mixed variable set until convergence or until additional beams are selected for conversion. One phantom and two clinical cases were used to validate the gradient factor and characterize the FusionArc strategy. Comparisons were made between standard IMRT, single-arc VMAT, and FusionArc plans with one to five IMRT/hybrid beams.Results: The gradient factor was found to be highly predictive of the VMAT angles that would benefit plan quality the most from beam modulation. Over the three cases studied, a FusionArc plan with three converted beams achieved superior dosimetric quality with reductions in final cost ranging from 26.4% to 48.1% compared to single-arc VMAT. Additionally, the three beam FusionArc plans required 22.4%-43.7% fewer MU/Gy than a seven beam IMRT plan. While the FusionArc plans with five converted beams offer larger reductions in final cost-32.9%-55.2% compared to single-arc VMAT-the decrease in MU/Gy compared to IMRT was noticeably smaller at 12.2%-18.5%, when compared to IMRT.Conclusions: A hybrid VMAT/IMRT strategy was implemented to find a high quality compromise between gantry-angle and intensity-based degrees of freedom. This

  15. FusionArc optimization: A hybrid volumetric modulated arc therapy (VMAT) and intensity modulated radiation therapy (IMRT) planning strategy

    PubMed Central

    Matuszak, Martha M.; Steers, Jennifer M.; Long, Troy; McShan, Daniel L.; Fraass, Benedick A.; Edwin Romeijn, H.; Ten Haken, Randall K.

    2013-01-01

    Purpose: To introduce a hybrid volumetric modulated arc therapy/intensity modulated radiation therapy (VMAT/IMRT) optimization strategy called FusionArc that combines the delivery efficiency of single-arc VMAT with the potentially desirable intensity modulation possible with IMRT. Methods: A beamlet-based inverse planning system was enhanced to combine the advantages of VMAT and IMRT into one comprehensive technique. In the hybrid strategy, baseline single-arc VMAT plans are optimized and then the current cost function gradients with respect to the beamlets are used to define a metric for predicting which beam angles would benefit from further intensity modulation. Beams with the highest metric values (called the gradient factor) are converted from VMAT apertures to IMRT fluence, and the optimization proceeds with the mixed variable set until convergence or until additional beams are selected for conversion. One phantom and two clinical cases were used to validate the gradient factor and characterize the FusionArc strategy. Comparisons were made between standard IMRT, single-arc VMAT, and FusionArc plans with one to five IMRT/hybrid beams. Results: The gradient factor was found to be highly predictive of the VMAT angles that would benefit plan quality the most from beam modulation. Over the three cases studied, a FusionArc plan with three converted beams achieved superior dosimetric quality with reductions in final cost ranging from 26.4% to 48.1% compared to single-arc VMAT. Additionally, the three beam FusionArc plans required 22.4%–43.7% fewer MU/Gy than a seven beam IMRT plan. While the FusionArc plans with five converted beams offer larger reductions in final cost—32.9%–55.2% compared to single-arc VMAT—the decrease in MU/Gy compared to IMRT was noticeably smaller at 12.2%–18.5%, when compared to IMRT. Conclusions: A hybrid VMAT/IMRT strategy was implemented to find a high quality compromise between gantry-angle and intensity-based degrees of freedom

  16. Optimized Autonomous Space In-situ Sensor-Web for volcano monitoring

    USGS Publications Warehouse

    Song, W.-Z.; Shirazi, B.; Kedar, S.; Chien, S.; Webb, F.; Tran, D.; Davis, A.; Pieri, D.; LaHusen, R.; Pallister, J.; Dzurisin, D.; Moran, S.; Lisowski, M.

    2008-01-01

    In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), is developing a prototype dynamic and scaleable hazard monitoring sensor-web and applying it to volcano monitoring. The combined Optimized Autonomous Space -In-situ Sensor-web (OASIS) will have two-way communication capability between ground and space assets, use both space and ground data for optimal allocation of limited power and bandwidth resources on the ground, and use smart management of competing demands for limited space assets. It will also enable scalability and seamless infusion of future space and in-situ assets into the sensor-web. The prototype will be focused on volcano hazard monitoring at Mount St. Helens, which has been active since October 2004. The system is designed to be flexible and easily configurable for many other applications as well. The primary goals of the project are: 1) integrating complementary space (i.e., Earth Observing One (EO-1) satellite) and in-situ (ground-based) elements into an interactive, autonomous sensor-web; 2) advancing sensor-web power and communication resource management technology; and 3) enabling scalability for seamless infusion of future space and in-situ assets into the sensor-web. To meet these goals, we are developing: 1) a test-bed in-situ array with smart sensor nodes capable of making autonomous data acquisition decisions; 2) efficient self-organization algorithm of sensor-web topology to support efficient data communication and command control; 3) smart bandwidth allocation algorithms in which sensor nodes autonomously determine packet priorities based on mission needs and local bandwidth information in real-time; and 4) remote network management and reprogramming tools. The space and in-situ control components of the system will be

  17. Observability considerations for multi-sensor and product fusion: Bias, information content, and validation (Invited)

    NASA Astrophysics Data System (ADS)

    Reid, J. S.; Zhang, J.; Hyer, E. J.; Campbell, J. R.; Christopher, S. A.; Ferrare, R. A.; Leptoukh, G. G.; Stackhouse, P. W.

    2009-12-01

    With the successful development of many aerosol products from the NASA A-train as well as new operational geostationary and polar orbiting sensors, the scientific community now has a host of new parameters to use in their analyses. The variety and quality of products has reached a point where the community has moved from basic observation-based science to sophisticated multi-component research that addresses the complex atmospheric environment. In order for these satellite data contribute to the science their uncertainty levels must move from semi-quantitative to quantitative. Initial attempts to quantify uncertainties have led to some recent debate in the community as to the efficacy of aerosol products from current and future NASA satellite sensors. In an effort to understand the state of satellite product fidelity, the Naval Research Laboratory and a newly reformed Global Energy and Water Cycle Experiment (GEWEX) aerosol panel have both initiated assessments of the nature of aerosol remote sensing uncertainty and bias. In this talk we go over areas of specific concern based on the authors’ experiences with the data, emphasizing the multi-sensor problem. We first enumerate potential biases, including retrieval, sampling/contextual, and cognitive bias. We show examples of how these biases can subsequently lead to the pitfalls of correlated/compensating errors, tautology, and confounding. The nature of bias is closely related to the information content of the sensor signal and its subsequent application to the derived aerosol quantity of interest (e.g., optical depth, flux, index of refraction, etc.). Consequently, purpose-specific validation methods must be employed, especially when generating multi-sensor products. Indeed, cloud and lower boundary condition biases in particular complicate the more typical methods of regressional bias elimination and histogram matching. We close with a discussion of sequestration of uncertainty in multi-sensor applications of

  18. Inertial head-tracker sensor fusion by a complementary separate-bias Kalman filter

    NASA Technical Reports Server (NTRS)

    Foxlin, Eric

    1996-01-01

    Current virtual environment and teleoperator applications are hampered by the need for an accurate, quick responding head-tracking system with a large working volume. Gyroscopic orientation sensors can overcome problems with jitter, latency, interference, line-of-sight obscurations, and limited range, but suffer from slow drift. Gravimetric inclinometers can detect attitude without drifting, but are slow and sensitive to transverse accelerations. This paper describes the design of a Kalman filter to integrate the data from these two types of sensors in order to achieve the excellent dynamic response of an inertial system without drift, and without the acceleration sensitivity of inclinometers.

  19. Inertial Head-Tracker Sensor Fusion by a Complementary Separate-Bias Kalman Filter

    NASA Technical Reports Server (NTRS)

    Foxlin, Eric

    1996-01-01

    Current virtual environment and teleoperator applications are hampered by the need for an accurate, quick-responding head-tracking system with a large working volume. Gyroscopic orientation sensors can overcome problems with jitter, latency, interference, line-of-sight obscurations, and limited range, but suffer from slow drift. Gravimetric inclinometers can detect attitude without drifting, but are slow and sensitive to transverse accelerations. This paper describes the design of a Kalman filter to integrate the data from these two types of sensors in order to achieve the excellent dynamic response of an inertial system without drift, and without the acceleration sensitivity of inclinometers.

  20. Optimization of Landscape Phage Fusion Protein-Modified Polymeric PEG-PE Micelles for Improved Breast Cancer Cell Targeting

    PubMed Central

    Wang, Tao; Petrenko, Valery A.; Torchilin, Vladimir P.

    2015-01-01

    Amphiphilic landscape phage fusion proteins with high affinity and selectivity towards breast cancer MCF-7 (Michigan Cancer Foundation-7) cells self-assemble with polymeric PEG-PE conjugates to form mixed micelles (phage-micelles) capable of cancer cell-targeted delivery of poorly-soluble drugs. While the PEG corona provides the stability and longevity to the micelles, its presence is a potential steric difficulties for the interaction of phage fusion protein with cell surface targets. We attempted to address this problem by controlling the length of the PEG block and the phage fusion protein quantity, selecting the optimal ones to produce a reasonable retention of the targeting affinity and selectivity of the MCF-7-specific phage fusion protein. Three PEG-PE conjugates with different PEG lengths were used to construct phage- and plain-micelles, followed by FACS analysis of the effect of the PEG length on their binding affinity and selectivity towards target MCF-7 cells using either a MCF-7 cell monoculture or a cell co-culture model composed of target cancer MCF-7 cells and non-target, non-cancer C166 cells expressing GFP (Green Fluorescent Protein). Both, the length of PEG and quantity of phage fusion protein had a profound impact on the targetability of the phage-micelles. Phage-micelles prepared with PEG2k-PE achieved a desirable binding affinity and selectivity. Incorporation of a minimal concentration of phage protein, up to 0.5%, produced maximal targeting efficiency towards MCF-7 cells. Overall, phage-micelles with PEG2k-PE and 0.5% of phage protein represent the optimal formulation for targeting towards breast cancer cells. PMID:26451274

  1. OASIS: A Data Fusion System Optimized for Access to Distributed Archives

    NASA Astrophysics Data System (ADS)

    Berriman, G. B.; Kong, M.; Good, J. C.

    2002-05-01

    The On-Line Archive Science Information Services (OASIS) is accessible as a java applet through the NASA/IPAC Infrared Science Archive home page. It uses Geographical Information System (GIS) technology to provide data fusion and interaction services for astronomers. These services include the ability to process and display arbitrarily large image files, and user-controlled contouring, overlay regeneration and multi-table/image interactions. OASIS has been optimized for access to distributed archives and data sets. Its second release (June 2002) provides a mechanism that enables access to OASIS from "third-party" services and data providers. That is, any data provider who creates a query form to an archive containing a collection of data (images, catalogs, spectra) can direct the result files from the query into OASIS. Similarly, data providers who serve links to datasets or remote services on a web page can access all of these data with one instance of OASIS. In this was any data or service provider is given access to the full suite of capabilites of OASIS. We illustrate the "third-party" access feature with two examples: queries to the high-energy image datasets accessible from GSFC SkyView, and links to data that are returned from a target-based query to the NASA Extragalactic Database (NED). The second release of OASIS also includes a file-transfer manager that reports the status of multiple data downloads from remote sources to the client machine. It is a prototype for a request management system that will ultimately control and manage compute-intensive jobs submitted through OASIS to computing grids, such as request for large scale image mosaics and bulk statistical analysis.

  2. A Sensor Fusion Method Based on an Integrated Neural Network and Kalman Filter for Vehicle Roll Angle Estimation.

    PubMed

    Vargas-Meléndez, Leandro; Boada, Beatriz L; Boada, María Jesús L; Gauchía, Antonio; Díaz, Vicente

    2016-01-01

    This article presents a novel estimator based on sensor fusion, which combines the Neural Network (NN) with a Kalman filter in order to estimate the vehicle roll angle. The NN estimates a "pseudo-roll angle" through variables that are easily measured from Inertial Measurement Unit (IMU) sensors. An IMU is a device that is commonly used for vehicle motion detection, and its cost has decreased during recent years. The pseudo-roll angle is introduced in the Kalman filter in order to filter noise and minimize the variance of the norm and maximum errors' estimation. The NN has been trained for J-turn maneuvers, double lane change maneuvers and lane change maneuvers at different speeds and road friction coefficients. The proposed method takes into account the vehicle non-linearities, thus yielding good roll angle estimation. Finally, the proposed estimator has been compared with one that uses the suspension deflections to obtain the pseudo-roll angle. Experimental results show the effectiveness of the proposed NN and Kalman filter-based estimator. PMID:27589763

  3. A Sensor Fusion Method Based on an Integrated Neural Network and Kalman Filter for Vehicle Roll Angle Estimation

    PubMed Central

    Vargas-Meléndez, Leandro; Boada, Beatriz L.; Boada, María Jesús L.; Gauchía, Antonio; Díaz, Vicente

    2016-01-01

    This article presents a novel estimator based on sensor fusion, which combines the Neural Network (NN) with a Kalman filter in order to estimate the vehicle roll angle. The NN estimates a “pseudo-roll angle” through variables that are easily measured from Inertial Measurement Unit (IMU) sensors. An IMU is a device that is commonly used for vehicle motion detection, and its cost has decreased during recent years. The pseudo-roll angle is introduced in the Kalman filter in order to filter noise and minimize the variance of the norm and maximum errors’ estimation. The NN has been trained for J-turn maneuvers, double lane change maneuvers and lane change maneuvers at different speeds and road friction coefficients. The proposed method takes into account the vehicle non-linearities, thus yielding good roll angle estimation. Finally, the proposed estimator has been compared with one that uses the suspension deflections to obtain the pseudo-roll angle. Experimental results show the effectiveness of the proposed NN and Kalman filter-based estimator. PMID:27589763

  4. A Sensor Fusion Method Based on an Integrated Neural Network and Kalman Filter for Vehicle Roll Angle Estimation.

    PubMed

    Vargas-Meléndez, Leandro; Boada, Beatriz L; Boada, María Jesús L; Gauchía, Antonio; Díaz, Vicente

    2016-08-31

    This article presents a novel estimator based on sensor fusion, which combines the Neural Network (NN) with a Kalman filter in order to estimate the vehicle roll angle. The NN estimates a "pseudo-roll angle" through variables that are easily measured from Inertial Measurement Unit (IMU) sensors. An IMU is a device that is commonly used for vehicle motion detection, and its cost has decreased during recent years. The pseudo-roll angle is introduced in the Kalman filter in order to filter noise and minimize the variance of the norm and maximum errors' estimation. The NN has been trained for J-turn maneuvers, double lane change maneuvers and lane change maneuvers at different speeds and road friction coefficients. The proposed method takes into account the vehicle non-linearities, thus yielding good roll angle estimation. Finally, the proposed estimator has been compared with one that uses the suspension deflections to obtain the pseudo-roll angle. Experimental results show the effectiveness of the proposed NN and Kalman filter-based estimator.

  5. Relative pose estimation of satellites using PMD-/CCD-sensor data fusion

    NASA Astrophysics Data System (ADS)

    Tzschichholz, Tristan; Boge, Toralf; Schilling, Klaus

    2015-04-01

    Rendezvous & Docking to passive objects, as of relevance for space debris removal, raises new challenges with respect to relative navigation. Whenever the position and orientation (pose) of an object is required in terrestrial and in space applications, sensor systems such as laser scanners and stereo vision systems are often employed. This paper presents an approach to pose estimation using a 3D time-of-flight camera for ranging information in combination with a high resolution grayscale camera. We have designed a pose estimation method that fuses the data streams of the two sensors in order to benefit from each sensors' advantages. A rigorous test campaign on a Real-Time Hardware-In-The-Loop Rendezvous and Docking Simulator - the European Proximity Operations Simulator (EPOS) - was performed in order to evaluate the performance of the resulting algorithm. The proposed pose estimation method does not exceed an average distance error of 3 cm while being capable of providing pose estimates at up to 60 FPS on recent hardware. Thus, when regarding proximity operations, an attractive sensor system is used to characterize the dynamics of the target object for safe approach results.

  6. A Navigation System for the Visually Impaired: A Fusion of Vision and Depth Sensor

    PubMed Central

    Kanwal, Nadia; Bostanci, Erkan; Currie, Keith; Clark, Adrian F.

    2015-01-01

    For a number of years, scientists have been trying to develop aids that can make visually impaired people more independent and aware of their surroundings. Computer-based automatic navigation tools are one example of this, motivated by the increasing miniaturization of electronics and the improvement in processing power and sensing capabilities. This paper presents a complete navigation system based on low cost and physically unobtrusive sensors such as a camera and an infrared sensor. The system is based around corners and depth values from Kinect's infrared sensor. Obstacles are found in images from a camera using corner detection, while input from the depth sensor provides the corresponding distance. The combination is both efficient and robust. The system not only identifies hurdles but also suggests a safe path (if available) to the left or right side and tells the user to stop, move left, or move right. The system has been tested in real time by both blindfolded and blind people at different indoor and outdoor locations, demonstrating that it operates adequately. PMID:27057135

  7. Optimal aeroelastic vehicle sensor placement for root migration flight control applications

    NASA Astrophysics Data System (ADS)

    Al-Shehabi, Abdul Ghafoor

    2001-09-01

    An important step in control design for elastic systems is the determination of the number and location of control system components, namely sensors. The number and placement of sensors can be critical to the robust functioning of active control systems, especially when the system of interest is a large high-speed aeroelastic vehicle. The position of the sensors affects not only system stability, but also the performance of the closed-loop system. In this dissertation, a new approach for sensor placement in the integrated rigid and vibrational control of flexible aircraft structures is developed. Traditional rigid-body augmentation objectives are addressed indirectly through input-output pair and compensation selection. Aeroelastic control suppression objectives are addressed directly through sensor placement. A nonlinear programming problem is posed to minimize a cost function with specified constraints, where the cost function terms are multiplied by appropriate weighting factors. Cost function criteria are based on complex frequency domain geometric pole-zero structures in order to gain stabilize or phase stabilize the aeroelastic modes. Specifically, these criteria are based on dipole magnitude and complementary departure angle. In turn, the control design approach utilizes one of the classical methods known as Evans root migration to exploit the pole-zero structures resulting from sensor placement. Desirable complementary departure angles can lead to significant aeroelastic damping improvement as loop gain is increased, while favorable dipole magnitudes can virtually eliminate the effects of aeroelastics in a feedback loop. Appropriate constraints include minimum phase aeroelastic zeros to avoid common problems associated with right-half plane zeros. To achieve desirable flight control system characteristics via optimal sensor locations, different kinds of blending filters for multiple sensors are investigated. Static filters, as well as dynamic filters with

  8. Optimization of radiation hardness and charge collection of edgeless silicon pixel sensors for photon science

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Tartarotti Maimone, D.; Pennicard, D.; Sarajlic, M.; Graafsma, H.

    2014-12-01

    Recent progress in active-edge technology of silicon sensors enables the development of large-area tiled silicon pixel detectors with small dead space between modules by utilizing edgeless sensors. Such technology has been proven in successful productions of ATLAS and Medipix-based silicon pixel sensors by a few foundries. However, the drawbacks of edgeless sensors are poor radiation hardness for ionizing radiation and non-uniform charge collection by edge pixels. In this work, the radiation hardness of edgeless sensors with different polarities has been investigated using Synopsys TCAD with X-ray radiation-damage parameters implemented. Results show that if no conventional guard ring is present, none of the current designs are able to achieve a high breakdown voltage (typically < 30 V) after irradiation to a dose of ~ 10 MGy. In addition, a charge-collection model has been developed and was used to calculate the charges collected by the edge pixels of edgeless sensors when illuminated with X-rays. The model takes into account the electric field distribution inside the pixel sensor, the absorption of X-rays, drift and diffusion of electrons and holes, charge sharing effects, and threshold settings in ASICs. It is found that the non-uniform charge collection of edge pixels is caused by the strong bending of the electric field and the non-uniformity depends on bias voltage, sensor thickness and distance from active edge to the last pixel (``edge space"). In particular, the last few pixels close to the active edge of the sensor are not sensitive to low-energy X-rays ( < 10 keV), especially for sensors with thicker Si and smaller edge space. The results from the model calculation have been compared to measurements and good agreement was obtained. The model can be used to optimize the edge design. From the edge optimization, it is found that in order to guarantee the sensitivity of the last few pixels to low-energy X-rays, the edge space should be kept at least 50% of

  9. Optimized autonomous space in-situ sensor web for volcano monitoring

    USGS Publications Warehouse

    Song, W.-Z.; Shirazi, B.; Huang, R.; Xu, M.; Peterson, N.; LaHusen, R.; Pallister, J.; Dzurisin, D.; Moran, S.; Lisowski, M.; Kedar, S.; Chien, S.; Webb, F.; Kiely, A.; Doubleday, J.; Davies, A.; Pieri, D.

    2010-01-01

    In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), have developed a prototype of dynamic and scalable hazard monitoring sensor-web and applied it to volcano monitoring. The combined Optimized Autonomous Space In-situ Sensor-web (OASIS) has two-way communication capability between ground and space assets, uses both space and ground data for optimal allocation of limited bandwidth resources on the ground, and uses smart management of competing demands for limited space assets. It also enables scalability and seamless infusion of future space and in-situ assets into the sensor-web. The space and in-situ control components of the system are integrated such that each element is capable of autonomously tasking the other. The ground in-situ was deployed into the craters and around the flanks of Mount St. Helens in July 2009, and linked to the command and control of the Earth Observing One (EO-1) satellite. ?? 2010 IEEE.

  10. Optimization of people evacuation plans on the basis of wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Amirgaliyev, Yedilkhan; Yunussov, Rassul; Mamyrbayev, Orken

    2016-01-01

    This paper introduces the optimization process for people salvation in critical situations by organizing their evacuation plan from enclosed areas using modern approaches of data acquisition on the basis of wireless sensor networks. The proposed technology allows the ability to gather information about people density on the surveyed area by the usage of wireless sensor networks, consistently covering the enclosed territory. It enables the update of the evacuation plan on the basis of people density information inside the enclosed areas online. It is proposed to use common video surveillance cameras as sensors. The advantage of visual surveillance using cameras is that it does not require additional technological equipment for the area and much more important does not impose rules and restriction on the surveillance objects (people in this case). Next tasks are to be solved: creation of mathematical model of optimal enclosed area surveillance by wireless sensors, database and data interrogation modelling of wireless sensor network, creation of algorithmic model for automated people counting using video signal for the covering area; creation of dynamic people evacuation model on the basis of maximum flow problem [1, 2].

  11. Increasing the Lifetime of Mobile WSNs via Dynamic Optimization of Sensor Node Communication Activity

    PubMed Central

    Guimarães, Dayan Adionel; Sakai, Lucas Jun; Alberti, Antonio Marcos; de Souza, Rausley Adriano Amaral

    2016-01-01

    In this paper, a simple and flexible method for increasing the lifetime of fixed or mobile wireless sensor networks is proposed. Based on past residual energy information reported by the sensor nodes, the sink node or another central node dynamically optimizes the communication activity levels of the sensor nodes to save energy without sacrificing the data throughput. The activity levels are defined to represent portions of time or time-frequency slots in a frame, during which the sensor nodes are scheduled to communicate with the sink node to report sensory measurements. Besides node mobility, it is considered that sensors’ batteries may be recharged via a wireless power transmission or equivalent energy harvesting scheme, bringing to the optimization problem an even more dynamic character. We report large increased lifetimes over the non-optimized network and comparable or even larger lifetime improvements with respect to an idealized greedy algorithm that uses both the real-time channel state and the residual energy information. PMID:27657075

  12. [Design and Optimization of Surface Plasmon Resonance Sensor Based on Side Polished Single-Mode Fiber].

    PubMed

    Feng, Xin-jie; Mao, Pei-ling; Chen, Xiao-long; Luo, Yun-han; Peng, Shui-hua; Chen, Chao-ying; Wang, Fang; Tang, Jie-yuan; Yu, Jian-hui; Zhang, Jun; Lu, Hui-hui; Chen, Zhe

    2015-05-01

    Fiber-coupling surface Plasmon resonance sensor has attractive advantages of information transmission such as small volume, anti-electric magnetic field interference, and online real-time remote detection. In order to improve the performance of the sensor, the effect of the residual fiber thickness and the silver film thickness to the sensitivity of the sensor and the depth of the resonance peaks and full width ar half maximum (FWHM) are analyzed respectively. The results show that the increasing fiber residual thickness weakens the SPR phenomenon, and that the increasing silver film thickness widens the resonance peak, while the sensitivity of the sensor does not change monotonously. Through the integration of refractive index sensing sensitivity and full width at half maximum, figure of merit is presented and regarded as the optimized objective. The optimal design is achieved in the case of the fiber residual thickness for 66. 5 µm, and the silver film thickness for 50 nm. The optimized design with the figure of merit of 98. 67 is expected to be applied in the bio-chemical sensing and analysis. PMID:26415471

  13. A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

    PubMed Central

    Costa, Daniel G.; Guedes, Luiz Affonso

    2011-01-01

    Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks. PMID:22163908

  14. [Optimization method of MOS sensor array for identification of traditional Chinese medicine based on electronic nose].

    PubMed

    Zou, Hui-Qin; Liu, Yong; Tao, Ou; Lin, Hui; Su, Yu-Zhen; Lin, Xiang-Long; Yan, Yong-Hong

    2013-01-01

    Optimization of sensor array is a significant topic in the application of electronic nose (EN). Stepwise discriminant analysis and cluster analysis combining with screening of typical index were employed to optimize the original array in the classification of 100 samples from 10 kinds of traditional Chinese medicine based on alpha-FOX3000 EN. And the identification ability was evaluated by three algorithm including principle component analysis, Fisher discriminant analysis and random forest. The results showed that the identification ability of EN was improved since not only the effective information was maintained but also the redundant one was eliminated by the optimized array. The optimized method was eventually established, it was accurate and efficient. And the optimized array was built up, that is, S1, S2, S5, S6, S8, S12.

  15. Real-time enhancement, registration, and fusion for a multi-sensor enhanced vision system

    NASA Astrophysics Data System (ADS)

    Hines, Glenn D.; Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

    2006-05-01

    Over the last few years NASA Langley Research Center (LaRC) has been developing an Enhanced Vision System (EVS) to aid pilots while flying in poor visibility conditions. The EVS captures imagery using two infrared video cameras. The cameras are placed in an enclosure that is mounted and flown forward-looking underneath the NASA LaRC ARIES 757 aircraft. The data streams from the cameras are processed in realtime and displayed on monitors on-board the aircraft. With proper processing the camera system can provide better-than-human-observed imagery particularly during poor visibility conditions. However, to obtain this goal requires several different stages of processing including enhancement, registration, and fusion, and specialized processing hardware for realtime performance. We are using a realtime implementation of the Retinex algorithm for image enhancement, affine transformations for registration, and weighted sums to perform fusion. All of the algorithms are executed on a single TI DM642 digital signal processor (DSP) clocked at 720 MHz. The image processing components were added to the EVS system, tested, and demonstrated during flight tests in August and September of 2005. In this paper we briefly discuss the EVS image processing hardware and algorithms. We then discuss implementation issues and show examples of the results obtained during flight tests.

  16. Multiple local feature representations and their fusion based on an SVR model for iris recognition using optimized Gabor filters

    NASA Astrophysics Data System (ADS)

    He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Dong, Hongxing

    2014-12-01

    Gabor descriptors have been widely used in iris texture representations. However, fixed basic Gabor functions cannot match the changing nature of diverse iris datasets. Furthermore, a single form of iris feature cannot overcome difficulties in iris recognition, such as illumination variations, environmental conditions, and device variations. This paper provides multiple local feature representations and their fusion scheme based on a support vector regression (SVR) model for iris recognition using optimized Gabor filters. In our iris system, a particle swarm optimization (PSO)- and a Boolean particle swarm optimization (BPSO)-based algorithm is proposed to provide suitable Gabor filters for each involved test dataset without predefinition or manual modulation. Several comparative experiments on JLUBR-IRIS, CASIA-I, and CASIA-V4-Interval iris datasets are conducted, and the results show that our work can generate improved local Gabor features by using optimized Gabor filters for each dataset. In addition, our SVR fusion strategy may make full use of their discriminative ability to improve accuracy and reliability. Other comparative experiments show that our approach may outperform other popular iris systems.

  17. Pose Estimation of Unmanned Aerial Vehicles Based on a Vision-Aided Multi-Sensor Fusion

    NASA Astrophysics Data System (ADS)

    Abdi, G.; Samadzadegan, F.; Kurz, F.

    2016-06-01

    GNSS/IMU navigation systems offer low-cost and robust solution to navigate UAVs. Since redundant measurements greatly improve the reliability of navigation systems, extensive researches have been made to enhance the efficiency and robustness of GNSS/IMU by additional sensors. This paper presents a method for integrating reference data, images taken from UAVs, barometric height data and GNSS/IMU data to estimate accurate and reliable pose parameters of UAVs. We provide improved pose estimations by integrating multi-sensor observations in an EKF algorithm with IMU motion model. The implemented methodology has demonstrated to be very efficient and reliable for automatic pose estimation. The calculated position and attitude of the UAV especially when we removed the GNSS from the working cycle clearly indicate the ability of the purposed methodology.

  18. Multi-sensor fusion for enhanced contextual awareness of everyday activities with ubiquitous devices.

    PubMed

    Guiry, John J; van de Ven, Pepijn; Nelson, John

    2014-03-21

    In this paper, the authors investigate the role that smart devices, including smartphones and smartwatches, can play in identifying activities of daily living. A feasibility study involving N = 10 participants was carried out to evaluate the devices' ability to differentiate between nine everyday activities. The activities examined include walking, running, cycling, standing, sitting, elevator ascents, elevator descents, stair ascents and stair descents. The authors also evaluated the ability of these devices to differentiate indoors from outdoors, with the aim of enhancing contextual awareness. Data from this study was used to train and test five well known machine learning algorithms: C4.5, CART, Naïve Bayes, Multi-Layer Perceptrons and finally Support Vector Machines. Both single and multi-sensor approaches were examined to better understand the role each sensor in the device can play in unobtrusive activity recognition. The authors found overall results to be promising, with some models correctly classifying up to 100% of all instances.

  19. Optimal sensor placement for leak location in water distribution networks using genetic algorithms.

    PubMed

    Casillas, Myrna V; Puig, Vicenç; Garza-Castañón, Luis E; Rosich, Albert

    2013-11-04

    This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the large size and non-linear integer nature of the resulting optimization problem, genetic algorithms (GAs) are used as the solution approach. The obtained results are compared with a semi-exhaustive search method with higher computational effort, proving that GA allows one to find near-optimal solutions with less computational load. Moreover, three ways of increasing the robustness of the GA-based sensor placement method have been proposed using a time horizon analysis, a distance-based scoring and considering different leaks sizes. A great advantage of the proposed methodology is that it does not depend on the isolation method chosen by the user, as long as it is based on leak sensitivity analysis. Experiments in two networks allow us to evaluate the performance of the proposed approach.

  20. Optimal Sensor Placement for Leak Location in Water Distribution Networks Using Genetic Algorithms

    PubMed Central

    Casillas, Myrna V.; Puig, Vicenç; Garza-Castañón, Luis E.; Rosich, Albert

    2013-01-01

    This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of