Navigation Algorithms for Formation Flying Missions
NASA Technical Reports Server (NTRS)
Huxel, Paul J.; Bishop, Robert H.
2004-01-01
The objective of the investigations is to develop navigation algorithms to support formation flying missions. In particular, we examine the advantages and concerns associated with the use of combinations of inertial and relative measurements, as well as address observability issues. In our analysis we consider the interaction between measurement types, update frequencies, and trajectory geometry and their cumulative impact on observability. Furthermore, we investigate how relative measurements affect inertial navigation in terms of algorithm performance.
Automated Driftmeter Fused with Inertial Navigation
2014-03-27
6 IMU Inertial Measurement Unit . . . . . . . . . . . . . . . . . . . . . . . 7 SLAM Simultaneous...timing lines to remain horizontal at all times, regardless of turbulence and within 20 degrees of roll , pitch, and yaw of the aircraft. It had two...introduced in 1960 [2]. The Kalman filter algorithm has been used to merge inertial navigational data from Inertial Measurement Units ( IMU ) with
Inertial navigation without accelerometers
NASA Astrophysics Data System (ADS)
Boehm, M.
The Kennedy-Thorndike (1932) experiment points to the feasibility of fiber-optic inertial velocimeters, to which state-of-the-art technology could furnish substantial sensitivity and accuracy improvements. Velocimeters of this type would obviate the use of both gyros and accelerometers, and allow inertial navigation to be conducted together with vehicle attitude control, through the derivation of rotation rates from the ratios of the three possible velocimeter pairs. An inertial navigator and reference system based on this approach would probably have both fewer components and simpler algorithms, due to the obviation of the first level of integration in classic inertial navigators.
Xian, Zhiwen; Hu, Xiaoping; Lian, Junxiang; Zhang, Lilian; Cao, Juliang; Wang, Yujie; Ma, Tao
2014-09-15
Navigation plays a vital role in our daily life. As traditional and commonly used navigation technologies, Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) can provide accurate location information, but suffer from the accumulative error of inertial sensors and cannot be used in a satellite denied environment. The remarkable navigation ability of animals shows that the pattern of the polarization sky can be used for navigation. A bio-inspired POLarization Navigation Sensor (POLNS) is constructed to detect the polarization of skylight. Contrary to the previous approach, we utilize all the outputs of POLNS to compute input polarization angle, based on Least Squares, which provides optimal angle estimation. In addition, a new sensor calibration algorithm is presented, in which the installation angle errors and sensor biases are taken into consideration. Derivation and implementation of our calibration algorithm are discussed in detail. To evaluate the performance of our algorithms, simulation and real data test are done to compare our algorithms with several exiting algorithms. Comparison results indicate that our algorithms are superior to the others and are more feasible and effective in practice.
NAVSIM 2: A computer program for simulating aided-inertial navigation for aircraft
NASA Technical Reports Server (NTRS)
Bjorkman, William S.
1987-01-01
NAVSIM II, a computer program for analytical simulation of aided-inertial navigation for aircraft, is described. The description is supported by a discussion of the program's application to the design and analysis of aided-inertial navigation systems as well as instructions for utilizing the program and for modifying it to accommodate new models, constraints, algorithms and scenarios. NAVSIM II simulates an airborne inertial navigation system built around a strapped-down inertial measurement unit and aided in its function by GPS, Doppler radar, altimeter, airspeed, and position-fix measurements. The measurements are incorporated into the navigation estimate via a UD-form Kalman filter. The simulation was designed and implemented using structured programming techniques and with particular attention to user-friendly operation.
Xian, Zhiwen; Hu, Xiaoping; Lian, Junxiang; Zhang, Lilian; Cao, Juliang; Wang, Yujie; Ma, Tao
2014-01-01
Navigation plays a vital role in our daily life. As traditional and commonly used navigation technologies, Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) can provide accurate location information, but suffer from the accumulative error of inertial sensors and cannot be used in a satellite denied environment. The remarkable navigation ability of animals shows that the pattern of the polarization sky can be used for navigation. A bio-inspired POLarization Navigation Sensor (POLNS) is constructed to detect the polarization of skylight. Contrary to the previous approach, we utilize all the outputs of POLNS to compute input polarization angle, based on Least Squares, which provides optimal angle estimation. In addition, a new sensor calibration algorithm is presented, in which the installation angle errors and sensor biases are taken into consideration. Derivation and implementation of our calibration algorithm are discussed in detail. To evaluate the performance of our algorithms, simulation and real data test are done to compare our algorithms with several exiting algorithms. Comparison results indicate that our algorithms are superior to the others and are more feasible and effective in practice. PMID:25225872
Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation
NASA Technical Reports Server (NTRS)
Karlgaard, Christopher D.; Kutty, Prasad; Schoenenberger, Mark
2016-01-01
This paper describes an algorithm for atmospheric state estimation based on a coupling between inertial navigation and flush air data-sensing pressure measurements. The navigation state is used in the atmospheric estimation algorithm along with the pressure measurements and a model of the surface pressure distribution to estimate the atmosphere using a nonlinear weighted least-squares algorithm. The approach uses a high-fidelity model of atmosphere stored in table-lookup form, along with simplified models propagated along the trajectory within the algorithm to aid the solution. Thus, the method is a reduced-order Kalman filter in which the inertial states are taken from the navigation solution and atmospheric states are estimated in the filter. The algorithm is applied to data from the Mars Science Laboratory entry, descent, and landing from August 2012. Reasonable estimates of the atmosphere are produced by the algorithm. The observability of winds along the trajectory are examined using an index based on the observability Gramian and the pressure measurement sensitivity matrix. The results indicate that bank reversals are responsible for adding information content. The algorithm is applied to the design of the pressure measurement system for the Mars 2020 mission. A linear covariance analysis is performed to assess estimator performance. The results indicate that the new estimator produces more precise estimates of atmospheric states than existing algorithms.
Failure detection and isolation analysis of a redundant strapdown inertial measurement unit
NASA Technical Reports Server (NTRS)
Motyka, P.; Landey, M.; Mckern, R.
1981-01-01
The objective of this study was to define and develop techniques for failure detection and isolation (FDI) algorithms for a dual fail/operational redundant strapdown inertial navigation system are defined and developed. The FDI techniques chosen include provisions for hard and soft failure detection in the context of flight control and navigation. Analyses were done to determine error detection and switching levels for the inertial navigation system, which is intended for a conventional takeoff or landing (CTOL) operating environment. In addition, investigations of false alarms and missed alarms were included for the FDI techniques developed, along with the analyses of filters to be used in conjunction with FDI processing. Two specific FDI algorithms were compared: the generalized likelihood test and the edge vector test. A deterministic digital computer simulation was used to compare and evaluate the algorithms and FDI systems.
Inertial Pocket Navigation System: Unaided 3D Positioning
Munoz Diaz, Estefania
2015-01-01
Inertial navigation systems use dead-reckoning to estimate the pedestrian's position. There are two types of pedestrian dead-reckoning, the strapdown algorithm and the step-and-heading approach. Unlike the strapdown algorithm, which consists of the double integration of the three orthogonal accelerometer readings, the step-and-heading approach lacks the vertical displacement estimation. We propose the first step-and-heading approach based on unaided inertial data solving 3D positioning. We present a step detector for steps up and down and a novel vertical displacement estimator. Our navigation system uses the sensor introduced in the front pocket of the trousers, a likely location of a smartphone. The proposed algorithms are based on the opening angle of the leg or pitch angle. We analyzed our step detector and compared it with the state-of-the-art, as well as our already proposed step length estimator. Lastly, we assessed our vertical displacement estimator in a real-world scenario. We found that our algorithms outperform the literature step and heading algorithms and solve 3D positioning using unaided inertial data. Additionally, we found that with the pitch angle, five activities are distinguishable: standing, sitting, walking, walking up stairs and walking down stairs. This information complements the pedestrian location and is of interest for applications, such as elderly care. PMID:25897501
Vision-Aided Inertial Navigation
NASA Technical Reports Server (NTRS)
Roumeliotis, Stergios I. (Inventor); Mourikis, Anastasios I. (Inventor)
2017-01-01
This document discloses, among other things, a system and method for implementing an algorithm to determine pose, velocity, acceleration or other navigation information using feature tracking data. The algorithm has computational complexity that is linear with the number of features tracked.
NASA Technical Reports Server (NTRS)
Mcgee, L. A.; Smith, G. L.; Hegarty, D. M.; Merrick, R. B.; Carson, T. M.; Schmidt, S. F.
1970-01-01
A preliminary study has been made of the navigation performance which might be achieved for the high cross-range space shuttle orbiter during final approach and landing by using an optimally augmented inertial navigation system. Computed navigation accuracies are presented for an on-board inertial navigation system augmented (by means of an optimal filter algorithm) with data from two different ground navigation aids; a precision ranging system and a microwave scanning beam landing guidance system. These results show that augmentation with either type of ground navigation aid is capable of providing a navigation performance at touchdown which should be adequate for the space shuttle. In addition, adequate navigation performance for space shuttle landing is obtainable from the precision ranging system even with a complete dropout of precision range measurements as much as 100 seconds before touchdown.
A Robust Method to Detect Zero Velocity for Improved 3D Personal Navigation Using Inertial Sensors
Xu, Zhengyi; Wei, Jianming; Zhang, Bo; Yang, Weijun
2015-01-01
This paper proposes a robust zero velocity (ZV) detector algorithm to accurately calculate stationary periods in a gait cycle. The proposed algorithm adopts an effective gait cycle segmentation method and introduces a Bayesian network (BN) model based on the measurements of inertial sensors and kinesiology knowledge to infer the ZV period. During the detected ZV period, an Extended Kalman Filter (EKF) is used to estimate the error states and calibrate the position error. The experiments reveal that the removal rate of ZV false detections by the proposed method increases 80% compared with traditional method at high walking speed. Furthermore, based on the detected ZV, the Personal Inertial Navigation System (PINS) algorithm aided by EKF performs better, especially in the altitude aspect. PMID:25831086
NASA Technical Reports Server (NTRS)
Hoang, TY
1994-01-01
A real-time, high-rate precision navigation Kalman filter algorithm is developed and analyzed. This Navigation algorithm blends various navigation data collected during terminal area approach of an instrumented helicopter. Navigation data collected include helicopter position and velocity from a global position system in differential mode (DGPS) as well as helicopter velocity and attitude from an inertial navigation system (INS). The goal of the Navigation algorithm is to increase the DGPS accuracy while producing navigational data at the 64 Hertz INS update rate. It is important to note that while the data was post flight processed, the Navigation algorithm was designed for real-time analysis. The design of the Navigation algorithm resulted in a nine-state Kalman filter. The Kalman filter's state matrix contains position, velocity, and velocity bias components. The filter updates positional readings with DGPS position, INS velocity, and velocity bias information. In addition, the filter incorporates a sporadic data rejection scheme. This relatively simple model met and exceeded the ten meter absolute positional requirement. The Navigation algorithm results were compared with truth data derived from a laser tracker. The helicopter flight profile included terminal glideslope angles of 3, 6, and 9 degrees. Two flight segments extracted during each terminal approach were used to evaluate the Navigation algorithm. The first segment recorded small dynamic maneuver in the lateral plane while motion in the vertical plane was recorded by the second segment. The longitudinal, lateral, and vertical averaged positional accuracies for all three glideslope approaches are as follows (mean plus or minus two standard deviations in meters): longitudinal (-0.03 plus or minus 1.41), lateral (-1.29 plus or minus 2.36), and vertical (-0.76 plus or minus 2.05).
Vetrella, Amedeo Rodi; Fasano, Giancarmine; Accardo, Domenico; Moccia, Antonio
2016-12-17
Autonomous navigation of micro-UAVs is typically based on the integration of low cost Global Navigation Satellite System (GNSS) receivers and Micro-Electro-Mechanical Systems (MEMS)-based inertial and magnetic sensors to stabilize and control the flight. The resulting navigation performance in terms of position and attitude accuracy may not suffice for other mission needs, such as the ones relevant to fine sensor pointing. In this framework, this paper presents a cooperative UAV navigation algorithm that allows a chief vehicle, equipped with inertial and magnetic sensors, a Global Positioning System (GPS) receiver, and a vision system, to improve its navigation performance (in real time or in the post processing phase) exploiting formation flying deputy vehicles equipped with GPS receivers. The focus is set on outdoor environments and the key concept is to exploit differential GPS among vehicles and vision-based tracking (DGPS/Vision) to build a virtual additional navigation sensor whose information is then integrated in a sensor fusion algorithm based on an Extended Kalman Filter. The developed concept and processing architecture are described, with a focus on DGPS/Vision attitude determination algorithm. Performance assessment is carried out on the basis of both numerical simulations and flight tests. In the latter ones, navigation estimates derived from the DGPS/Vision approach are compared with those provided by the onboard autopilot system of a customized quadrotor. The analysis shows the potential of the developed approach, mainly deriving from the possibility to exploit magnetic- and inertial-independent accurate attitude information.
Optimal Parameter Design of Coarse Alignment for Fiber Optic Gyro Inertial Navigation System.
Lu, Baofeng; Wang, Qiuying; Yu, Chunmei; Gao, Wei
2015-06-25
Two different coarse alignment algorithms for Fiber Optic Gyro (FOG) Inertial Navigation System (INS) based on inertial reference frame are discussed in this paper. Both of them are based on gravity vector integration, therefore, the performance of these algorithms is determined by integration time. In previous works, integration time is selected by experience. In order to give a criterion for the selection process, and make the selection of the integration time more accurate, optimal parameter design of these algorithms for FOG INS is performed in this paper. The design process is accomplished based on the analysis of the error characteristics of these two coarse alignment algorithms. Moreover, this analysis and optimal parameter design allow us to make an adequate selection of the most accurate algorithm for FOG INS according to the actual operational conditions. The analysis and simulation results show that the parameter provided by this work is the optimal value, and indicate that in different operational conditions, the coarse alignment algorithms adopted for FOG INS are different in order to achieve better performance. Lastly, the experiment results validate the effectiveness of the proposed algorithm.
Architectural elements of hybrid navigation systems for future space transportation
NASA Astrophysics Data System (ADS)
Trigo, Guilherme F.; Theil, Stephan
2018-06-01
The fundamental limitations of inertial navigation, currently employed by most launchers, have raised interest for GNSS-aided solutions. Combination of inertial measurements and GNSS outputs allows inertial calibration online, solving the issue of inertial drift. However, many challenges and design options unfold. In this work we analyse several architectural elements and design aspects of a hybrid GNSS/INS navigation system conceived for space transportation. The most fundamental architectural features such as coupling depth, modularity between filter and inertial propagation, and open-/closed-loop nature of the configuration, are discussed in the light of the envisaged application. Importance of the inertial propagation algorithm and sensor class in the overall system are investigated, being the handling of sensor errors and uncertainties that arise with lower grade sensory also considered. In terms of GNSS outputs we consider receiver solutions (position and velocity) and raw measurements (pseudorange, pseudorange-rate and time-difference carrier phase). Receiver clock error handling options and atmospheric error correction schemes for these measurements are analysed under flight conditions. System performance with different GNSS measurements is estimated through covariance analysis, being the differences between loose and tight coupling emphasized through partial outage simulation. Finally, we discuss options for filter algorithm robustness against non-linearities and system/measurement errors. A possible scheme for fault detection, isolation and recovery is also proposed.
Research on the error model of airborne celestial/inertial integrated navigation system
NASA Astrophysics Data System (ADS)
Zheng, Xiaoqiang; Deng, Xiaoguo; Yang, Xiaoxu; Dong, Qiang
2015-02-01
Celestial navigation subsystem of airborne celestial/inertial integrated navigation system periodically correct the positioning error and heading drift of the inertial navigation system, by which the inertial navigation system can greatly improve the accuracy of long-endurance navigation. Thus the navigation accuracy of airborne celestial navigation subsystem directly decides the accuracy of the integrated navigation system if it works for long time. By building the mathematical model of the airborne celestial navigation system based on the inertial navigation system, using the method of linear coordinate transformation, we establish the error transfer equation for the positioning algorithm of airborne celestial system. Based on these we built the positioning error model of the celestial navigation. And then, based on the positioning error model we analyze and simulate the positioning error which are caused by the error of the star tracking platform with the MATLAB software. Finally, the positioning error model is verified by the information of the star obtained from the optical measurement device in range and the device whose location are known. The analysis and simulation results show that the level accuracy and north accuracy of tracking platform are important factors that limit airborne celestial navigation systems to improve the positioning accuracy, and the positioning error have an approximate linear relationship with the level error and north error of tracking platform. The error of the verification results are in 1000m, which shows that the model is correct.
Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation
NASA Technical Reports Server (NTRS)
Karlgaard, Christopher D.; Kutty, Prasad; Schoenenberger, Mark
2015-01-01
This paper describes an algorithm for atmospheric state estimation that is based on a coupling between inertial navigation and flush air data sensing pressure measurements. In this approach, the full navigation state is used in the atmospheric estimation algorithm along with the pressure measurements and a model of the surface pressure distribution to directly estimate atmospheric winds and density using a nonlinear weighted least-squares algorithm. The approach uses a high fidelity model of atmosphere stored in table-look-up form, along with simplified models of that are propagated along the trajectory within the algorithm to provide prior estimates and covariances to aid the air data state solution. Thus, the method is essentially a reduced-order Kalman filter in which the inertial states are taken from the navigation solution and atmospheric states are estimated in the filter. The algorithm is applied to data from the Mars Science Laboratory entry, descent, and landing from August 2012. Reasonable estimates of the atmosphere and winds are produced by the algorithm. The observability of winds along the trajectory are examined using an index based on the discrete-time observability Gramian and the pressure measurement sensitivity matrix. The results indicate that bank reversals are responsible for adding information content to the system. The algorithm is then applied to the design of the pressure measurement system for the Mars 2020 mission. The pressure port layout is optimized to maximize the observability of atmospheric states along the trajectory. Linear covariance analysis is performed to assess estimator performance for a given pressure measurement uncertainty. The results indicate that the new tightly-coupled estimator can produce enhanced estimates of atmospheric states when compared with existing algorithms.
Vetrella, Amedeo Rodi; Fasano, Giancarmine; Accardo, Domenico; Moccia, Antonio
2016-01-01
Autonomous navigation of micro-UAVs is typically based on the integration of low cost Global Navigation Satellite System (GNSS) receivers and Micro-Electro-Mechanical Systems (MEMS)-based inertial and magnetic sensors to stabilize and control the flight. The resulting navigation performance in terms of position and attitude accuracy may not suffice for other mission needs, such as the ones relevant to fine sensor pointing. In this framework, this paper presents a cooperative UAV navigation algorithm that allows a chief vehicle, equipped with inertial and magnetic sensors, a Global Positioning System (GPS) receiver, and a vision system, to improve its navigation performance (in real time or in the post processing phase) exploiting formation flying deputy vehicles equipped with GPS receivers. The focus is set on outdoor environments and the key concept is to exploit differential GPS among vehicles and vision-based tracking (DGPS/Vision) to build a virtual additional navigation sensor whose information is then integrated in a sensor fusion algorithm based on an Extended Kalman Filter. The developed concept and processing architecture are described, with a focus on DGPS/Vision attitude determination algorithm. Performance assessment is carried out on the basis of both numerical simulations and flight tests. In the latter ones, navigation estimates derived from the DGPS/Vision approach are compared with those provided by the onboard autopilot system of a customized quadrotor. The analysis shows the potential of the developed approach, mainly deriving from the possibility to exploit magnetic- and inertial-independent accurate attitude information. PMID:27999318
Walking Distance Estimation Using Walking Canes with Inertial Sensors
Suh, Young Soo
2018-01-01
A walking distance estimation algorithm for cane users is proposed using an inertial sensor unit attached to various positions on the cane. A standard inertial navigation algorithm using an indirect Kalman filter was applied to update the velocity and position of the cane during movement. For quadripod canes, a standard zero-velocity measurement-updating method is proposed. For standard canes, a velocity-updating method based on an inverted pendulum model is proposed. The proposed algorithms were verified by three walking experiments with two different types of canes and different positions of the sensor module. PMID:29342971
Concept of AHRS Algorithm Designed for Platform Independent Imu Attitude Alignment
NASA Astrophysics Data System (ADS)
Tomaszewski, Dariusz; Rapiński, Jacek; Pelc-Mieczkowska, Renata
2017-12-01
Nowadays, along with the advancement of technology one can notice the rapid development of various types of navigation systems. So far the most popular satellite navigation, is now supported by positioning results calculated with use of other measurement system. The method and manner of integration will depend directly on the destination of system being developed. To increase the frequency of readings and improve the operation of outdoor navigation systems, one will support satellite navigation systems (GPS, GLONASS ect.) with inertial navigation. Such method of navigation consists of several steps. The first stage is the determination of initial orientation of inertial measurement unit, called INS alignment. During this process, on the basis of acceleration and the angular velocity readings, values of Euler angles (pitch, roll, yaw) are calculated allowing for unambiguous orientation of the sensor coordinate system relative to external coordinate system. The following study presents the concept of AHRS (Attitude and heading reference system) algorithm, allowing to define the Euler angles.The study were conducted with the use of readings from low-cost MEMS cell phone sensors. Subsequently the results of the study were analyzed to determine the accuracy of featured algorithm. On the basis of performed experiments the legitimacy of developed algorithm was stated.
Fusion of Low-Cost Imaging and Inertial Sensors for Navigation
2007-01-01
an Integrated GPS/MEMS Inertial Navigation Pack- age. In Proceedings of ION GNSS 2004, pp. 825–832, September 2004. [3] R. G. Brown and P. Y. Hwang ...track- ing, with no a priori knowledge is provided in [13]. An on- line (Extended Kalman Filter-based) method for calculat- ing a trajectory by tracking...transformation, effectively constraining the resulting correspondence search space. The algorithm was incorporated into an extended Kalman filter and
Improved artificial bee colony algorithm based gravity matching navigation method.
Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang
2014-07-18
Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position.
Improved Artificial Bee Colony Algorithm Based Gravity Matching Navigation Method
Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang
2014-01-01
Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position. PMID:25046019
Huang, Weiquan; Fang, Tao; Luo, Li; Zhao, Lin; Che, Fengzhu
2017-07-03
The grid strapdown inertial navigation system (SINS) used in polar navigation also includes three kinds of periodic oscillation errors as common SINS are based on a geographic coordinate system. Aiming ships which have the external information to conduct a system reset regularly, suppressing the Schuler periodic oscillation is an effective way to enhance navigation accuracy. The Kalman filter based on the grid SINS error model which applies to the ship is established in this paper. The errors of grid-level attitude angles can be accurately estimated when the external velocity contains constant error, and then correcting the errors of the grid-level attitude angles through feedback correction can effectively dampen the Schuler periodic oscillation. The simulation results show that with the aid of external reference velocity, the proposed external level damping algorithm based on the Kalman filter can suppress the Schuler periodic oscillation effectively. Compared with the traditional external level damping algorithm based on the damping network, the algorithm proposed in this paper can reduce the overshoot errors when the state of grid SINS is switched from the non-damping state to the damping state, and this effectively improves the navigation accuracy of the system.
Space Launch Systems Block 1B Preliminary Navigation System Design
NASA Technical Reports Server (NTRS)
Oliver, T. Emerson; Park, Thomas; Anzalone, Evan; Smith, Austin; Strickland, Dennis; Patrick, Sean
2018-01-01
NASA is currently building the Space Launch Systems (SLS) Block 1 launch vehicle for the Exploration Mission 1 (EM-1) test flight. In parallel, NASA is also designing the Block 1B launch vehicle. The Block 1B vehicle is an evolution of the Block 1 vehicle and extends the capability of the NASA launch vehicle. This evolution replaces the Interim Cryogenic Propulsive Stage (ICPS) with the Exploration Upper Stage (EUS). As the vehicle evolves to provide greater lift capability, increased robustness for manned missions, and the capability to execute more demanding missions so must the SLS Integrated Navigation System evolved to support those missions. This paper describes the preliminary navigation systems design for the SLS Block 1B vehicle. The evolution of the navigation hard-ware and algorithms from an inertial-only navigation system for Block 1 ascent flight to a tightly coupled GPS-aided inertial navigation system for Block 1B is described. The Block 1 GN&C system has been designed to meet a LEO insertion target with a specified accuracy. The Block 1B vehicle navigation system is de-signed to support the Block 1 LEO target accuracy as well as trans-lunar or trans-planetary injection accuracy. Additionally, the Block 1B vehicle is designed to support human exploration and thus is designed to minimize the probability of Loss of Crew (LOC) through high-quality inertial instruments and robust algorithm design, including Fault Detection, Isolation, and Recovery (FDIR) logic.
Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning
NASA Astrophysics Data System (ADS)
Evennou, Frédéric; Marx, François
2006-12-01
This paper presents an aided dead-reckoning navigation structure and signal processing algorithms for self localization of an autonomous mobile device by fusing pedestrian dead reckoning and WiFi signal strength measurements. WiFi and inertial navigation systems (INS) are used for positioning and attitude determination in a wide range of applications. Over the last few years, a number of low-cost inertial sensors have become available. Although they exhibit large errors, WiFi measurements can be used to correct the drift weakening the navigation based on this technology. On the other hand, INS sensors can interact with the WiFi positioning system as they provide high-accuracy real-time navigation. A structure based on a Kalman filter and a particle filter is proposed. It fuses the heterogeneous information coming from those two independent technologies. Finally, the benefits of the proposed architecture are evaluated and compared with the pure WiFi and INS positioning systems.
Landmark-Based Drift Compensation Algorithm for Inertial Pedestrian Navigation
Munoz Diaz, Estefania; Caamano, Maria; Fuentes Sánchez, Francisco Javier
2017-01-01
The navigation of pedestrians based on inertial sensors, i.e., accelerometers and gyroscopes, has experienced a great growth over the last years. However, the noise of medium- and low-cost sensors causes a high error in the orientation estimation, particularly in the yaw angle. This error, called drift, is due to the bias of the z-axis gyroscope and other slow changing errors, such as temperature variations. We propose a seamless landmark-based drift compensation algorithm that only uses inertial measurements. The proposed algorithm adds a great value to the state of the art, because the vast majority of the drift elimination algorithms apply corrections to the estimated position, but not to the yaw angle estimation. Instead, the presented algorithm computes the drift value and uses it to prevent yaw errors and therefore position errors. In order to achieve this goal, a detector of landmarks, i.e., corners and stairs, and an association algorithm have been developed. The results of the experiments show that it is possible to reliably detect corners and stairs using only inertial measurements eliminating the need that the user takes any action, e.g., pressing a button. Associations between re-visited landmarks are successfully made taking into account the uncertainty of the position. After that, the drift is computed out of all associations and used during a post-processing stage to obtain a low-drifted yaw angle estimation, that leads to successfully drift compensated trajectories. The proposed algorithm has been tested with quasi-error-free turn rate measurements introducing known biases and with medium-cost gyroscopes in 3D indoor and outdoor scenarios. PMID:28671622
Przemyslaw, Baranski; Pawel, Strumillo
2012-01-01
The paper presents an algorithm for estimating a pedestrian location in an urban environment. The algorithm is based on the particle filter and uses different data sources: a GPS receiver, inertial sensors, probability maps and a stereo camera. Inertial sensors are used to estimate a relative displacement of a pedestrian. A gyroscope estimates a change in the heading direction. An accelerometer is used to count a pedestrian's steps and their lengths. The so-called probability maps help to limit GPS inaccuracy by imposing constraints on pedestrian kinematics, e.g., it is assumed that a pedestrian cannot cross buildings, fences etc. This limits position inaccuracy to ca. 10 m. Incorporation of depth estimates derived from a stereo camera that are compared to the 3D model of an environment has enabled further reduction of positioning errors. As a result, for 90% of the time, the algorithm is able to estimate a pedestrian location with an error smaller than 2 m, compared to an error of 6.5 m for a navigation based solely on GPS. PMID:22969321
6DOF Testing of the SLS Inertial Navigation Unit
NASA Technical Reports Server (NTRS)
Geohagan, Kevin W.; Bernard, William P.; Oliver, T. Emerson; Strickland, Dennis J.; Leggett, Jared O.
2018-01-01
The Navigation System on the NASA Space Launch System (SLS) Block 1 vehicle performs initial alignment of the Inertial Navigation System (INS) navigation frame through gyrocompass alignment (GCA). In lieu of direct testing of GCA accuracy in support of requirement verification, the SLS Navigation Team proposed and conducted an engineering test to, among other things, validate the GCA performance and overall behavior of the SLS INS model through comparison with test data. This paper will detail dynamic hardware testing of the SLS INS, conducted by the SLS Navigation Team at Marshall Space Flight Center's 6DOF Table Facility, in support of GCA performance characterization and INS model validation. A 6-DOF motion platform was used to produce 6DOF pad twist and sway dynamics while a simulated SLS flight computer communicated with the INS. Tests conducted include an evaluation of GCA algorithm robustness to increasingly dynamic pad environments, an examination of GCA algorithm stability and accuracy over long durations, and a long-duration static test to gather enough data for Allan Variance analysis. Test setup, execution, and data analysis will be discussed, including analysis performed in support of SLS INS model validation.
Huang, Haoqian; Chen, Xiyuan; Zhang, Bo; Wang, Jian
2017-01-01
The underwater navigation system, mainly consisting of MEMS inertial sensors, is a key technology for the wide application of underwater gliders and plays an important role in achieving high accuracy navigation and positioning for a long time of period. However, the navigation errors will accumulate over time because of the inherent errors of inertial sensors, especially for MEMS grade IMU (Inertial Measurement Unit) generally used in gliders. The dead reckoning module is added to compensate the errors. In the complicated underwater environment, the performance of MEMS sensors is degraded sharply and the errors will become much larger. It is difficult to establish the accurate and fixed error model for the inertial sensor. Therefore, it is very hard to improve the accuracy of navigation information calculated by sensors. In order to solve the problem mentioned, the more suitable filter which integrates the multi-model method with an EKF approach can be designed according to different error models to give the optimal estimation for the state. The key parameters of error models can be used to determine the corresponding filter. The Adams explicit formula which has an advantage of high precision prediction is simultaneously fused into the above filter to achieve the much more improvement in attitudes estimation accuracy. The proposed algorithm has been proved through theory analyses and has been tested by both vehicle experiments and lake trials. Results show that the proposed method has better accuracy and effectiveness in terms of attitudes estimation compared with other methods mentioned in the paper for inertial navigation applied to underwater gliders. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Enhanced Pedestrian Navigation Based on Course Angle Error Estimation Using Cascaded Kalman Filters
Park, Chan Gook
2018-01-01
An enhanced pedestrian dead reckoning (PDR) based navigation algorithm, which uses two cascaded Kalman filters (TCKF) for the estimation of course angle and navigation errors, is proposed. The proposed algorithm uses a foot-mounted inertial measurement unit (IMU), waist-mounted magnetic sensors, and a zero velocity update (ZUPT) based inertial navigation technique with TCKF. The first stage filter estimates the course angle error of a human, which is closely related to the heading error of the IMU. In order to obtain the course measurements, the filter uses magnetic sensors and a position-trace based course angle. For preventing magnetic disturbance from contaminating the estimation, the magnetic sensors are attached to the waistband. Because the course angle error is mainly due to the heading error of the IMU, and the characteristic error of the heading angle is highly dependent on that of the course angle, the estimated course angle error is used as a measurement for estimating the heading error in the second stage filter. At the second stage, an inertial navigation system-extended Kalman filter-ZUPT (INS-EKF-ZUPT) method is adopted. As the heading error is estimated directly by using course-angle error measurements, the estimation accuracy for the heading and yaw gyro bias can be enhanced, compared with the ZUPT-only case, which eventually enhances the position accuracy more efficiently. The performance enhancements are verified via experiments, and the way-point position error for the proposed method is compared with those for the ZUPT-only case and with other cases that use ZUPT and various types of magnetic heading measurements. The results show that the position errors are reduced by a maximum of 90% compared with the conventional ZUPT based PDR algorithms. PMID:29690539
Gao, Wei; Zhang, Ya; Wang, Jianguo
2014-01-01
The integrated navigation system with strapdown inertial navigation system (SINS), Beidou (BD) receiver and Doppler velocity log (DVL) can be used in marine applications owing to the fact that the redundant and complementary information from different sensors can markedly improve the system accuracy. However, the existence of multisensor asynchrony will introduce errors into the system. In order to deal with the problem, conventionally the sampling interval is subdivided, which increases the computational complexity. In this paper, an innovative integrated navigation algorithm based on a Cubature Kalman filter (CKF) is proposed correspondingly. A nonlinear system model and observation model for the SINS/BD/DVL integrated system are established to more accurately describe the system. By taking multi-sensor asynchronization into account, a new sampling principle is proposed to make the best use of each sensor's information. Further, CKF is introduced in this new algorithm to enable the improvement of the filtering accuracy. The performance of this new algorithm has been examined through numerical simulations. The results have shown that the positional error can be effectively reduced with the new integrated navigation algorithm. Compared with the traditional algorithm based on EKF, the accuracy of the SINS/BD/DVL integrated navigation system is improved, making the proposed nonlinear integrated navigation algorithm feasible and efficient. PMID:24434842
Swarm Optimization-Based Magnetometer Calibration for Personal Handheld Devices
Ali, Abdelrahman; Siddharth, Siddharth; Syed, Zainab; El-Sheimy, Naser
2012-01-01
Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a processor that generates position and orientation solutions by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are usually corrupted by several errors, including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO)-based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometers. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. Furthermore, the proposed algorithm can help in the development of Pedestrian Navigation Devices (PNDs) when combined with inertial sensors and GPS/Wi-Fi for indoor navigation and Location Based Services (LBS) applications.
Jiang, Weiping; Wang, Li; Niu, Xiaoji; Zhang, Quan; Zhang, Hui; Tang, Min; Hu, Xiangyun
2014-01-01
A high-precision image-aided inertial navigation system (INS) is proposed as an alternative to the carrier-phase-based differential Global Navigation Satellite Systems (CDGNSSs) when satellite-based navigation systems are unavailable. In this paper, the image/INS integrated algorithm is modeled by a tightly-coupled iterative extended Kalman filter (IEKF). Tightly-coupled integration ensures that the integrated system is reliable, even if few known feature points (i.e., less than three) are observed in the images. A new global observability analysis of this tightly-coupled integration is presented to guarantee that the system is observable under the necessary conditions. The analysis conclusions were verified by simulations and field tests. The field tests also indicate that high-precision position (centimeter-level) and attitude (half-degree-level)-integrated solutions can be achieved in a global reference. PMID:25330046
NASA Astrophysics Data System (ADS)
Bu, Yanlong; Zhang, Qiang; Ding, Chibiao; Tang, Geshi; Wang, Hang; Qiu, Rujin; Liang, Libo; Yin, Hejun
2017-02-01
This paper presents an interplanetary optical navigation algorithm based on two spherical celestial bodies. The remarkable characteristic of the method is that key navigation parameters can be estimated depending entirely on known sizes and ephemerides of two celestial bodies, especially positioning is realized through a single image and does not rely on traditional terrestrial radio tracking any more. Actual Earth-Moon group photos captured by China's Chang'e-5T1 probe were used to verify the effectiveness of the algorithm. From 430,000 km away from the Earth, the camera pointing accuracy reaches 0.01° (one sigma) and the inertial positioning error is less than 200 km, respectively; meanwhile, the cost of the ground control and human resources are greatly reduced. The algorithm is flexible, easy to implement, and can provide reference to interplanetary autonomous navigation in the solar system.
Navigation strategy and filter design for solar electric missions
NASA Technical Reports Server (NTRS)
Tapley, B. D.; Hagar, H., Jr.
1972-01-01
Methods which have been proposed to improve the navigation accuracy for the low-thrust space vehicle include modifications to the standard Sequential- and Batch-type orbit determination procedures and the use of inertial measuring units (IMU) which measures directly the acceleration applied to the vehicle. The navigation accuracy obtained using one of the more promising modifications to the orbit determination procedures is compared with a combined IMU-Standard. The unknown accelerations are approximated as both first-order and second-order Gauss-Markov processes. The comparison is based on numerical results obtained in a study of the navigation requirements of a numerically simulated 152-day low-thrust mission to the asteroid Eros. The results obtained in the simulation indicate that the DMC algorithm will yield a significant improvement over the navigation accuracies achieved with previous estimation algorithms. In addition, the DMC algorithms will yield better navigation accuracies than the IMU-Standard Orbit Determination algorithm, except for extremely precise IMU measurements, i.e., gyroplatform alignment .01 deg and accelerometer signal-to-noise ratio .07. Unless these accuracies are achieved, the IMU navigation accuracies are generally unacceptable.
NASA Astrophysics Data System (ADS)
Sun, Wei; Ding, Wei; Yan, Huifang; Duan, Shunli
2018-06-01
Shoe-mounted pedestrian navigation systems based on micro inertial sensors rely on zero velocity updates to correct their positioning errors in time, which effectively makes determining the zero velocity interval play a key role during normal walking. However, as walking gaits are complicated, and vary from person to person, it is difficult to detect walking gaits with a fixed threshold method. This paper proposes a pedestrian gait classification method based on a hidden Markov model. Pedestrian gait data are collected with a micro inertial measurement unit installed at the instep. On the basis of analyzing the characteristics of the pedestrian walk, a single direction angular rate gyro output is used to classify gait features. The angular rate data are modeled into a univariate Gaussian mixture model with three components, and a four-state left–right continuous hidden Markov model (CHMM) is designed to classify the normal walking gait. The model parameters are trained and optimized using the Baum–Welch algorithm and then the sliding window Viterbi algorithm is used to decode the gait. Walking data are collected through eight subjects walking along the same route at three different speeds; the leave-one-subject-out cross validation method is conducted to test the model. Experimental results show that the proposed algorithm can accurately detect different walking gaits of zero velocity interval. The location experiment shows that the precision of CHMM-based pedestrian navigation improved by 40% when compared to the angular rate threshold method.
A Polar Initial Alignment Algorithm for Unmanned Underwater Vehicles
Yan, Zheping; Wang, Lu; Wang, Tongda; Zhang, Honghan; Zhang, Xun; Liu, Xiangling
2017-01-01
Due to its highly autonomy, the strapdown inertial navigation system (SINS) is widely used in unmanned underwater vehicles (UUV) navigation. Initial alignment is crucial because the initial alignment results will be used as the initial SINS value, which might affect the subsequent SINS results. Due to the rapid convergence of Earth meridians, there is a calculation overflow in conventional initial alignment algorithms, making conventional initial algorithms are invalid for polar UUV navigation. To overcome these problems, a polar initial alignment algorithm for UUV is proposed in this paper, which consists of coarse and fine alignment algorithms. Based on the principle of the conical slow drift of gravity, the coarse alignment algorithm is derived under the grid frame. By choosing the velocity and attitude as the measurement, the fine alignment with the Kalman filter (KF) is derived under the grid frame. Simulation and experiment are realized among polar, conventional and transversal initial alignment algorithms for polar UUV navigation. Results demonstrate that the proposed polar initial alignment algorithm can complete the initial alignment of UUV in the polar region rapidly and accurately. PMID:29168735
6DOF Testing of the SLS Inertial Navigation Unit
NASA Technical Reports Server (NTRS)
Geohagan, Kevin; Bernard, Bill; Oliver, T. Emerson; Leggett, Jared; Strickland, Dennis
2018-01-01
The Navigation System on the NASA Space Launch System (SLS) Block 1 vehicle performs initial alignment of the Inertial Navigation System (INS) navigation frame through gyrocompass alignment (GCA). Because the navigation architecture for the SLS Block 1 vehicle is a purely inertial system, the accuracy of the achieved orbit relative to mission requirements is very sensitive to initial alignment accuracy. The assessment of this sensitivity and many others via simulation is a part of the SLS Model-Based Design and Model-Based Requirements approach. As a part of the aforementioned, 6DOF Monte Carlo simulation is used in large part to develop and demonstrate verification of program requirements. To facilitate this and the GN&C flight software design process, an SLS-Program-controlled Design Math Model (DMM) of the SLS INS was developed by the SLS Navigation Team. The SLS INS model implements all of the key functions of the hardware-namely, GCA, inertial navigation, and FDIR (Fault Detection, Isolation, and Recovery)-in support of SLS GN&C design requirements verification. Despite the strong sensitivity to initial alignment, GCA accuracy requirements were not verified by test due to program cost and schedule constraints. Instead, the system relies upon assessments performed using the SLS INS model. In order to verify SLS program requirements by analysis, the SLS INS model is verified and validated against flight hardware. In lieu of direct testing of GCA accuracy in support of requirement verification, the SLS Navigation Team proposed and conducted an engineering test to, among other things, validate the GCA performance and overall behavior of the SLS INS model through comparison with test data. This paper will detail dynamic hardware testing of the SLS INS, conducted by the SLS Navigation Team at Marshall Space Flight Center's 6DOF Table Facility, in support of GCA performance characterization and INS model validation. A 6-DOF motion platform was used to produce 6DOF pad twist and sway dynamics while a simulated SLS flight computer communicated with the INS. Tests conducted include an evaluation of GCA algorithm robustness to increasingly dynamic pad environments, an examination of GCA algorithm stability and accuracy over long durations, and a long-duration static test to gather enough data for Allan Variance analysis. Test setup, execution, and data analysis will be discussed, including analysis performed in support of SLS INS model validation.
A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation
Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao
2016-01-01
The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms. PMID:27999361
A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation.
Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao
2016-12-19
The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms.
A Novel Grid SINS/DVL Integrated Navigation Algorithm for Marine Application
Kang, Yingyao; Zhao, Lin; Cheng, Jianhua; Fan, Xiaoliang
2018-01-01
Integrated navigation algorithms under the grid frame have been proposed based on the Kalman filter (KF) to solve the problem of navigation in some special regions. However, in the existing study of grid strapdown inertial navigation system (SINS)/Doppler velocity log (DVL) integrated navigation algorithms, the Earth models of the filter dynamic model and the SINS mechanization are not unified. Besides, traditional integrated systems with the KF based correction scheme are susceptible to measurement errors, which would decrease the accuracy and robustness of the system. In this paper, an adaptive robust Kalman filter (ARKF) based hybrid-correction grid SINS/DVL integrated navigation algorithm is designed with the unified reference ellipsoid Earth model to improve the navigation accuracy in middle-high latitude regions for marine application. Firstly, to unify the Earth models, the mechanization of grid SINS is introduced and the error equations are derived based on the same reference ellipsoid Earth model. Then, a more accurate grid SINS/DVL filter model is designed according to the new error equations. Finally, a hybrid-correction scheme based on the ARKF is proposed to resist the effect of measurement errors. Simulation and experiment results show that, compared with the traditional algorithms, the proposed navigation algorithm can effectively improve the navigation performance in middle-high latitude regions by the unified Earth models and the ARKF based hybrid-correction scheme. PMID:29373549
Yan, Zheping; Wang, Lu; Wang, Tongda; Yang, Zewen; Chen, Tao; Xu, Jian
2018-03-30
To solve the navigation accuracy problems of multi-Unmanned Underwater Vehicles (multi-UUVs) in the polar region, a polar cooperative navigation algorithm for multi-UUVs considering communication delays is proposed in this paper. UUVs are important pieces of equipment in ocean engineering for marine development. For UUVs to complete missions, precise navigation is necessary. It is difficult for UUVs to establish true headings because of the rapid convergence of Earth meridians and the severe polar environment. Based on the polar grid navigation algorithm, UUV navigation in the polar region can be accomplished with the Strapdown Inertial Navigation System (SINS) in the grid frame. To save costs, a leader-follower type of system is introduced in this paper. The leader UUV helps the follower UUVs to achieve high navigation accuracy. Follower UUVs correct their own states based on the information sent by the leader UUV and the relative position measured by ultra-short baseline (USBL) acoustic positioning. The underwater acoustic communication delay is quantized by the model. In this paper, considering underwater acoustic communication delay, the conventional adaptive Kalman filter (AKF) is modified to adapt to polar cooperative navigation. The results demonstrate that the polar cooperative navigation algorithm for multi-UUVs that considers communication delays can effectively navigate the sailing of multi-UUVs in the polar region.
Yan, Zheping; Wang, Lu; Wang, Tongda; Yang, Zewen; Chen, Tao; Xu, Jian
2018-01-01
To solve the navigation accuracy problems of multi-Unmanned Underwater Vehicles (multi-UUVs) in the polar region, a polar cooperative navigation algorithm for multi-UUVs considering communication delays is proposed in this paper. UUVs are important pieces of equipment in ocean engineering for marine development. For UUVs to complete missions, precise navigation is necessary. It is difficult for UUVs to establish true headings because of the rapid convergence of Earth meridians and the severe polar environment. Based on the polar grid navigation algorithm, UUV navigation in the polar region can be accomplished with the Strapdown Inertial Navigation System (SINS) in the grid frame. To save costs, a leader-follower type of system is introduced in this paper. The leader UUV helps the follower UUVs to achieve high navigation accuracy. Follower UUVs correct their own states based on the information sent by the leader UUV and the relative position measured by ultra-short baseline (USBL) acoustic positioning. The underwater acoustic communication delay is quantized by the model. In this paper, considering underwater acoustic communication delay, the conventional adaptive Kalman filter (AKF) is modified to adapt to polar cooperative navigation. The results demonstrate that the polar cooperative navigation algorithm for multi-UUVs that considers communication delays can effectively navigate the sailing of multi-UUVs in the polar region. PMID:29601537
Initial Alignment for SINS Based on Pseudo-Earth Frame in Polar Regions.
Gao, Yanbin; Liu, Meng; Li, Guangchun; Guang, Xingxing
2017-06-16
An accurate initial alignment must be required for inertial navigation system (INS). The performance of initial alignment directly affects the following navigation accuracy. However, the rapid convergence of meridians and the small horizontalcomponent of rotation of Earth make the traditional alignment methods ineffective in polar regions. In this paper, from the perspective of global inertial navigation, a novel alignment algorithm based on pseudo-Earth frame and backward process is proposed to implement the initial alignment in polar regions. Considering that an accurate coarse alignment of azimuth is difficult to obtain in polar regions, the dynamic error modeling with large azimuth misalignment angle is designed. At the end of alignment phase, the strapdown attitude matrix relative to local geographic frame is obtained without influence of position errors and cumbersome computation. As a result, it would be more convenient to access the following polar navigation system. Then, it is also expected to unify the polar alignment algorithm as much as possible, thereby further unifying the form of external reference information. Finally, semi-physical static simulation and in-motion tests with large azimuth misalignment angle assisted by unscented Kalman filter (UKF) validate the effectiveness of the proposed method.
2016-12-01
based complementary filter developed at the Naval Postgraduate School, is developed. The performance of a consumer-grade nine-degrees-of-freedom IMU...measurement unit, complementary filter , gait phase detection, zero velocity update, MEMS, IMU, AHRS, GPS denied, distributed sensor, virtual sensor...algorithm and quaternion-based complementary filter developed at the Naval Postgraduate School, is developed. The performance of a consumer-grade nine
NASA Astrophysics Data System (ADS)
Liu, Zengjun; Wang, Lei; Li, Kui; Gao, Jiaxin
2017-05-01
Hybrid inertial navigation system (HINS) is a new kind of inertial navigation system (INS), which combines advantages of platform INS, strap-down INS and rotational INS. HINS has a physical platform to isolate the angular motion as platform INS does, HINS also uses strap-down attitude algorithms and applies rotation modulation technique. Tri-axis HINS has three gimbals to isolate the angular motion in the dynamic base, in which way the system can reduce the effects of angular motion and improve the positioning precision. However, the angular motion will affect the compensation of some error parameters, especially for the lever arm effect. The lever arm effect caused by position errors between the accelerometers and rotation center cannot be ignored due to the rapid rotation of inertial measurement unit (IMU) and it will cause fluctuation and stage in velocity in HINS. The influences of angular motion on the lever arm effect compensation are analyzed firstly in this paper, and then the compensation method of lever arm effect based on the photoelectric encoders in dynamic base is proposed. Results of experiments on turntable show that after compensation, the fluctuations and stages in velocity curve disappear.
FPGA-based real-time embedded system for RISS/GPS integrated navigation.
Abdelfatah, Walid Farid; Georgy, Jacques; Iqbal, Umar; Noureldin, Aboelmagd
2012-01-01
Navigation algorithms integrating measurements from multi-sensor systems overcome the problems that arise from using GPS navigation systems in standalone mode. Algorithms which integrate the data from 2D low-cost reduced inertial sensor system (RISS), consisting of a gyroscope and an odometer or wheel encoders, along with a GPS receiver via a Kalman filter has proved to be worthy in providing a consistent and more reliable navigation solution compared to standalone GPS receivers. It has been also shown to be beneficial, especially in GPS-denied environments such as urban canyons and tunnels. The main objective of this paper is to narrow the idea-to-implementation gap that follows the algorithm development by realizing a low-cost real-time embedded navigation system capable of computing the data-fused positioning solution. The role of the developed system is to synchronize the measurements from the three sensors, relative to the pulse per second signal generated from the GPS, after which the navigation algorithm is applied to the synchronized measurements to compute the navigation solution in real-time. Employing a customizable soft-core processor on an FPGA in the kernel of the navigation system, provided the flexibility for communicating with the various sensors and the computation capability required by the Kalman filter integration algorithm.
FPGA-Based Real-Time Embedded System for RISS/GPS Integrated Navigation
Abdelfatah, Walid Farid; Georgy, Jacques; Iqbal, Umar; Noureldin, Aboelmagd
2012-01-01
Navigation algorithms integrating measurements from multi-sensor systems overcome the problems that arise from using GPS navigation systems in standalone mode. Algorithms which integrate the data from 2D low-cost reduced inertial sensor system (RISS), consisting of a gyroscope and an odometer or wheel encoders, along with a GPS receiver via a Kalman filter has proved to be worthy in providing a consistent and more reliable navigation solution compared to standalone GPS receivers. It has been also shown to be beneficial, especially in GPS-denied environments such as urban canyons and tunnels. The main objective of this paper is to narrow the idea-to-implementation gap that follows the algorithm development by realizing a low-cost real-time embedded navigation system capable of computing the data-fused positioning solution. The role of the developed system is to synchronize the measurements from the three sensors, relative to the pulse per second signal generated from the GPS, after which the navigation algorithm is applied to the synchronized measurements to compute the navigation solution in real-time. Employing a customizable soft-core processor on an FPGA in the kernel of the navigation system, provided the flexibility for communicating with the various sensors and the computation capability required by the Kalman filter integration algorithm. PMID:22368460
Multiple nodes transfer alignment for airborne missiles based on inertial sensor network
NASA Astrophysics Data System (ADS)
Si, Fan; Zhao, Yan
2017-09-01
Transfer alignment is an important initialization method for airborne missiles because the alignment accuracy largely determines the performance of the missile. However, traditional alignment methods are limited by complicated and unknown flexure angle, and cannot meet the actual requirement when wing flexure deformation occurs. To address this problem, we propose a new method that uses the relative navigation parameters between the weapons and fighter to achieve transfer alignment. First, in the relative inertial navigation algorithm, the relative attitudes and positions are constantly computed in wing flexure deformation situations. Secondly, the alignment results of each weapon are processed using a data fusion algorithm to improve the overall performance. Finally, the feasibility and performance of the proposed method were evaluated under two typical types of deformation, and the simulation results demonstrated that the new transfer alignment method is practical and has high-precision.
Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1
NASA Technical Reports Server (NTRS)
Park, Thomas; Oliver, Emerson; Smith, Austin
2018-01-01
The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GN&C software from the set of healthy measurements. This paper provides an overview of the algorithms used for both fault-detection and measurement down selection.
Automated Point Cloud Correspondence Detection for Underwater Mapping Using AUVs
NASA Technical Reports Server (NTRS)
Hammond, Marcus; Clark, Ashley; Mahajan, Aditya; Sharma, Sumant; Rock, Stephen
2015-01-01
An algorithm for automating correspondence detection between point clouds composed of multibeam sonar data is presented. This allows accurate initialization for point cloud alignment techniques even in cases where accurate inertial navigation is not available, such as iceberg profiling or vehicles with low-grade inertial navigation systems. Techniques from computer vision literature are used to extract, label, and match keypoints between "pseudo-images" generated from these point clouds. Image matches are refined using RANSAC and information about the vehicle trajectory. The resulting correspondences can be used to initialize an iterative closest point (ICP) registration algorithm to estimate accumulated navigation error and aid in the creation of accurate, self-consistent maps. The results presented use multibeam sonar data obtained from multiple overlapping passes of an underwater canyon in Monterey Bay, California. Using strict matching criteria, the method detects 23 between-swath correspondence events in a set of 155 pseudo-images with zero false positives. Using less conservative matching criteria doubles the number of matches but introduces several false positive matches as well. Heuristics based on known vehicle trajectory information are used to eliminate these.
Free-Inertial and Damped-Inertial Navigation Mechanization and Error Equations
1975-04-18
AD-A014 356 FREE-INERTIAL AND DAMPED-INERTIAL NAVIGATION MECHANIZATION AND ERROR EQUATIONS Warren G. Heller Analytic Sciences Corporation Prepared...IHI IL JI -J THE ANALYTIC SCIENCES CORPORATION TR-312-1-1 FREE-INERTIAL AND DAMPED-INERTIAL NAViGATION MECHANIZATION AND ERROR EQUATIONS Ap~ril 18...PERIOO COVC/REO Fr-,- 1wer l and Dmped-Inertial Navigation Technical Mechanization and Error Equations 8/20-73 - 8/20/74 S. PjLtFORJ4djNjOjO, REPORT
Underwater terrain-aided navigation system based on combination matching algorithm.
Li, Peijuan; Sheng, Guoliang; Zhang, Xiaofei; Wu, Jingqiu; Xu, Baochun; Liu, Xing; Zhang, Yao
2018-07-01
Considering that the terrain-aided navigation (TAN) system based on iterated closest contour point (ICCP) algorithm diverges easily when the indicative track of strapdown inertial navigation system (SINS) is large, Kalman filter is adopted in the traditional ICCP algorithm, difference between matching result and SINS output is used as the measurement of Kalman filter, then the cumulative error of the SINS is corrected in time by filter feedback correction, and the indicative track used in ICCP is improved. The mathematic model of the autonomous underwater vehicle (AUV) integrated into the navigation system and the observation model of TAN is built. Proper matching point number is designated by comparing the simulation results of matching time and matching precision. Simulation experiments are carried out according to the ICCP algorithm and the mathematic model. It can be concluded from the simulation experiments that the navigation accuracy and stability are improved with the proposed combinational algorithm in case that proper matching point number is engaged. It will be shown that the integrated navigation system is effective in prohibiting the divergence of the indicative track and can meet the requirements of underwater, long-term and high precision of the navigation system for autonomous underwater vehicles. Copyright © 2017. Published by Elsevier Ltd.
Flight evaluation of differential GPS aided inertial navigation systems
NASA Technical Reports Server (NTRS)
Mcnally, B. David; Paielli, Russell A.; Bach, Ralph E., Jr.; Warner, David N., Jr.
1992-01-01
Algorithms are described for integration of Differential Global Positioning System (DGPS) data with Inertial Navigation System (INS) data to provide an integrated DGPS/INS navigation system. The objective is to establish the benefits that can be achieved through various levels of integration of DGPS with INS for precision navigation. An eight state Kalman filter integration was implemented in real-time on a twin turbo-prop transport aircraft to evaluate system performance during terminal approach and landing operations. A fully integrated DGPS/INS system is also presented which models accelerometer and rate-gyro measurement errors plus position, velocity, and attitude errors. The fully integrated system was implemented off-line using range-domain (seventeen-state) and position domain (fifteen-state) Kalman filters. Both filter integration approaches were evaluated using data collected during the flight test. Flight-test data consisted of measurements from a 5 channel Precision Code GPS receiver, a strap-down Inertial Navigation Unit (INU), and GPS satellite differential range corrections from a ground reference station. The aircraft was laser tracked to determine its true position. Results indicate that there is no significant improvement in positioning accuracy with the higher levels of DGPS/INS integration. All three systems provided high-frequency (e.g., 20 Hz) estimates of position and velocity. The fully integrated system provided estimates of inertial sensor errors which may be used to improve INS navigation accuracy should GPS become unavailable, and improved estimates of acceleration, attitude, and body rates which can be used for guidance and control. Precision Code DGPS/INS positioning accuracy (root-mean-square) was 1.0 m cross-track and 3.0 m vertical. (This AGARDograph was sponsored by the Guidance and Control Panel.)
NASA Technical Reports Server (NTRS)
Bryant, W. H.; Morrell, F. R.
1981-01-01
An experimental redundant strapdown inertial measurement unit (RSDIMU) is developed as a link to satisfy safety and reliability considerations in the integrated avionics concept. The unit includes four two degree-of-freedom tuned rotor gyros, and four accelerometers in a skewed and separable semioctahedral array. These sensors are coupled to four microprocessors which compensate sensor errors. These microprocessors are interfaced with two flight computers which process failure detection, isolation, redundancy management, and general flight control/navigation algorithms. Since the RSDIMU is a developmental unit, it is imperative that the flight computers provide special visibility and facility in algorithm modification.
Tightly Integrating Optical And Inertial Sensors For Navigation Using The UKF
2008-03-01
832. September 2004. 3. Brown , Robert Grover and Patrick Y.C. Hwang . Introduction to Random Signals and Applied Kalman Filtering. John Wiley and Sons...effectiveness of fusing imaging and inertial sensors using an Extended Kalman Filter (EKF) algorithm has been shown in previous research efforts. In this...model assumed by the EKF. In order to cope with divergence problem, the Unscented (Sigma-Point) Kalman Filter (UKF) has been proposed in the literature in
An adaptive deep-coupled GNSS/INS navigation system with hybrid pre-filter processing
NASA Astrophysics Data System (ADS)
Wu, Mouyan; Ding, Jicheng; Zhao, Lin; Kang, Yingyao; Luo, Zhibin
2018-02-01
The deep-coupling of a global navigation satellite system (GNSS) with an inertial navigation system (INS) can provide accurate and reliable navigation information. There are several kinds of deeply-coupled structures. These can be divided mainly into coherent and non-coherent pre-filter based structures, which have their own strong advantages and disadvantages, especially in accuracy and robustness. In this paper, the existing pre-filters of the deeply-coupled structures are analyzed and modified to improve them firstly. Then, an adaptive GNSS/INS deeply-coupled algorithm with hybrid pre-filters processing is proposed to combine the advantages of coherent and non-coherent structures. An adaptive hysteresis controller is designed to implement the hybrid pre-filters processing strategy. The simulation and vehicle test results show that the adaptive deeply-coupled algorithm with hybrid pre-filters processing can effectively improve navigation accuracy and robustness, especially in a GNSS-challenged environment.
Benefits of combined GPS/GLONASS with low-cost MEMS IMUs for vehicular urban navigation.
Angrisano, Antonio; Petovello, Mark; Pugliano, Giovanni
2012-01-01
The integration of Global Navigation Satellite Systems (GNSS) with Inertial Navigation Systems (INS) has been very actively researched for many years due to the complementary nature of the two systems. In particular, during the last few years the integration with micro-electromechanical system (MEMS) inertial measurement units (IMUs) has been investigated. In fact, recent advances in MEMS technology have made possible the development of a new generation of low cost inertial sensors characterized by small size and light weight, which represents an attractive option for mass-market applications such as vehicular and pedestrian navigation. However, whereas there has been much interest in the integration of GPS with a MEMS-based INS, few research studies have been conducted on expanding this application to the revitalized GLONASS system. This paper looks at the benefits of adding GLONASS to existing GPS/INS(MEMS) systems using loose and tight integration strategies. The relative benefits of various constraints are also assessed. Results show that when satellite visibility is poor (approximately 50% solution availability) the benefits of GLONASS are only seen with tight integration algorithms. For more benign environments, a loosely coupled GPS/GLONASS/INS system offers performance comparable to that of a tightly coupled GPS/INS system, but with reduced complexity and development time.
Accuracy Enhancement of Inertial Sensors Utilizing High Resolution Spectral Analysis
Noureldin, Aboelmagd; Armstrong, Justin; El-Shafie, Ahmed; Karamat, Tashfeen; McGaughey, Don; Korenberg, Michael; Hussain, Aini
2012-01-01
In both military and civilian applications, the inertial navigation system (INS) and the global positioning system (GPS) are two complementary technologies that can be integrated to provide reliable positioning and navigation information for land vehicles. The accuracy enhancement of INS sensors and the integration of INS with GPS are the subjects of widespread research. Wavelet de-noising of INS sensors has had limited success in removing the long-term (low-frequency) inertial sensor errors. The primary objective of this research is to develop a novel inertial sensor accuracy enhancement technique that can remove both short-term and long-term error components from inertial sensor measurements prior to INS mechanization and INS/GPS integration. A high resolution spectral analysis technique called the fast orthogonal search (FOS) algorithm is used to accurately model the low frequency range of the spectrum, which includes the vehicle motion dynamics and inertial sensor errors. FOS models the spectral components with the most energy first and uses an adaptive threshold to stop adding frequency terms when fitting a term does not reduce the mean squared error more than fitting white noise. The proposed method was developed, tested and validated through road test experiments involving both low-end tactical grade and low cost MEMS-based inertial systems. The results demonstrate that in most cases the position accuracy during GPS outages using FOS de-noised data is superior to the position accuracy using wavelet de-noising.
Wei, Wenhui; Gao, Zhaohui; Gao, Shesheng; Jia, Ke
2018-04-09
In order to meet the requirements of autonomy and reliability for the navigation system, combined with the method of measuring speed by using the spectral redshift information of the natural celestial bodies, a new scheme, consisting of Strapdown Inertial Navigation System (SINS)/Spectral Redshift (SRS)/Geomagnetic Navigation System (GNS), is designed for autonomous integrated navigation systems. The principle of this SINS/SRS/GNS autonomous integrated navigation system is explored, and the corresponding mathematical model is established. Furthermore, a robust adaptive central difference particle filtering algorithm is proposed for this autonomous integrated navigation system. The simulation experiments are conducted and the results show that the designed SINS/SRS/GNS autonomous integrated navigation system possesses good autonomy, strong robustness and high reliability, thus providing a new solution for autonomous navigation technology.
Integrated communications and optical navigation system
NASA Astrophysics Data System (ADS)
Mueller, J.; Pajer, G.; Paluszek, M.
2013-12-01
The Integrated Communications and Optical Navigation System (ICONS) is a flexible navigation system for spacecraft that does not require global positioning system (GPS) measurements. The navigation solution is computed using an Unscented Kalman Filter (UKF) that can accept any combination of range, range-rate, planet chord width, landmark, and angle measurements using any celestial object. Both absolute and relative orbit determination is supported. The UKF employs a full nonlinear dynamical model of the orbit including gravity models and disturbance models. The ICONS package also includes attitude determination algorithms using the UKF algorithm with the Inertial Measurement Unit (IMU). The IMU is used as the dynamical base for the attitude determination algorithms. This makes the sensor a more capable plug-in replacement for a star tracker, thus reducing the integration and test cost of adding this sensor to a spacecraft. Recent additions include an integrated optical communications system which adds communications, and integrated range and range rate measurement and timing. The paper includes test results from trajectories based on the NASA New Horizons spacecraft.
Institute of Navigation, Annual Meeting, 47th, Williamsburg, VA, June 10-12, 1991, Proceedings
NASA Astrophysics Data System (ADS)
1991-11-01
The present volume of navigation and exploration discusses space exploration, mapping and geodesy, aircraft navigation, undersea navigation, land and vehicular location, international and legal aspects of navigation, the history of navigation technology and applications, Loran development and implementation, GPS and GLONASS developments, and search and rescue. Topics addressed include stabilization of low orbiting spacecraft using GPS, the employment of laser navigation for automatic rendezvous and docking systems, enhanced pseudostatic processing, and the expanding role of sensor fusion. Attention is given to a gravity-aided inertial navigation system, recent developments in aviation products liability and navigation, the ICAO future air navigation system, and Loran's implementation in NAS. Also discussed are Inmarsat integrated navigation/communication activities, the GPS program status, the evolution of military GPS technology into the Navcore V receiver engine, and Sarsat location algorithms.
Strapdown cost trend study and forecast
NASA Technical Reports Server (NTRS)
Eberlein, A. J.; Savage, P. G.
1975-01-01
The potential cost advantages offered by advanced strapdown inertial technology in future commercial short-haul aircraft are summarized. The initial procurement cost and six year cost-of-ownership, which includes spares and direct maintenance cost were calculated for kinematic and inertial navigation systems such that traditional and strapdown mechanization costs could be compared. Cost results for the inertial navigation systems showed that initial costs and the cost of ownership for traditional triple redundant gimbaled inertial navigators are three times the cost of the equivalent skewed redundant strapdown inertial navigator. The net cost advantage for the strapdown kinematic system is directly attributable to the reduction in sensor count for strapdown. The strapdown kinematic system has the added advantage of providing a fail-operational inertial navigation capability for no additional cost due to the use of inertial grade sensors and attitude reference computers.
SLS Model Based Design: A Navigation Perspective
NASA Technical Reports Server (NTRS)
Oliver, T. Emerson; Anzalone, Evan; Park, Thomas; Geohagan, Kevin
2018-01-01
The SLS Program has implemented a Model-based Design (MBD) and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team is responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1B design, the additional GPS Receiver hardware model is managed as a DMM at the vehicle design level. This paper describes the models, and discusses the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the navigation components.
Observability-Based Guidance and Sensor Placement
NASA Astrophysics Data System (ADS)
Hinson, Brian T.
Control system performance is highly dependent on the quality of sensor information available. In a growing number of applications, however, the control task must be accomplished with limited sensing capabilities. This thesis addresses these types of problems from a control-theoretic point-of-view, leveraging system nonlinearities to improve sensing performance. Using measures of observability as an information quality metric, guidance trajectories and sensor distributions are designed to improve the quality of sensor information. An observability-based sensor placement algorithm is developed to compute optimal sensor configurations for a general nonlinear system. The algorithm utilizes a simulation of the nonlinear system as the source of input data, and convex optimization provides a scalable solution method. The sensor placement algorithm is applied to a study of gyroscopic sensing in insect wings. The sensor placement algorithm reveals information-rich areas on flexible insect wings, and a comparison to biological data suggests that insect wings are capable of acting as gyroscopic sensors. An observability-based guidance framework is developed for robotic navigation with limited inertial sensing. Guidance trajectories and algorithms are developed for range-only and bearing-only navigation that improve navigation accuracy. Simulations and experiments with an underwater vehicle demonstrate that the observability measure allows tuning of the navigation uncertainty.
Gravity Gradiometry and Map Matching: An Aid to Aircraft Inertial Navigation Systems
2010-03-01
improve its performance. In all of these cases, because information from two or more different navigation systems feeds into a navigation solution...GRAVITY GRADIOMETRY AND MAP MATCHING: AN AID TO AIRCRAFT INERTIAL NAVIGATION SYSTEMS THESIS...M06 GRAVITY GRADIOMETRY AND MAP MATCHING: AN AID TO AIRCRAFT INERTIAL NAVIGATION SYSTEMS THESIS Presented to the Faculty Department of
Hybrid Transverse Polar Navigation for High-Precision and Long-Term INSs
Wu, Qiuping; Zhang, Rong; Hu, Peida; Li, Haixia
2018-01-01
Transverse navigation has been proposed to help inertial navigation systems (INSs) fill the gap of polar navigation ability. However, as the transverse system does not have the ability of navigate globally, a complicated switch between the transverse and the traditional algorithms is necessary when the system moves across the polar circles. To maintain the inner continuity and consistency of the core algorithm, a hybrid transverse polar navigation is proposed in this research based on a combination of Earth-fixed-frame mechanization and transverse-frame outputs. Furthermore, a thorough analysis of kinematic error characteristics, proper damping technology and corresponding long-term contributions of main error sources is conducted for the high-precision INSs. According to the analytical expressions of the long-term navigation errors in polar areas, the 24-h period symmetrical oscillation with a slowly divergent amplitude dominates the transverse horizontal position errors, and the first-order drift dominates the transverse azimuth error, which results from the g0 gyro drift coefficients that occur in corresponding directions. Simulations are conducted to validate the theoretical analysis and the deduced analytical expressions. The results show that the proposed hybrid transverse navigation can ensure the same accuracy and oscillation characteristics in polar areas as the traditional algorithm in low and mid latitude regions. PMID:29757242
Hybrid Transverse Polar Navigation for High-Precision and Long-Term INSs.
Wu, Ruonan; Wu, Qiuping; Han, Fengtian; Zhang, Rong; Hu, Peida; Li, Haixia
2018-05-12
Transverse navigation has been proposed to help inertial navigation systems (INSs) fill the gap of polar navigation ability. However, as the transverse system does not have the ability of navigate globally, a complicated switch between the transverse and the traditional algorithms is necessary when the system moves across the polar circles. To maintain the inner continuity and consistency of the core algorithm, a hybrid transverse polar navigation is proposed in this research based on a combination of Earth-fixed-frame mechanization and transverse-frame outputs. Furthermore, a thorough analysis of kinematic error characteristics, proper damping technology and corresponding long-term contributions of main error sources is conducted for the high-precision INSs. According to the analytical expressions of the long-term navigation errors in polar areas, the 24-h period symmetrical oscillation with a slowly divergent amplitude dominates the transverse horizontal position errors, and the first-order drift dominates the transverse azimuth error, which results from the gyro drift coefficients that occur in corresponding directions. Simulations are conducted to validate the theoretical analysis and the deduced analytical expressions. The results show that the proposed hybrid transverse navigation can ensure the same accuracy and oscillation characteristics in polar areas as the traditional algorithm in low and mid latitude regions.
Wang, Lingling; Fu, Li
2018-01-01
In order to decrease the velocity sculling error under vibration environments, a new sculling error compensation algorithm for strapdown inertial navigation system (SINS) using angular rate and specific force measurements as inputs is proposed in this paper. First, the sculling error formula in incremental velocity update is analytically derived in terms of the angular rate and specific force. Next, two-time scale perturbation models of the angular rate and specific force are constructed. The new sculling correction term is derived and a gravitational search optimization method is used to determine the parameters in the two-time scale perturbation models. Finally, the performance of the proposed algorithm is evaluated in a stochastic real sculling environment, which is different from the conventional algorithms simulated in a pure sculling circumstance. A series of test results demonstrate that the new sculling compensation algorithm can achieve balanced real/pseudo sculling correction performance during velocity update with the advantage of less computation load compared with conventional algorithms. PMID:29346323
Particle swarm optimization algorithm based low cost magnetometer calibration
NASA Astrophysics Data System (ADS)
Ali, A. S.; Siddharth, S., Syed, Z., El-Sheimy, N.
2011-12-01
Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a microprocessor provide inertial digital data from which position and orientation is obtained by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the absolute user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are corrupted by several errors including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO) based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometer. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. The estimated bias and scale factor errors from the proposed algorithm improve the heading accuracy and the results are also statistically significant. Also, it can help in the development of the Pedestrian Navigation Devices (PNDs) when combined with the INS and GPS/Wi-Fi especially in the indoor environments
An IMM-Aided ZUPT Methodology for an INS/DVL Integrated Navigation System.
Yao, Yiqing; Xu, Xiaosu; Xu, Xiang
2017-09-05
Inertial navigation system (INS)/Doppler velocity log (DVL) integration is the most common navigation solution for underwater vehicles. Due to the complex underwater environment, the velocity information provided by DVL always contains some errors. To improve navigation accuracy, zero velocity update (ZUPT) technology is considered, which is an effective algorithm for land vehicles to mitigate the navigation error during the pure INS mode. However, in contrast to ground vehicles, the ZUPT solution cannot be used directly for underwater vehicles because of the existence of the water current. In order to leverage the strengths of the ZUPT method and the INS/DVL solution, an interactive multiple model (IMM)-aided ZUPT methodology for the INS/DVL-integrated underwater navigation system is proposed. Both the INS/DVL and INS/ZUPT models are constructed and operated in parallel, with weights calculated according to their innovations and innovation covariance matrices. Simulations are conducted to evaluate the proposed algorithm. The results indicate that the IMM-aided ZUPT solution outperforms both the INS/DVL solution and the INS/ZUPT solution in the underwater environment, which can properly distinguish between the ZUPT and non-ZUPT conditions. In addition, during DVL outage, the effectiveness of the proposed algorithm is also verified.
The impact of inertial navigation on air safety.
DOT National Transportation Integrated Search
1971-05-01
An analysis of inertial navigation system performance data was carried out to assess the probable impact of inertial navigation on the aircraft collision risk in the North Atlantic region. These data were used to calculate the collision risk between ...
Wei, Wenhui; Gao, Zhaohui; Gao, Shesheng; Jia, Ke
2018-01-01
In order to meet the requirements of autonomy and reliability for the navigation system, combined with the method of measuring speed by using the spectral redshift information of the natural celestial bodies, a new scheme, consisting of Strapdown Inertial Navigation System (SINS)/Spectral Redshift (SRS)/Geomagnetic Navigation System (GNS), is designed for autonomous integrated navigation systems. The principle of this SINS/SRS/GNS autonomous integrated navigation system is explored, and the corresponding mathematical model is established. Furthermore, a robust adaptive central difference particle filtering algorithm is proposed for this autonomous integrated navigation system. The simulation experiments are conducted and the results show that the designed SINS/SRS/GNS autonomous integrated navigation system possesses good autonomy, strong robustness and high reliability, thus providing a new solution for autonomous navigation technology. PMID:29642549
Drift Reduction in Pedestrian Navigation System by Exploiting Motion Constraints and Magnetic Field.
Ilyas, Muhammad; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok
2016-09-09
Pedestrian navigation systems (PNS) using foot-mounted MEMS inertial sensors use zero-velocity updates (ZUPTs) to reduce drift in navigation solutions and estimate inertial sensor errors. However, it is well known that ZUPTs cannot reduce all errors, especially as heading error is not observable. Hence, the position estimates tend to drift and even cyclic ZUPTs are applied in updated steps of the Extended Kalman Filter (EKF). This urges the use of other motion constraints for pedestrian gait and any other valuable heading reduction information that is available. In this paper, we exploit two more motion constraints scenarios of pedestrian gait: (1) walking along straight paths; (2) standing still for a long time. It is observed that these motion constraints (called "virtual sensor"), though considerably reducing drift in PNS, still need an absolute heading reference. One common absolute heading estimation sensor is the magnetometer, which senses the Earth's magnetic field and, hence, the true heading angle can be calculated. However, magnetometers are susceptible to magnetic distortions, especially in indoor environments. In this work, an algorithm, called magnetic anomaly detection (MAD) and compensation is designed by incorporating only healthy magnetometer data in the EKF updating step, to reduce drift in zero-velocity updated INS. Experiments are conducted in GPS-denied and magnetically distorted environments to validate the proposed algorithms.
Hub, Andreas; Hartter, Tim; Kombrink, Stefan; Ertl, Thomas
2008-01-01
PURPOSE.: This study describes the development of a multi-functional assistant system for the blind which combines localisation, real and virtual navigation within modelled environments and the identification and tracking of fixed and movable objects. The approximate position of buildings is determined with a global positioning sensor (GPS), then the user establishes exact position at a specific landmark, like a door. This location initialises indoor navigation, based on an inertial sensor, a step recognition algorithm and map. Tracking of movable objects is provided by another inertial sensor and a head-mounted stereo camera, combined with 3D environmental models. This study developed an algorithm based on shape and colour to identify objects and used a common face detection algorithm to inform the user of the presence and position of others. The system allows blind people to determine their position with approximately 1 metre accuracy. Virtual exploration of the environment can be accomplished by moving one's finger on a touch screen of a small portable tablet PC. The name of rooms, building features and hazards, modelled objects and their positions are presented acoustically or in Braille. Given adequate environmental models, this system offers blind people the opportunity to navigate independently and safely, even within unknown environments. Additionally, the system facilitates education and rehabilitation by providing, in several languages, object names, features and relative positions.
INTEGRATED INS/GPS NAVIGATION FROM A POPULAR PERSPECTIVE
DOT National Transportation Integrated Search
2002-02-13
Inertial navigation, blended with other navigation aids Global Positioning System (GPS) in particular, has gained significance due to enhanced navigation and inertial reference performance and dissimilarity for fault tolerance and anti-jamming. Relat...
Liu, Bingqi; Wei, Shihui; Su, Guohua; Wang, Jiping; Lu, Jiazhen
2018-01-01
The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible. PMID:29695041
Liu, Bingqi; Wei, Shihui; Su, Guohua; Wang, Jiping; Lu, Jiazhen
2018-04-24
The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible.
Adaptive Estimation of Multiple Fading Factors for GPS/INS Integrated Navigation Systems.
Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao
2017-06-01
The Kalman filter has been widely applied in the field of dynamic navigation and positioning. However, its performance will be degraded in the presence of significant model errors and uncertain interferences. In the literature, the fading filter was proposed to control the influences of the model errors, and the H-infinity filter can be adopted to address the uncertainties by minimizing the estimation error in the worst case. In this paper, a new multiple fading factor, suitable for the Global Positioning System (GPS) and the Inertial Navigation System (INS) integrated navigation system, is proposed based on the optimization of the filter, and a comprehensive filtering algorithm is constructed by integrating the advantages of the H-infinity filter and the proposed multiple fading filter. Measurement data of the GPS/INS integrated navigation system are collected under actual conditions. Stability and robustness of the proposed filtering algorithm are tested with various experiments and contrastive analysis are performed with the measurement data. Results demonstrate that both the filter divergence and the influences of outliers are restrained effectively with the proposed filtering algorithm, and precision of the filtering results are improved simultaneously.
NASA Technical Reports Server (NTRS)
Hruby, R. J.; Bjorkman, W. S.
1977-01-01
Flight test results of the strapdown inertial reference unit (SIRU) navigation system are presented. The fault-tolerant SIRU navigation system features a redundant inertial sensor unit and dual computers. System software provides for detection and isolation of inertial sensor failures and continued operation in the event of failures. Flight test results include assessments of the system's navigational performance and fault tolerance.
Loose and Tight GNSS/INS Integrations: Comparison of Performance Assessed in Real Urban Scenarios.
Falco, Gianluca; Pini, Marco; Marucco, Gianluca
2017-01-29
Global Navigation Satellite Systems (GNSSs) remain the principal mean of positioning in many applications and systems, but in several types of environment, the performance of standalone receivers is degraded. Although many works show the benefits of the integration between GNSS and Inertial Navigation Systems (INSs), tightly-coupled architectures are mainly implemented in professional devices and are based on high-grade Inertial Measurement Units (IMUs). This paper investigates the performance improvements enabled by the tight integration, using low-cost sensors and a mass-market GNSS receiver. Performance is assessed through a series of tests carried out in real urban scenarios and is compared against commercial modules, operating in standalone mode or featuring loosely-coupled integrations. The paper describes the developed tight-integration algorithms with a terse mathematical model and assesses their efficacy from a practical perspective.
Strapdown system performance optimization test evaluations (SPOT), volume 1
NASA Technical Reports Server (NTRS)
Blaha, R. J.; Gilmore, J. P.
1973-01-01
A three axis inertial system was packaged in an Apollo gimbal fixture for fine grain evaluation of strapdown system performance in dynamic environments. These evaluations have provided information to assess the effectiveness of real-time compensation techniques and to study system performance tradeoffs to factors such as quantization and iteration rate. The strapdown performance and tradeoff studies conducted include: (1) Compensation models and techniques for the inertial instrument first-order error terms were developed and compensation effectivity was demonstrated in four basic environments; single and multi-axis slew, and single and multi-axis oscillatory. (2) The theoretical coning bandwidth for the first-order quaternion algorithm expansion was verified. (3) Gyro loop quantization was identified to affect proportionally the system attitude uncertainty. (4) Land navigation evaluations identified the requirement for accurate initialization alignment in order to pursue fine grain navigation evaluations.
Gao, Zhouzheng; Zhang, Hongping; Ge, Maorong; Niu, Xiaoji; Shen, Wenbin; Wickert, Jens; Schuh, Harald
2015-03-10
The continuity and reliability of precise GNSS positioning can be seriously limited by severe user observation environments. The Inertial Navigation System (INS) can overcome such drawbacks, but its performance is clearly restricted by INS sensor errors over time. Accordingly, the tightly coupled integration of GPS and INS can overcome the disadvantages of each individual system and together form a new navigation system with a higher accuracy, reliability and availability. Recently, ionosphere-constrained (IC) precise point positioning (PPP) utilizing raw GPS observations was proven able to improve both the convergence and positioning accuracy of the conventional PPP using ionosphere-free combined observations (LC-PPP). In this paper, a new mode of tightly coupled integration, in which the IC-PPP instead of LC-PPP is employed, is implemented to further improve the performance of the coupled system. We present the detailed mathematical model and the related algorithm of the new integration of IC-PPP and INS. To evaluate the performance of the new tightly coupled integration, data of both airborne and vehicle experiments with a geodetic GPS receiver and tactical grade inertial measurement unit are processed and the results are analyzed. The statistics show that the new approach can further improve the positioning accuracy compared with both IC-PPP and the tightly coupled integration of the conventional PPP and INS.
An IMM-Aided ZUPT Methodology for an INS/DVL Integrated Navigation System
Yao, Yiqing
2017-01-01
Inertial navigation system (INS)/Doppler velocity log (DVL) integration is the most common navigation solution for underwater vehicles. Due to the complex underwater environment, the velocity information provided by DVL always contains some errors. To improve navigation accuracy, zero velocity update (ZUPT) technology is considered, which is an effective algorithm for land vehicles to mitigate the navigation error during the pure INS mode. However, in contrast to ground vehicles, the ZUPT solution cannot be used directly for underwater vehicles because of the existence of the water current. In order to leverage the strengths of the ZUPT method and the INS/DVL solution, an interactive multiple model (IMM)-aided ZUPT methodology for the INS/DVL-integrated underwater navigation system is proposed. Both the INS/DVL and INS/ZUPT models are constructed and operated in parallel, with weights calculated according to their innovations and innovation covariance matrices. Simulations are conducted to evaluate the proposed algorithm. The results indicate that the IMM-aided ZUPT solution outperforms both the INS/DVL solution and the INS/ZUPT solution in the underwater environment, which can properly distinguish between the ZUPT and non-ZUPT conditions. In addition, during DVL outage, the effectiveness of the proposed algorithm is also verified. PMID:28872602
Inertial aided cycle slip detection and identification for integrated PPP GPS and INS.
Du, Shuang; Gao, Yang
2012-10-25
The recently developed integrated Precise Point Positioning (PPP) GPS/INS system can be useful to many applications, such as UAV navigation systems, land vehicle/machine automation and mobile mapping systems. Since carrier phase measurements are the primary observables in PPP GPS, cycle slips, which often occur due to high dynamics, signal obstructions and low satellite elevation, must be detected and repaired in order to ensure the navigation performance. In this research, a new algorithm of cycle slip detection and identification has been developed. With the aiding from INS, the proposed method jointly uses WL and EWL phase combinations to uniquely determine cycle slips in the L1 and L2 frequencies. To verify the efficiency of the algorithm, both tactical-grade and consumer-grade IMUs are tested by using a real dataset collected from two field tests. The results indicate that the proposed algorithm can efficiently detect and identify the cycle slips and subsequently improve the navigation performance of the integrated system.
NASA Astrophysics Data System (ADS)
Maass, Bolko
2016-12-01
This paper describes an efficient and easily implemented algorithmic approach to extracting an approximation to an image's dominant projected illumination direction, based on intermediary results from a segmentation-based crater detection algorithm (CDA), at a computational cost that is negligible in comparison to that of the prior stages of the CDA. Most contemporary CDAs built for spacecraft navigation use this illumination direction as a means of improving performance or even require it to function at all. Deducing the illumination vector from the image alone reduces the reliance on external information such as the accurate knowledge of the spacecraft inertial state, accurate time base and solar system ephemerides. Therefore, a method such as the one described in this paper is a prerequisite for true "Lost in Space" operation of a purely segmentation-based crater detecting and matching method for spacecraft navigation. The proposed method is verified using ray-traced lunar elevation model data, asteroid image data, and in a laboratory setting with a camera in the loop.
Tightly-Coupled Image-Aided Inertial Navigation Using the Unscented Kalman Filter
2007-01-01
Integrated GPS/MEMS Inertial Navigation Package. In Proceedings of ION GNSS 2004, pp. 825–832, September 2004. [2] R. G. Brown and P. Y. Hwang ...Tightly-Coupled Image-Aided Inertial Navigation Using the Unscented Kalman Filter S. Ebcin, Air Force Institute of Technology M. Veth, Air Force...inertial sen- sors using an extended Kalman filter (EKF) algo- rithm. In this approach, the image feature corre- spondence search was aided using the
Flight test results of the strapdown hexad inertial reference unit (SIRU). Volume 2: Test report
NASA Technical Reports Server (NTRS)
Hruby, R. J.; Bjorkman, W. S.
1977-01-01
Results of flight tests of the Strapdown Inertial Reference Unit (SIRU) navigation system are presented. The fault tolerant SIRU navigation system features a redundant inertial sensor unit and dual computers. System software provides for detection and isolation of inertial sensor failures and continued operation in the event of failures. Flight test results include assessments of the system's navigational performance and fault tolerance. Performance shortcomings are analyzed.
NASA Technical Reports Server (NTRS)
Bryant, W. H.; Morrell, F. R.
1981-01-01
Attention is given to a redundant strapdown inertial measurement unit for integrated avionics. The system consists of four two-degree-of-freedom turned rotor gyros and four two-degree-of-freedom accelerometers in a skewed and separable semi-octahedral array. The unit is coupled through instrument electronics to two flight computers which compensate sensor errors. The flight computers are interfaced to the microprocessors and process failure detection, isolation, redundancy management and flight control/navigation algorithms. The unit provides dual fail-operational performance and has data processing frequencies consistent with integrated avionics concepts presently planned.
Satellite Imagery Assisted Road-Based Visual Navigation System
NASA Astrophysics Data System (ADS)
Volkova, A.; Gibbens, P. W.
2016-06-01
There is a growing demand for unmanned aerial systems as autonomous surveillance, exploration and remote sensing solutions. Among the key concerns for robust operation of these systems is the need to reliably navigate the environment without reliance on global navigation satellite system (GNSS). This is of particular concern in Defence circles, but is also a major safety issue for commercial operations. In these circumstances, the aircraft needs to navigate relying only on information from on-board passive sensors such as digital cameras. An autonomous feature-based visual system presented in this work offers a novel integral approach to the modelling and registration of visual features that responds to the specific needs of the navigation system. It detects visual features from Google Earth* build a feature database. The same algorithm then detects features in an on-board cameras video stream. On one level this serves to localise the vehicle relative to the environment using Simultaneous Localisation and Mapping (SLAM). On a second level it correlates them with the database to localise the vehicle with respect to the inertial frame. The performance of the presented visual navigation system was compared using the satellite imagery from different years. Based on comparison results, an analysis of the effects of seasonal, structural and qualitative changes of the imagery source on the performance of the navigation algorithm is presented. * The algorithm is independent of the source of satellite imagery and another provider can be used
A RLS-SVM Aided Fusion Methodology for INS during GPS Outages
Yao, Yiqing; Xu, Xiaosu
2017-01-01
In order to maintain a relatively high accuracy of navigation performance during global positioning system (GPS) outages, a novel robust least squares support vector machine (LS-SVM)-aided fusion methodology is explored to provide the pseudo-GPS position information for the inertial navigation system (INS). The relationship between the yaw, specific force, velocity, and the position increment is modeled. Rather than share the same weight in the traditional LS-SVM, the proposed algorithm allocates various weights for different data, which makes the system immune to the outliers. Field test data was collected to evaluate the proposed algorithm. The comparison results indicate that the proposed algorithm can effectively provide position corrections for standalone INS during the 300 s GPS outage, which outperforms the traditional LS-SVM method. Historical information is also involved to better represent the vehicle dynamics. PMID:28245549
A RLS-SVM Aided Fusion Methodology for INS during GPS Outages.
Yao, Yiqing; Xu, Xiaosu
2017-02-24
In order to maintain a relatively high accuracy of navigation performance during global positioning system (GPS) outages, a novel robust least squares support vector machine (LS-SVM)-aided fusion methodology is explored to provide the pseudo-GPS position information for the inertial navigation system (INS). The relationship between the yaw, specific force, velocity, and the position increment is modeled. Rather than share the same weight in the traditional LS-SVM, the proposed algorithm allocates various weights for different data, which makes the system immune to the outliers. Field test data was collected to evaluate the proposed algorithm. The comparison results indicate that the proposed algorithm can effectively provide position corrections for standalone INS during the 300 s GPS outage, which outperforms the traditional LS-SVM method. Historical information is also involved to better represent the vehicle dynamics.
Using multiple IMUs in a stacked filter configuration for calibration and fine alignment
NASA Astrophysics Data System (ADS)
El-Osery, Aly; Bruder, Stephen; Wedeward, Kevin
2018-05-01
Determination of a vehicle or person's position and/or orientation is a critical task for a multitude of applications ranging from automated cars and first responders to missiles and fighter jets. Most of these applications rely primarily on global navigation satellite systems, e.g., GPS, which are highly vulnerable to degradation whether by environmental factors or malicious actions. The use of inertial navigation techniques has been shown to provide increased reliability of navigation systems in these situations. Due to advances in MEMS technology and processing capabilities, the use of small and low-cost inertial measurement units (IMUs) are becoming increasingly feasible, which results in small size, weight and power (SWaP) solutions. A known limitation of MEMS IMUs are errors that causes the navigation solution to drift; furthermore, calibration and initialization are challenging tasks. In this paper, we investigate the use of multiple IMUs to aid in calibrating the navigation system and obtaining accurate initialization by performing fine alignment. By using a centralized filter, physical constraints between the multiple IMUs on a rigid body are leveraged to provide relative updates, which in turn aids in the estimation of the individual biases and scale-factors. Developed algorithms will be validated through simulation and actual measurements using low-cost IMUs.
Drift Reduction in Pedestrian Navigation System by Exploiting Motion Constraints and Magnetic Field
Ilyas, Muhammad; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok
2016-01-01
Pedestrian navigation systems (PNS) using foot-mounted MEMS inertial sensors use zero-velocity updates (ZUPTs) to reduce drift in navigation solutions and estimate inertial sensor errors. However, it is well known that ZUPTs cannot reduce all errors, especially as heading error is not observable. Hence, the position estimates tend to drift and even cyclic ZUPTs are applied in updated steps of the Extended Kalman Filter (EKF). This urges the use of other motion constraints for pedestrian gait and any other valuable heading reduction information that is available. In this paper, we exploit two more motion constraints scenarios of pedestrian gait: (1) walking along straight paths; (2) standing still for a long time. It is observed that these motion constraints (called “virtual sensor”), though considerably reducing drift in PNS, still need an absolute heading reference. One common absolute heading estimation sensor is the magnetometer, which senses the Earth’s magnetic field and, hence, the true heading angle can be calculated. However, magnetometers are susceptible to magnetic distortions, especially in indoor environments. In this work, an algorithm, called magnetic anomaly detection (MAD) and compensation is designed by incorporating only healthy magnetometer data in the EKF updating step, to reduce drift in zero-velocity updated INS. Experiments are conducted in GPS-denied and magnetically distorted environments to validate the proposed algorithms. PMID:27618056
NASA Astrophysics Data System (ADS)
Belyaev, E. N.
2017-10-01
The paper investigates the method of applying mobile scanning systems (MSSs) with inertial navigators in the underground conditions for carrying out the surveying tasks. The available mobile laser scanning systems cannot be used in the underground environment since Global Positioning System (GPS) signals cannot be received in mines. This signal not only is necessary for space positioning, but also operates as the main corrective signal for the primary navigation system - the inertial navigation system. The idea of the method described in this paper consists in using MSSs with a different correction of the inertial system than GPS is.
Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1
NASA Technical Reports Server (NTRS)
Park, Thomas; Smith, Austin; Oliver, T. Emerson
2018-01-01
The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GNC software from the set of healthy measurements. This paper explores the trades and analyses that were performed in selecting a set of robust fault-detection algorithms included in the GN&C flight software. These trades included both an assessment of hardware-provided health and status data as well as an evaluation of different algorithms based on time-to-detection, type of failures detected, and probability of detecting false positives. We then provide an overview of the algorithms used for both fault-detection and measurement down selection. We next discuss the role of trajectory design, flexible-body models, and vehicle response to off-nominal conditions in setting the detection thresholds. Lastly, we present lessons learned from software integration and hardware-in-the-loop testing.
Orion MPCV GN and C End-to-End Phasing Tests
NASA Technical Reports Server (NTRS)
Neumann, Brian C.
2013-01-01
End-to-end integration tests are critical risk reduction efforts for any complex vehicle. Phasing tests are an end-to-end integrated test that validates system directional phasing (polarity) from sensor measurement through software algorithms to end effector response. Phasing tests are typically performed on a fully integrated and assembled flight vehicle where sensors are stimulated by moving the vehicle and the effectors are observed for proper polarity. Orion Multi-Purpose Crew Vehicle (MPCV) Pad Abort 1 (PA-1) Phasing Test was conducted from inertial measurement to Launch Abort System (LAS). Orion Exploration Flight Test 1 (EFT-1) has two end-to-end phasing tests planned. The first test from inertial measurement to Crew Module (CM) reaction control system thrusters uses navigation and flight control system software algorithms to process commands. The second test from inertial measurement to CM S-Band Phased Array Antenna (PAA) uses navigation and communication system software algorithms to process commands. Future Orion flights include Ascent Abort Flight Test 2 (AA-2) and Exploration Mission 1 (EM-1). These flights will include additional or updated sensors, software algorithms and effectors. This paper will explore the implementation of end-to-end phasing tests on a flight vehicle which has many constraints, trade-offs and compromises. Orion PA-1 Phasing Test was conducted at White Sands Missile Range (WSMR) from March 4-6, 2010. This test decreased the risk of mission failure by demonstrating proper flight control system polarity. Demonstration was achieved by stimulating the primary navigation sensor, processing sensor data to commands and viewing propulsion response. PA-1 primary navigation sensor was a Space Integrated Inertial Navigation System (INS) and Global Positioning System (GPS) (SIGI) which has onboard processing, INS (3 accelerometers and 3 rate gyros) and no GPS receiver. SIGI data was processed by GN&C software into thrust magnitude and direction commands. The processing changes through three phases of powered flight: pitchover, downrange and reorientation. The primary inputs to GN&C are attitude position, attitude rates, angle of attack (AOA) and angle of sideslip (AOS). Pitch and yaw attitude and attitude rate responses were verified by using a flight spare SIGI mounted to a 2-axis rate table. AOA and AOS responses were verified by using a data recorded from SIGI movements on a robotic arm located at NASA Johnson Space Center. The data was consolidated and used in an open-loop data input to the SIGI. Propulsion was the Launch Abort System (LAS) Attitude Control Motor (ACM) which consisted of a solid motor with 8 nozzles. Each nozzle has active thrust control by varying throat area with a pintle. LAS ACM pintles are observable through optically transparent nozzle covers. SIGI movements on robot arm, SIGI rate table movements and LAS ACM pintle responses were video recorded as test artifacts for analysis and evaluation. The PA-1 Phasing Test design was determined based on test performance requirements, operational restrictions and EGSE capabilities. This development progressed during different stages. For convenience these development stages are initial, working group, tiger team, Engineering Review Team (ERT) and final.
Gao, Zhouzheng; Zhang, Hongping; Ge, Maorong; Niu, Xiaoji; Shen, Wenbin; Wickert, Jens; Schuh, Harald
2015-01-01
The continuity and reliability of precise GNSS positioning can be seriously limited by severe user observation environments. The Inertial Navigation System (INS) can overcome such drawbacks, but its performance is clearly restricted by INS sensor errors over time. Accordingly, the tightly coupled integration of GPS and INS can overcome the disadvantages of each individual system and together form a new navigation system with a higher accuracy, reliability and availability. Recently, ionosphere-constrained (IC) precise point positioning (PPP) utilizing raw GPS observations was proven able to improve both the convergence and positioning accuracy of the conventional PPP using ionosphere-free combined observations (LC-PPP). In this paper, a new mode of tightly coupled integration, in which the IC-PPP instead of LC-PPP is employed, is implemented to further improve the performance of the coupled system. We present the detailed mathematical model and the related algorithm of the new integration of IC-PPP and INS. To evaluate the performance of the new tightly coupled integration, data of both airborne and vehicle experiments with a geodetic GPS receiver and tactical grade inertial measurement unit are processed and the results are analyzed. The statistics show that the new approach can further improve the positioning accuracy compared with both IC-PPP and the tightly coupled integration of the conventional PPP and INS. PMID:25763647
An enhanced inertial navigation system based on a low-cost IMU and laser scanner
NASA Astrophysics Data System (ADS)
Kim, Hyung-Soon; Baeg, Seung-Ho; Yang, Kwang-Woong; Cho, Kuk; Park, Sangdeok
2012-06-01
This paper describes an enhanced fusion method for an Inertial Navigation System (INS) based on a 3-axis accelerometer sensor, a 3-axis gyroscope sensor and a laser scanner. In GPS-denied environments, indoor or dense forests, a pure INS odometry is available for estimating the trajectory of a human or robot. However it has a critical implementation problem: a drift error of velocity, position and heading angles. Commonly the problem can be solved by fusing visual landmarks, a magnetometer or radio beacons. These methods are not robust in diverse environments: darkness, fog or sunlight, an unstable magnetic field and an environmental obstacle. We propose to overcome the drift problem using an Iterative Closest Point (ICP) scan matching algorithm with a laser scanner. This system consists of three parts. The first is the INS. It estimates attitude, velocity, position based on a 6-axis Inertial Measurement Unit (IMU) with both 'Heuristic Reduction of Gyro Drift' (HRGD) and 'Heuristic Reduction of Velocity Drift' (HRVD) methods. A frame-to-frame ICP matching algorithm for estimating position and attitude by laser scan data is the second. The third is an extended kalman filter method for multi-sensor data fusing: INS and Laser Range Finder (LRF). The proposed method is simple and robust in diverse environments, so we could reduce the drift error efficiently. We confirm the result comparing an odometry of the experimental result with ICP and LRF aided-INS in a long corridor.
Validation of Inertial and Optical Navigation Techniques for Space Applications with UAVS
NASA Astrophysics Data System (ADS)
Montaño, J.; Wis, M.; Pulido, J. A.; Latorre, A.; Molina, P.; Fernández, E.; Angelats, E.; Colomina, I.
2015-09-01
PERIGEO is an R&D project, funded by the INNPRONTA 2011-2014 programme from Spanish CDTI, which aims to investigate the use of UAV technologies and processes for the validation of space oriented technologies. For this purpose, among different space missions and technologies, a set of activities for absolute and relative navigation are being carried out to deal with the attitude and position estimation problem from a temporal image sequence from a camera on the visible spectrum and/or Light Detection and Ranging (LIDAR) sensor. The process is covered entirely: from sensor measurements and data acquisition (images, LiDAR ranges and angles), data pre-processing (calibration and co-registration of camera and LIDAR data), features and landmarks extraction from the images and image/LiDAR-based state estimation. In addition to image processing area, classical navigation system based on inertial sensors is also included in the research. The reason of combining both approaches is to enable the possibility to keep navigation capability in environments or missions where the radio beacon or reference signal as the GNSS satellite is not available (as for example an atmospheric flight in Titan). The rationale behind the combination of those systems is that they complement each other. The INS is capable of providing accurate position, velocity and full attitude estimations at high data rates. However, they need an absolute reference observation to compensate the time accumulative errors caused by inertial sensor inaccuracies. On the other hand, imaging observables can provide absolute and relative positioning and attitude estimations. However they need that the sensor head is pointing toward ground (something that may not be possible if the carrying platform is maneuvering) to provide accurate estimations and they are not capable of provide some hundreds of Hz that can deliver an INS. This mutual complementarity has been observed in PERIGEO and because of this they are combined into one system. The inertial navigation system implemented in PERIGEO is based on a classical loosely coupled INS/GNSS approach that is very similar to the implementation of the INS/Imaging navigation system that is mentioned above. The activities envisaged in PERIGEO cover the algorithms development and validation and technology testing on UAVs under representative conditions. Past activities have covered the design and development of the algorithms and systems. This paper presents the most recent activities and results on the area of image processing for robust estimation within PERIGEO, which are related with the hardware platforms definition (including sensors) and its integration in UAVs. Results for the tests performed during the flight campaigns in representative outdoor environments will be also presented (at the time of the full paper submission the tests will be performed), as well as analyzed, together with a roadmap definition for future developments.
Compensation of Horizontal Gravity Disturbances for High Precision Inertial Navigation
Cao, Juliang; Wu, Meiping; Lian, Junxiang; Cai, Shaokun; Wang, Lin
2018-01-01
Horizontal gravity disturbances are an important factor that affects the accuracy of inertial navigation systems in long-duration ship navigation. In this paper, from the perspective of the coordinate system and vector calculation, the effects of horizontal gravity disturbance on the initial alignment and navigation calculation are simultaneously analyzed. Horizontal gravity disturbances cause the navigation coordinate frame built in initial alignment to not be consistent with the navigation coordinate frame in which the navigation calculation is implemented. The mismatching of coordinate frame violates the vector calculation law, which will have an adverse effect on the precision of the inertial navigation system. To address this issue, two compensation methods suitable for two different navigation coordinate frames are proposed, one of the methods implements the compensation in velocity calculation, and the other does the compensation in attitude calculation. Finally, simulations and ship navigation experiments confirm the effectiveness of the proposed methods. PMID:29562653
Gao, Yanbin; Liu, Shifei; Atia, Mohamed M.; Noureldin, Aboelmagd
2015-01-01
This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory. PMID:26389906
Gao, Yanbin; Liu, Shifei; Atia, Mohamed M; Noureldin, Aboelmagd
2015-09-15
This paper takes advantage of the complementary characteristics of Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) to provide periodic corrections to Inertial Navigation System (INS) alternatively in different environmental conditions. In open sky, where GPS signals are available and LiDAR measurements are sparse, GPS is integrated with INS. Meanwhile, in confined outdoor environments and indoors, where GPS is unreliable or unavailable and LiDAR measurements are rich, LiDAR replaces GPS to integrate with INS. This paper also proposes an innovative hybrid scan matching algorithm that combines the feature-based scan matching method and Iterative Closest Point (ICP) based scan matching method. The algorithm can work and transit between two modes depending on the number of matched line features over two scans, thus achieving efficiency and robustness concurrently. Two integration schemes of INS and LiDAR with hybrid scan matching algorithm are implemented and compared. Real experiments are performed on an Unmanned Ground Vehicle (UGV) for both outdoor and indoor environments. Experimental results show that the multi-sensor integrated system can remain sub-meter navigation accuracy during the whole trajectory.
NASA Astrophysics Data System (ADS)
Konurin, AI; Khmelinin, AP; Denisova, EV
2018-03-01
The currently available drill navigation systems, with their benefits and shortcomings are reviewed. A mathematical model is built to describe the inertial navigation system movement in horizontal and inclined drilling. A prototype model of the inertial navigation system for rotary percussion drills has been designed.
On-the-fly Locata/inertial navigation system integration for precise maritime application
NASA Astrophysics Data System (ADS)
Jiang, Wei; Li, Yong; Rizos, Chris
2013-10-01
The application of Global Navigation Satellite System (GNSS) technology has meant that marine navigators have greater access to a more consistent and accurate positioning capability than ever before. However, GNSS may not be able to meet all emerging navigation performance requirements for maritime applications with respect to service robustness, accuracy, integrity and availability. In particular, applications in port areas (for example automated docking) and in constricted waterways, have very stringent performance requirements. Even when an integrated inertial navigation system (INS)/GNSS device is used there may still be performance gaps. GNSS signals are easily blocked or interfered with, and sometimes the satellite geometry may not be good enough for high accuracy and high reliability applications. Furthermore, the INS accuracy degrades rapidly during GNSS outages. This paper investigates the use of a portable ground-based positioning system, known as ‘Locata’, which was integrated with an INS, to provide accurate navigation in a marine environment without reliance on GNSS signals. An ‘on-the-fly’ Locata resolution algorithm that takes advantage of geometry change via an extended Kalman filter is proposed in this paper. Single-differenced Locata carrier phase measurements are utilized to achieve accurate and reliable solutions. A ‘loosely coupled’ decentralized Locata/INS integration architecture based on the Kalman filter is used for data processing. In order to evaluate the system performance, a field trial was conducted on Sydney Harbour. A Locata network consisting of eight Locata transmitters was set up near the Sydney Harbour Bridge. The experiment demonstrated that the Locata on-the-fly (OTF) algorithm is effective and can improve the system accuracy in comparison with the conventional ‘known point initialization’ (KPI) method. After the OTF and KPI comparison, the OTF Locata/INS integration is then assessed further and its performance improvement on both stand-alone OTF Locata and INS is shown. The Locata/INS integration can achieve centimetre-level accuracy for position solutions, and centimetre-per-second accuracy for velocity determination.
Yuan, Xuebing; Yu, Shuai; Zhang, Shengzhi; Wang, Guoping; Liu, Sheng
2015-01-01
Inertial navigation based on micro-electromechanical system (MEMS) inertial measurement units (IMUs) has attracted numerous researchers due to its high reliability and independence. The heading estimation, as one of the most important parts of inertial navigation, has been a research focus in this field. Heading estimation using magnetometers is perturbed by magnetic disturbances, such as indoor concrete structures and electronic equipment. The MEMS gyroscope is also used for heading estimation. However, the accuracy of gyroscope is unreliable with time. In this paper, a wearable multi-sensor system has been designed to obtain the high-accuracy indoor heading estimation, according to a quaternion-based unscented Kalman filter (UKF) algorithm. The proposed multi-sensor system including one three-axis accelerometer, three single-axis gyroscopes, one three-axis magnetometer and one microprocessor minimizes the size and cost. The wearable multi-sensor system was fixed on waist of pedestrian and the quadrotor unmanned aerial vehicle (UAV) for heading estimation experiments in our college building. The results show that the mean heading estimation errors are less 10° and 5° to multi-sensor system fixed on waist of pedestrian and the quadrotor UAV, respectively, compared to the reference path. PMID:25961384
AUV Underwater Positioning Algorithm Based on Interactive Assistance of SINS and LBL.
Zhang, Tao; Chen, Liping; Li, Yao
2015-12-30
This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a three-dimensional TDOA positioning algorithm of Taylor series expansion and a multi-sensor information fusion algorithm. The final simulation results show that compared to traditional underwater positioning algorithms, this scheme can not only directly correct accumulative errors caused by a dead reckoning algorithm, but also solves the problem of ambiguous correlation peaks caused by multipath transmission of underwater acoustic signals. The proposed method can calibrate the accumulative error of the AUV position more directly and effectively, which prolongs the underwater operating duration of the AUV.
1979-12-01
because of the use of complex computational algorithms (Ref 25). Another important factor effecting the cost of soft- ware is the size of the development...involved the alignment and navigational algorithm portions of the software. The second avionics system application was the development of an inertial...001 1 COAT CONL CREA CINT CMAT CSTR COPR CAPP New Code .001 .001 .001 .001 1001 ,OO .00 Device TDAT T03NL TREA TINT Types o * Quantity OGAT OONL OREA
Zhang, Jiayu; Li, Jie; Zhang, Xi; Che, Xiaorui; Huang, Yugang; Feng, Kaiqiang
2018-05-04
The Semi-Strapdown Inertial Navigation System (SSINS) provides a new solution to attitude measurement of a high-speed rotating missile. However, micro-electro-mechanical-systems (MEMS) inertial measurement unit (MIMU) outputs are corrupted by significant sensor errors. In order to improve the navigation precision, a rotation modulation technology method called Rotation Semi-Strapdown Inertial Navigation System (RSSINS) is introduced into SINS. In fact, the stability of the modulation angular rate is difficult to achieve in a high-speed rotation environment. The changing rotary angular rate has an impact on the inertial sensor error self-compensation. In this paper, the influence of modulation angular rate error, including acceleration-deceleration process, and instability of the angular rate on the navigation accuracy of RSSINS is deduced and the error characteristics of the reciprocating rotation scheme are analyzed. A new compensation method is proposed to remove or reduce sensor errors so as to make it possible to maintain high precision autonomous navigation performance by MIMU when there is no external aid. Experiments have been carried out to validate the performance of the method. In addition, the proposed method is applicable for modulation angular rate error compensation under various dynamic conditions.
An Application of UAV Attitude Estimation Using a Low-Cost Inertial Navigation System
NASA Technical Reports Server (NTRS)
Eure, Kenneth W.; Quach, Cuong Chi; Vazquez, Sixto L.; Hogge, Edward F.; Hill, Boyd L.
2013-01-01
Unmanned Aerial Vehicles (UAV) are playing an increasing role in aviation. Various methods exist for the computation of UAV attitude based on low cost microelectromechanical systems (MEMS) and Global Positioning System (GPS) receivers. There has been a recent increase in UAV autonomy as sensors are becoming more compact and onboard processing power has increased significantly. Correct UAV attitude estimation will play a critical role in navigation and separation assurance as UAVs share airspace with civil air traffic. This paper describes attitude estimation derived by post-processing data from a small low cost Inertial Navigation System (INS) recorded during the flight of a subscale commercial off the shelf (COTS) UAV. Two discrete time attitude estimation schemes are presented here in detail. The first is an adaptation of the Kalman Filter to accommodate nonlinear systems, the Extended Kalman Filter (EKF). The EKF returns quaternion estimates of the UAV attitude based on MEMS gyro, magnetometer, accelerometer, and pitot tube inputs. The second scheme is the complementary filter which is a simpler algorithm that splits the sensor frequency spectrum based on noise characteristics. The necessity to correct both filters for gravity measurement errors during turning maneuvers is demonstrated. It is shown that the proposed algorithms may be used to estimate UAV attitude. The effects of vibration on sensor measurements are discussed. Heuristic tuning comments pertaining to sensor filtering and gain selection to achieve acceptable performance during flight are given. Comparisons of attitude estimation performance are made between the EKF and the complementary filter.
In-flight angular alignment of inertial navigation systems by means of radio aids
NASA Technical Reports Server (NTRS)
Tanner, W.
1972-01-01
The principles involved in the angular alignment of the inertial reference by nondirectional data from radio aids are developed and compared with conventional methods of alignment such as gyro-compassing and pendulous vertical determination. The specific problem is considered of the space shuttle reentry and a proposed technique for the alignment of the inertial reference system some time before landing. A description is given of the digital simulation of a transponder interrogation system and of its interaction with the inertial navigation system. Data from reentry simulations are used to demonstrate the effectiveness of in-flight inertial system alignment. Concluding remarks refer to other potential applications such as space shuttle orbit insertion and air navigation of conventional aircraft.
NASA Technical Reports Server (NTRS)
Morrell, Frederick R.; Bailey, Melvin L.
1987-01-01
A vector-based failure detection and isolation technique for a skewed array of two degree-of-freedom inertial sensors is developed. Failure detection is based on comparison of parity equations with a threshold, and isolation is based on comparison of logic variables which are keyed to pass/fail results of the parity test. A multi-level approach to failure detection is used to ensure adequate coverage for the flight control, display, and navigation avionics functions. Sensor error models are introduced to expose the susceptibility of the parity equations to sensor errors and physical separation effects. The algorithm is evaluated in a simulation of a commercial transport operating in a range of light to severe turbulence environments. A bias-jump failure level of 0.2 deg/hr was detected and isolated properly in the light and moderate turbulence environments, but not detected in the extreme turbulence environment. An accelerometer bias-jump failure level of 1.5 milli-g was detected over all turbulence environments. For both types of inertial sensor, hard-over, and null type failures were detected in all environments without incident. The algorithm functioned without false alarm or isolation over all turbulence environments for the runs tested.
Inertial Pointing and Positioning System
NASA Technical Reports Server (NTRS)
Yee, Robert (Inventor); Robbins, Fred (Inventor)
1998-01-01
An inertial pointing and control system and method for pointing to a designated target with known coordinates from a platform to provide accurate position, steering, and command information. The system continuously receives GPS signals and corrects Inertial Navigation System (INS) dead reckoning or drift errors. An INS is mounted directly on a pointing instrument rather than in a remote location on the platform for-monitoring the terrestrial position and instrument attitude. and for pointing the instrument at designated celestial targets or ground based landmarks. As a result. the pointing instrument and die INS move independently in inertial space from the platform since the INS is decoupled from the platform. Another important characteristic of the present system is that selected INS measurements are combined with predefined coordinate transformation equations and control logic algorithms under computer control in order to generate inertial pointing commands to the pointing instrument. More specifically. the computer calculates the desired instrument angles (Phi, Theta. Psi). which are then compared to the Euler angles measured by the instrument- mounted INS. and forms the pointing command error angles as a result of the compared difference.
NASA Astrophysics Data System (ADS)
Lu, Jiazhen; Yang, Lie
2018-05-01
To achieve accurate and completely autonomous navigation for spacecraft, inertial/celestial integrated navigation gets increasing attention. In this study, a missile-borne inertial/stellar refraction integrated navigation scheme is proposed. Position Dilution of Precision (PDOP) for stellar refraction is introduced and the corresponding equation is derived. Based on the condition when PDOP reaches the minimum value, an optimized observation scheme is proposed. To verify the feasibility of the proposed scheme, numerical simulation is conducted. The results of the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are compared and impact factors of navigation accuracy are studied in the simulation. The simulation results indicated that the proposed observation scheme has an accurate positioning performance, and the results of EKF and UKF are similar.
Lu, Jiazhen; Yang, Lie
2018-05-01
To achieve accurate and completely autonomous navigation for spacecraft, inertial/celestial integrated navigation gets increasing attention. In this study, a missile-borne inertial/stellar refraction integrated navigation scheme is proposed. Position Dilution of Precision (PDOP) for stellar refraction is introduced and the corresponding equation is derived. Based on the condition when PDOP reaches the minimum value, an optimized observation scheme is proposed. To verify the feasibility of the proposed scheme, numerical simulation is conducted. The results of the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are compared and impact factors of navigation accuracy are studied in the simulation. The simulation results indicated that the proposed observation scheme has an accurate positioning performance, and the results of EKF and UKF are similar.
SLS Block 1-B and Exploration Upper Stage Navigation System Design
NASA Technical Reports Server (NTRS)
Oliver, T. Emerson; Park, Thomas B.; Smith, Austin; Anzalone, Evan; Bernard, Bill; Strickland, Dennis; Geohagan, Kevin; Green, Melissa; Leggett, Jarred
2018-01-01
The SLS Block 1B vehicle is planned to extend NASA's heavy lift capability beyond the initial SLS Block 1 vehicle. The most noticeable change for this vehicle from SLS Block 1 is the swapping of the upper stage from the Interim Cryogenic Propulsion stage (ICPS), a modified Delta IV upper stage, to the more capable Exploration Upper Stage (EUS). As the vehicle evolves to provide greater lift capability and execute more demanding missions so must the SLS Integrated Navigation System to support those missions. The SLS Block 1 vehicle carries two independent navigation systems. The responsibility of the two systems is delineated between ascent and upper stage flight. The Block 1 navigation system is responsible for the phase of flight between the launch pad and insertion into Low-Earth Orbit (LEO). The upper stage system assumes the mission from LEO to payload separation. For the Block 1B vehicle, the two functions are combined into a single system intended to navigate from ground to payload insertion. Both are responsible for self-disposal once payload delivery is achieved. The evolution of the navigation hardware and algorithms from an inertial-only navigation system for Block 1 ascent flight to a tightly coupled GPS-aided inertial navigation system for Block 1-B is described. The Block 1 GN&C system has been designed to meet a LEO insertion target with a specified accuracy. The Block 1-B vehicle navigation system is designed to support the Block 1 LEO target accuracy as well as trans-lunar or trans-planetary injection accuracy. This is measured in terms of payload impact and stage disposal requirements. Additionally, the Block 1-B vehicle is designed to support human exploration and thus is designed to minimize the probability of Loss of Crew (LOC) through high-quality inertial instruments and Fault Detection, Isolation, and Recovery (FDIR) logic. The preliminary Block 1B integrated navigation system design is presented along with the challenges associated with meeting the design objectives. This paper also addresses the design considerations associated with the use of Block 1 and Commercial Off-the-Shelf (COTS) avionics for Block 1-B/EUS as part of an integrated vehicle suite for orbital operations.
Analysis of key technologies in geomagnetic navigation
NASA Astrophysics Data System (ADS)
Zhang, Xiaoming; Zhao, Yan
2008-10-01
Because of the costly price and the error accumulation of high precise Inertial Navigation Systems (INS) and the vulnerability of Global Navigation Satellite Systems (GNSS), the geomagnetic navigation technology, a passive autonomous navigation method, is paid attention again. Geomagnetic field is a natural spatial physical field, and is a function of position and time in near earth space. The navigation technology based on geomagnetic field is researched in a wide range of commercial and military applications. This paper presents the main features and the state-of-the-art of Geomagnetic Navigation System (GMNS). Geomagnetic field models and reference maps are described. Obtaining, modeling and updating accurate Anomaly Magnetic Field information is an important step for high precision geomagnetic navigation. In addition, the errors of geomagnetic measurement using strapdown magnetometers are analyzed. The precise geomagnetic data is obtained by means of magnetometer calibration and vehicle magnetic field compensation. According to the measurement data and reference map or model of geomagnetic field, the vehicle's position and attitude can be obtained using matching algorithm or state-estimating method. The tendency of geomagnetic navigation in near future is introduced at the end of this paper.
NASA Astrophysics Data System (ADS)
Vinande, Eric T.
This research proposes several means to overcome challenges in the urban environment to ground vehicle global positioning system (GPS) receiver navigation performance through the integration of external sensor information. The effects of narrowband radio frequency interference and signal attenuation, both common in the urban environment, are examined with respect to receiver signal tracking processes. Low-cost microelectromechanical systems (MEMS) inertial sensors, suitable for the consumer market, are the focus of receiver augmentation as they provide an independent measure of motion and are independent of vehicle systems. A method for estimating the mounting angles of an inertial sensor cluster utilizing typical urban driving maneuvers is developed and is able to provide angular measurements within two degrees of truth. The integration of GPS and MEMS inertial sensors is developed utilizing a full state navigation filter. Appropriate statistical methods are developed to evaluate the urban environment navigation improvement due to the addition of MEMS inertial sensors. A receiver evaluation metric that combines accuracy, availability, and maximum error measurements is presented and evaluated over several drive tests. Following a description of proper drive test techniques, record and playback systems are evaluated as the optimal way of testing multiple receivers and/or integrated navigation systems in the urban environment as they simplify vehicle testing requirements.
A new systematic calibration method of ring laser gyroscope inertial navigation system
NASA Astrophysics Data System (ADS)
Wei, Guo; Gao, Chunfeng; Wang, Qi; Wang, Qun; Xiong, Zhenyu; Long, Xingwu
2016-10-01
Inertial navigation system has been the core component of both military and civil navigation systems. Before the INS is put into application, it is supposed to be calibrated in the laboratory in order to compensate repeatability error caused by manufacturing. Discrete calibration method cannot fulfill requirements of high-accurate calibration of the mechanically dithered ring laser gyroscope navigation system with shock absorbers. This paper has analyzed theories of error inspiration and separation in detail and presented a new systematic calibration method for ring laser gyroscope inertial navigation system. Error models and equations of calibrated Inertial Measurement Unit are given. Then proper rotation arrangement orders are depicted in order to establish the linear relationships between the change of velocity errors and calibrated parameter errors. Experiments have been set up to compare the systematic errors calculated by filtering calibration result with those obtained by discrete calibration result. The largest position error and velocity error of filtering calibration result are only 0.18 miles and 0.26m/s compared with 2 miles and 1.46m/s of discrete calibration result. These results have validated the new systematic calibration method and proved its importance for optimal design and accuracy improvement of calibration of mechanically dithered ring laser gyroscope inertial navigation system.
Zhang, Jiayu; Li, Jie; Zhang, Xi; Che, Xiaorui; Huang, Yugang; Feng, Kaiqiang
2018-01-01
The Semi-Strapdown Inertial Navigation System (SSINS) provides a new solution to attitude measurement of a high-speed rotating missile. However, micro-electro-mechanical-systems (MEMS) inertial measurement unit (MIMU) outputs are corrupted by significant sensor errors. In order to improve the navigation precision, a rotation modulation technology method called Rotation Semi-Strapdown Inertial Navigation System (RSSINS) is introduced into SINS. In fact, the stability of the modulation angular rate is difficult to achieve in a high-speed rotation environment. The changing rotary angular rate has an impact on the inertial sensor error self-compensation. In this paper, the influence of modulation angular rate error, including acceleration-deceleration process, and instability of the angular rate on the navigation accuracy of RSSINS is deduced and the error characteristics of the reciprocating rotation scheme are analyzed. A new compensation method is proposed to remove or reduce sensor errors so as to make it possible to maintain high precision autonomous navigation performance by MIMU when there is no external aid. Experiments have been carried out to validate the performance of the method. In addition, the proposed method is applicable for modulation angular rate error compensation under various dynamic conditions. PMID:29734707
AUV Underwater Positioning Algorithm Based on Interactive Assistance of SINS and LBL
Zhang, Tao; Chen, Liping; Li, Yao
2015-01-01
This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a three-dimensional TDOA positioning algorithm of Taylor series expansion and a multi-sensor information fusion algorithm. The final simulation results show that compared to traditional underwater positioning algorithms, this scheme can not only directly correct accumulative errors caused by a dead reckoning algorithm, but also solves the problem of ambiguous correlation peaks caused by multipath transmission of underwater acoustic signals. The proposed method can calibrate the accumulative error of the AUV position more directly and effectively, which prolongs the underwater operating duration of the AUV. PMID:26729120
An Effective Terrain Aided Navigation for Low-Cost Autonomous Underwater Vehicles.
Zhou, Ling; Cheng, Xianghong; Zhu, Yixian; Dai, Chenxi; Fu, Jinbo
2017-03-25
Terrain-aided navigation is a potentially powerful solution for obtaining submerged position fixes for autonomous underwater vehicles. The application of terrain-aided navigation with high-accuracy inertial navigation systems has demonstrated meter-level navigation accuracy in sea trials. However, available sensors may be limited depending on the type of the mission. Such limitations, especially for low-grade navigation sensors, not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ terrain-aided navigation. To address this problem, a tightly-coupled navigation is presented to successfully estimate the critical sensor errors by incorporating raw sensor data directly into an augmented navigation system. Furthermore, three-dimensional distance errors are calculated, providing measurement updates through the particle filter for absolute and bounded position error. The development of the terrain aided navigation system is elaborated for a vehicle equipped with a non-inertial-grade strapdown inertial navigation system, a 4-beam Doppler Velocity Log range sensor and a sonar altimeter. Using experimental data for navigation performance evaluation in areas with different terrain characteristics, the experiment results further show that the proposed method can be successfully applied to the low-cost AUVs and significantly improves navigation performance.
An Effective Terrain Aided Navigation for Low-Cost Autonomous Underwater Vehicles
Zhou, Ling; Cheng, Xianghong; Zhu, Yixian; Dai, Chenxi; Fu, Jinbo
2017-01-01
Terrain-aided navigation is a potentially powerful solution for obtaining submerged position fixes for autonomous underwater vehicles. The application of terrain-aided navigation with high-accuracy inertial navigation systems has demonstrated meter-level navigation accuracy in sea trials. However, available sensors may be limited depending on the type of the mission. Such limitations, especially for low-grade navigation sensors, not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ terrain-aided navigation. To address this problem, a tightly-coupled navigation is presented to successfully estimate the critical sensor errors by incorporating raw sensor data directly into an augmented navigation system. Furthermore, three-dimensional distance errors are calculated, providing measurement updates through the particle filter for absolute and bounded position error. The development of the terrain aided navigation system is elaborated for a vehicle equipped with a non-inertial-grade strapdown inertial navigation system, a 4-beam Doppler Velocity Log range sensor and a sonar altimeter. Using experimental data for navigation performance evaluation in areas with different terrain characteristics, the experiment results further show that the proposed method can be successfully applied to the low-cost AUVs and significantly improves navigation performance. PMID:28346346
Analysis of navigation and guidance requirements for commercial VTOL operations
NASA Technical Reports Server (NTRS)
Hoffman, W. C.; Zvara, J.; Hollister, W. M.
1975-01-01
The paper presents some results of a program undertaken to define navigation and guidance requirements for commercial VTOL operations in the takeoff, cruise, terminal and landing phases of flight in weather conditions up to and including Category III. Quantitative navigation requirements are given for the parameters range, coverage, operation near obstacles, horizontal accuracy, multiple landing aircraft, multiple pad requirements, inertial/radio-inertial requirements, reliability/redundancy, update rate, and data link requirements in all flight phases. A multi-configuration straw-man navigation and guidance system for commercial VTOL operations is presented. Operation of the system is keyed to a fully automatic approach for navigation, guidance and control, with pilot as monitor-manager. The system is a hybrid navigator using a relatively low-cost inertial sensor with DME updates and MLS in the approach/departure phases.
Li, Zheng; Zhang, Hai; Zhou, Qifan; Che, Huan
2017-09-05
The main objective of the introduced study is to design an adaptive Inertial Navigation System/Global Navigation Satellite System (INS/GNSS) tightly-coupled integration system that can provide more reliable navigation solutions by making full use of an adaptive Kalman filter (AKF) and satellite selection algorithm. To achieve this goal, we develop a novel redundant measurement noise covariance estimation (RMNCE) theorem, which adaptively estimates measurement noise properties by analyzing the difference sequences of system measurements. The proposed RMNCE approach is then applied to design both a modified weighted satellite selection algorithm and a type of adaptive unscented Kalman filter (UKF) to improve the performance of the tightly-coupled integration system. In addition, an adaptive measurement noise covariance expanding algorithm is developed to mitigate outliers when facing heavy multipath and other harsh situations. Both semi-physical simulation and field experiments were conducted to evaluate the performance of the proposed architecture and were compared with state-of-the-art algorithms. The results validate that the RMNCE provides a significant improvement in the measurement noise covariance estimation and the proposed architecture can improve the accuracy and reliability of the INS/GNSS tightly-coupled systems. The proposed architecture can effectively limit positioning errors under conditions of poor GNSS measurement quality and outperforms all the compared schemes.
Li, Zheng; Zhang, Hai; Zhou, Qifan; Che, Huan
2017-01-01
The main objective of the introduced study is to design an adaptive Inertial Navigation System/Global Navigation Satellite System (INS/GNSS) tightly-coupled integration system that can provide more reliable navigation solutions by making full use of an adaptive Kalman filter (AKF) and satellite selection algorithm. To achieve this goal, we develop a novel redundant measurement noise covariance estimation (RMNCE) theorem, which adaptively estimates measurement noise properties by analyzing the difference sequences of system measurements. The proposed RMNCE approach is then applied to design both a modified weighted satellite selection algorithm and a type of adaptive unscented Kalman filter (UKF) to improve the performance of the tightly-coupled integration system. In addition, an adaptive measurement noise covariance expanding algorithm is developed to mitigate outliers when facing heavy multipath and other harsh situations. Both semi-physical simulation and field experiments were conducted to evaluate the performance of the proposed architecture and were compared with state-of-the-art algorithms. The results validate that the RMNCE provides a significant improvement in the measurement noise covariance estimation and the proposed architecture can improve the accuracy and reliability of the INS/GNSS tightly-coupled systems. The proposed architecture can effectively limit positioning errors under conditions of poor GNSS measurement quality and outperforms all the compared schemes. PMID:28872629
Innovative use of global navigation satellite systems for flight inspection
NASA Astrophysics Data System (ADS)
Kim, Eui-Ho
The International Civil Aviation Organization (ICAO) mandates flight inspection in every country to provide safety during flight operations. Among many criteria of flight inspection, airborne inspection of Instrument Landing Systems (ILS) is very important because the ILS is the primary landing guidance system worldwide. During flight inspection of the ILS, accuracy in ILS landing guidance is checked by using a Flight Inspection System (FIS). Therefore, a flight inspection system must have high accuracy in its positioning capability to detect any deviation so that accurate guidance of the ILS can be maintained. Currently, there are two Automated Flight Inspection Systems (AFIS). One is called Inertial-based AFIS, and the other one is called Differential GPS-based (DGPS-based) AFIS. The Inertial-based AFIS enables efficient flight inspection procedures, but its drawback is high cost because it requires a navigation-grade Inertial Navigation System (INS). On the other hand, the DGPS-based AFIS has relatively low cost, but flight inspection procedures require landing and setting up a reference receiver. Most countries use either one of the systems based on their own preferences. There are around 1200 ILS in the U.S., and each ILS must be inspected every 6 to 9 months. Therefore, it is important to manage the airborne inspection of the ILS in a very efficient manner. For this reason, the Federal Aviation Administration (FAA) mainly uses the Inertial-based AFIS, which has better efficiency than the DGPS-based AFIS in spite of its high cost. Obviously, the FAA spends tremendous resources on flight inspection. This thesis investigates the value of GPS and the FAA's augmentation to GPS for civil aviation called the Wide Area Augmentation System (or WAAS) for flight inspection. Because standard GPS or WAAS position outputs cannot meet the required accuracy for flight inspection, in this thesis, various algorithms are developed to improve the positioning ability of Flight Inspection Systems (FIS) by using GPS and WAAS in novel manners. The algorithms include Adaptive Carrier Smoothing (ACS), optimizing WAAS accuracy and stability, and reference point-based precise relative positioning for real-time and near-real-time applications. The developed systems are WAAS-aided FIS, WAAS-based FIS, and stand-alone GPS-based FIS. These systems offer both high efficiency and low cost, and they have different advantages over one another in terms of accuracy, integrity, and worldwide availability. The performance of each system is tested with experimental flight test data and shown to have accuracy that is sufficient for flight inspection and superior to the current Inertial-based AFIS.
14 CFR 121.355 - Equipment for operations on which specialized means of navigation are used.
Code of Federal Regulations, 2010 CFR
2010-01-01
.... (a) No certificate holder may conduct an operation— (1) Using Doppler Radar or an Inertial Navigation... approved in accordance with appendix G to this part; or (2) Using Doppler Radar or an Inertial Navigation... authorized for the particular operation. (b) Notwithstanding paragraph (a) of this section, Doppler Radar and...
14 CFR 121.355 - Equipment for operations on which specialized means of navigation are used.
Code of Federal Regulations, 2011 CFR
2011-01-01
.... (a) No certificate holder may conduct an operation— (1) Using Doppler Radar or an Inertial Navigation... approved in accordance with appendix G to this part; or (2) Using Doppler Radar or an Inertial Navigation... authorized for the particular operation. (b) Notwithstanding paragraph (a) of this section, Doppler Radar and...
14 CFR 121.355 - Equipment for operations on which specialized means of navigation are used.
Code of Federal Regulations, 2012 CFR
2012-01-01
.... (a) No certificate holder may conduct an operation— (1) Using Doppler Radar or an Inertial Navigation... approved in accordance with appendix G to this part; or (2) Using Doppler Radar or an Inertial Navigation... authorized for the particular operation. (b) Notwithstanding paragraph (a) of this section, Doppler Radar and...
14 CFR 121.355 - Equipment for operations on which specialized means of navigation are used.
Code of Federal Regulations, 2014 CFR
2014-01-01
.... (a) No certificate holder may conduct an operation— (1) Using Doppler Radar or an Inertial Navigation... approved in accordance with appendix G to this part; or (2) Using Doppler Radar or an Inertial Navigation... authorized for the particular operation. (b) Notwithstanding paragraph (a) of this section, Doppler Radar and...
14 CFR 121.355 - Equipment for operations on which specialized means of navigation are used.
Code of Federal Regulations, 2013 CFR
2013-01-01
.... (a) No certificate holder may conduct an operation— (1) Using Doppler Radar or an Inertial Navigation... approved in accordance with appendix G to this part; or (2) Using Doppler Radar or an Inertial Navigation... authorized for the particular operation. (b) Notwithstanding paragraph (a) of this section, Doppler Radar and...
Tian, Xiaochun; Chen, Jiabin; Han, Yongqiang; Shang, Jianyu; Li, Nan
2016-01-01
Zero velocity update (ZUPT) plays an important role in pedestrian navigation algorithms with the premise that the zero velocity interval (ZVI) should be detected accurately and effectively. A novel adaptive ZVI detection algorithm based on a smoothed pseudo Wigner–Ville distribution to remove multiple frequencies intelligently (SPWVD-RMFI) is proposed in this paper. The novel algorithm adopts the SPWVD-RMFI method to extract the pedestrian gait frequency and to calculate the optimal ZVI detection threshold in real time by establishing the function relationships between the thresholds and the gait frequency; then, the adaptive adjustment of thresholds with gait frequency is realized and improves the ZVI detection precision. To put it into practice, a ZVI detection experiment is carried out; the result shows that compared with the traditional fixed threshold ZVI detection method, the adaptive ZVI detection algorithm can effectively reduce the false and missed detection rate of ZVI; this indicates that the novel algorithm has high detection precision and good robustness. Furthermore, pedestrian trajectory positioning experiments at different walking speeds are carried out to evaluate the influence of the novel algorithm on positioning precision. The results show that the ZVI detected by the adaptive ZVI detection algorithm for pedestrian trajectory calculation can achieve better performance. PMID:27669266
Closing the Gap Between Research and Field Applications for Multi-UAV Cooperative Missions
2013-09-01
IMU Inertial Measurement Units INCOSE International Council on Systems Engineering ISR Intelligence Surveillance and Reconnaissance ISTAR...light-weight and low-cost inertial measurement units ( IMUs ) are widely adopted for navigation of small- scale UAVs. Low-costs IMUs are characterized...by high measurement noises and large measurement biases. Hence pure initial navigation using low-cost IMUs drifts rapidly. In practice, inertial
Gyroscope-reduced inertial navigation system for flight vehicle motion estimation
NASA Astrophysics Data System (ADS)
Wang, Xin; Xiao, Lu
2017-01-01
In this paper, a novel configuration of strategically distributed accelerometer sensors with the aid of one gyro to infer a flight vehicle's angular motion is presented. The MEMS accelerometer and gyro sensors are integrated to form a gyroscope-reduced inertial measurement unit (GR-IMU). The motivation for gyro aided accelerometers array is to have direct measurements of angular rates, which is an improvement to the traditional gyroscope-free inertial system that employs only direct measurements of specific force. Some technical issues regarding error calibration in accelerometers and gyro in GR-IMU are put forward. The GR-IMU based inertial navigation system can be used to find a complete attitude solution for flight vehicle motion estimation. Results of numerical simulation are given to illustrate the effectiveness of the proposed configuration. The gyroscope-reduced inertial navigation system based on distributed accelerometer sensors can be developed into a cost effective solution for a fast reaction, MEMS based motion capture system. Future work will include the aid from external navigation references (e.g. GPS) to improve long time mission performance.
Meta-image navigation augmenters for unmanned aircraft systems (MINA for UAS)
NASA Astrophysics Data System (ADS)
Òªelik, Koray; Somani, Arun K.; Schnaufer, Bernard; Hwang, Patrick Y.; McGraw, Gary A.; Nadke, Jeremy
2013-05-01
GPS is a critical sensor for Unmanned Aircraft Systems (UASs) due to its accuracy, global coverage and small hardware footprint, but is subject to denial due to signal blockage or RF interference. When GPS is unavailable, position, velocity and attitude (PVA) performance from other inertial and air data sensors is not sufficient, especially for small UASs. Recently, image-based navigation algorithms have been developed to address GPS outages for UASs, since most of these platforms already include a camera as standard equipage. Performing absolute navigation with real-time aerial images requires georeferenced data, either images or landmarks, as a reference. Georeferenced imagery is readily available today, but requires a large amount of storage, whereas collections of discrete landmarks are compact but must be generated by pre-processing. An alternative, compact source of georeferenced data having large coverage area is open source vector maps from which meta-objects can be extracted for matching against real-time acquired imagery. We have developed a novel, automated approach called MINA (Meta Image Navigation Augmenters), which is a synergy of machine-vision and machine-learning algorithms for map aided navigation. As opposed to existing image map matching algorithms, MINA utilizes publicly available open-source geo-referenced vector map data, such as OpenStreetMap, in conjunction with real-time optical imagery from an on-board, monocular camera to augment the UAS navigation computer when GPS is not available. The MINA approach has been experimentally validated with both actual flight data and flight simulation data and results are presented in the paper.
Code of Federal Regulations, 2010 CFR
2010-01-01
... latitudes, a review of navigation, flight planning, and applicable meteorology. (3) The methods for updating... Radar or Inertial Navigation System must submit a request for evaluation of the system to the Flight... operations 30 days prior to the start of evaluation flights. (b) The application must contain: (1) A summary...
Code of Federal Regulations, 2014 CFR
2014-01-01
... latitudes, a review of navigation, flight planning, and applicable meteorology. (3) The methods for updating... Radar or Inertial Navigation System must submit a request for evaluation of the system to the Flight... operations 30 days prior to the start of evaluation flights. (b) The application must contain: (1) A summary...
Code of Federal Regulations, 2013 CFR
2013-01-01
... latitudes, a review of navigation, flight planning, and applicable meteorology. (3) The methods for updating... Radar or Inertial Navigation System must submit a request for evaluation of the system to the Flight... operations 30 days prior to the start of evaluation flights. (b) The application must contain: (1) A summary...
Code of Federal Regulations, 2011 CFR
2011-01-01
... latitudes, a review of navigation, flight planning, and applicable meteorology. (3) The methods for updating... Radar or Inertial Navigation System must submit a request for evaluation of the system to the Flight... operations 30 days prior to the start of evaluation flights. (b) The application must contain: (1) A summary...
Code of Federal Regulations, 2012 CFR
2012-01-01
... latitudes, a review of navigation, flight planning, and applicable meteorology. (3) The methods for updating... Radar or Inertial Navigation System must submit a request for evaluation of the system to the Flight... operations 30 days prior to the start of evaluation flights. (b) The application must contain: (1) A summary...
Development of a GPS/INS/MAG navigation system and waypoint navigator for a VTOL UAV
NASA Astrophysics Data System (ADS)
Meister, Oliver; Mönikes, Ralf; Wendel, Jan; Frietsch, Natalie; Schlaile, Christian; Trommer, Gert F.
2007-04-01
Unmanned aerial vehicles (UAV) can be used for versatile surveillance and reconnaissance missions. If a UAV is capable of flying automatically on a predefined path the range of possible applications is widened significantly. This paper addresses the development of the integrated GPS/INS/MAG navigation system and a waypoint navigator for a small vertical take-off and landing (VTOL) unmanned four-rotor helicopter with a take-off weight below 1 kg. The core of the navigation system consists of low cost inertial sensors which are continuously aided with GPS, magnetometer compass, and a barometric height information. Due to the fact, that the yaw angle becomes unobservable during hovering flight, the integration with a magnetic compass is mandatory. This integration must be robust with respect to errors caused by the terrestrial magnetic field deviation and interferences from surrounding electronic devices as well as ferrite metals. The described integration concept with a Kalman filter overcomes the problem that erroneous magnetic measurements yield to an attitude error in the roll and pitch axis. The algorithm provides long-term stable navigation information even during GPS outages which is mandatory for the flight control of the UAV. In the second part of the paper the guidance algorithms are discussed in detail. These algorithms allow the UAV to operate in a semi-autonomous mode position hold as well an complete autonomous waypoint mode. In the position hold mode the helicopter maintains its position regardless of wind disturbances which ease the pilot job during hold-and-stare missions. The autonomous waypoint navigator enable the flight outside the range of vision and beyond the range of the radio link. Flight test results of the implemented modes of operation are shown.
STEPPING - Smartphone-Based Portable Pedestrian Indoor Navigation
NASA Astrophysics Data System (ADS)
Lukianto, C.; Sternberg, H.
2011-12-01
Many current smartphones are fitted with GPS receivers, which, in combination with a map application form a pedestrian navigation system for outdoor purposes. However, once an area with insufficient satellite signal coverage is entered, these navigation systems cease to function. For indoor positioning, there are already several solutions available which are usually based on measured distances to reference points. These solutions can achieve resolutions as low as the sub-millimetre range depending on the complexity of the set-up. STEPPING project, developed at HCU Hamburg Germany aims at designing an indoor navigation system consisting of a small inertial navigation system and a new, robust sensor fusion algorithm running on a current smartphone. As this system is theoretically able to integrate any available positioning method, it is independent of a particular method and can thus be realized on a smartphone without affecting user mobility. Potential applications include --but are not limited to: Large trade fairs, airports, parking decks and shopping malls, as well as ambient assisted living scenarios.
NASA Astrophysics Data System (ADS)
Yu, Yuting; Cheng, Ming
2018-05-01
Aiming at various configuration scheme and inertial measurement units of Strapdown Inertial Navigation System, selected tetrahedron skew configuration and coaxial orthogonal configuration by nine low cost IMU to build system. Calculation and simulation the performance index, reliability and fault diagnosis ability of the navigation system. Analysis shows that the reliability and reconfiguration scheme of skew configuration is superior to the orthogonal configuration scheme, while the performance index and fault diagnosis ability of the system are similar. The work in this paper provides a strong reference for the selection of engineering applications.
Tawk, Youssef; Tomé, Phillip; Botteron, Cyril; Stebler, Yannick; Farine, Pierre-André
2014-01-01
The use of global navigation satellite system receivers for navigation still presents many challenges in urban canyon and indoor environments, where satellite availability is typically reduced and received signals are attenuated. To improve the navigation performance in such environments, several enhancement methods can be implemented. For instance, external aid provided through coupling with other sensors has proven to contribute substantially to enhancing navigation performance and robustness. Within this context, coupling a very simple GPS receiver with an Inertial Navigation System (INS) based on low-cost micro-electro-mechanical systems (MEMS) inertial sensors is considered in this paper. In particular, we propose a GPS/INS Tightly Coupled Assisted PLL (TCAPLL) architecture, and present most of the associated challenges that need to be addressed when dealing with very-low-performance MEMS inertial sensors. In addition, we propose a data monitoring system in charge of checking the quality of the measurement flow in the architecture. The implementation of the TCAPLL is discussed in detail, and its performance under different scenarios is assessed. Finally, the architecture is evaluated through a test campaign using a vehicle that is driven in urban environments, with the purpose of highlighting the pros and cons of combining MEMS inertial sensors with GPS over GPS alone. PMID:24569773
Integrated INS/GPS Navigation from a Popular Perspective
NASA Technical Reports Server (NTRS)
Omerbashich, Mensur
2002-01-01
Inertial navigation, blended with other navigation aids, Global Positioning System (GPS) in particular, has gained significance due to enhanced navigation and inertial reference performance and dissimilarity for fault tolerance and anti-jamming. Relatively new concepts based upon using Differential GPS (DGPS) blended with Inertial (and visual) Navigation Sensors (INS) offer the possibility of low cost, autonomous aircraft landing. The FAA has decided to implement the system in a sophisticated form as a new standard navigation tool during this decade. There have been a number of new inertial sensor concepts in the recent past that emphasize increased accuracy of INS/GPS versus INS and reliability of navigation, as well as lower size and weight, and higher power, fault tolerance, and long life. The principles of GPS are not discussed; rather the attention is directed towards general concepts and comparative advantages. A short introduction to the problems faced in kinematics is presented. The intention is to relate the basic principles of kinematics to probably the most used navigation method in the future-INS/GPS. An example of the airborne INS is presented, with emphasis on how it works. The discussion of the error types and sources in navigation, and of the role of filters in optimal estimation of the errors then follows. The main question this paper is trying to answer is 'What are the benefits of the integration of INS and GPS and how is this, navigation concept of the future achieved in reality?' The main goal is to communicate the idea about what stands behind a modern navigation method.
SGA-WZ: A New Strapdown Airborne Gravimeter
Huang, Yangming; Olesen, Arne Vestergaard; Wu, Meiping; Zhang, Kaidong
2012-01-01
Inertial navigation systems and gravimeters are now routinely used to map the regional gravitational quantities from an aircraft with mGal accuracy and a spatial resolution of a few kilometers. However, airborne gravimeter of this kind is limited by the inaccuracy of the inertial sensor performance, the integrated navigation technique and the kinematic acceleration determination. As the GPS technique developed, the vehicle acceleration determination is no longer the limiting factor in airborne gravity due to the cancellation of the common mode acceleration in differential mode. A new airborne gravimeter taking full advantage of the inertial navigation system is described with improved mechanical design, high precision time synchronization, better thermal control and optimized sensor modeling. Apart from the general usage, the Global Positioning System (GPS) after differentiation is integrated to the inertial navigation system which provides not only more precise altitude information along with the navigation aiding, but also an effective way to calculate the vehicle acceleration. Design description and test results on the performance of the gyroscopes and accelerations will be emphasized. Analysis and discussion of the airborne field test results are also given. PMID:23012545
Li, Zong-Tao; Wu, Tie-Jun; Lin, Can-Long; Ma, Long-Hua
2011-01-01
A new generalized optimum strapdown algorithm with coning and sculling compensation is presented, in which the position, velocity and attitude updating operations are carried out based on the single-speed structure in which all computations are executed at a single updating rate that is sufficiently high to accurately account for high frequency angular rate and acceleration rectification effects. Different from existing algorithms, the updating rates of the coning and sculling compensations are unrelated with the number of the gyro incremental angle samples and the number of the accelerometer incremental velocity samples. When the output sampling rate of inertial sensors remains constant, this algorithm allows increasing the updating rate of the coning and sculling compensation, yet with more numbers of gyro incremental angle and accelerometer incremental velocity in order to improve the accuracy of system. Then, in order to implement the new strapdown algorithm in a single FPGA chip, the parallelization of the algorithm is designed and its computational complexity is analyzed. The performance of the proposed parallel strapdown algorithm is tested on the Xilinx ISE 12.3 software platform and the FPGA device XC6VLX550T hardware platform on the basis of some fighter data. It is shown that this parallel strapdown algorithm on the FPGA platform can greatly decrease the execution time of algorithm to meet the real-time and high precision requirements of system on the high dynamic environment, relative to the existing implemented on the DSP platform. PMID:22164058
Stellar Inertial Navigation Workstation
NASA Technical Reports Server (NTRS)
Johnson, W.; Johnson, B.; Swaminathan, N.
1989-01-01
Software and hardware assembled to support specific engineering activities. Stellar Inertial Navigation Workstation (SINW) is integrated computer workstation providing systems and engineering support functions for Space Shuttle guidance and navigation-system logistics, repair, and procurement activities. Consists of personal-computer hardware, packaged software, and custom software integrated together into user-friendly, menu-driven system. Designed to operate on IBM PC XT. Applied in business and industry to develop similar workstations.
2007-01-01
Intelligent Robots and Systems, vol- ume 1, pp. 123–128, September 2002. [2] R. G. Brown and P. Y. Hwang . Introduction to Ran- dom Signals and Applied... Kalman Filter-based) method for calculat- ing a trajectory by tracking features at an unknown location on the Earth’s surface, provided the topography...Extended Kalman Filter (EKF) and an automatic target tracking algorithm. In the following section, the integration architecture is presented, which in
NASA tracking ship navigation systems
NASA Technical Reports Server (NTRS)
Mckenna, J. J.
1976-01-01
The ship position and attitude measurement system that was installed aboard the tracking ship Vanguard is described. An overview of the entire system is given along with a description of how precise time and frequency is utilized. The instrumentation is broken down into its basic components. Particular emphasis is given to the inertial navigation system. Each navigation system used, a mariner star tracker, navigation satellite system, Loran C and OMEGA in conjunction with the inertial system is described. The accuracy of each system is compared along with their limitations.
Spatial filtering self-velocimeter for vehicle application using a CMOS linear image sensor
NASA Astrophysics Data System (ADS)
He, Xin; Zhou, Jian; Nie, Xiaoming; Long, Xingwu
2015-03-01
The idea of using a spatial filtering velocimeter (SFV) to measure the velocity of a vehicle for an inertial navigation system is put forward. The presented SFV is based on a CMOS linear image sensor with a high-speed data rate, large pixel size, and built-in timing generator. These advantages make the image sensor suitable to measure vehicle velocity. The power spectrum of the output signal is obtained by fast Fourier transform and is corrected by a frequency spectrum correction algorithm. This velocimeter was used to measure the velocity of a conveyor belt driven by a rotary table and the measurement uncertainty is ˜0.54%. Furthermore, it was also installed on a vehicle together with a laser Doppler velocimeter (LDV) to measure self-velocity. The measurement result of the designed SFV is compared with that of the LDV. It is shown that the measurement result of the SFV is coincident with that of the LDV. Therefore, the designed SFV is suitable for a vehicle self-contained inertial navigation system.
NASA Astrophysics Data System (ADS)
Theil, S.; Ammann, N.; Andert, F.; Franz, T.; Krüger, H.; Lehner, H.; Lingenauber, M.; Lüdtke, D.; Maass, B.; Paproth, C.; Wohlfeil, J.
2018-03-01
Since 2010 the German Aerospace Center is working on the project Autonomous Terrain-based Optical Navigation (ATON). Its objective is the development of technologies which allow autonomous navigation of spacecraft in orbit around and during landing on celestial bodies like the Moon, planets, asteroids and comets. The project developed different image processing techniques and optical navigation methods as well as sensor data fusion. The setup—which is applicable to many exploration missions—consists of an inertial measurement unit, a laser altimeter, a star tracker and one or multiple navigation cameras. In the past years, several milestones have been achieved. It started with the setup of a simulation environment including the detailed simulation of camera images. This was continued by hardware-in-the-loop tests in the Testbed for Robotic Optical Navigation (TRON) where images were generated by real cameras in a simulated downscaled lunar landing scene. Data were recorded in helicopter flight tests and post-processed in real-time to increase maturity of the algorithms and to optimize the software. Recently, two more milestones have been achieved. In late 2016, the whole navigation system setup was flying on an unmanned helicopter while processing all sensor information onboard in real time. For the latest milestone the navigation system was tested in closed-loop on the unmanned helicopter. For that purpose the ATON navigation system provided the navigation state for the guidance and control of the unmanned helicopter replacing the GPS-based standard navigation system. The paper will give an introduction to the ATON project and its concept. The methods and algorithms of ATON are briefly described. The flight test results of the latest two milestones are presented and discussed.
NASA Astrophysics Data System (ADS)
Trigo, Guilherme F.; Maass, Bolko; Krüger, Hans; Theil, Stephan
2018-01-01
Accurate autonomous navigation capabilities are essential for future lunar robotic landing missions with a pin-point landing requirement, since in the absence of direct line of sight to ground control during critical approach and landing phases, or when facing long signal delays the herein before mentioned capability is needed to establish a guidance solution to reach the landing site reliably. This paper focuses on the processing and evaluation of data collected from flight tests that consisted of scaled descent scenarios where the unmanned helicopter of approximately 85 kg approached a landing site from altitudes of 50 m down to 1 m for a downrange distance of 200 m. Printed crater targets were distributed along the ground track and their detection provided earth-fixed measurements. The Crater Navigation (CNav) algorithm used to detect and match the crater targets is an unmodified method used for real lunar imagery. We analyze the absolute position and attitude solutions of CNav obtained and recorded during these flight tests, and investigate the attainable quality of vehicle pose estimation using both CNav and measurements from a tactical-grade inertial measurement unit. The navigation filter proposed for this end corrects and calibrates the high-rate inertial propagation with the less frequent crater navigation fixes through a closed-loop, loosely coupled hybrid setup. Finally, the attainable accuracy of the fused solution is evaluated by comparison with the on-board ground-truth solution of a dual-antenna high-grade GNSS receiver. It is shown that the CNav is an enabler for building autonomous navigation systems with high quality and suitability for exploration mission scenarios.
GPS/Optical/Inertial Integration for 3D Navigation Using Multi-Copter Platforms
NASA Technical Reports Server (NTRS)
Dill, Evan T.; Young, Steven D.; Uijt De Haag, Maarten
2017-01-01
In concert with the continued advancement of a UAS traffic management system (UTM), the proposed uses of autonomous unmanned aerial systems (UAS) have become more prevalent in both the public and private sectors. To facilitate this anticipated growth, a reliable three-dimensional (3D) positioning, navigation, and mapping (PNM) capability will be required to enable operation of these platforms in challenging environments where global navigation satellite systems (GNSS) may not be available continuously. Especially, when the platform's mission requires maneuvering through different and difficult environments like outdoor opensky, outdoor under foliage, outdoor-urban and indoor, and may include transitions between these environments. There may not be a single method to solve the PNM problem for all environments. The research presented in this paper is a subset of a broader research effort, described in [1]. The research is focused on combining data from dissimilar sensor technologies to create an integrated navigation and mapping method that can enable reliable operation in both an outdoor and structured indoor environment. The integrated navigation and mapping design is utilizes a Global Positioning System (GPS) receiver, an Inertial Measurement Unit (IMU), a monocular digital camera, and three short to medium range laser scanners. This paper describes specifically the techniques necessary to effectively integrate the monocular camera data within the established mechanization. To evaluate the developed algorithms a hexacopter was built, equipped with the discussed sensors, and both hand-carried and flown through representative environments. This paper highlights the effect that the monocular camera has on the aforementioned sensor integration scheme's reliability, accuracy and availability.
NASA Technical Reports Server (NTRS)
Knox, C. E.
1978-01-01
Navigation error data from these flights are presented in a format utilizing three independent axes - horizontal, vertical, and time. The navigation position estimate error term and the autopilot flight technical error term are combined to form the total navigation error in each axis. This method of error presentation allows comparisons to be made between other 2-, 3-, or 4-D navigation systems and allows experimental or theoretical determination of the navigation error terms. Position estimate error data are presented with the navigation system position estimate based on dual DME radio updates that are smoothed with inertial velocities, dual DME radio updates that are smoothed with true airspeed and magnetic heading, and inertial velocity updates only. The normal mode of navigation with dual DME updates that are smoothed with inertial velocities resulted in a mean error of 390 m with a standard deviation of 150 m in the horizontal axis; a mean error of 1.5 m low with a standard deviation of less than 11 m in the vertical axis; and a mean error as low as 252 m with a standard deviation of 123 m in the time axis.
Cheng, Jianhua; Wang, Tongda; Wang, Lu; Wang, Zhenmin
2017-10-23
Because of the harsh polar environment, the master strapdown inertial navigation system (SINS) has low accuracy and the system model information becomes abnormal. In this case, existing polar transfer alignment (TA) algorithms which use the measurement information provided by master SINS would lose their effectiveness. In this paper, a new polar TA algorithm with the aid of a star sensor and based on an adaptive unscented Kalman filter (AUKF) is proposed to deal with the problems. Since the measurement information provided by master SINS is inaccurate, the accurate information provided by the star sensor is chosen as the measurement. With the compensation of lever-arm effect and the model of star sensor, the nonlinear navigation equations are derived. Combined with the attitude matching method, the filter models for polar TA are designed. An AUKF is introduced to solve the abnormal information of system model. Then, the AUKF is used to estimate the states of TA. Results have demonstrated that the performance of the new polar TA algorithm is better than the state-of-the-art polar TA algorithms. Therefore, the new polar TA algorithm proposed in this paper is effectively to ensure and improve the accuracy of TA in the harsh polar environment.
Cheng, Jianhua; Wang, Tongda; Wang, Lu; Wang, Zhenmin
2017-01-01
Because of the harsh polar environment, the master strapdown inertial navigation system (SINS) has low accuracy and the system model information becomes abnormal. In this case, existing polar transfer alignment (TA) algorithms which use the measurement information provided by master SINS would lose their effectiveness. In this paper, a new polar TA algorithm with the aid of a star sensor and based on an adaptive unscented Kalman filter (AUKF) is proposed to deal with the problems. Since the measurement information provided by master SINS is inaccurate, the accurate information provided by the star sensor is chosen as the measurement. With the compensation of lever-arm effect and the model of star sensor, the nonlinear navigation equations are derived. Combined with the attitude matching method, the filter models for polar TA are designed. An AUKF is introduced to solve the abnormal information of system model. Then, the AUKF is used to estimate the states of TA. Results have demonstrated that the performance of the new polar TA algorithm is better than the state-of-the-art polar TA algorithms. Therefore, the new polar TA algorithm proposed in this paper is effectively to ensure and improve the accuracy of TA in the harsh polar environment. PMID:29065521
NASA Astrophysics Data System (ADS)
Chen, Yuanpei; Wang, Lingcao; Li, Kui
2017-10-01
Rotary inertial navigation modulation mechanism can greatly improve the inertial navigation system (INS) accuracy through the rotation. Based on the single-axis rotational inertial navigation system (RINS), a self-calibration method is put forward. The whole system is applied with the rotation modulation technique so that whole inertial measurement unit (IMU) of system can rotate around the motor shaft without any external input. In the process of modulation, some important errors can be decoupled. Coupled with the initial position information and attitude information of the system as the reference, the velocity errors and attitude errors in the rotation are used as measurement to perform Kalman filtering to estimate part of important errors of the system after which the errors can be compensated into the system. The simulation results show that the method can complete the self-calibration of the single-axis RINS in 15 minutes and estimate gyro drifts of three-axis, the installation error angle of the IMU and the scale factor error of the gyro on z-axis. The calibration accuracy of optic gyro drifts could be about 0.003°/h (1σ) as well as the scale factor error could be about 1 parts per million (1σ). The errors estimate reaches the system requirements which can effectively improve the longtime navigation accuracy of the vehicle or the boat.
Applicability of APT aided-inertial system to crustal movement monitoring
NASA Technical Reports Server (NTRS)
Soltz, J. A.
1978-01-01
The APT system, its stage of development, hardware, and operations are described. The algorithms required to perform the real-time functions of navigation and profiling are presented. The results of computer simulations demonstrate the feasibility of APT for its primary mission: topographic mapping with an accuracy of 15 cm in the vertical. Also discussed is the suitability of modifying APT for the purpose of making vertical crustal movement measurements accurate to 2 cm in the vertical, and at least marginal feasibility is indicated.
An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database.
Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang
2016-01-28
In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m.
An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database
Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang
2016-01-01
In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m. PMID:26828496
Development of a Closed-Loop Strap Down Attitude System for an Ultrahigh Altitude Flight Experiment
NASA Technical Reports Server (NTRS)
Whitmore, Stephen A.; Fife, Mike; Brashear, Logan
1997-01-01
A low-cost attitude system has been developed for an ultrahigh altitude flight experiment. The experiment uses a remotely piloted sailplane, with the wings modified for flight at altitudes greater than 100,000 ft. Mission requirements deem it necessary to measure the aircraft pitch and bank angles with accuracy better than 1.0 deg and heading with accuracy better than 5.0 deg. Vehicle cost restrictions and gross weight limits make installing a commercial inertial navigation system unfeasible. Instead, a low-cost attitude system was developed using strap down components. Monte Carlo analyses verified that two vector measurements, magnetic field and velocity, are required to completely stabilize the error equations. In the estimating algorithm, body-axis observations of the airspeed vector and the magnetic field are compared against the inertial velocity vector and a magnetic-field reference model. Residuals are fed back to stabilize integration of rate gyros. The effectiveness of the estimating algorithm was demonstrated using data from the NASA Dryden Flight Research Center Systems Research Aircraft (SRA) flight tests. The algorithm was applied with good results to a maximum 10' pitch and bank angles. Effects of wind shears were evaluated and, for most cases, can be safely ignored.
Li, Kui; Wang, Lei; Lv, Yanhong; Gao, Pengyu; Song, Tianxiao
2015-10-20
Getting a land vehicle's accurate position, azimuth and attitude rapidly is significant for vehicle based weapons' combat effectiveness. In this paper, a new approach to acquire vehicle's accurate position and orientation is proposed. It uses biaxial optical detection platform (BODP) to aim at and lock in no less than three pre-set cooperative targets, whose accurate positions are measured beforehand. Then, it calculates the vehicle's accurate position, azimuth and attitudes by the rough position and orientation provided by vehicle based navigation systems and no less than three couples of azimuth and pitch angles measured by BODP. The proposed approach does not depend on Global Navigation Satellite System (GNSS), thus it is autonomous and difficult to interfere. Meanwhile, it only needs a rough position and orientation as algorithm's iterative initial value, consequently, it does not have high performance requirement for Inertial Navigation System (INS), odometer and other vehicle based navigation systems, even in high precise applications. This paper described the system's working procedure, presented theoretical deviation of the algorithm, and then verified its effectiveness through simulation and vehicle experiments. The simulation and experimental results indicate that the proposed approach can achieve positioning and orientation accuracy of 0.2 m and 20″ respectively in less than 3 min.
Multi-Sensor Fusion with Interaction Multiple Model and Chi-Square Test Tolerant Filter.
Yang, Chun; Mohammadi, Arash; Chen, Qing-Wei
2016-11-02
Motivated by the key importance of multi-sensor information fusion algorithms in the state-of-the-art integrated navigation systems due to recent advancements in sensor technologies, telecommunication, and navigation systems, the paper proposes an improved and innovative fault-tolerant fusion framework. An integrated navigation system is considered consisting of four sensory sub-systems, i.e., Strap-down Inertial Navigation System (SINS), Global Navigation System (GPS), the Bei-Dou2 (BD2) and Celestial Navigation System (CNS) navigation sensors. In such multi-sensor applications, on the one hand, the design of an efficient fusion methodology is extremely constrained specially when no information regarding the system's error characteristics is available. On the other hand, the development of an accurate fault detection and integrity monitoring solution is both challenging and critical. The paper addresses the sensitivity issues of conventional fault detection solutions and the unavailability of a precisely known system model by jointly designing fault detection and information fusion algorithms. In particular, by using ideas from Interacting Multiple Model (IMM) filters, the uncertainty of the system will be adjusted adaptively by model probabilities and using the proposed fuzzy-based fusion framework. The paper also addresses the problem of using corrupted measurements for fault detection purposes by designing a two state propagator chi-square test jointly with the fusion algorithm. Two IMM predictors, running in parallel, are used and alternatively reactivated based on the received information form the fusion filter to increase the reliability and accuracy of the proposed detection solution. With the combination of the IMM and the proposed fusion method, we increase the failure sensitivity of the detection system and, thereby, significantly increase the overall reliability and accuracy of the integrated navigation system. Simulation results indicate that the proposed fault tolerant fusion framework provides superior performance over its traditional counterparts.
Multi-Sensor Fusion with Interaction Multiple Model and Chi-Square Test Tolerant Filter
Yang, Chun; Mohammadi, Arash; Chen, Qing-Wei
2016-01-01
Motivated by the key importance of multi-sensor information fusion algorithms in the state-of-the-art integrated navigation systems due to recent advancements in sensor technologies, telecommunication, and navigation systems, the paper proposes an improved and innovative fault-tolerant fusion framework. An integrated navigation system is considered consisting of four sensory sub-systems, i.e., Strap-down Inertial Navigation System (SINS), Global Navigation System (GPS), the Bei-Dou2 (BD2) and Celestial Navigation System (CNS) navigation sensors. In such multi-sensor applications, on the one hand, the design of an efficient fusion methodology is extremely constrained specially when no information regarding the system’s error characteristics is available. On the other hand, the development of an accurate fault detection and integrity monitoring solution is both challenging and critical. The paper addresses the sensitivity issues of conventional fault detection solutions and the unavailability of a precisely known system model by jointly designing fault detection and information fusion algorithms. In particular, by using ideas from Interacting Multiple Model (IMM) filters, the uncertainty of the system will be adjusted adaptively by model probabilities and using the proposed fuzzy-based fusion framework. The paper also addresses the problem of using corrupted measurements for fault detection purposes by designing a two state propagator chi-square test jointly with the fusion algorithm. Two IMM predictors, running in parallel, are used and alternatively reactivated based on the received information form the fusion filter to increase the reliability and accuracy of the proposed detection solution. With the combination of the IMM and the proposed fusion method, we increase the failure sensitivity of the detection system and, thereby, significantly increase the overall reliability and accuracy of the integrated navigation system. Simulation results indicate that the proposed fault tolerant fusion framework provides superior performance over its traditional counterparts. PMID:27827832
Differential GPS/inertial navigation approach/landing flight test results
NASA Technical Reports Server (NTRS)
Snyder, Scott; Schipper, Brian; Vallot, Larry; Parker, Nigel; Spitzer, Cary
1992-01-01
In November of 1990 a joint Honeywell/NASA-Langley differential GPS/inertial flight test was conducted at Wallops Island, Virginia. The test objective was to acquire a system performance database and demonstrate automatic landing using an integrated differential GPS/INS (Global Positioning System/inertial navigation system) with barometric and radar altimeters. The flight test effort exceeded program objectives with over 120 landings, 36 of which were fully automatic differential GPS/inertial landings. Flight test results obtained from post-flight data analysis are discussed. These results include characteristics of differential GPS/inertial error, using the Wallops Island Laser Tracker as a reference. Data on the magnitude of the differential corrections and vertical channel performance with and without radar altimeter augmentation are provided.
Fast two-position initial alignment for SINS using velocity plus angular rate measurements
NASA Astrophysics Data System (ADS)
Chang, Guobin
2015-10-01
An improved two-position initial alignment model for strapdown inertial navigation system is proposed. In addition to the velocity, angular rates are incorporated as measurements. The measurement equations in full three channels are derived in both navigation and body frames and the latter of which is found to be preferred. The cross-correlation between the process and the measurement noises is analyzed and addressed in the Kalman filter. The incorporation of the angular rates, without introducing additional device or external signal, speeds up the convergence of estimating the attitudes, especially the heading. In the simulation study, different algorithms are tested with different initial errors, and the advantages of the proposed method compared to the conventional one are validated by the simulation results.
Precise laser gyroscope for autonomous inertial navigation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kuznetsov, A G; Molchanov, A V; Izmailov, E A
2015-01-31
Requirements to gyroscopes of strapdown inertial navigation systems for aircraft application are formulated. The construction of a ring helium – neon laser designed for autonomous navigation is described. The processes that determine the laser service life and the relation between the random error of the angular velocity measurement and the surface relief features of the cavity mirrors are analysed. The results of modelling one of the promising approaches to processing the laser gyroscope signals are presented. (laser gyroscopes)
Meng, Xiaoli
2017-01-01
Precise and robust localization in a large-scale outdoor environment is essential for an autonomous vehicle. In order to improve the performance of the fusion of GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit)/DMI (Distance-Measuring Instruments), a multi-constraint fault detection approach is proposed to smooth the vehicle locations in spite of GNSS jumps. Furthermore, the lateral localization error is compensated by the point cloud-based lateral localization method proposed in this paper. Experiment results have verified the algorithms proposed in this paper, which shows that the algorithms proposed in this paper are capable of providing precise and robust vehicle localization. PMID:28926996
Meng, Xiaoli; Wang, Heng; Liu, Bingbing
2017-09-18
Precise and robust localization in a large-scale outdoor environment is essential for an autonomous vehicle. In order to improve the performance of the fusion of GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit)/DMI (Distance-Measuring Instruments), a multi-constraint fault detection approach is proposed to smooth the vehicle locations in spite of GNSS jumps. Furthermore, the lateral localization error is compensated by the point cloud-based lateral localization method proposed in this paper. Experiment results have verified the algorithms proposed in this paper, which shows that the algorithms proposed in this paper are capable of providing precise and robust vehicle localization.
Systems and Methods for Determining Inertial Navigation System Faults
NASA Technical Reports Server (NTRS)
Bharadwaj, Raj Mohan (Inventor); Bageshwar, Vibhor L. (Inventor); Kim, Kyusung (Inventor)
2017-01-01
An inertial navigation system (INS) includes a primary inertial navigation system (INS) unit configured to receive accelerometer measurements from an accelerometer and angular velocity measurements from a gyroscope. The primary INS unit is further configured to receive global navigation satellite system (GNSS) signals from a GNSS sensor and to determine a first set of kinematic state vectors based on the accelerometer measurements, the angular velocity measurements, and the GNSS signals. The INS further includes a secondary INS unit configured to receive the accelerometer measurements and the angular velocity measurements and to determine a second set of kinematic state vectors of the vehicle based on the accelerometer measurements and the angular velocity measurements. A health management system is configured to compare the first set of kinematic state vectors and the second set of kinematic state vectors to determine faults associated with the accelerometer or the gyroscope based on the comparison.
An adaptive reentry guidance method considering the influence of blackout zone
NASA Astrophysics Data System (ADS)
Wu, Yu; Yao, Jianyao; Qu, Xiangju
2018-01-01
Reentry guidance has been researched as a popular topic because it is critical for a successful flight. In view that the existing guidance methods do not take into account the accumulated navigation error of Inertial Navigation System (INS) in the blackout zone, in this paper, an adaptive reentry guidance method is proposed to obtain the optimal reentry trajectory quickly with the target of minimum aerodynamic heating rate. The terminal error in position and attitude can be also reduced with the proposed method. In this method, the whole reentry guidance task is divided into two phases, i.e., the trajectory updating phase and the trajectory planning phase. In the first phase, the idea of model predictive control (MPC) is used, and the receding optimization procedure ensures the optimal trajectory in the next few seconds. In the trajectory planning phase, after the vehicle has flown out of the blackout zone, the optimal reentry trajectory is obtained by online planning to adapt to the navigation information. An effective swarm intelligence algorithm, i.e. pigeon inspired optimization (PIO) algorithm, is applied to obtain the optimal reentry trajectory in both of the two phases. Compared to the trajectory updating method, the proposed method can reduce the terminal error by about 30% considering both the position and attitude, especially, the terminal error of height has almost been eliminated. Besides, the PIO algorithm performs better than the particle swarm optimization (PSO) algorithm both in the trajectory updating phase and the trajectory planning phases.
Development and Flight Test of a Robust Optical-Inertial Navigation System Using Low-Cost Sensors
2008-03-01
for this test. Though, marketed as a GPS/INS, it was in fact used simply as an IMU for this test. The raw inertial measurement data (from the...Performance Evaluation of Low Cost MEMS-Based IMU Integrated With GPS for Land Vehicle Navigation Application. MS Thesis, UCGE Reports Number
Superconducting tensor gravity gradiometer for satellite geodesy and inertial navigation
NASA Technical Reports Server (NTRS)
Paik, H. J.
1981-01-01
A sensitive gravity gradiometer can provide much needed gravity data of the earth and improve the accuracy of inertial navigation. Superconductivity and other properties of materials at low temperatures can be used to obtain a sensitive, low-drift gravity gradiometer; by differencing the outputs of accelerometer pairs using superconducting circuits, it is possible to construct a tensor gravity gradiometer which measures all the in-line and cross components of the tensor simultaneously. Additional superconducting circuits can be provided to determine the linear and angular acceleration vectors. A tensor gravity gradiometer with these features is being developed for satellite geodesy. The device constitutes a complete package of inertial navigation instruments with angular and linear acceleration readouts as well as gravity signals.
NASA Technical Reports Server (NTRS)
Bishop, Robert H.; DeMars, Kyle; Trawny, Nikolas; Crain, Tim; Hanak, Chad; Carson, John M.; Christian, John
2016-01-01
The navigation filter architecture successfully deployed on the Morpheus flight vehicle is presented. The filter was developed as a key element of the NASA Autonomous Landing and Hazard Avoidance Technology (ALHAT) project and over the course of 15 free fights was integrated into the Morpheus vehicle, operations, and flight control loop. Flight testing completed by demonstrating autonomous hazard detection and avoidance, integration of an altimeter, surface relative velocity (velocimeter) and hazard relative navigation (HRN) measurements into the onboard dual-state inertial estimator Kalman flter software, and landing within 2 meters of the vertical testbed GPS-based navigation solution at the safe landing site target. Morpheus followed a trajectory that included an ascent phase followed by a partial descent-to-landing, although the proposed filter architecture is applicable to more general planetary precision entry, descent, and landings. The main new contribution is the incorporation of a sophisticated hazard relative navigation sensor-originally intended to locate safe landing sites-into the navigation system and employed as a navigation sensor. The formulation of a dual-state inertial extended Kalman filter was designed to address the precision planetary landing problem when viewed as a rendezvous problem with an intended landing site. For the required precision navigation system that is capable of navigating along a descent-to-landing trajectory to a precise landing, the impact of attitude errors on the translational state estimation are included in a fully integrated navigation structure in which translation state estimation is combined with attitude state estimation. The map tie errors are estimated as part of the process, thereby creating a dual-state filter implementation. Also, the filter is implemented using inertial states rather than states relative to the target. External measurements include altimeter, velocimeter, star camera, terrain relative navigation sensor, and a hazard relative navigation sensor providing information regarding hazards on a map generated on-the-fly.
A Coarse-Alignment Method Based on the Optimal-REQUEST Algorithm
Zhu, Yongyun
2018-01-01
In this paper, we proposed a coarse-alignment method for strapdown inertial navigation systems based on attitude determination. The observation vectors, which can be obtained by inertial sensors, usually contain various types of noise, which affects the convergence rate and the accuracy of the coarse alignment. Given this drawback, we studied an attitude-determination method named optimal-REQUEST, which is an optimal method for attitude determination that is based on observation vectors. Compared to the traditional attitude-determination method, the filtering gain of the proposed method is tuned autonomously; thus, the convergence rate of the attitude determination is faster than in the traditional method. Within the proposed method, we developed an iterative method for determining the attitude quaternion. We carried out simulation and turntable tests, which we used to validate the proposed method’s performance. The experiment’s results showed that the convergence rate of the proposed optimal-REQUEST algorithm is faster and that the coarse alignment’s stability is higher. In summary, the proposed method has a high applicability to practical systems. PMID:29337895
Research into Kinect/Inertial Measurement Units Based on Indoor Robots.
Li, Huixia; Wen, Xi; Guo, Hang; Yu, Min
2018-03-12
As indoor mobile navigation suffers from low positioning accuracy and accumulation error, we carried out research into an integrated location system for a robot based on Kinect and an Inertial Measurement Unit (IMU). In this paper, the close-range stereo images are used to calculate the attitude information and the translation amount of the adjacent positions of the robot by means of the absolute orientation algorithm, for improving the calculation accuracy of the robot's movement. Relying on the Kinect visual measurement and the strap-down IMU devices, we also use Kalman filtering to obtain the errors of the position and attitude outputs, in order to seek the optimal estimation and correct the errors. Experimental results show that the proposed method is able to improve the positioning accuracy and stability of the indoor mobile robot.
Inflight alignment of payload inertial reference from Shuttle navigation system
NASA Astrophysics Data System (ADS)
Treder, A. J.; Norris, R. E.; Ruprecht, R.
Two methods for payload attitude initialization from the STS Orbiter have been proposed: body axis maneuvers (BAM) and star line maneuvers (SLM). The first achieves alignment directly through the Shuttle star tracker, while the second, indirectly through the stellar-updated Shuttle inertial platform. The Inertial Upper Stage (IUS) with its strapdown navigation system is used to demonstrate in-flight alignment techniques. Significant accuracy can be obtained with minimal impact on Orbiter operations, with payload inertial reference potentially approaching the accuracy of the Shuttle star tracker. STS-6 flight performance parameters, including alignment stability, are discussed and compared with operational complexity. Results indicate overall alignment stability of .06 deg, 3 sigma per axis.
Wang, Wei; Chen, Xiyuan
2018-02-23
In view of the fact the accuracy of the third-degree Cubature Kalman Filter (CKF) used for initial alignment under large misalignment angle conditions is insufficient, an improved fifth-degree CKF algorithm is proposed in this paper. In order to make full use of the innovation on filtering, the innovation covariance matrix is calculated recursively by an innovative sequence with an exponent fading factor. Then a new adaptive error covariance matrix scaling algorithm is proposed. The Singular Value Decomposition (SVD) method is used for improving the numerical stability of the fifth-degree CKF in this paper. In order to avoid the overshoot caused by excessive scaling of error covariance matrix during the convergence stage, the scaling scheme is terminated when the gradient of azimuth reaches the maximum. The experimental results show that the improved algorithm has better alignment accuracy with large misalignment angles than the traditional algorithm.
1978-07-01
l)ground volocity-es ft/S VEL(2) ground velocity-north Wt/ VEL (3)’ ground velocity-up ft/S 4 .ASM) ft/s2 ABM (2 specific force a f,/.2 hB(3) -ft/S 2...Inertial Navigation Sytem Standardized Software _______________ Reej-977, C.S. Draper Lab., Softwre Deelopent, Fitnal Technical Report,, Cambridge
High-accuracy self-calibration method for dual-axis rotation-modulating RLG-INS
NASA Astrophysics Data System (ADS)
Wei, Guo; Gao, Chunfeng; Wang, Qi; Wang, Qun; Long, Xingwu
2017-05-01
Inertial navigation system has been the core component of both military and civil navigation systems. Dual-axis rotation modulation can completely eliminate the inertial elements constant errors of the three axes to improve the system accuracy. But the error caused by the misalignment angles and the scale factor error cannot be eliminated through dual-axis rotation modulation. And discrete calibration method cannot fulfill requirements of high-accurate calibration of the mechanically dithered ring laser gyroscope navigation system with shock absorbers. This paper has analyzed the effect of calibration error during one modulated period and presented a new systematic self-calibration method for dual-axis rotation-modulating RLG-INS. Procedure for self-calibration of dual-axis rotation-modulating RLG-INS has been designed. The results of self-calibration simulation experiment proved that: this scheme can estimate all the errors in the calibration error model, the calibration precision of the inertial sensors scale factor error is less than 1ppm and the misalignment is less than 5″. These results have validated the systematic self-calibration method and proved its importance for accuracy improvement of dual -axis rotation inertial navigation system with mechanically dithered ring laser gyroscope.
INS/GNSS Tightly-Coupled Integration Using Quaternion-Based AUPF for USV.
Xia, Guoqing; Wang, Guoqing
2016-08-02
This paper addresses the problem of integration of Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) for the purpose of developing a low-cost, robust and highly accurate navigation system for unmanned surface vehicles (USVs). A tightly-coupled integration approach is one of the most promising architectures to fuse the GNSS data with INS measurements. However, the resulting system and measurement models turn out to be nonlinear, and the sensor stochastic measurement errors are non-Gaussian and distributed in a practical system. Particle filter (PF), one of the most theoretical attractive non-linear/non-Gaussian estimation methods, is becoming more and more attractive in navigation applications. However, the large computation burden limits its practical usage. For the purpose of reducing the computational burden without degrading the system estimation accuracy, a quaternion-based adaptive unscented particle filter (AUPF), which combines the adaptive unscented Kalman filter (AUKF) with PF, has been proposed in this paper. The unscented Kalman filter (UKF) is used in the algorithm to improve the proposal distribution and generate a posterior estimates, which specify the PF importance density function for generating particles more intelligently. In addition, the computational complexity of the filter is reduced with the avoidance of the re-sampling step. Furthermore, a residual-based covariance matching technique is used to adapt the measurement error covariance. A trajectory simulator based on a dynamic model of USV is used to test the proposed algorithm. Results show that quaternion-based AUPF can significantly improve the overall navigation accuracy and reliability.
Research on the optimal structure configuration of dither RLG used in skewed redundant INS
NASA Astrophysics Data System (ADS)
Gao, Chunfeng; Wang, Qi; Wei, Guo; Long, Xingwu
2016-05-01
The actual combat effectiveness of weapon equipment is restricted by the performance of Inertial Navigation System (INS), especially in high reliability required situations such as fighter, satellite and submarine. Through the use of skewed sensor geometries, redundant technique has been applied to reduce the cost and improve the reliability of the INS. In this paper, the structure configuration and the inertial sensor characteristics of Skewed Redundant Strapdown Inertial Navigation System (SRSINS) using dithered Ring Laser Gyroscope (RLG) are analyzed. For the dither coupling effects of the dither gyro, the system measurement errors can be amplified either the individual gyro dither frequency is near one another or the structure of the SRSINS is unreasonable. Based on the characteristics of RLG, the research on coupled vibration of dithered RLG in SRSINS is carried out. On the principle of optimal navigation performance, optimal reliability and optimal cost-effectiveness, the comprehensive evaluation scheme of the inertial sensor configuration of SRINS is given.
Zhang, Tao; Zhu, Yongyun; Zhou, Feng; Yan, Yaxiong; Tong, Jinwu
2017-06-17
Initial alignment of the strapdown inertial navigation system (SINS) is intended to determine the initial attitude matrix in a short time with certain accuracy. The alignment accuracy of the quaternion filter algorithm is remarkable, but the convergence rate is slow. To solve this problem, this paper proposes an improved quaternion filter algorithm for faster initial alignment based on the error model of the quaternion filter algorithm. The improved quaternion filter algorithm constructs the K matrix based on the principle of optimal quaternion algorithm, and rebuilds the measurement model by containing acceleration and velocity errors to make the convergence rate faster. A doppler velocity log (DVL) provides the reference velocity for the improved quaternion filter alignment algorithm. In order to demonstrate the performance of the improved quaternion filter algorithm in the field, a turntable experiment and a vehicle test are carried out. The results of the experiments show that the convergence rate of the proposed improved quaternion filter is faster than that of the tradition quaternion filter algorithm. In addition, the improved quaternion filter algorithm also demonstrates advantages in terms of correctness, effectiveness, and practicability.
Comparison of Factorization-Based Filtering for Landing Navigation
NASA Technical Reports Server (NTRS)
McCabe, James S.; Brown, Aaron J.; DeMars, Kyle J.; Carson, John M., III
2017-01-01
This paper develops and analyzes methods for fusing inertial navigation data with external data, such as data obtained from an altimeter and a star camera. The particular filtering techniques are based upon factorized forms of the Kalman filter, specifically the UDU and Cholesky factorizations. The factorized Kalman filters are utilized to ensure numerical stability of the navigation solution. Simulations are carried out to compare the performance of the different approaches along a lunar descent trajectory using inertial and external data sources. It is found that the factorized forms improve upon conventional filtering techniques in terms of ensuring numerical stability for the investigated landing navigation scenario.
GPS free navigation inspired by insects through monocular camera and inertial sensors
NASA Astrophysics Data System (ADS)
Liu, Yi; Liu, J. G.; Cao, H.; Huang, Y.
2015-12-01
Navigation without GPS and other knowledge of environment have been studied for many decades. Advance technology have made sensors more compact and subtle that can be easily integrated into micro and hand-hold device. Recently researchers found that bee and fruit fly have an effectively and efficiently navigation mechanism through optical flow information and process only with their miniature brain. We present a navigation system inspired by the study of insects through a calibrated camera and other inertial sensors. The system utilizes SLAM theory and can be worked in many GPS denied environment. Simulation and experimental results are presented for validation and quantification.
Lightweight, Miniature Inertial Measurement System
NASA Technical Reports Server (NTRS)
Tang, Liang; Crassidis, Agamemnon
2012-01-01
A miniature, lighter-weight, and highly accurate inertial navigation system (INS) is coupled with GPS receivers to provide stable and highly accurate positioning, attitude, and inertial measurements while being subjected to highly dynamic maneuvers. In contrast to conventional methods that use extensive, groundbased, real-time tracking and control units that are expensive, large, and require excessive amounts of power to operate, this method focuses on the development of an estimator that makes use of a low-cost, miniature accelerometer array fused with traditional measurement systems and GPS. Through the use of a position tracking estimation algorithm, onboard accelerometers are numerically integrated and transformed using attitude information to obtain an estimate of position in the inertial frame. Position and velocity estimates are subject to drift due to accelerometer sensor bias and high vibration over time, and so require the integration with GPS information using a Kalman filter to provide highly accurate and reliable inertial tracking estimations. The method implemented here uses the local gravitational field vector. Upon determining the location of the local gravitational field vector relative to two consecutive sensors, the orientation of the device may then be estimated, and the attitude determined. Improved attitude estimates further enhance the inertial position estimates. The device can be powered either by batteries, or by the power source onboard its target platforms. A DB9 port provides the I/O to external systems, and the device is designed to be mounted in a waterproof case for all-weather conditions.
GPS/INS Sensor Fusion Using GPS Wind up Model
NASA Technical Reports Server (NTRS)
Williamson, Walton R. (Inventor)
2013-01-01
A method of stabilizing an inertial navigation system (INS), includes the steps of: receiving data from an inertial navigation system; and receiving a finite number of carrier phase observables using at least one GPS receiver from a plurality of GPS satellites; calculating a phase wind up correction; correcting at least one of the finite number of carrier phase observables using the phase wind up correction; and calculating a corrected IMU attitude or velocity or position using the corrected at least one of the finite number of carrier phase observables; and performing a step selected from the steps consisting of recording, reporting, or providing the corrected IMU attitude or velocity or position to another process that uses the corrected IMU attitude or velocity or position. A GPS stabilized inertial navigation system apparatus is also described.
Inertial navigation sensor integrated obstacle detection system
NASA Technical Reports Server (NTRS)
Bhanu, Bir (Inventor); Roberts, Barry A. (Inventor)
1992-01-01
A system that incorporates inertial sensor information into optical flow computations to detect obstacles and to provide alternative navigational paths free from obstacles. The system is a maximally passive obstacle detection system that makes selective use of an active sensor. The active detection typically utilizes a laser. Passive sensor suite includes binocular stereo, motion stereo and variable fields-of-view. Optical flow computations involve extraction, derotation and matching of interest points from sequential frames of imagery, for range interpolation of the sensed scene, which in turn provides obstacle information for purposes of safe navigation.
Improved navigation by combining VOR/DME information with air or inertial data
NASA Technical Reports Server (NTRS)
Bobick, J. C.; Bryson, A. E., Jr.
1972-01-01
The improvement was determined in navigational accuracy obtainable by combining VOR/DME information (from one or two stations) with air data (airspeed and heading) or with data from an inertial navigation system (INS) by means of a maximum-likelihood filter. It was found that the addition of air data to the information from one VOR/DME station reduces the RMS position error by a factor of about 2, whereas the addition of inertial data from a low-quality INS reduces the RMS position error by a factor of about 3. The use of information from two VOR/DME stations with air or inertial data yields large factors of improvement in RMS position accuracy over the use of a single VOR/DME station, roughly 15 to 20 for the air-data case and 25 to 35 for the inertial-data case. As far as position accuracy is concerned, at most one VOR station need be used. When continuously updating an INS with VOR/DME information, the use of a high-quality INS (0.01 deg/hr gyro drift) instead of a low-quality INS (1.0 deg/hr gyro drift) does not substantially improve position accuracy.
NASA Technical Reports Server (NTRS)
Vallot, Lawrence; Snyder, Scott; Schipper, Brian; Parker, Nigel; Spitzer, Cary
1991-01-01
NASA-Langley has conducted a flight test program evaluating a differential GPS/inertial navigation system's (DGPS/INS) utility as an approach/landing aid. The DGPS/INS airborne and ground components are based on off-the-shelf transport aircraft avionics, namely a global positioning/inertial reference unit (GPIRU) and two GPS sensor units (GPSSUs). Systematic GPS errors are measured by the ground GPSSU and transmitted to the aircraft GPIRU, allowing the errors to be eliminated or greatly reduced in the airborne equipment. Over 120 landings were flown; 36 of these were fully automatic DGPS/INS landings.
A novel navigation method used in a ballistic missile
NASA Astrophysics Data System (ADS)
Qian, Hua-ming; Sun, Long; Cai, Jia-nan; Peng, Yu
2013-10-01
The traditional strapdown inertial/celestial integrated navigation method used in a ballistic missile cannot accurately estimate the accelerometer bias. It might cause a divergence of navigation errors. To solve this problem, a new navigation method named strapdown inertial/starlight refractive celestial integrated navigation is proposed. To verify the feasibility of the proposed method, a simulated program of a ballistic missile is presented. The simulation results indicated that, when multiple refraction stars are used, the proposed method can accurately estimate the accelerometer bias, and suppress the divergence of navigation errors completely. Specifically, in order to apply this method to a ballistic missile, a novel measurement equation based on stellar refraction was developed. Furthermore a method to calculate the number of refraction stars observed by the stellar sensor was given. Finally, the relationship between the number of refraction stars used and the navigation accuracy is analysed.
Impact Assessment of GNSS Spoofing Attacks on INS/GNSS Integrated Navigation System.
Liu, Yang; Li, Sihai; Fu, Qiangwen; Liu, Zhenbo
2018-05-04
In the face of emerging Global Navigation Satellite System (GNSS) spoofing attacks, there is a need to give a comprehensive analysis on how the inertial navigation system (INS)/GNSS integrated navigation system responds to different kinds of spoofing attacks. A better understanding of the integrated navigation system’s behavior with spoofed GNSS measurements gives us valuable clues to develop effective spoofing defenses. This paper focuses on an impact assessment of GNSS spoofing attacks on the integrated navigation system Kalman filter’s error covariance, innovation sequence and inertial sensor bias estimation. A simple and straightforward measurement-level trajectory spoofing simulation framework is presented, serving as the basis for an impact assessment of both unsynchronized and synchronized spoofing attacks. Recommendations are given for spoofing detection and mitigation based on our findings in the impact assessment process.
Real-time single-frequency GPS/MEMS-IMU attitude determination of lightweight UAVs.
Eling, Christian; Klingbeil, Lasse; Kuhlmann, Heiner
2015-10-16
In this paper, a newly-developed direct georeferencing system for the guidance, navigation and control of lightweight unmanned aerial vehicles (UAVs), having a weight limit of 5 kg and a size limit of 1.5 m, and for UAV-based surveying and remote sensing applications is presented. The system is intended to provide highly accurate positions and attitudes (better than 5 cm and 0.5°) in real time, using lightweight components. The main focus of this paper is on the attitude determination with the system. This attitude determination is based on an onboard single-frequency GPS baseline, MEMS (micro-electro-mechanical systems) inertial sensor readings, magnetic field observations and a 3D position measurement. All of this information is integrated in a sixteen-state error space Kalman filter. Special attention in the algorithm development is paid to the carrier phase ambiguity resolution of the single-frequency GPS baseline observations. We aim at a reliable and instantaneous ambiguity resolution, since the system is used in urban areas, where frequent losses of the GPS signal lock occur and the GPS measurement conditions are challenging. Flight tests and a comparison to a navigation-grade inertial navigation system illustrate the performance of the developed system in dynamic situations. Evaluations show that the accuracies of the system are 0.05° for the roll and the pitch angle and 0.2° for the yaw angle. The ambiguities of the single-frequency GPS baseline can be resolved instantaneously in more than 90% of the cases.
In-flight alignment using H ∞ filter for strapdown INS on aircraft.
Pei, Fu-Jun; Liu, Xuan; Zhu, Li
2014-01-01
In-flight alignment is an effective way to improve the accuracy and speed of initial alignment for strapdown inertial navigation system (INS). During the aircraft flight, strapdown INS alignment was disturbed by lineal and angular movements of the aircraft. To deal with the disturbances in dynamic initial alignment, a novel alignment method for SINS is investigated in this paper. In this method, an initial alignment error model of SINS in the inertial frame is established. The observability of the system is discussed by piece-wise constant system (PWCS) theory and observable degree is computed by the singular value decomposition (SVD) theory. It is demonstrated that the system is completely observable, and all the system state parameters can be estimated by optimal filter. Then a H ∞ filter was designed to resolve the uncertainty of measurement noise. The simulation results demonstrate that the proposed algorithm can reach a better accuracy under the dynamic disturbance condition.
On the Design of Attitude-Heading Reference Systems Using the Allan Variance.
Hidalgo-Carrió, Javier; Arnold, Sascha; Poulakis, Pantelis
2016-04-01
The Allan variance is a method to characterize stochastic random processes. The technique was originally developed to characterize the stability of atomic clocks and has also been successfully applied to the characterization of inertial sensors. Inertial navigation systems (INS) can provide accurate results in a short time, which tend to rapidly degrade in longer time intervals. During the last decade, the performance of inertial sensors has significantly improved, particularly in terms of signal stability, mechanical robustness, and power consumption. The mass and volume of inertial sensors have also been significantly reduced, offering system-level design and accommodation advantages. This paper presents a complete methodology for the characterization and modeling of inertial sensors using the Allan variance, with direct application to navigation systems. Although the concept of sensor fusion is relatively straightforward, accurate characterization and sensor-information filtering is not a trivial task, yet they are essential for good performance. A complete and reproducible methodology utilizing the Allan variance, including all the intermediate steps, is described. An end-to-end (E2E) process for sensor-error characterization and modeling up to the final integration in the sensor-fusion scheme is explained in detail. The strength of this approach is demonstrated with representative tests on novel, high-grade inertial sensors. Experimental navigation results are presented from two distinct robotic applications: a planetary exploration rover prototype and an autonomous underwater vehicle (AUV).
A Kalman Approach to Lunar Surface Navigation using Radiometric and Inertial Measurements
NASA Technical Reports Server (NTRS)
Chelmins, David T.; Welch, Bryan W.; Sands, O. Scott; Nguyen, Binh V.
2009-01-01
Future lunar missions supporting the NASA Vision for Space Exploration will rely on a surface navigation system to determine astronaut position, guide exploration, and return safely to the lunar habitat. In this report, we investigate one potential architecture for surface navigation, using an extended Kalman filter to integrate radiometric and inertial measurements. We present a possible infrastructure to support this technique, and we examine an approach to simulating navigational accuracy based on several different system configurations. The results show that position error can be reduced to 1 m after 5 min of processing, given two satellites, one surface communication terminal, and knowledge of the starting position to within 100 m.
Zhang, Tao; Shi, Hongfei; Chen, Liping; Li, Yao; Tong, Jinwu
2016-03-11
This paper researches an AUV (Autonomous Underwater Vehicle) positioning method based on SINS (Strapdown Inertial Navigation System)/LBL (Long Base Line) tightly coupled algorithm. This algorithm mainly includes SINS-assisted searching method of optimum slant-range of underwater acoustic propagation multipath, SINS/LBL tightly coupled model and multi-sensor information fusion algorithm. Fuzzy correlation peak problem of underwater LBL acoustic propagation multipath could be solved based on SINS positional information, thus improving LBL positional accuracy. Moreover, introduction of SINS-centered LBL locating information could compensate accumulative AUV position error effectively and regularly. Compared to loosely coupled algorithm, this tightly coupled algorithm can still provide accurate location information when there are fewer than four available hydrophones (or within the signal receiving range). Therefore, effective positional calibration area of tightly coupled system based on LBL array is wider and has higher reliability and fault tolerance than loosely coupled. It is more applicable to AUV positioning based on SINS/LBL.
Zhang, Tao; Shi, Hongfei; Chen, Liping; Li, Yao; Tong, Jinwu
2016-01-01
This paper researches an AUV (Autonomous Underwater Vehicle) positioning method based on SINS (Strapdown Inertial Navigation System)/LBL (Long Base Line) tightly coupled algorithm. This algorithm mainly includes SINS-assisted searching method of optimum slant-range of underwater acoustic propagation multipath, SINS/LBL tightly coupled model and multi-sensor information fusion algorithm. Fuzzy correlation peak problem of underwater LBL acoustic propagation multipath could be solved based on SINS positional information, thus improving LBL positional accuracy. Moreover, introduction of SINS-centered LBL locating information could compensate accumulative AUV position error effectively and regularly. Compared to loosely coupled algorithm, this tightly coupled algorithm can still provide accurate location information when there are fewer than four available hydrophones (or within the signal receiving range). Therefore, effective positional calibration area of tightly coupled system based on LBL array is wider and has higher reliability and fault tolerance than loosely coupled. It is more applicable to AUV positioning based on SINS/LBL. PMID:26978361
Cloud Absorption Radiometer Autonomous Navigation System - CANS
NASA Technical Reports Server (NTRS)
Kahle, Duncan; Gatebe, Charles; McCune, Bill; Hellwig, Dustan
2013-01-01
CAR (cloud absorption radiometer) acquires spatial reference data from host aircraft navigation systems. This poses various problems during CAR data reduction, including navigation data format, accuracy of position data, accuracy of airframe inertial data, and navigation data rate. Incorporating its own navigation system, which included GPS (Global Positioning System), roll axis inertia and rates, and three axis acceleration, CANS expedites data reduction and increases the accuracy of the CAR end data product. CANS provides a self-contained navigation system for the CAR, using inertial reference and GPS positional information. The intent of the software application was to correct the sensor with respect to aircraft roll in real time based upon inputs from a precision navigation sensor. In addition, the navigation information (including GPS position), attitude data, and sensor position details are all streamed to a remote system for recording and later analysis. CANS comprises a commercially available inertial navigation system with integral GPS capability (Attitude Heading Reference System AHRS) integrated into the CAR support structure and data system. The unit is attached to the bottom of the tripod support structure. The related GPS antenna is located on the P-3 radome immediately above the CAR. The AHRS unit provides a RS-232 data stream containing global position and inertial attitude and velocity data to the CAR, which is recorded concurrently with the CAR data. This independence from aircraft navigation input provides for position and inertial state data that accounts for very small changes in aircraft attitude and position, sensed at the CAR location as opposed to aircraft state sensors typically installed close to the aircraft center of gravity. More accurate positional data enables quicker CAR data reduction with better resolution. The CANS software operates in two modes: initialization/calibration and operational. In the initialization/calibration mode, the software aligns the precision navigation sensors and initializes the communications interfaces with the sensor and the remote computing system. It also monitors the navigation data state for quality and ensures that the system maintains the required fidelity for attitude and positional information. In the operational mode, the software runs at 12.5 Hz and gathers the required navigation/attitude data, computes the required sensor correction values, and then commands the sensor to the required roll correction. In this manner, the sensor will stay very near to vertical at all times, greatly improving the resulting collected data and imagery. CANS greatly improves quality of resulting imagery and data collected. In addition, the software component of the system outputs a concisely formatted, high-speed data stream that can be used for further science data processing. This precision, time-stamped data also can benefit other instruments on the same aircraft platform by providing extra information from the mission flight.
Inertial Measurements for Aero-assisted Navigation (IMAN)
NASA Technical Reports Server (NTRS)
Jah, Moriba; Lisano, Michael; Hockney, George
2007-01-01
IMAN is a Python tool that provides inertial sensor-based estimates of spacecraft trajectories within an atmospheric influence. It provides Kalman filter-derived spacecraft state estimates based upon data collected onboard, and is shown to perform at a level comparable to the conventional methods of spacecraft navigation in terms of accuracy and at a higher level with regard to the availability of results immediately after completion of an atmospheric drag pass.
A Dynamic Precision Evaluation Method for the Star Sensor in the Stellar-Inertial Navigation System.
Lu, Jiazhen; Lei, Chaohua; Yang, Yanqiang
2017-06-28
Integrating the advantages of INS (inertial navigation system) and the star sensor, the stellar-inertial navigation system has been used for a wide variety of applications. The star sensor is a high-precision attitude measurement instrument; therefore, determining how to validate its accuracy is critical in guaranteeing its practical precision. The dynamic precision evaluation of the star sensor is more difficult than a static precision evaluation because of dynamic reference values and other impacts. This paper proposes a dynamic precision verification method of star sensor with the aid of inertial navigation device to realize real-time attitude accuracy measurement. Based on the gold-standard reference generated by the star simulator, the altitude and azimuth angle errors of the star sensor are calculated for evaluation criteria. With the goal of diminishing the impacts of factors such as the sensors' drift and devices, the innovative aspect of this method is to employ static accuracy for comparison. If the dynamic results are as good as the static results, which have accuracy comparable to the single star sensor's precision, the practical precision of the star sensor is sufficiently high to meet the requirements of the system specification. The experiments demonstrate the feasibility and effectiveness of the proposed method.
Deppe, Olaf; Dorner, Georg; König, Stefan; Martin, Tim; Voigt, Sven; Zimmermann, Steffen
2017-01-01
In the following paper, we present an industry perspective of inertial sensors for navigation purposes driven by applications and customer needs. Microelectromechanical system (MEMS) inertial sensors have revolutionized consumer, automotive, and industrial applications and they have started to fulfill the high end tactical grade performance requirements of hybrid navigation systems on a series production scale. The Fiber Optic Gyroscope (FOG) technology, on the other hand, is further pushed into the near navigation grade performance region and beyond. Each technology has its special pros and cons making it more or less suitable for specific applications. In our overview paper, we present latest improvements at NG LITEF in tactical and navigation grade MEMS accelerometers, MEMS gyroscopes, and Fiber Optic Gyroscopes, based on our long-term experience in the field. We demonstrate how accelerometer performance has improved by switching from wet etching to deep reactive ion etching (DRIE) technology. For MEMS gyroscopes, we show that better than 1°/h series production devices are within reach, and for FOGs we present how limitations in noise performance were overcome by signal processing. The paper also intends a comparison of the different technologies, emphasizing suitability for different navigation applications, thus providing guidance to system engineers. PMID:28287483
Coupled Integration of CSAC, MIMU, and GNSS for Improved PNT Performance
Ma, Lin; You, Zheng; Liu, Tianyi; Shi, Shuai
2016-01-01
Positioning, navigation, and timing (PNT) is a strategic key technology widely used in military and civilian applications. Global navigation satellite systems (GNSS) are the most important PNT techniques. However, the vulnerability of GNSS threatens PNT service quality, and integrations with other information are necessary. A chip scale atomic clock (CSAC) provides high-precision frequency and high-accuracy time information in a short time. A micro inertial measurement unit (MIMU) provides a strap-down inertial navigation system (SINS) with rich navigation information, better real-time feed, anti-jamming, and error accumulation. This study explores the coupled integration of CSAC, MIMU, and GNSS to enhance PNT performance. The architecture of coupled integration is designed and degraded when any subsystem fails. A mathematical model for a precise time aiding navigation filter is derived rigorously. The CSAC aids positioning by weighted linear optimization when the visible satellite number is four or larger. By contrast, CSAC converts the GNSS observations to range measurements by “clock coasting” when the visible satellite number is less than four, thereby constraining the error divergence of micro inertial navigation and improving the availability of GNSS signals and the positioning accuracy of the integration. Field vehicle experiments, both in open-sky area and in a harsh environment, show that the integration can improve the positioning probability and accuracy. PMID:27187399
Coupled Integration of CSAC, MIMU, and GNSS for Improved PNT Performance.
Ma, Lin; You, Zheng; Liu, Tianyi; Shi, Shuai
2016-05-12
Positioning, navigation, and timing (PNT) is a strategic key technology widely used in military and civilian applications. Global navigation satellite systems (GNSS) are the most important PNT techniques. However, the vulnerability of GNSS threatens PNT service quality, and integrations with other information are necessary. A chip scale atomic clock (CSAC) provides high-precision frequency and high-accuracy time information in a short time. A micro inertial measurement unit (MIMU) provides a strap-down inertial navigation system (SINS) with rich navigation information, better real-time feed, anti-jamming, and error accumulation. This study explores the coupled integration of CSAC, MIMU, and GNSS to enhance PNT performance. The architecture of coupled integration is designed and degraded when any subsystem fails. A mathematical model for a precise time aiding navigation filter is derived rigorously. The CSAC aids positioning by weighted linear optimization when the visible satellite number is four or larger. By contrast, CSAC converts the GNSS observations to range measurements by "clock coasting" when the visible satellite number is less than four, thereby constraining the error divergence of micro inertial navigation and improving the availability of GNSS signals and the positioning accuracy of the integration. Field vehicle experiments, both in open-sky area and in a harsh environment, show that the integration can improve the positioning probability and accuracy.
NASA Technical Reports Server (NTRS)
Holley, M. D.; Swingle, W. L.; Bachman, S. L.; Leblanc, C. J.; Howard, H. T.; Biggs, H. M.
1976-01-01
The primary guidance, navigation, and control systems for both the lunar module and the command module are described. Development of the Apollo primary guidance systems is traced from adaptation of the Polaris Mark II system through evolution from Block I to Block II configurations; the discussion includes design concepts used, test and qualification programs performed, and major problems encountered. The major subsystems (inertial, computer, and optical) are covered. Separate sections on the inertial components (gyroscopes and accelerometers) are presented because these components represent a major contribution to the success of the primary guidance, navigation, and control system.
Novel Hybrid of LS-SVM and Kalman Filter for GPS/INS Integration
NASA Astrophysics Data System (ADS)
Xu, Zhenkai; Li, Yong; Rizos, Chris; Xu, Xiaosu
Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) technologies can overcome the drawbacks of the individual systems. One of the advantages is that the integrated solution can provide continuous navigation capability even during GPS outages. However, bridging the GPS outages is still a challenge when Micro-Electro-Mechanical System (MEMS) inertial sensors are used. Methods being currently explored by the research community include applying vehicle motion constraints, optimal smoother, and artificial intelligence (AI) techniques. In the research area of AI, the neural network (NN) approach has been extensively utilised up to the present. In an NN-based integrated system, a Kalman filter (KF) estimates position, velocity and attitude errors, as well as the inertial sensor errors, to output navigation solutions while GPS signals are available. At the same time, an NN is trained to map the vehicle dynamics with corresponding KF states, and to correct INS measurements when GPS measurements are unavailable. To achieve good performance it is critical to select suitable quality and an optimal number of samples for the NN. This is sometimes too rigorous a requirement which limits real world application of NN-based methods.The support vector machine (SVM) approach is based on the structural risk minimisation principle, instead of the minimised empirical error principle that is commonly implemented in an NN. The SVM can avoid local minimisation and over-fitting problems in an NN, and therefore potentially can achieve a higher level of global performance. This paper focuses on the least squares support vector machine (LS-SVM), which can solve highly nonlinear and noisy black-box modelling problems. This paper explores the application of the LS-SVM to aid the GPS/INS integrated system, especially during GPS outages. The paper describes the principles of the LS-SVM and of the KF hybrid method, and introduces the LS-SVM regression algorithm. Field test data is processed to evaluate the performance of the proposed approach.
Testing of the high accuracy inertial navigation system in the Shuttle Avionics Integration Lab
NASA Technical Reports Server (NTRS)
Strachan, Russell L.; Evans, James M.
1991-01-01
The description, results, and interpretation is presented of comparison testing between the High Accuracy Inertial Navigation System (HAINS) and KT-70 Inertial Measurement Unit (IMU). The objective was to show the HAINS can replace the KT-70 IMU in the space shuttle Orbiter, both singularly and totally. This testing was performed in the Guidance, Navigation, and Control Test Station (GTS) of the Shuttle Avionics Integration Lab (SAIL). A variety of differences between the two instruments are explained. Four, 5 day test sessions were conducted varying the number and slot position of the HAINS and KT-70 IMUs. The various steps in the calibration and alignment procedure are explained. Results and their interpretation are presented. The HAINS displayed a high level of performance accuracy previously unseen with the KT-70 IMU. The most significant improvement of the performance came in the Tuned Inertial/Extended Launch Hold tests. The HAINS exceeded the 4 hr specification requirement. The results obtained from the SAIL tests were generally well beyond the requirements of the procurement specification.
Dai, Dongkai; Wang, Xingshu; Zhan, Dejun; Huang, Zongsheng
2014-01-01
A new method for dynamic measurement of deflections of the vertical (DOV) is proposed in this paper. The integration of an inertial navigation system (INS) and global navigation satellite system (GNSS) is constructed to measure the body's attitude with respect to the astronomical coordinates. Simultaneously, the attitude with respect to the geodetic coordinates is initially measured by a star sensor under quasi-static condition and then maintained by the laser gyroscope unit (LGU), which is composed of three gyroscopes in the INS, when the vehicle travels along survey lines. Deflections of the vertical are calculated by using the difference between the attitudes with respect to the geodetic coordinates and astronomical coordinates. Moreover, an algorithm for removing the trend error of the vertical deflections is developed with the aid of Earth Gravitational Model 2008 (EGM2008). In comparison with traditional methods, the new method required less accurate GNSS, because the dynamic acceleration calculation is avoided. The errors of inertial sensors are well resolved in the INS/GNSS integration, which is implemented by a Rauch–Tung–Striebel (RTS) smoother. In addition, a single-axis indexed INS is adopted to improve the observability of the system errors and to restrain the inertial sensor errors. The proposed method is validated by Monte Carlo simulations. The results show that deflections of the vertical can achieve a precision of better than 1″ for a single survey line. The proposed method can be applied to a gravimetry system based on a ground vehicle or ship with a speed lower than 25 m/s. PMID:25192311
Dai, Dongkai; Wang, Xingshu; Zhan, Dejun; Huang, Zongsheng
2014-09-03
A new method for dynamic measurement of deflections of the vertical (DOV) is proposed in this paper. The integration of an inertial navigation system (INS) and global navigation satellite system (GNSS) is constructed to measure the body's attitude with respect to the astronomical coordinates. Simultaneously, the attitude with respect to the geodetic coordinates is initially measured by a star sensor under quasi-static condition and then maintained by the laser gyroscope unit (LGU), which is composed of three gyroscopes in the INS, when the vehicle travels along survey lines. Deflections of the vertical are calculated by using the difference between the attitudes with respect to the geodetic coordinates and astronomical coordinates. Moreover, an algorithm for removing the trend error of the vertical deflections is developed with the aid of Earth Gravitational Model 2008 (EGM2008). In comparison with traditional methods, the new method required less accurate GNSS, because the dynamic acceleration calculation is avoided. The errors of inertial sensors are well resolved in the INS/GNSS integration, which is implemented by a Rauch-Tung-Striebel (RTS) smoother. In addition, a single-axis indexed INS is adopted to improve the observability of the system errors and to restrain the inertial sensor errors. The proposed method is validated by Monte Carlo simulations. The results show that deflections of the vertical can achieve a precision of better than 1″ for a single survey line. The proposed method can be applied to a gravimetry system based on a ground vehicle or ship with a speed lower than 25 m/s.
Flight test results of the strapdown ring laser gyro tetrad inertial navigation system
NASA Technical Reports Server (NTRS)
Carestia, R. A.; Hruby, R. J.; Bjorkman, W. S.
1983-01-01
A helicopter flight test program undertaken to evaluate the performance of Tetrad (a strap down, laser gyro, inertial navigation system) is described. The results of 34 flights show a mean final navigational velocity error of 5.06 knots, with a standard deviation of 3.84 knots; a corresponding mean final position error of 2.66 n. mi., with a standard deviation of 1.48 n. mi.; and a modeled mean position error growth rate for the 34 tests of 1.96 knots, with a standard deviation of 1.09 knots. No laser gyro or accelerometer failures were detected during the flight tests. Off line parity residual studies used simulated failures with the prerecorded flight test and laboratory test data. The airborne Tetrad system's failure--detection logic, exercised during the tests, successfully demonstrated the detection of simulated ""hard'' failures and the system's ability to continue successfully to navigate by removing the simulated faulted sensor from the computations. Tetrad's four ring laser gyros provided reliable and accurate angular rate sensing during the 4 yr of the test program, and no sensor failures were detected during the evaluation of free inertial navigation performance.
The Location GNSS Modules for the Components of Proteus System
NASA Astrophysics Data System (ADS)
Brzostowski, K.; Darakchiev, R.; Foks-Ryznar, A.; Sitek, P.
2012-01-01
The Proteus system - the Integrated Mobile System for Counterterrorism and Rescue Operations is a complex innovative project. To assure the best possible localization of mobile components of the system, many different Global Navigation Satellite System (GNSS) modules were taken into account. In order to chose the best solution many types of tests were done. Full results and conclusions are presented in this paper. The idea of measurements was to test modules in GPS Standard Positioning Service (SPS) with EGNOS system specification according to certain algorithms. The tests had to answer the question: what type of GNSS modules should be used on different components with respect to specific usage of Proteus system. The second goal of tests was to check the solution quality of integrated GNSS/INS (Inertial Navigation System) and its possible usage in some Proteus system components.
A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications
Yu, Chunyang; Lan, Haiyu; Gu, Fuqiang; Yu, Fei; El-Sheimy, Naser
2017-01-01
In this research, a new Map/INS/Wi-Fi integrated system for indoor location-based service (LBS) applications based on a cascaded Particle/Kalman filter framework structure is proposed. Two-dimension indoor map information, together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value, are integrated for estimating positioning information. The main challenge of this research is how to make effective use of various measurements that complement each other in order to obtain an accurate, continuous, and low-cost position solution without increasing the computational burden of the system. Therefore, to eliminate the cumulative drift caused by low-cost IMU sensor errors, the ubiquitous Wi-Fi signal and non-holonomic constraints are rationally used to correct the IMU-derived navigation solution through the extended Kalman Filter (EKF). Moreover, the map-aiding method and map-matching method are innovatively combined to constrain the primary Wi-Fi/IMU-derived position through an Auxiliary Value Particle Filter (AVPF). Different sources of information are incorporated through a cascaded structure EKF/AVPF filter algorithm. Indoor tests show that the proposed method can effectively reduce the accumulation of positioning errors of a stand-alone Inertial Navigation System (INS), and provide a stable, continuous and reliable indoor location service. PMID:28574471
A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications.
Yu, Chunyang; Lan, Haiyu; Gu, Fuqiang; Yu, Fei; El-Sheimy, Naser
2017-06-02
In this research, a new Map/INS/Wi-Fi integrated system for indoor location-based service (LBS) applications based on a cascaded Particle/Kalman filter framework structure is proposed. Two-dimension indoor map information, together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value, are integrated for estimating positioning information. The main challenge of this research is how to make effective use of various measurements that complement each other in order to obtain an accurate, continuous, and low-cost position solution without increasing the computational burden of the system. Therefore, to eliminate the cumulative drift caused by low-cost IMU sensor errors, the ubiquitous Wi-Fi signal and non-holonomic constraints are rationally used to correct the IMU-derived navigation solution through the extended Kalman Filter (EKF). Moreover, the map-aiding method and map-matching method are innovatively combined to constrain the primary Wi-Fi/IMU-derived position through an Auxiliary Value Particle Filter (AVPF). Different sources of information are incorporated through a cascaded structure EKF/AVPF filter algorithm. Indoor tests show that the proposed method can effectively reduce the accumulation of positioning errors of a stand-alone Inertial Navigation System (INS), and provide a stable, continuous and reliable indoor location service.
Pushbroom Stereo for High-Speed Navigation in Cluttered Environments
2014-09-01
inertial measurement sensors such as Achtelik et al .’s implemention of PTAM (parallel tracking and mapping) [15] with a barometric altimeter, stable flights...in indoor and outdoor environments are possible [1]. With a full vison- aided inertial navigation system (VINS), Li et al . have shown remarkable...avoidance on small UAVs. Stereo systems suffer from a similar speed issue, with most modern systems running at or below 30 Hz [8], [27]. Honegger et
Modern Inertial and Satellite Navigation Systems
1994-05-02
rotor spins, the harder it is to disturb it. This technique is called spin stabilization and it is commonly used for communication satellites. Moder... using a generalization of the complex number called the quaternion . Modem Inertial and Satellite Navigation Systems page 32. 4.2 Exdrson in Pincile...length by an integer. Positive feedback arises from the use of a lasing medium, a gas, liquid, crystal ions, or any of a number of other possibilities
A Self-Alignment Algorithm for SINS Based on Gravitational Apparent Motion and Sensor Data Denoising
Liu, Yiting; Xu, Xiaosu; Liu, Xixiang; Yao, Yiqing; Wu, Liang; Sun, Jin
2015-01-01
Initial alignment is always a key topic and difficult to achieve in an inertial navigation system (INS). In this paper a novel self-initial alignment algorithm is proposed using gravitational apparent motion vectors at three different moments and vector-operation. Simulation and analysis showed that this method easily suffers from the random noise contained in accelerometer measurements which are used to construct apparent motion directly. Aiming to resolve this problem, an online sensor data denoising method based on a Kalman filter is proposed and a novel reconstruction method for apparent motion is designed to avoid the collinearity among vectors participating in the alignment solution. Simulation, turntable tests and vehicle tests indicate that the proposed alignment algorithm can fulfill initial alignment of strapdown INS (SINS) under both static and swinging conditions. The accuracy can either reach or approach the theoretical values determined by sensor precision under static or swinging conditions. PMID:25923932
Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization
NASA Astrophysics Data System (ADS)
Liu, Zexi
2018-01-01
Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.
Localization of a mobile laser scanner via dimensional reduction
NASA Astrophysics Data System (ADS)
Lehtola, Ville V.; Virtanen, Juho-Pekka; Vaaja, Matti T.; Hyyppä, Hannu; Nüchter, Andreas
2016-11-01
We extend the concept of intrinsic localization from a theoretical one-dimensional (1D) solution onto a 2D manifold that is embedded in a 3D space, and then recover the full six degrees of freedom for a mobile laser scanner with a simultaneous localization and mapping algorithm (SLAM). By intrinsic localization, we mean that no reference coordinate system, such as global navigation satellite system (GNSS), nor inertial measurement unit (IMU) are used. Experiments are conducted with a 2D laser scanner mounted on a rolling prototype platform, VILMA. The concept offers potential in being extendable to other wheeled platforms.
Radio/FADS/IMU integrated navigation for Mars entry
NASA Astrophysics Data System (ADS)
Jiang, Xiuqiang; Li, Shuang; Huang, Xiangyu
2018-03-01
Supposing future orbiting and landing collaborative exploration mission as the potential project background, this paper addresses the issue of Mars entry integrated navigation using radio beacon, flush air data sensing system (FADS), and inertial measurement unit (IMU). The range and Doppler information sensed from an orbiting radio beacon, the dynamic pressure and heating data sensed from flush air data sensing system, and acceleration and attitude angular rate outputs from an inertial measurement unit are integrated in an unscented Kalman filter to perform state estimation and suppress the system and measurement noise. Computer simulations show that the proposed integrated navigation scheme can enhance the navigation accuracy, which enables precise entry guidance for the given Mars orbiting and landing collaborative exploration mission.
Fuzzy adaptive integration scheme for low-cost SINS/GPS navigation system
NASA Astrophysics Data System (ADS)
Nourmohammadi, Hossein; Keighobadi, Jafar
2018-01-01
Due to weak stand-alone accuracy as well as poor run-to-run stability of micro-electro mechanical system (MEMS)-based inertial sensors, special approaches are required to integrate low-cost strap-down inertial navigation system (SINS) with global positioning system (GPS), particularly in long-term applications. This paper aims to enhance long-term performance of conventional SINS/GPS navigation systems using a fuzzy adaptive integration scheme. The main concept behind the proposed adaptive integration is the good performance of attitude-heading reference system (AHRS) in low-accelerated motions and its degradation in maneuvered or accelerated motions. Depending on vehicle maneuvers, gravity-based attitude angles can be intelligently utilized to improve orientation estimation in the SINS. Knowledge-based fuzzy inference system is developed for decision-making between the AHRS and the SINS according to vehicle maneuvering conditions. Inertial measurements are the main input data of the fuzzy system to determine the maneuvering level during the vehicle motions. Accordingly, appropriate weighting coefficients are produced to combine the SINS/GPS and the AHRS, efficiently. The assessment of the proposed integrated navigation system is conducted via real data in airborne tests.
Space shuttle navigation analysis. Volume 2: Baseline system navigation
NASA Technical Reports Server (NTRS)
Jones, H. L.; Luders, G.; Matchett, G. A.; Rains, R. G.
1980-01-01
Studies related to the baseline navigation system for the orbiter are presented. The baseline navigation system studies include a covariance analysis of the Inertial Measurement Unit calibration and alignment procedures, postflight IMU error recovery for the approach and landing phases, on-orbit calibration of IMU instrument biases, and a covariance analysis of entry and prelaunch navigation system performance.
Simultaneous dual-band radar development
NASA Technical Reports Server (NTRS)
Liskow, C. L.
1974-01-01
Efforts to design and construct an airborne imaging radar operating simultaneously at L band and X band with an all-inertial navigation system in order to form a dual-band radar system are described. The areas of development include duplex transmitters, receivers, and recorders, a control module, motion compensation for both bands, and adaptation of a commercial inertial navigation system. Installation of the system in the aircraft and flight tests are described. Circuit diagrams, performance figures, and some radar images are presented.
Wang, Wei; Chen, Xiyuan
2018-01-01
In view of the fact the accuracy of the third-degree Cubature Kalman Filter (CKF) used for initial alignment under large misalignment angle conditions is insufficient, an improved fifth-degree CKF algorithm is proposed in this paper. In order to make full use of the innovation on filtering, the innovation covariance matrix is calculated recursively by an innovative sequence with an exponent fading factor. Then a new adaptive error covariance matrix scaling algorithm is proposed. The Singular Value Decomposition (SVD) method is used for improving the numerical stability of the fifth-degree CKF in this paper. In order to avoid the overshoot caused by excessive scaling of error covariance matrix during the convergence stage, the scaling scheme is terminated when the gradient of azimuth reaches the maximum. The experimental results show that the improved algorithm has better alignment accuracy with large misalignment angles than the traditional algorithm. PMID:29473912
Advanced Pedestrian Positioning System to Smartphones and Smartwatches.
Correa, Alejandro; Munoz Diaz, Estefania; Bousdar Ahmed, Dina; Morell, Antoni; Lopez Vicario, Jose
2016-11-11
In recent years, there has been an increasing interest in the development of pedestrian navigation systems for satellite-denied scenarios. The popularization of smartphones and smartwatches is an interesting opportunity for reducing the infrastructure cost of the positioning systems. Nowadays, smartphones include inertial sensors that can be used in pedestrian dead-reckoning (PDR) algorithms for the estimation of the user's position. Both smartphones and smartwatches include WiFi capabilities allowing the computation of the received signal strength (RSS). We develop a new method for the combination of RSS measurements from two different receivers using a Gaussian mixture model. We also analyze the implication of using a WiFi network designed for communication purposes in an indoor positioning system when the designer cannot control the network configuration. In this work, we design a hybrid positioning system that combines inertial measurements, from low-cost inertial sensors embedded in a smartphone, with RSS measurements through an extended Kalman filter. The system has been validated in a real scenario, and results show that our system improves the positioning accuracy of the PDR system thanks to the use of two WiFi receivers. The designed system obtains an accuracy up to 1.4 m in a scenario of 6000 m 2 .
NASA Astrophysics Data System (ADS)
Navidi, N.; Landry, R., Jr.
2015-08-01
Nowadays, Global Positioning System (GPS) receivers are aided by some complementary radio navigation systems and Inertial Navigation Systems (INS) to obtain more accuracy and robustness in land vehicular navigation. Extended Kalman Filter (EKF) is an acceptable conventional method to estimate the position, the velocity, and the attitude of the navigation system when INS measurements are fused with GPS data. However, the usage of the low-cost Inertial Measurement Units (IMUs) based on the Micro-Electro-Mechanical Systems (MEMS), for the land navigation systems, reduces the precision and stability of the navigation system due to their inherent errors. The main goal of this paper is to provide a new model for fusing low-cost IMU and GPS measurements. The proposed model is based on EKF aided by Fuzzy Inference Systems (FIS) as a promising method to solve the mentioned problems. This model considers the parameters of the measurement noise to adjust the measurement and noise process covariance. The simulation results show the efficiency of the proposed method to reduce the navigation system errors compared with EKF.
Real-Time Single-Frequency GPS/MEMS-IMU Attitude Determination of Lightweight UAVs
Eling, Christian; Klingbeil, Lasse; Kuhlmann, Heiner
2015-01-01
In this paper, a newly-developed direct georeferencing system for the guidance, navigation and control of lightweight unmanned aerial vehicles (UAVs), having a weight limit of 5 kg and a size limit of 1.5 m, and for UAV-based surveying and remote sensing applications is presented. The system is intended to provide highly accurate positions and attitudes (better than 5 cm and 0.5∘) in real time, using lightweight components. The main focus of this paper is on the attitude determination with the system. This attitude determination is based on an onboard single-frequency GPS baseline, MEMS (micro-electro-mechanical systems) inertial sensor readings, magnetic field observations and a 3D position measurement. All of this information is integrated in a sixteen-state error space Kalman filter. Special attention in the algorithm development is paid to the carrier phase ambiguity resolution of the single-frequency GPS baseline observations. We aim at a reliable and instantaneous ambiguity resolution, since the system is used in urban areas, where frequent losses of the GPS signal lock occur and the GPS measurement conditions are challenging. Flight tests and a comparison to a navigation-grade inertial navigation system illustrate the performance of the developed system in dynamic situations. Evaluations show that the accuracies of the system are 0.05∘ for the roll and the pitch angle and 0.2∘ for the yaw angle. The ambiguities of the single-frequency GPS baseline can be resolved instantaneously in more than 90% of the cases. PMID:26501281
Sensors integration for smartphone navigation: performances and future challenges
NASA Astrophysics Data System (ADS)
Aicardi, I.; Dabove, P.; Lingua, A.; Piras, M.
2014-08-01
Nowadays the modern smartphones include several sensors which are usually adopted in geomatic application, as digital camera, GNSS (Global Navigation Satellite System) receivers, inertial platform, RFID and Wi-Fi systems. In this paper the authors would like to testing the performances of internal sensors (Inertial Measurement Unit, IMU) of three modern smartphones (Samsung GalaxyS4, Samsung GalaxyS5 and iPhone4) compared to external mass-market IMU platform in order to verify their accuracy levels, in terms of positioning. Moreover, the Image Based Navigation (IBN) approach is also investigated: this approach can be very useful in hard-urban environment or for indoor positioning, as alternative to GNSS positioning. IBN allows to obtain a sub-metrical accuracy, but a special database of georeferenced images (Image DataBase, IDB) is needed, moreover it is necessary to use dedicated algorithm to resizing the images which are collected by smartphone, in order to share it with the server where is stored the IDB. Moreover, it is necessary to characterize smartphone camera lens in terms of focal length and lens distortions. The authors have developed an innovative method with respect to those available today, which has been tested in a covered area, adopting a special support where all sensors under testing have been installed. Geomatic instrument have been used to define the reference trajectory, with purpose to compare this one, with the path obtained with IBN solution. First results leads to have an horizontal and vertical accuracies better than 60 cm, respect to the reference trajectories. IBN method, sensors, test and result will be described in the paper.
Investigation on navigation patterns of inertial/celestial integrated systems
NASA Astrophysics Data System (ADS)
Luo, Dacheng; Liu, Yan; Liu, Zhiguo; Jiao, Wei; Wang, Qiuyan
2014-11-01
It is known that Strapdown Inertial Navigation System (SINS), Global Navigation Satellite System (GNSS) and Celestial Navigation System (CNS) can complement each other's advantages. The SINS/CNS integrated system, which has the characteristics of strong autonomy, high accuracy and good anti-jamming, is widely used in military and civilian applications. Similar to SINS/GNSS integrated system, the SINS/CNS integrated system can also be divided into three kinds according to the difference of integrating depth, i.e., loosely coupled pattern, tightly coupled pattern and deeply coupled pattern. In this paper, the principle and characteristics of each pattern of SINS/CNS system are analyzed. Based on the comparison of these patterns, a novel deeply coupled SINS/CNS integrated navigation scheme is proposed. The innovation of this scheme is that a new star pattern matching method aided by SINS information is put forward. Thus the complementary features of these two subsystems are reflected.
NASA Astrophysics Data System (ADS)
Treder, Alfred J.; Meldahl, Keith L.
The recorded histories of Shuttle/Orbiter attitude and Inertial Upper Stage (IUS) attitude have been analyzed for all joint flights of the IUS in the Orbiter. This database was studied to determine the behavior of relative alignment between the IUS and Shuttle navigation systems. It is found that the overall accuracy of physical alignment has a Shuttle Orbiter bias component less than 5 arcmin/axis and a short-term stability upper bound of 0.5 arcmin/axis, both at 1 sigma. Summaries of the experienced physical and inertial alginment offsets are shown in this paper, together with alignment variation data, illustrated with some flight histories. Also included is a table of candidate values for some error source groups in an Orbiter/IUS attitude errror model. Experience indicates that the Shuttle is much more accurate and stable as an orbiting launch platform than has so far been advertised. This information will be valuable for future Shuttle payloads, especially those (such as the Aeroassisted Flight Experiment) which carry their own inertial navigation systems, and which could update or initialize their attitude determination systems using the Shuttle as the reference.
INS/GNSS Integration for Aerobatic Flight Applications and Aircraft Motion Surveying.
V Hinüber, Edgar L; Reimer, Christian; Schneider, Tim; Stock, Michael
2017-04-26
This paper presents field tests of challenging flight applications obtained with a new family of lightweight low-power INS/GNSS ( inertial navigation system/global satellite navigation system ) solutions based on MEMS ( micro-electro-mechanical- sensor ) machined sensors, being used for UAV ( unmanned aerial vehicle ) navigation and control as well as for aircraft motion dynamics analysis and trajectory surveying. One key is a 42+ state extended Kalman-filter-based powerful data fusion, which also allows the estimation and correction of parameters that are typically affected by sensor aging, especially when applying MEMS-based inertial sensors, and which is not yet deeply considered in the literature. The paper presents the general system architecture, which allows iMAR Navigation the integration of all classes of inertial sensors and GNSS ( global navigation satellite system ) receivers from very-low-cost MEMS and high performance MEMS over FOG ( fiber optical gyro ) and RLG ( ring laser gyro ) up to HRG ( hemispherical resonator gyro ) technology, and presents detailed flight test results obtained under extreme flight conditions. As a real-world example, the aerobatic maneuvers of the World Champion 2016 (Red Bull Air Race) are presented. Short consideration is also given to surveying applications, where the ultimate performance of the same data fusion, but applied on gravimetric surveying, is discussed.
INS/GNSS Integration for Aerobatic Flight Applications and Aircraft Motion Surveying
v. Hinüber, Edgar L.; Reimer, Christian; Schneider, Tim; Stock, Michael
2017-01-01
This paper presents field tests of challenging flight applications obtained with a new family of lightweight low-power INS/GNSS (inertial navigation system/global satellite navigation system) solutions based on MEMS (micro-electro-mechanical- sensor) machined sensors, being used for UAV (unmanned aerial vehicle) navigation and control as well as for aircraft motion dynamics analysis and trajectory surveying. One key is a 42+ state extended Kalman-filter-based powerful data fusion, which also allows the estimation and correction of parameters that are typically affected by sensor aging, especially when applying MEMS-based inertial sensors, and which is not yet deeply considered in the literature. The paper presents the general system architecture, which allows iMAR Navigation the integration of all classes of inertial sensors and GNSS (global navigation satellite system) receivers from very-low-cost MEMS and high performance MEMS over FOG (fiber optical gyro) and RLG (ring laser gyro) up to HRG (hemispherical resonator gyro) technology, and presents detailed flight test results obtained under extreme flight conditions. As a real-world example, the aerobatic maneuvers of the World Champion 2016 (Red Bull Air Race) are presented. Short consideration is also given to surveying applications, where the ultimate performance of the same data fusion, but applied on gravimetric surveying, is discussed. PMID:28445417
Autonomous integrated GPS/INS navigation experiment for OMV. Phase 1: Feasibility study
NASA Technical Reports Server (NTRS)
Upadhyay, Triveni N.; Priovolos, George J.; Rhodehamel, Harley
1990-01-01
The phase 1 research focused on the experiment definition. A tightly integrated Global Positioning System/Inertial Navigation System (GPS/INS) navigation filter design was analyzed and was shown, via detailed computer simulation, to provide precise position, velocity, and attitude (alignment) data to support navigation and attitude control requirements of future NASA missions. The application of the integrated filter was also shown to provide the opportunity to calibrate inertial instrument errors which is particularly useful in reducing INS error growth during times of GPS outages. While the Orbital Maneuvering Vehicle (OMV) provides a good target platform for demonstration and for possible flight implementation to provide improved capability, a successful proof-of-concept ground demonstration can be obtained using any simulated mission scenario data, such as Space Transfer Vehicle, Shuttle-C, Space Station.
INERTIAL INSTRUMENT SYSTEM FOR AERIAL SURVEYING.
Brown, Russell H.; Chapman, William H.; Hanna, William F.; Mongan, Charles E.; Hursh, John W.
1987-01-01
The purpose of this report is to describe an inertial guidance or navigation system that will enable use of relatively light aircraft for efficient data-gathering in geologgy, hydrology, terrain mapping, and gravity-field mapping. The instrument system capitalizes not only on virtual state-of-the-art inertial guidance technology but also on similarly advanced technology for measuring distance with electromagnetic radiating devices. The distance measurement can be made with a transceiver beamed at either a cooperative taget, with a specially designed reflecting surface, or a noncooperative target, such as the Earth's surface. The instrument system features components that use both techniques. Thus, a laser tracker device, which updates the inertial guidance unit or navigator in flight, makes distance measurements to a retroreflector target mounted at a ground-control point; a laser profiler device, beamed vertically downward, makes distance measurements to the Earth's surface along a path that roughly mirrors the aircraft flight path.
Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems.
Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing
2016-07-26
This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF) is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD) parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF), unscented Kalman filter (UKF), and CKF approaches.
Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems
Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing
2016-01-01
This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF) is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD) parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF), unscented Kalman filter (UKF), and CKF approaches. PMID:27472336
NASA Astrophysics Data System (ADS)
Lu, Jiazhen; Liang, Shufang; Yang, Yanqiang
2017-10-01
Micro-electro-mechanical systems (MEMS) inertial measurement devices tend to be widely used in inertial navigation systems and have quickly emerged on the market due to their characteristics of low cost, high reliability and small size. Calibration is the most effective way to remove the deterministic error of an inertial reference unit (IRU), which in this paper consists of three orthogonally mounted MEMS gyros. However, common testing methods in the lab cannot predict the corresponding errors precisely when the turntable’s working condition is restricted. In this paper, the turntable can only provide a relatively small rotation angle. Moreover, the errors must be compensated exactly because of the great effect caused by the high angular velocity of the craft. To deal with this question, a new method is proposed to evaluate the MEMS IRU’s performance. In the calibration procedure, a one-axis table that can rotate a limited angle in the form of a sine function is utilized to provide the MEMS IRU’s angular velocity. A new algorithm based on Fourier series is designed to calculate the misalignment and scale factor errors. The proposed method is tested in a set of experiments, and the calibration results are compared to a traditional calibration method performed under normal working conditions to verify their correctness. In addition, a verification test in the given rotation speed is implemented for further demonstration.
Han, Houzeng; Wang, Jian; Wang, Jinling; Tan, Xinglong
2015-01-01
The integration of Global Navigation Satellite Systems (GNSS) carrier phases with Inertial Navigation System (INS) measurements is essential to provide accurate and continuous position, velocity and attitude information, however it is necessary to fix ambiguities rapidly and reliably to obtain high accuracy navigation solutions. In this paper, we present the notion of combining the Global Positioning System (GPS), the BeiDou Navigation Satellite System (BDS) and low-cost micro-electro-mechanical sensors (MEMS) inertial systems for reliable navigation. An adaptive multipath factor-based tightly-coupled (TC) GPS/BDS/INS integration algorithm is presented and the overall performance of the integrated system is illustrated. A twenty seven states TC GPS/BDS/INS model is adopted with an extended Kalman filter (EKF), which is carried out by directly fusing ambiguity fixed double-difference (DD) carrier phase measurements with the INS predicted pseudoranges to estimate the error states. The INS-aided integer ambiguity resolution (AR) strategy is developed by using a dynamic model, a two-step estimation procedure is applied with adaptively estimated covariance matrix to further improve the AR performance. A field vehicular test was carried out to demonstrate the positioning performance of the combined system. The results show the TC GPS/BDS/INS system significantly improves the single-epoch AR reliability as compared to that of GPS/BDS-only or single satellite navigation system integrated strategy, especially for high cut-off elevations. The AR performance is also significantly improved for the combined system with adaptive covariance matrix in the presence of low elevation multipath related to the GNSS-only case. A total of fifteen simulated outage tests also show that the time to relock of the GPS/BDS signals is shortened, which improves the system availability. The results also indicate that TC integration system achieves a few centimeters accuracy in positioning based on the comparison analysis and covariance analysis, even in harsh environments (e.g., in urban canyons), thus we can see the advantage of positioning at high cut-off elevations that the combined GPS/BDS brings. PMID:25875191
Han, Houzeng; Wang, Jian; Wang, Jinling; Tan, Xinglong
2015-04-14
The integration of Global Navigation Satellite Systems (GNSS) carrier phases with Inertial Navigation System (INS) measurements is essential to provide accurate and continuous position, velocity and attitude information, however it is necessary to fix ambiguities rapidly and reliably to obtain high accuracy navigation solutions. In this paper, we present the notion of combining the Global Positioning System (GPS), the BeiDou Navigation Satellite System (BDS) and low-cost micro-electro-mechanical sensors (MEMS) inertial systems for reliable navigation. An adaptive multipath factor-based tightly-coupled (TC) GPS/BDS/INS integration algorithm is presented and the overall performance of the integrated system is illustrated. A twenty seven states TC GPS/BDS/INS model is adopted with an extended Kalman filter (EKF), which is carried out by directly fusing ambiguity fixed double-difference (DD) carrier phase measurements with the INS predicted pseudoranges to estimate the error states. The INS-aided integer ambiguity resolution (AR) strategy is developed by using a dynamic model, a two-step estimation procedure is applied with adaptively estimated covariance matrix to further improve the AR performance. A field vehicular test was carried out to demonstrate the positioning performance of the combined system. The results show the TC GPS/BDS/INS system significantly improves the single-epoch AR reliability as compared to that of GPS/BDS-only or single satellite navigation system integrated strategy, especially for high cut-off elevations. The AR performance is also significantly improved for the combined system with adaptive covariance matrix in the presence of low elevation multipath related to the GNSS-only case. A total of fifteen simulated outage tests also show that the time to relock of the GPS/BDS signals is shortened, which improves the system availability. The results also indicate that TC integration system achieves a few centimeters accuracy in positioning based on the comparison analysis and covariance analysis, even in harsh environments (e.g., in urban canyons), thus we can see the advantage of positioning at high cut-off elevations that the combined GPS/BDS brings.
NASA Astrophysics Data System (ADS)
Štefanička, Tomáš; Ďuračiová, Renata; Seres, Csaba
2017-12-01
As a complex of buildings, the Faculty of Natural Sciences of the Comenius University in Bratislava tends to be difficult to navigate in spite of its size. An indoor navigation application could potentially save a lot of time and frustration. There are currently numerous technologies used in indoor navigation systems. Some of them focus on a high degree of precision and require significant financial investment; others provide only static information about a current location. In this paper we focused on the determination of an approximate location using inertial measurement systems available on most smartphones, i.e., a gyroscope and an accelerometer. The actual position of the device was calculated using "a walk detection method" based on a delayed lack of motion. We have developed an indoor navigation application that relies solely on open source JavaScript libraries to visualize the interior of the building and calculate the shortest path utilizing Dijsktra's routing algorithm. The application logic is located on the client side, so the software is able to work offline. Our solution represents an accessible lowcost and platform-independent web application that can significantly improve navigation at the Faculty of Natural Sciences. Although our application has been developed on a specific building complex, it could be used in other interiors as well.
Gravity compensation in a Strapdown Inertial Navigation System to improve the attitude accuracy
NASA Astrophysics Data System (ADS)
Zhu, Jing; Wang, Jun; Wang, Xingshu; Yang, Shuai
2017-10-01
Attitude errors in a strapdown inertial navigation system due to gravity disturbances and system noises can be relatively large, although they are bound within the Schuler and the Earth rotation period. The principal objective of the investigation is to determine to what extent accurate gravity data can improve the attitude accuracy. The way the gravity disturbances affect the attitude were analyzed and compared with system noises by the analytic solution and simulation. The gravity disturbances affect the attitude accuracy by introducing the initial attitude error and the equivalent accelerometer bias. With the development of the high precision inertial devices and the application of the rotation modulation technology, the gravity disturbance cannot be neglected anymore. The gravity compensation was performed using the EGM2008 and simulations with and without accurate gravity compensation under varying navigation conditions were carried out. The results show that the gravity compensation improves the horizontal components of attitude accuracy evidently while the yaw angle is badly affected by the uncompensated gyro bias in vertical channel.
Wang, Qi; Gao, Chunfeng; Zhou, Jian; Wei, Guo; Nie, Xiaoming; Long, Xingwu
2018-05-01
In the field of land navigation, a laser Doppler velocimeter (LDV) can be used to provide the velocity of a vehicle for an integrated navigation system with a strapdown inertial navigation system. In order to suppress the influence of vehicle jolts on a one-dimensional (1D) LDV, this paper designs a split-reuse two-dimensional (2D) LDV. The velocimeter is made up of two 1D velocimeter probes that are mirror-mounted. By the different effects of the vertical vibration on the two probes, the velocimeter can calculate the forward velocity and the vertical velocity of a vehicle. The results of the vehicle-integrated navigation experiments show that the 2D LDV not only can actually suppress the influence of vehicle jolts and greatly improve the navigation positioning accuracy, but also can give high-precision altitude information. The maximum horizontal position errors of the two experiments are 2.6 m and 3.2 m in 1.9 h, and the maximum altitude errors are 0.24 m and 0.22 m, respectively.
NASA Astrophysics Data System (ADS)
Lu, Jiazhen; Lei, Chaohua; Yang, Yanqiang; Liu, Ming
2017-06-01
Many countries have been paying great attention to space exploration, especially about the Moon and the Mars. Autonomous and high-accuracy navigation systems are needed for probers and rovers to accomplish missions. Inertial navigation system (INS)/celestial navigation system (CNS) based navigation system has been used widely on the lunar rovers. Initialization is a particularly important step for navigation. This paper presents an in-motion alignment and positioning method for lunar rovers by INS/CNS/odometer integrated navigation. The method can estimate not only the position and attitude errors, but also the biases of the accelerometers and gyros using the standard Kalman filter. The differences between the platform star azimuth, elevation angles and the computed star azimuth, elevation angles, and the difference between the velocity measured by odometer and the velocity measured by inertial sensors are taken as measurements. The semi-physical experiments are implemented to demonstrate that the position error can reduce to 10 m and attitude error is within 2″ during 5 min. The experiment results prove that it is an effective and attractive initialization approach for lunar rovers.
In-Flight Alignment Using H ∞ Filter for Strapdown INS on Aircraft
Pei, Fu-Jun; Liu, Xuan; Zhu, Li
2014-01-01
In-flight alignment is an effective way to improve the accuracy and speed of initial alignment for strapdown inertial navigation system (INS). During the aircraft flight, strapdown INS alignment was disturbed by lineal and angular movements of the aircraft. To deal with the disturbances in dynamic initial alignment, a novel alignment method for SINS is investigated in this paper. In this method, an initial alignment error model of SINS in the inertial frame is established. The observability of the system is discussed by piece-wise constant system (PWCS) theory and observable degree is computed by the singular value decomposition (SVD) theory. It is demonstrated that the system is completely observable, and all the system state parameters can be estimated by optimal filter. Then a H ∞ filter was designed to resolve the uncertainty of measurement noise. The simulation results demonstrate that the proposed algorithm can reach a better accuracy under the dynamic disturbance condition. PMID:24511300
Song, Tianxiao; Wang, Xueyun; Liang, Wenwei; Xing, Li
2018-05-14
Benefiting from frame structure, RINS can improve the navigation accuracy by modulating the inertial sensor errors with proper rotation scheme. In the traditional motor control method, the measurements of the photoelectric encoder are always adopted to drive inertial measurement unit (IMU) to rotate. However, when carrier conducts heading motion, the inertial sensor errors may no longer be zero-mean in navigation coordinate. Meanwhile, some high-speed carriers like aircraft need to roll a certain angle to balance the centrifugal force during the heading motion, which may result in non-negligible coupling errors, caused by the FOG installation errors and scale factor errors. Moreover, the error parameters of FOG are susceptible to the temperature and magnetic field, and the pre-calibration is a time-consuming process which is difficult to completely suppress the FOG-related errors. In this paper, an improved motor control method with the measurements of FOG is proposed to address these problems, with which the outer frame can insulate the carrier's roll motion and the inner frame can simultaneously achieve the rotary modulation on the basis of insulating the heading motion. The results of turntable experiments indicate that the navigation performance of dual-axis RINS has been significantly improved over the traditional method, which could still be maintained even with large FOG installation errors and scale factor errors, proving that the proposed method can relax the requirements for the accuracy of FOG-related errors.
The Airborne Ocean Color Imager - System description and image processing
NASA Technical Reports Server (NTRS)
Wrigley, Robert C.; Slye, Robert E.; Klooster, Steven A.; Freedman, Richard S.; Carle, Mark; Mcgregor, Lloyd F.
1992-01-01
The Airborne Ocean Color Imager was developed as an aircraft instrument to simulate the spectral and radiometric characteristics of the next generation of satellite ocean color instrumentation. Data processing programs have been developed as extensions of the Coastal Zone Color Scanner algorithms for atmospheric correction and bio-optical output products. The latter include several bio-optical algorithms for estimating phytoplankton pigment concentration, as well as one for the diffuse attenuation coefficient of the water. Additional programs have been developed to geolocate these products and remap them into a georeferenced data base, using data from the aircraft's inertial navigation system. Examples illustrate the sequential data products generated by the processing system, using data from flightlines near the mouth of the Mississippi River: from raw data to atmospherically corrected data, to bio-optical data, to geolocated data, and, finally, to georeferenced data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Niven, W.A.
The long-term position accuracy of an inertial navigation system depends primarily on the ability of the gyroscopes to maintain a near-perfect reference orientation. Small imperfections in the gyroscopes cause them to drift slowly away from their initial orientation, thereby producing errors in the system's calculations of position. The A3FIX is a computer program subroutine developed to estimate inertial navigation system gyro drift rates with the navigator stopped or moving slowly. It processes data of the navigation system's position error to arrive at estimates of the north- south and vertical gyro drift rates. It also computes changes in the east--west gyromore » drift rate if the navigator is stopped and if data on the system's azimuth error changes are also available. The report describes the subroutine, its capabilities, and gives examples of gyro drift rate estimates that were computed during the testing of a high quality inertial system under the PASSPORT program at the Lawrence Livermore Laboratory. The appendices provide mathematical derivations of the estimation equations that are used in the subroutine, a discussion of the estimation errors, and a program listing and flow diagram. The appendices also contain a derivation of closed form solutions to the navigation equations to clarify the effects that motion and time-varying drift rates induce in the phase-plane relationships between the Schulerfiltered errors in latitude and azimuth snd between the Schulerfiltered errors in latitude and longitude. (auth)« less
Surface navigation on Mars with a Navigation Satellite
NASA Technical Reports Server (NTRS)
Vijayaraghavan, A.; Thurman, Sam W.; Kahn, Robert D.; Hastrup, Rolf C.
1992-01-01
Radiometric navigation data from the Deep Space Network (DSN) stations on the earth to transponders and other surface elements such as rovers and landers on Mars, can determine their positions to only within a kilometer in inertial space. The positional error is mostly in the z-component of the surface element parallel to the Martian spin-axis. However, with Doppler and differenced-Doppler data from a Navigation Satellite in orbit around Mars to two or more of such transponders on the planetary surface, their positions can be determined to within 15 meters (or 20 meters for one-way Doppler beacons on Mars) in inertial space. In this case, the transponders (or other vehicles) on Mars need not even be capable of directly communicating to the earth. When the Navigation Satellite data is complemented by radiometric observations from the DSN stations also, directly to the surface elements on Mars, their positions can be determined to within 3 meters in inertial space. The relative positions of such surface elements on Mars (relative to one another) in Mars-fixed coordinates, however, can be determined to within 5 meters from simply range and Doppler data from the DSN stations to the surface elements. These results are obtained from covariance studies assuming X-band data noise levels and data-arcs not exceeding 10 days. They are significant in the planning and deployment of a Mars-based navigation network necessary to support real-time operations during critical phases of manned exploration of Mars.
Surface navigation on Mars with a Navigation Satellite
NASA Astrophysics Data System (ADS)
Vijayaraghavan, A.; Thurman, Sam W.; Kahn, Robert D.; Hastrup, Rolf C.
Radiometric navigation data from the Deep Space Network (DSN) stations on the earth to transponders and other surface elements such as rovers and landers on Mars, can determine their positions to only within a kilometer in inertial space. The positional error is mostly in the z-component of the surface element parallel to the Martian spin-axis. However, with Doppler and differenced-Doppler data from a Navigation Satellite in orbit around Mars to two or more of such transponders on the planetary surface, their positions can be determined to within 15 meters (or 20 meters for one-way Doppler beacons on Mars) in inertial space. In this case, the transponders (or other vehicles) on Mars need not even be capable of directly communicating to the earth. When the Navigation Satellite data is complemented by radiometric observations from the DSN stations also, directly to the surface elements on Mars, their positions can be determined to within 3 meters in inertial space. The relative positions of such surface elements on Mars (relative to one another) in Mars-fixed coordinates, however, can be determined to within 5 meters from simply range and Doppler data from the DSN stations to the surface elements. These results are obtained from covariance studies assuming X-band data noise levels and data-arcs not exceeding 10 days. They are significant in the planning and deployment of a Mars-based navigation network necessary to support real-time operations during critical phases of manned exploration of Mars.
Wang, Qiuying; Guo, Zheng; Sun, Zhiguo; Cui, Xufei; Liu, Kaiyue
2018-01-01
Pedestrian-positioning technology based on the foot-mounted micro inertial measurement unit (MIMU) plays an important role in the field of indoor navigation and has received extensive attention in recent years. However, the positioning accuracy of the inertial-based pedestrian-positioning method is rapidly reduced because of the relatively low measurement accuracy of the measurement sensor. The zero-velocity update (ZUPT) is an error correction method which was proposed to solve the cumulative error because, on a regular basis, the foot is stationary during the ordinary gait; this is intended to reduce the position error growth of the system. However, the traditional ZUPT has poor performance because the time of foot touchdown is short when the pedestrians move faster, which decreases the positioning accuracy. Considering these problems, a forward and reverse calculation method based on the adaptive zero-velocity interval adjustment for the foot-mounted MIMU location method is proposed in this paper. To solve the inaccuracy of the zero-velocity interval detector during fast pedestrian movement where the contact time of the foot on the ground is short, an adaptive zero-velocity interval detection algorithm based on fuzzy logic reasoning is presented in this paper. In addition, to improve the effectiveness of the ZUPT algorithm, forward and reverse multiple solutions are presented. Finally, with the basic principles and derivation process of this method, the MTi-G710 produced by the XSENS company is used to complete the test. The experimental results verify the correctness and applicability of the proposed method. PMID:29883399
NASA Astrophysics Data System (ADS)
Fabbrini, L.; Messina, M.; Greco, M.; Pinelli, G.
2011-10-01
In the context of augmented integrity Inertial Navigation System (INS), recent technological developments have been focusing on landmark extraction from high-resolution synthetic aperture radar (SAR) images in order to retrieve aircraft position and attitude. The article puts forward a processing chain that can automatically detect linear landmarks on highresolution synthetic aperture radar (SAR) images and can be successfully exploited also in the context of augmented integrity INS. The processing chain uses constant false alarm rate (CFAR) edge detectors as the first step of the whole processing procedure. Our studies confirm that the ratio of averages (RoA) edge detector detects object boundaries more effectively than Student T-test and Wilcoxon-Mann-Whitney (WMW) test. Nevertheless, all these statistical edge detectors are sensitive to violation of the assumptions which underlie their theory. In addition to presenting a solution to the previous problem, we put forward a new post-processing algorithm useful to remove the main false alarms, to select the most probable edge position, to reconstruct broken edges and finally to vectorize them. SAR images from the "MSTAR clutter" dataset were used to prove the effectiveness of the proposed algorithms.
NASA Technical Reports Server (NTRS)
Rogers, Aaron; Anderson, Kalle; Mracek, Anna; Zenick, Ray
2004-01-01
With the space industry's increasing focus upon multi-spacecraft formation flight missions, the ability to precisely determine system topology and the orientation of member spacecraft relative to both inertial space and each other is becoming a critical design requirement. Topology determination in satellite systems has traditionally made use of GPS or ground uplink position data for low Earth orbits, or, alternatively, inter-satellite ranging between all formation pairs. While these techniques work, they are not ideal for extension to interplanetary missions or to large fleets of decentralized, mixed-function spacecraft. The Vision-Based Attitude and Formation Determination System (VBAFDS) represents a novel solution to both the navigation and topology determination problems with an integrated approach that combines a miniature star tracker with a suite of robust processing algorithms. By combining a single range measurement with vision data to resolve complete system topology, the VBAFDS design represents a simple, resource-efficient solution that is not constrained to certain Earth orbits or formation geometries. In this paper, analysis and design of the VBAFDS integrated guidance, navigation and control (GN&C) technology will be discussed, including hardware requirements, algorithm development, and simulation results in the context of potential mission applications.
NASA Technical Reports Server (NTRS)
1977-01-01
The use of computers for aircraft control, flight simulation, and inertial navigation is explored. The man-machine relation problem in aviation is addressed. Simple and self-adapting autopilots are described and the assets and liabilities of digital navigation techniques are assessed.
Competitive evaluation of failure detection algorithms for strapdown redundant inertial instruments
NASA Technical Reports Server (NTRS)
Wilcox, J. C.
1973-01-01
Algorithms for failure detection, isolation, and correction of redundant inertial instruments in the strapdown dodecahedron configuration are competitively evaluated in a digital computer simulation that subjects them to identical environments. Their performance is compared in terms of orientation and inertial velocity errors and in terms of missed and false alarms. The algorithms appear in the simulation program in modular form, so that they may be readily extracted for use elsewhere. The simulation program and its inputs and outputs are described. The algorithms, along with an eight algorithm that was not simulated, also compared analytically to show the relationships among them.
2011-03-01
with the Earth but does follow the Earth’s orbit around the sun . Though it is not a true inertial frame, for the sake of terrestrial navigation it can...the center of the Earth , with the x and y-axes on the equatorial plane and the z- axis along the Earth’s axis of rotation. The i-frame does not spin...be considered as such. Earth -centered Earth -fixed frame (e-frame) - The origin is fixed at the center of the Earth , with the x- axis on the equatorial
Computer-aided system for detecting runway incursions
NASA Astrophysics Data System (ADS)
Sridhar, Banavar; Chatterji, Gano B.
1994-07-01
A synthetic vision system for enhancing the pilot's ability to navigate and control the aircraft on the ground is described. The system uses the onboard airport database and images acquired by external sensors. Additional navigation information needed by the system is provided by the Inertial Navigation System and the Global Positioning System. The various functions of the system, such as image enhancement, map generation, obstacle detection, collision avoidance, guidance, etc., are identified. The available technologies, some of which were developed at NASA, that are applicable to the aircraft ground navigation problem are noted. Example images of a truck crossing the runway while the aircraft flies close to the runway centerline are described. These images are from a sequence of images acquired during one of the several flight experiments conducted by NASA to acquire data to be used for the development and verification of the synthetic vision concepts. These experiments provide a realistic database including video and infrared images, motion states from the Inertial Navigation System and the Global Positioning System, and camera parameters.
Application of GPS to Enable Launch Vehicle Upper Stage Heliocentric Disposal
NASA Technical Reports Server (NTRS)
Anzalone, Evan J.; Oliver, T. Emerson
2017-01-01
To properly dispose of the upper stage of the Space Launch System, the vehicle must perform a burn in Earth orbit to perform a close flyby of the Lunar surface to gain adequate energy to enter into heliocentric space. This architecture was selected to meet NASA requirements to limit orbital debris in the Earth-Moon system. The choice of a flyby for heliocentric disposal was driven by mission and vehicle constraints. This paper describes the SLS mission for Exploration Mission -1, a high level overview of the Block 1 vehicle, and the various disposal options considered. The research focuses on this analysis in terms of the mission design and navigation problem, focusing on the vehicle-level requirements that enable a successful mission. An inertial-only system is shown to be insufficient for heliocentric flyby due to large inertial integration errors from launch through disposal maneuver while on a trans-lunar trajectory. The various options for aiding the navigation system are presented and details are provided on the use of GPS to bound the state errors in orbit to improve the capability for stage disposal. The state estimation algorithm used is described as well as its capability in determination of the vehicle state at the start of the planned maneuver. This data, both dispersions on state and on errors, is then used to develop orbital targets to use for meeting the required Lunar flyby for entering onto a heliocentric trajectory. The effect of guidance and navigation errors on this capability is described as well as the identified constraints for achieving the disposal requirements. Additionally, discussion is provided on continued analysis and identification of system considerations that can drive the ability to integrate onto a vehicle intended for deep space.
Sampling and Control Circuit Board for an Inertial Measurement Unit
NASA Technical Reports Server (NTRS)
Chelmins, David; Powis, Rick
2012-01-01
Spacesuit navigation is one component of NASA s efforts to return humans to the Moon. Studies performed at the NASA Glenn Research Center (GRC) considered various navigation technologies and filtering approaches to enable navigation on the lunar surface. As part of this effort, microelectromechanical systems (MEMS) inertial measurement units (IMUs) were studied to determine if they could supplement a radiometric infrastructure. MEMS IMUs were included in the Lunar Extra-Vehicular Activity Crewmember Location Determination System (LECLDS) testbed during NASA s annual Desert Research and Technology Studies (D-RATS) event in 2009 and 2010. The testbed included one IMU in 2009 and three IMUs in 2010, along with a custom circuit board interfacing between the navigation processor and each IMU. The board was revised for the 2010 test, and this paper documents the design details of this latest revision of the interface circuit board and firmware.
General test plan redundant sensor strapdown IMU evaluation program
NASA Technical Reports Server (NTRS)
Hartwell, T.; Irwin, H. A.; Miyatake, Y.; Wedekind, D. E.
1971-01-01
The general test plan for a redundant sensor strapdown inertial measuring unit evaluation program is presented. The inertial unit contains six gyros and three orthogonal accelerometers. The software incorporates failure detection and correction logic and a land vehicle navigation program. The principal objective of the test is a demonstration of the practicability, reliability, and performance of the inertial measuring unit with failure detection and correction in operational environments.
El-Diasty, Mohammed; Pagiatakis, Spiros
2009-01-01
In this paper, we examine the effect of changing the temperature points on MEMS-based inertial sensor random error. We collect static data under different temperature points using a MEMS-based inertial sensor mounted inside a thermal chamber. Rigorous stochastic models, namely Autoregressive-based Gauss-Markov (AR-based GM) models are developed to describe the random error behaviour. The proposed AR-based GM model is initially applied to short stationary inertial data to develop the stochastic model parameters (correlation times). It is shown that the stochastic model parameters of a MEMS-based inertial unit, namely the ADIS16364, are temperature dependent. In addition, field kinematic test data collected at about 17 °C are used to test the performance of the stochastic models at different temperature points in the filtering stage using Unscented Kalman Filter (UKF). It is shown that the stochastic model developed at 20 °C provides a more accurate inertial navigation solution than the ones obtained from the stochastic models developed at -40 °C, -20 °C, 0 °C, +40 °C, and +60 °C. The temperature dependence of the stochastic model is significant and should be considered at all times to obtain optimal navigation solution for MEMS-based INS/GPS integration.
Advanced Pedestrian Positioning System to Smartphones and Smartwatches
Correa, Alejandro; Munoz Diaz, Estefania; Bousdar Ahmed, Dina; Morell, Antoni; Lopez Vicario, Jose
2016-01-01
In recent years, there has been an increasing interest in the development of pedestrian navigation systems for satellite-denied scenarios. The popularization of smartphones and smartwatches is an interesting opportunity for reducing the infrastructure cost of the positioning systems. Nowadays, smartphones include inertial sensors that can be used in pedestrian dead-reckoning (PDR) algorithms for the estimation of the user’s position. Both smartphones and smartwatches include WiFi capabilities allowing the computation of the received signal strength (RSS). We develop a new method for the combination of RSS measurements from two different receivers using a Gaussian mixture model. We also analyze the implication of using a WiFi network designed for communication purposes in an indoor positioning system when the designer cannot control the network configuration. In this work, we design a hybrid positioning system that combines inertial measurements, from low-cost inertial sensors embedded in a smartphone, with RSS measurements through an extended Kalman filter. The system has been validated in a real scenario, and results show that our system improves the positioning accuracy of the PDR system thanks to the use of two WiFi receivers. The designed system obtains an accuracy up to 1.4 m in a scenario of 6000 m2. PMID:27845715
Lyu, Weiwei; Cheng, Xianghong
2017-11-28
Transfer alignment is always a key technology in a strapdown inertial navigation system (SINS) because of its rapidity and accuracy. In this paper a transfer alignment model is established, which contains the SINS error model and the measurement model. The time delay in the process of transfer alignment is analyzed, and an H∞ filtering method with delay compensation is presented. Then the H∞ filtering theory and the robust mechanism of H∞ filter are deduced and analyzed in detail. In order to improve the transfer alignment accuracy in SINS with time delay, an adaptive H∞ filtering method with delay compensation is proposed. Since the robustness factor plays an important role in the filtering process and has effect on the filtering accuracy, the adaptive H∞ filter with delay compensation can adjust the value of robustness factor adaptively according to the dynamic external environment. The vehicle transfer alignment experiment indicates that by using the adaptive H∞ filtering method with delay compensation, the transfer alignment accuracy and the pure inertial navigation accuracy can be dramatically improved, which demonstrates the superiority of the proposed filtering method.
Remarks to SBS PCM based self-navigation of laser drivers
NASA Astrophysics Data System (ADS)
Kalal, M.; Matena, L.; Kong, HJ; Martinkova, M.; Cha, S.
2016-03-01
A novel technology of self-navigation of laser drivers on injected inertial fusion energy pellets employing phase conjugating mirrors based on stimulating Brillouin scattering was recently proposed. Its feasibility as well as various implications were gradually studied and working solutions to potential problems were always suggested. As this technology could help to overcome several burning key issues of inertial fusion (e.g., a sufficiently precise navigation of laser drivers on injected pellets in the case of a direct drive scheme and decreased requirements on high-repetition high-power lasers) it gradually started to attract a carefully measured tentative interest among the major inertial fusion oriented laboratories and projects. In this paper the next step in this research path will be reported. It concerns the resulting phase and amplitude structures created by multiple low energy drivers (glints) illuminating the pellet during the first stage of the process after their reflection and a subsequent superposition on the collecting/focusing final optics. It was demonstrated that with a large number of such drivers acting simultaneously from many angles the situation gets somewhat complicated and requires more detailed studies/suggestions of suitable configurations.
Han, Houzeng; Xu, Tianhe; Wang, Jian
2016-01-01
Precise Point Positioning (PPP) makes use of the undifferenced pseudorange and carrier phase measurements with ionospheric-free (IF) combinations to achieve centimeter-level positioning accuracy. Conventionally, the IF ambiguities are estimated as float values. To improve the PPP positioning accuracy and shorten the convergence time, the integer phase clock model with between-satellites single-difference (BSSD) operation is used to recover the integer property. However, the continuity and availability of stand-alone PPP is largely restricted by the observation environment. The positioning performance will be significantly degraded when GPS operates under challenging environments, if less than five satellites are present. A commonly used approach is integrating a low cost inertial sensor to improve the positioning performance and robustness. In this study, a tightly coupled (TC) algorithm is implemented by integrating PPP with inertial navigation system (INS) using an Extended Kalman filter (EKF). The navigation states, inertial sensor errors and GPS error states are estimated together. The troposphere constrained approach, which utilizes external tropospheric delay as virtual observation, is applied to further improve the ambiguity-fixed height positioning accuracy, and an improved adaptive filtering strategy is implemented to improve the covariance modelling considering the realistic noise effect. A field vehicular test with a geodetic GPS receiver and a low cost inertial sensor was conducted to validate the improvement on positioning performance with the proposed approach. The results show that the positioning accuracy has been improved with inertial aiding. Centimeter-level positioning accuracy is achievable during the test, and the PPP/INS TC integration achieves a fast re-convergence after signal outages. For troposphere constrained solutions, a significant improvement for the height component has been obtained. The overall positioning accuracies of the height component are improved by 30.36%, 16.95% and 24.07% for three different convergence times, i.e., 60, 50 and 30 min, respectively. It shows that the ambiguity-fixed horizontal positioning accuracy has been significantly improved. When compared with the conventional PPP solution, it can be seen that position accuracies are improved by 19.51%, 61.11% and 23.53% for the north, east and height components, respectively, after one hour convergence through the troposphere constraint fixed PPP/INS with adaptive covariance model. PMID:27399721
HyMoTrack: A Mobile AR Navigation System for Complex Indoor Environments.
Gerstweiler, Georg; Vonach, Emanuel; Kaufmann, Hannes
2015-12-24
Navigating in unknown big indoor environments with static 2D maps is a challenge, especially when time is a critical factor. In order to provide a mobile assistant, capable of supporting people while navigating in indoor locations, an accurate and reliable localization system is required in almost every corner of the building. We present a solution to this problem through a hybrid tracking system specifically designed for complex indoor spaces, which runs on mobile devices like smartphones or tablets. The developed algorithm only uses the available sensors built into standard mobile devices, especially the inertial sensors and the RGB camera. The combination of multiple optical tracking technologies, such as 2D natural features and features of more complex three-dimensional structures guarantees the robustness of the system. All processing is done locally and no network connection is needed. State-of-the-art indoor tracking approaches use mainly radio-frequency signals like Wi-Fi or Bluetooth for localizing a user. In contrast to these approaches, the main advantage of the developed system is the capability of delivering a continuous 3D position and orientation of the mobile device with centimeter accuracy. This makes it usable for localization and 3D augmentation purposes, e.g. navigation tasks or location-based information visualization.
HyMoTrack: A Mobile AR Navigation System for Complex Indoor Environments
Gerstweiler, Georg; Vonach, Emanuel; Kaufmann, Hannes
2015-01-01
Navigating in unknown big indoor environments with static 2D maps is a challenge, especially when time is a critical factor. In order to provide a mobile assistant, capable of supporting people while navigating in indoor locations, an accurate and reliable localization system is required in almost every corner of the building. We present a solution to this problem through a hybrid tracking system specifically designed for complex indoor spaces, which runs on mobile devices like smartphones or tablets. The developed algorithm only uses the available sensors built into standard mobile devices, especially the inertial sensors and the RGB camera. The combination of multiple optical tracking technologies, such as 2D natural features and features of more complex three-dimensional structures guarantees the robustness of the system. All processing is done locally and no network connection is needed. State-of-the-art indoor tracking approaches use mainly radio-frequency signals like Wi-Fi or Bluetooth for localizing a user. In contrast to these approaches, the main advantage of the developed system is the capability of delivering a continuous 3D position and orientation of the mobile device with centimeter accuracy. This makes it usable for localization and 3D augmentation purposes, e.g. navigation tasks or location-based information visualization. PMID:26712755
Li, Kui; Wang, Lei; Lv, Yanhong; Gao, Pengyu; Song, Tianxiao
2015-01-01
Getting a land vehicle’s accurate position, azimuth and attitude rapidly is significant for vehicle based weapons’ combat effectiveness. In this paper, a new approach to acquire vehicle’s accurate position and orientation is proposed. It uses biaxial optical detection platform (BODP) to aim at and lock in no less than three pre-set cooperative targets, whose accurate positions are measured beforehand. Then, it calculates the vehicle’s accurate position, azimuth and attitudes by the rough position and orientation provided by vehicle based navigation systems and no less than three couples of azimuth and pitch angles measured by BODP. The proposed approach does not depend on Global Navigation Satellite System (GNSS), thus it is autonomous and difficult to interfere. Meanwhile, it only needs a rough position and orientation as algorithm’s iterative initial value, consequently, it does not have high performance requirement for Inertial Navigation System (INS), odometer and other vehicle based navigation systems, even in high precise applications. This paper described the system’s working procedure, presented theoretical deviation of the algorithm, and then verified its effectiveness through simulation and vehicle experiments. The simulation and experimental results indicate that the proposed approach can achieve positioning and orientation accuracy of 0.2 m and 20″ respectively in less than 3 min. PMID:26492249
NASA Technical Reports Server (NTRS)
Stieler, B.
1971-01-01
An inertial navigation system is described and analyzed based on two two-degree-of-freedom Schuler-gyropendulums and one two-degree-of-freedom azimuth gyro. The three sensors, each base motion isolated about its two input axes, are mounted on a common base, strapped down to the vehicle. The up and down pointing spin vectors of the two properly tuned gyropendulums track the vertical and indicate physically their velocity with respect to inertial space. The spin vector of the azimuth gyro is pointing northerly parallel to the earth axis. The system can be made self-aligning on a stationary base. If external measurements for the north direction and the vertical are available, initial disturbance torques can be measured and easily biased out. The error analysis shows that the system is practicable with today's technology.
Cheng, Jianhua; Dong, Jinlu; Landry, Rene; Chen, Daidai
2014-07-29
In order to improve the accuracy and reliability of micro-electro mechanical systems (MEMS) navigation systems, an orthogonal rotation method-based nine-gyro redundant MEMS configuration is presented. By analyzing the accuracy and reliability characteristics of an inertial navigation system (INS), criteria for redundant configuration design are introduced. Then the orthogonal rotation configuration is formed through a two-rotation of a set of orthogonal inertial sensors around a space vector. A feasible installation method is given for the real engineering realization of this proposed configuration. The performances of the novel configuration and another six configurations are comprehensively compared and analyzed. Simulation and experimentation are also conducted, and the results show that the orthogonal rotation configuration has the best reliability, accuracy and fault detection and isolation (FDI) performance when the number of gyros is nine.
Three axis electronic flight motion simulator real time control system design and implementation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gao, Zhiyuan; Miao, Zhonghua, E-mail: zhonghua-miao@163.com; Wang, Xiaohua
2014-12-15
A three axis electronic flight motion simulator is reported in this paper including the modelling, the controller design as well as the hardware implementation. This flight motion simulator could be used for inertial navigation test and high precision inertial navigation system with good dynamic and static performances. A real time control system is designed, several control system implementation problems were solved including time unification with parallel port interrupt, high speed finding-zero method of rotary inductosyn, zero-crossing management with continuous rotary, etc. Tests were carried out to show the effectiveness of the proposed real time control system.
Three axis electronic flight motion simulator real time control system design and implementation.
Gao, Zhiyuan; Miao, Zhonghua; Wang, Xuyong; Wang, Xiaohua
2014-12-01
A three axis electronic flight motion simulator is reported in this paper including the modelling, the controller design as well as the hardware implementation. This flight motion simulator could be used for inertial navigation test and high precision inertial navigation system with good dynamic and static performances. A real time control system is designed, several control system implementation problems were solved including time unification with parallel port interrupt, high speed finding-zero method of rotary inductosyn, zero-crossing management with continuous rotary, etc. Tests were carried out to show the effectiveness of the proposed real time control system.
Tian, Qinglin; Salcic, Zoran; Wang, Kevin I-Kai; Pan, Yun
2015-12-05
Pedestrian dead reckoning is a common technique applied in indoor inertial navigation systems that is able to provide accurate tracking performance within short distances. Sensor drift is the main bottleneck in extending the system to long-distance and long-term tracking. In this paper, a hybrid system integrating traditional pedestrian dead reckoning based on the use of inertial measurement units, short-range radio frequency systems and particle filter map matching is proposed. The system is a drift-free pedestrian navigation system where position error and sensor drift is regularly corrected and is able to provide long-term accurate and reliable tracking. Moreover, the whole system is implemented on a commercial off-the-shelf smartphone and achieves real-time positioning and tracking performance with satisfactory accuracy.
North Atlantic (NAT) aided inertial navigation system simulation volume I. : technical results
DOT National Transportation Integrated Search
1973-07-01
Current air traffic operations over the North ATlantic (NAT) and the application of hybrid navigation systems to obtain more accurate performance on these NAT routes are reviewed. A digital computer simulation program (NATNAV - North ATlantic NAVigat...
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.
Robust human machine interface based on head movements applied to assistive robotics.
Perez, Elisa; López, Natalia; Orosco, Eugenio; Soria, Carlos; Mut, Vicente; Freire-Bastos, Teodiano
2013-01-01
This paper presents an interface that uses two different sensing techniques and combines both results through a fusion process to obtain the minimum-variance estimator of the orientation of the user's head. Sensing techniques of the interface are based on an inertial sensor and artificial vision. The orientation of the user's head is used to steer the navigation of a robotic wheelchair. Also, a control algorithm for assistive technology system is presented. The system is evaluated by four individuals with severe motors disability and a quantitative index was developed, in order to objectively evaluate the performance. The results obtained are promising since most users could perform the proposed tasks with the robotic wheelchair.
Robust Human Machine Interface Based on Head Movements Applied to Assistive Robotics
Perez, Elisa; López, Natalia; Orosco, Eugenio; Soria, Carlos; Mut, Vicente; Freire-Bastos, Teodiano
2013-01-01
This paper presents an interface that uses two different sensing techniques and combines both results through a fusion process to obtain the minimum-variance estimator of the orientation of the user's head. Sensing techniques of the interface are based on an inertial sensor and artificial vision. The orientation of the user's head is used to steer the navigation of a robotic wheelchair. Also, a control algorithm for assistive technology system is presented. The system is evaluated by four individuals with severe motors disability and a quantitative index was developed, in order to objectively evaluate the performance. The results obtained are promising since most users could perform the proposed tasks with the robotic wheelchair. PMID:24453877
Application of aircraft navigation sensors to enhanced vision systems
NASA Technical Reports Server (NTRS)
Sweet, Barbara T.
1993-01-01
In this presentation, the applicability of various aircraft navigation sensors to enhanced vision system design is discussed. First, the accuracy requirements of the FAA for precision landing systems are presented, followed by the current navigation systems and their characteristics. These systems include Instrument Landing System (ILS), Microwave Landing System (MLS), Inertial Navigation, Altimetry, and Global Positioning System (GPS). Finally, the use of navigation system data to improve enhanced vision systems is discussed. These applications include radar image rectification, motion compensation, and image registration.
Weak and Dynamic GNSS Signal Tracking Strategies for Flight Missions in the Space Service Volume
Jing, Shuai; Zhan, Xingqun; Liu, Baoyu; Chen, Maolin
2016-01-01
Weak-signal and high-dynamics are of two primary concerns of space navigation using GNSS (Global Navigation Satellite System) in the space service volume (SSV). The paper firstly defines a reference assumption third-order phase-locked loop (PLL) as the baseline of an onboard GNSS receiver, and proves the incompetence of this conventional architecture. Then an adaptive four-state Kalman filter (KF)-based algorithm is introduced to realize the optimization of loop noise bandwidth, which can adaptively regulate its filter gain according to the received signal power and line-of-sight (LOS) dynamics. To overcome the matter of losing lock in weak-signal and high-dynamic environments, an open loop tracking strategy aided by an inertial navigation system (INS) is recommended, and the traditional maximum likelihood estimation (MLE) method is modified in a non-coherent way by reconstructing the likelihood cost function. Furthermore, a typical mission with combined orbital maneuvering and non-maneuvering arcs is taken as a destination object to test the two proposed strategies. Finally, the experiment based on computer simulation identifies the effectiveness of an adaptive four-state KF-based strategy under non-maneuvering conditions and the virtue of INS-assisted methods under maneuvering conditions. PMID:27598164
Yang, Yanqiang; Zhang, Chunxi; Lu, Jiazhen
2017-01-16
Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between SINS and star sensors have been one of the main factors that restrict the actual accuracy of SINS/CNS. In this paper, an integration algorithm based on the star vector observations is derived considering the star sensor installation error. Then, the star sensor installation error is accurately estimated based on Kalman Filtering (KF). Meanwhile, a local observability analysis is performed on the rank of observability matrix obtained via linearization observation equation, and the observable conditions are presented and validated. The number of star vectors should be greater than or equal to 2, and the times of posture adjustment also should be greater than or equal to 2. Simulations indicate that the star sensor installation error could be readily observable based on the maneuvering condition; moreover, the attitude errors of SINS are less than 7 arc-seconds. This analysis method and conclusion are useful in the ballistic trajectory design of near-Earth flight vehicles.
Weak and Dynamic GNSS Signal Tracking Strategies for Flight Missions in the Space Service Volume.
Jing, Shuai; Zhan, Xingqun; Liu, Baoyu; Chen, Maolin
2016-09-02
Weak-signal and high-dynamics are of two primary concerns of space navigation using GNSS (Global Navigation Satellite System) in the space service volume (SSV). The paper firstly defines a reference assumption third-order phase-locked loop (PLL) as the baseline of an onboard GNSS receiver, and proves the incompetence of this conventional architecture. Then an adaptive four-state Kalman filter (KF)-based algorithm is introduced to realize the optimization of loop noise bandwidth, which can adaptively regulate its filter gain according to the received signal power and line-of-sight (LOS) dynamics. To overcome the matter of losing lock in weak-signal and high-dynamic environments, an open loop tracking strategy aided by an inertial navigation system (INS) is recommended, and the traditional maximum likelihood estimation (MLE) method is modified in a non-coherent way by reconstructing the likelihood cost function. Furthermore, a typical mission with combined orbital maneuvering and non-maneuvering arcs is taken as a destination object to test the two proposed strategies. Finally, the experiment based on computer simulation identifies the effectiveness of an adaptive four-state KF-based strategy under non-maneuvering conditions and the virtue of INS-assisted methods under maneuvering conditions.
Proximity Navigation of Highly Constrained Spacecraft
NASA Technical Reports Server (NTRS)
Scarritt, S.; Swartwout, M.
2007-01-01
Bandit is a 3-kg automated spacecraft in development at Washington University in St. Louis. Bandit's primary mission is to demonstrate proximity navigation, including docking, around a 25-kg student-built host spacecraft. However, because of extreme constraints in mass, power and volume, traditional sensing and actuation methods are not available. In particular, Bandit carries only 8 fixed-magnitude cold-gas thrusters to control its 6 DOF motion. Bandit lacks true inertial sensing, and the ability to sense position relative to the host has error bounds that approach the size of the Bandit itself. Some of the navigation problems are addressed through an extremely robust, error-tolerant soft dock. In addition, we have identified a control methodology that performs well in this constrained environment: behavior-based velocity potential functions, which use a minimum-seeking method similar to Lyapunov functions. We have also adapted the discrete Kalman filter for use on Bandit for position estimation and have developed a similar measurement vs. propagation weighting algorithm for attitude estimation. This paper provides an overview of Bandit and describes the control and estimation approach. Results using our 6DOF flight simulator are provided, demonstrating that these methods show promise for flight use.
Performance Characteristic Mems-Based IMUs for UAVs Navigation
NASA Astrophysics Data System (ADS)
Mohamed, H. A.; Hansen, J. M.; Elhabiby, M. M.; El-Sheimy, N.; Sesay, A. B.
2015-08-01
Accurate 3D reconstruction has become essential for non-traditional mapping applications such as urban planning, mining industry, environmental monitoring, navigation, surveillance, pipeline inspection, infrastructure monitoring, landslide hazard analysis, indoor localization, and military simulation. The needs of these applications cannot be satisfied by traditional mapping, which is based on dedicated data acquisition systems designed for mapping purposes. Recent advances in hardware and software development have made it possible to conduct accurate 3D mapping without using costly and high-end data acquisition systems. Low-cost digital cameras, laser scanners, and navigation systems can provide accurate mapping if they are properly integrated at the hardware and software levels. Unmanned Aerial Vehicles (UAVs) are emerging as a mobile mapping platform that can provide additional economical and practical advantages. However, such economical and practical requirements need navigation systems that can provide uninterrupted navigation solution. Hence, testing the performance characteristics of Micro-Electro-Mechanical Systems (MEMS) or low cost navigation sensors for various UAV applications is important research. This work focuses on studying the performance characteristics under different manoeuvres using inertial measurements integrated with single point positioning, Real-Time-Kinematic (RTK), and additional navigational aiding sensors. Furthermore, the performance of the inertial sensors is tested during Global Positioning System (GPS) signal outage.
Self-calibration method of the inner lever-arm parameters for a tri-axis RINS
NASA Astrophysics Data System (ADS)
Song, Tianxiao; Li, Kui; Sui, Jie; Liu, Zengjun; Liu, Juncheng
2017-11-01
A rotational inertial navigation system (RINS) could improve navigation performance by modulating the inertial sensor errors with rotatable gimbals. When an inertial measurement unit (IMU) rotates, the deviations between the accelerometer-sensitive points and the IMU center will lead to an inner lever-arm effect. In this paper, a self-calibration method of the inner lever-arm parameters for a tri-axis RINS is proposed. A novel rotation scheme with variable angular rate rotation is designed to motivate the velocity errors caused by the inner lever-arm effect. By extending all inner lever-arm parameters as filter states, a Kalman filter with velocity errors as measurement is established to achieve the calibration. The accuracy and feasibility of the proposed method are illustrated by both simulations and experiments. The final results indicate that the inner lever-arm effect is significantly restrained after compensation by the calibration results.
Evaluation of STOL navigation avionics
NASA Technical Reports Server (NTRS)
Dunn, W. R., Jr.
1977-01-01
Research projects, including work on a vector magnetometer for aircraft attitude measurement, are summarized. The earth's electric field phenomena was investigated in its application to aircraft control and navigation. Research on electronic aircraft cabin noise suppression is reviewed and strapdown inertial reference unit technical support is outlined.
NASA Astrophysics Data System (ADS)
Lu, Jiazhen; Lei, Chaohua; Yang, Yanqiang; Liu, Ming
2016-12-01
An integrated inertial/celestial navigation system (INS/CNS) has wide applicability in lunar rovers as it provides accurate and autonomous navigational information. Initialization is particularly vital for a INS. This paper proposes a two-position initialization method based on a standard Kalman filter. The difference between the computed star vector and the measured star vector is measured. With the aid of a star sensor and the two positions, the attitudinal and positional errors can be greatly reduced, and the biases of three gyros and accelerometers can also be estimated. The semi-physical simulation results show that the positional and attitudinal errors converge within 0.07″ and 0.1 m, respectively, when the given initial positional error is 1 km and the attitudinal error is 10°. These good results show that the proposed method can accomplish alignment, positioning and calibration functions simultaneously. Thus the proposed two-position initialization method has the potential for application in lunar rover navigation.
Investigation of Air Transportation Technology at Ohio University, 1989-1990
NASA Technical Reports Server (NTRS)
Lilley, Robert W.
1990-01-01
The activities of the participants in the Joint University Program (JUP) at Ohio University are briefly surveyed. During 1989 to 1990, five topics received emphasis. A spectrum-efficient weather data uplink system was designed, constructed, and flight tested. An integrated Global Positioning System/Inertial Navigation System (GPS/INS) study continued, utilizing the Redundant strapdown Inertial Measurement Unit (IMU) on loan from NASA. The Ridge Regression theory was refined and applied to air navigation scenarios. System Identification theory was applied to GPS data to point the way to better understanding of the effects of Selective Availability on civilian users of this navigation system. An analysis of thought-related (electroencephalographic) signals for application to control of computer systems that could have significance in aiding paraplegics or for hands-off systems control in industrial or air traffic control areas was carried out.
NASA Astrophysics Data System (ADS)
Uijt de Haag, Maarten; Campbell, Jacob; van Graas, Frank
2005-05-01
Synthetic Vision Systems (SVS) provide pilots with a virtual visual depiction of the external environment. When using SVS for aircraft precision approach guidance systems accurate positioning relative to the runway with a high level of integrity is required. Precision approach guidance systems in use today require ground-based electronic navigation components with at least one installation at each airport, and in many cases multiple installations to service approaches to all qualifying runways. A terrain-referenced approach guidance system is envisioned to provide precision guidance to an aircraft without the use of ground-based electronic navigation components installed at the airport. This autonomy makes it a good candidate for integration with an SVS. At the Ohio University Avionics Engineering Center (AEC), work has been underway in the development of such a terrain referenced navigation system. When used in conjunction with an Inertial Measurement Unit (IMU) and a high accuracy/resolution terrain database, this terrain referenced navigation system can provide navigation and guidance information to the pilot on a SVS or conventional instruments. The terrain referenced navigation system, under development at AEC, operates on similar principles as other terrain navigation systems: a ground sensing sensor (in this case an airborne laser scanner) gathers range measurements to the terrain; this data is then matched in some fashion with an onboard terrain database to find the most likely position solution and used to update an inertial sensor-based navigator. AEC's system design differs from today's common terrain navigators in its use of a high resolution terrain database (~1 meter post spacing) in conjunction with an airborne laser scanner which is capable of providing tens of thousands independent terrain elevation measurements per second with centimeter-level accuracies. When combined with data from an inertial navigator the high resolution terrain database and laser scanner system is capable of providing near meter-level horizontal and vertical position estimates. Furthermore, the system under development capitalizes on 1) The position and integrity benefits provided by the Wide Area Augmentation System (WAAS) to reduce the initial search space size and; 2) The availability of high accuracy/resolution databases. This paper presents results from flight tests where the terrain reference navigator is used to provide guidance cues for a precision approach.
A novel redundant INS based on triple rotary inertial measurement units
NASA Astrophysics Data System (ADS)
Chen, Gang; Li, Kui; Wang, Wei; Li, Peng
2016-10-01
Accuracy and reliability are two key performances of inertial navigation system (INS). Rotation modulation (RM) can attenuate the bias of inertial sensors and make it possible for INS to achieve higher navigation accuracy with lower-class sensors. Therefore, the conflict between the accuracy and cost of INS can be eased. Traditional system redundancy and recently researched sensor redundancy are two primary means to improve the reliability of INS. However, how to make the best use of the redundant information from redundant sensors hasn’t been studied adequately, especially in rotational INS. This paper proposed a novel triple rotary unit strapdown inertial navigation system (TRUSINS), which combines RM and sensor redundancy design to enhance the accuracy and reliability of rotational INS. Each rotary unit independently rotates to modulate the errors of two gyros and two accelerometers. Three units can provide double sets of measurements along all three axes of body frame to constitute a couple of INSs which make TRUSINS redundant. Experiments and simulations based on a prototype which is made up of six fiber-optic gyros with drift stability of 0.05° h-1 show that TRUSINS can achieve positioning accuracy of about 0.256 n mile h-1, which is ten times better than that of a normal non-rotational INS with the same level inertial sensors. The theoretical analysis and the experimental results show that due to the advantage of the innovative structure, the designed fault detection and isolation (FDI) strategy can tolerate six sensor faults at most, and is proved to be effective and practical. Therefore, TRUSINS is particularly suitable and highly beneficial for the applications where high accuracy and high reliability is required.
Automatic Calibration of an Airborne Imaging System to an Inertial Navigation Unit
NASA Technical Reports Server (NTRS)
Ansar, Adnan I.; Clouse, Daniel S.; McHenry, Michael C.; Zarzhitsky, Dimitri V.; Pagdett, Curtis W.
2013-01-01
This software automatically calibrates a camera or an imaging array to an inertial navigation system (INS) that is rigidly mounted to the array or imager. In effect, it recovers the coordinate frame transformation between the reference frame of the imager and the reference frame of the INS. This innovation can automatically derive the camera-to-INS alignment using image data only. The assumption is that the camera fixates on an area while the aircraft flies on orbit. The system then, fully automatically, solves for the camera orientation in the INS frame. No manual intervention or ground tie point data is required.
Feng, Guohu; Wu, Wenqi; Wang, Jinling
2012-01-01
A matrix Kalman filter (MKF) has been implemented for an integrated navigation system using visual/inertial/magnetic sensors. The MKF rearranges the original nonlinear process model in a pseudo-linear process model. We employ the observability rank criterion based on Lie derivatives to verify the conditions under which the nonlinear system is observable. It has been proved that such observability conditions are: (a) at least one degree of rotational freedom is excited, and (b) at least two linearly independent horizontal lines and one vertical line are observed. Experimental results have validated the correctness of these observability conditions. PMID:23012523
Location of geographical objects in crisis situations
NASA Astrophysics Data System (ADS)
Rybansky, M.; Kratochvil, V.
2014-02-01
This article summarizes the various expressions of object positioning using different coordinate data and different methods, such as use of maps, exploiting the properties of digital Global System for Mobile Communications (GSM) networks, Global Navigational Satellite Systems (GNSS), Inertial Navigation Systems (INS), Inertial Measurement Systems (IMS), hybrid methods and non-contact (remote sensing) methods; all with varying level of accuracy. Furthermore, the article describes some geographical identifiers and verbal means to describe location of geographical objects such as settlements, rivers, forest, roads, etc. All of the location methods have some advantages and disadvantages, especially in emergency situations, when usually the crisis management has a lack of time in a decision process.
Station Keeping Results for Seabotix vLBV300 Underwater Vehicle near Newport, OR
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hollinger, Geoffrey
This data set presents results testing the station keeping abilities of a tethered Seabotix vLBV300 underwater vehicle equipped with an inertial navigation system. These results are from an offshore deployment on April 20, 2016 off the coast of Newport, OR (44.678 degrees N, 124.109 degrees W). During the mission period, the sea state varied between 3 and 4, with an average significant wave height of 1.6 m. The vehicle utilizes an inertial navigation system based on a Gladiator Landmark 40 IMU coupled with a Teledyne Explorer Doppler Velocity Log to perform station keeping at a desired location and orientation.
Lyu, Weiwei
2017-01-01
Transfer alignment is always a key technology in a strapdown inertial navigation system (SINS) because of its rapidity and accuracy. In this paper a transfer alignment model is established, which contains the SINS error model and the measurement model. The time delay in the process of transfer alignment is analyzed, and an H∞ filtering method with delay compensation is presented. Then the H∞ filtering theory and the robust mechanism of H∞ filter are deduced and analyzed in detail. In order to improve the transfer alignment accuracy in SINS with time delay, an adaptive H∞ filtering method with delay compensation is proposed. Since the robustness factor plays an important role in the filtering process and has effect on the filtering accuracy, the adaptive H∞ filter with delay compensation can adjust the value of robustness factor adaptively according to the dynamic external environment. The vehicle transfer alignment experiment indicates that by using the adaptive H∞ filtering method with delay compensation, the transfer alignment accuracy and the pure inertial navigation accuracy can be dramatically improved, which demonstrates the superiority of the proposed filtering method. PMID:29182592
Systematic Calibration for Ultra-High Accuracy Inertial Measurement Units.
Cai, Qingzhong; Yang, Gongliu; Song, Ningfang; Liu, Yiliang
2016-06-22
An inertial navigation system (INS) has been widely used in challenging GPS environments. With the rapid development of modern physics, an atomic gyroscope will come into use in the near future with a predicted accuracy of 5 × 10(-6)°/h or better. However, existing calibration methods and devices can not satisfy the accuracy requirements of future ultra-high accuracy inertial sensors. In this paper, an improved calibration model is established by introducing gyro g-sensitivity errors, accelerometer cross-coupling errors and lever arm errors. A systematic calibration method is proposed based on a 51-state Kalman filter and smoother. Simulation results show that the proposed calibration method can realize the estimation of all the parameters using a common dual-axis turntable. Laboratory and sailing tests prove that the position accuracy in a five-day inertial navigation can be improved about 8% by the proposed calibration method. The accuracy can be improved at least 20% when the position accuracy of the atomic gyro INS can reach a level of 0.1 nautical miles/5 d. Compared with the existing calibration methods, the proposed method, with more error sources and high order small error parameters calibrated for ultra-high accuracy inertial measurement units (IMUs) using common turntables, has a great application potential in future atomic gyro INSs.
Georgy, Jacques; Noureldin, Aboelmagd
2011-01-01
Satellite navigation systems such as the global positioning system (GPS) are currently the most common technique used for land vehicle positioning. However, in GPS-denied environments, there is an interruption in the positioning information. Low-cost micro-electro mechanical system (MEMS)-based inertial sensors can be integrated with GPS and enhance the performance in denied GPS environments. The traditional technique for this integration problem is Kalman filtering (KF). Due to the inherent errors of low-cost MEMS inertial sensors and their large stochastic drifts, KF, with its linearized models, has limited capabilities in providing accurate positioning. Particle filtering (PF) was recently suggested as a nonlinear filtering technique to accommodate for arbitrary inertial sensor characteristics, motion dynamics and noise distributions. An enhanced version of PF called the Mixture PF is utilized in this study to perform tightly coupled integration of a three dimensional (3D) reduced inertial sensors system (RISS) with GPS. In this work, the RISS consists of one single-axis gyroscope and a two-axis accelerometer used together with the vehicle's odometer to obtain 3D navigation states. These sensors are then integrated with GPS in a tightly coupled scheme. In loosely-coupled integration, at least four satellites are needed to provide acceptable GPS position and velocity updates for the integration filter. The advantage of the tightly-coupled integration is that it can provide GPS measurement update(s) even when the number of visible satellites is three or lower, thereby improving the operation of the navigation system in environments with partial blockages by providing continuous aiding to the inertial sensors even during limited GPS satellite availability. To effectively exploit the capabilities of PF, advanced modeling for the stochastic drift of the vertically aligned gyroscope is used. In order to benefit from measurement updates for such drift, which are loosely-coupled updates, a hybrid loosely/tightly coupled solution is proposed. This solution is suitable for downtown environments because of the long natural outages or degradation of GPS. The performance of the proposed 3D Navigation solution using Mixture PF for 3D RISS/GPS integration is examined by road test trajectories in a land vehicle and compared to the KF counterpart.
Georgy, Jacques; Noureldin, Aboelmagd
2011-01-01
Satellite navigation systems such as the global positioning system (GPS) are currently the most common technique used for land vehicle positioning. However, in GPS-denied environments, there is an interruption in the positioning information. Low-cost micro-electro mechanical system (MEMS)-based inertial sensors can be integrated with GPS and enhance the performance in denied GPS environments. The traditional technique for this integration problem is Kalman filtering (KF). Due to the inherent errors of low-cost MEMS inertial sensors and their large stochastic drifts, KF, with its linearized models, has limited capabilities in providing accurate positioning. Particle filtering (PF) was recently suggested as a nonlinear filtering technique to accommodate for arbitrary inertial sensor characteristics, motion dynamics and noise distributions. An enhanced version of PF called the Mixture PF is utilized in this study to perform tightly coupled integration of a three dimensional (3D) reduced inertial sensors system (RISS) with GPS. In this work, the RISS consists of one single-axis gyroscope and a two-axis accelerometer used together with the vehicle’s odometer to obtain 3D navigation states. These sensors are then integrated with GPS in a tightly coupled scheme. In loosely-coupled integration, at least four satellites are needed to provide acceptable GPS position and velocity updates for the integration filter. The advantage of the tightly-coupled integration is that it can provide GPS measurement update(s) even when the number of visible satellites is three or lower, thereby improving the operation of the navigation system in environments with partial blockages by providing continuous aiding to the inertial sensors even during limited GPS satellite availability. To effectively exploit the capabilities of PF, advanced modeling for the stochastic drift of the vertically aligned gyroscope is used. In order to benefit from measurement updates for such drift, which are loosely-coupled updates, a hybrid loosely/tightly coupled solution is proposed. This solution is suitable for downtown environments because of the long natural outages or degradation of GPS. The performance of the proposed 3D Navigation solution using Mixture PF for 3D RISS/GPS integration is examined by road test trajectories in a land vehicle and compared to the KF counterpart. PMID:22163846
Wang, Jianren; Xu, Junkai; Shull, Peter B
2018-03-01
Vertical jump height is widely used for assessing motor development, functional ability, and motor capacity. Traditional methods for estimating vertical jump height rely on force plates or optical marker-based motion capture systems limiting assessment to people with access to specialized laboratories. Current wearable designs need to be attached to the skin or strapped to an appendage which can potentially be uncomfortable and inconvenient to use. This paper presents a novel algorithm for estimating vertical jump height based on foot-worn inertial sensors. Twenty healthy subjects performed countermovement jumping trials and maximum jump height was determined via inertial sensors located above the toe and under the heel and was compared with the gold standard maximum jump height estimation via optical marker-based motion capture. Average vertical jump height estimation errors from inertial sensing at the toe and heel were -2.2±2.1 cm and -0.4±3.8 cm, respectively. Vertical jump height estimation with the presented algorithm via inertial sensing showed excellent reliability at the toe (ICC(2,1)=0.98) and heel (ICC(2,1)=0.97). There was no significant bias in the inertial sensing at the toe, but proportional bias (b=1.22) and fixed bias (a=-10.23cm) were detected in inertial sensing at the heel. These results indicate that the presented algorithm could be applied to foot-worn inertial sensors to estimate maximum jump height enabling assessment outside of traditional laboratory settings, and to avoid bias errors, the toe may be a more suitable location for inertial sensor placement than the heel.
Inversion Method for Early Detection of ARES-1 Case Breach Failure
NASA Technical Reports Server (NTRS)
Mackey, Ryan M.; Kulikov, Igor K.; Bajwa, Anupa; Berg, Peter; Smelyanskiy, Vadim
2010-01-01
A document describes research into the problem of detecting a case breach formation at an early stage of a rocket flight. An inversion algorithm for case breach allocation is proposed and analyzed. It is shown how the case breach can be allocated at an early stage of its development by using the rocket sensor data and the output data from the control block of the rocket navigation system. The results are simulated with MATLAB/Simulink software. The efficiency of an inversion algorithm for a case breach location is discussed. The research was devoted to the analysis of the ARES-l flight during the first 120 seconds after the launch and early prediction of case breach failure. During this time, the rocket is propelled by its first-stage Solid Rocket Booster (SRB). If a breach appears in SRB case, the gases escaping through it will produce the (side) thrust directed perpendicular to the rocket axis. The side thrust creates torque influencing the rocket attitude. The ARES-l control system will compensate for the side thrust until it reaches some critical value, after which the flight will be uncontrollable. The objective of this work was to obtain the start time of case breach development and its location using the rocket inertial navigation sensors and GNC data. The algorithm was effective for the detection and location of a breach in an SRB field joint at an early stage of its development.
The UAV take-off and landing system used for small areas of mobile vehicles
NASA Astrophysics Data System (ADS)
Ren, Tian-Yu; Duanmu, Qing-Duo; Wu, Bo-Qi
2018-03-01
In order to realize an UAV formation cluster system based on the current GPS and the fault and insufficiency of Beidou integrated navigation system in strong jamming environment. Due to the impact of the compass on the plane crash, navigation system error caused by the mobile area to help reduce the need for large landing sites and not in the small fast moving area to achieve the reality of the landing. By using Strapdown inertial and all-optical system to form Composite UAV flight control system, the photoelectric composite strapdown inertial coupling is realized, and through the laser and microwave telemetry link compound communication mechanism, using all-optical strapdown inertial and visual navigation system to solve the deviation of take-off and landing caused by electromagnetic interference, all-optical bidirectional data link realizes two-way position correction of landing site and aircraft, thus achieves the accurate recovery of UAV formation cluster in the mobile narrow area which the traditional navigation system can't realize. This system is a set of efficient unmanned aerial vehicle Group Take-off/descending system, which is suitable for many tasks, and not only realizes the reliable continuous navigation under the complex electromagnetic interference environment, moreover, the intelligent flight and Take-off and landing of unmanned aerial vehicles relative to the fast moving and small recovery sites in complex electromagnetic interference environment can not only improve the safe operation rate of unmanned aerial vehicle, but also guarantee the operation safety of the aircraft, and the more has important social value for the application foreground of the aircraft.
Inertial Navigation System Standardized Software Development. Volume 1. Introduction and Summary
1976-06-01
the Loran receiver, the Tacan receiver, the Omega receiver, the satelite based instrumentation, the multimode radar, the star tracker and the visual...accelerometer scale factor, and the barometric altimeter bias. The accuracy (1o values) of typical navigation-aid measurements (other than satelite derived
2010-03-01
Characterization Solutions Enabled by Laser Doppler Vibrometer Measurements, Proc. SPIE, Fifth International Conference on Vibration Measurements by Laser ...commercial capabilities: Ring Laser Gyros, Fiber Optic Gyros, and Micro-Electro-Mechanical Systems (MEMS) gyros and accelerometers. RLGs and FOGs are now...augmentation sensors have been tied into the inertial systems; e.g., GPS, velocity meters, seekers, star trackers, magnetometers, lidar , etc. The
An onboard navigation system which fulfills Mars aerocapture guidance requirements
NASA Technical Reports Server (NTRS)
Brand, Timothy J.; Fuhry, Douglas P.; Shepperd, Stanley W.
1989-01-01
The development of a candidate autonomous onboard Mars approach navigation scheme capable of supporting aerocapture into Mars orbit is discussed. An aerocapture guidance and navigation system which can run independently of the preaerocapture navigation was used to define a preliminary set of accuracy requirements at entry interface. These requirements are used to evaluate the proposed preaerocapture navigation scheme. This scheme uses optical sightings on Deimos with a star tracker and an inertial measurement unit for instrumentation as a source for navigation nformation. Preliminary results suggest that the approach will adequately support aerocaputre into Mars orbit.
Autonomous Navigation of Small Uavs Based on Vehicle Dynamic Model
NASA Astrophysics Data System (ADS)
Khaghani, M.; Skaloud, J.
2016-03-01
This paper presents a novel approach to autonomous navigation for small UAVs, in which the vehicle dynamic model (VDM) serves as the main process model within the navigation filter. The proposed method significantly increases the accuracy and reliability of autonomous navigation, especially for small UAVs with low-cost IMUs on-board. This is achieved with no extra sensor added to the conventional INS/GNSS setup. This improvement is of special interest in case of GNSS outages, where inertial coasting drifts very quickly. In the proposed architecture, the solution to VDM equations provides the estimate of position, velocity, and attitude, which is updated within the navigation filter based on available observations, such as IMU data or GNSS measurements. The VDM is also fed with the control input to the UAV, which is available within the control/autopilot system. The filter is capable of estimating wind velocity and dynamic model parameters, in addition to navigation states and IMU sensor errors. Monte Carlo simulations reveal major improvements in navigation accuracy compared to conventional INS/GNSS navigation system during the autonomous phase, when satellite signals are not available due to physical obstruction or electromagnetic interference for example. In case of GNSS outages of a few minutes, position and attitude accuracy experiences improvements of orders of magnitude compared to inertial coasting. It means that during such scenario, the position-velocity-attitude (PVA) determination is sufficiently accurate to navigate the UAV to a home position without any signal that depends on vehicle environment.
Differential GPS/inertial navigation approach/landing flight test results
NASA Technical Reports Server (NTRS)
Snyder, Scott; Schipper, Brian; Vallot, Larry; Parker, Nigel; Spitzer, Cary
1992-01-01
Results of a joint Honeywell/NASA-Langley differential GPS/inertial flight test conducted in November 1990 are discussed focusing on postflight data analysis. The test was aimed at acquiring a system performance database and demonstrating automatic landing based on an integrated differential GPS/INS with barometric and radar altimeters. Particular attention is given to characteristics of DGPS/inertial error and the magnitude of the differential corrections and vertical channel performance with and without altimeter augmentation. It is shown that DGPS/inertial integrated with a radar altimeter is capable of providing a precision approach and autoland guidance of manned return space vehicles within the Space Shuttle accuracy requirements.
Error reduction by combining strapdown inertial measurement units in a baseball stitch
NASA Astrophysics Data System (ADS)
Tracy, Leah
A poor musical performance is rarely due to an inferior instrument. When a device is under performing, the temptation is to find a better device or a new technology to achieve performance objectives; however, another solution may be improving how existing technology is used through a better understanding of device characteristics, i.e., learning to play the instrument better. This thesis explores improving position and attitude estimates of inertial navigation systems (INS) through an understanding of inertial sensor errors, manipulating inertial measurement units (IMUs) to reduce that error and multisensor fusion of multiple IMUs to reduce error in a GPS denied environment.
Space shuttle navigation analysis
NASA Technical Reports Server (NTRS)
Jones, H. L.; Luders, G.; Matchett, G. A.; Sciabarrasi, J. E.
1976-01-01
A detailed analysis of space shuttle navigation for each of the major mission phases is presented. A covariance analysis program for prelaunch IMU calibration and alignment for the orbital flight tests (OFT) is described, and a partial error budget is presented. The ascent, orbital operations and deorbit maneuver study considered GPS-aided inertial navigation in the Phase III GPS (1984+) time frame. The entry and landing study evaluated navigation performance for the OFT baseline system. Detailed error budgets and sensitivity analyses are provided for both the ascent and entry studies.
Pulmonary Nodule Recognition Based on Multiple Kernel Learning Support Vector Machine-PSO
Zhu, Zhichuan; Zhao, Qingdong; Liu, Liwei; Zhang, Lijuan
2018-01-01
Pulmonary nodule recognition is the core module of lung CAD. The Support Vector Machine (SVM) algorithm has been widely used in pulmonary nodule recognition, and the algorithm of Multiple Kernel Learning Support Vector Machine (MKL-SVM) has achieved good results therein. Based on grid search, however, the MKL-SVM algorithm needs long optimization time in course of parameter optimization; also its identification accuracy depends on the fineness of grid. In the paper, swarm intelligence is introduced and the Particle Swarm Optimization (PSO) is combined with MKL-SVM algorithm to be MKL-SVM-PSO algorithm so as to realize global optimization of parameters rapidly. In order to obtain the global optimal solution, different inertia weights such as constant inertia weight, linear inertia weight, and nonlinear inertia weight are applied to pulmonary nodules recognition. The experimental results show that the model training time of the proposed MKL-SVM-PSO algorithm is only 1/7 of the training time of the MKL-SVM grid search algorithm, achieving better recognition effect. Moreover, Euclidean norm of normalized error vector is proposed to measure the proximity between the average fitness curve and the optimal fitness curve after convergence. Through statistical analysis of the average of 20 times operation results with different inertial weights, it can be seen that the dynamic inertial weight is superior to the constant inertia weight in the MKL-SVM-PSO algorithm. In the dynamic inertial weight algorithm, the parameter optimization time of nonlinear inertia weight is shorter; the average fitness value after convergence is much closer to the optimal fitness value, which is better than the linear inertial weight. Besides, a better nonlinear inertial weight is verified. PMID:29853983
Pulmonary Nodule Recognition Based on Multiple Kernel Learning Support Vector Machine-PSO.
Li, Yang; Zhu, Zhichuan; Hou, Alin; Zhao, Qingdong; Liu, Liwei; Zhang, Lijuan
2018-01-01
Pulmonary nodule recognition is the core module of lung CAD. The Support Vector Machine (SVM) algorithm has been widely used in pulmonary nodule recognition, and the algorithm of Multiple Kernel Learning Support Vector Machine (MKL-SVM) has achieved good results therein. Based on grid search, however, the MKL-SVM algorithm needs long optimization time in course of parameter optimization; also its identification accuracy depends on the fineness of grid. In the paper, swarm intelligence is introduced and the Particle Swarm Optimization (PSO) is combined with MKL-SVM algorithm to be MKL-SVM-PSO algorithm so as to realize global optimization of parameters rapidly. In order to obtain the global optimal solution, different inertia weights such as constant inertia weight, linear inertia weight, and nonlinear inertia weight are applied to pulmonary nodules recognition. The experimental results show that the model training time of the proposed MKL-SVM-PSO algorithm is only 1/7 of the training time of the MKL-SVM grid search algorithm, achieving better recognition effect. Moreover, Euclidean norm of normalized error vector is proposed to measure the proximity between the average fitness curve and the optimal fitness curve after convergence. Through statistical analysis of the average of 20 times operation results with different inertial weights, it can be seen that the dynamic inertial weight is superior to the constant inertia weight in the MKL-SVM-PSO algorithm. In the dynamic inertial weight algorithm, the parameter optimization time of nonlinear inertia weight is shorter; the average fitness value after convergence is much closer to the optimal fitness value, which is better than the linear inertial weight. Besides, a better nonlinear inertial weight is verified.
A hybrid data fusion method for GNSS/INS integration navigation system
NASA Astrophysics Data System (ADS)
Yang, Ling; Li, Bofeng; Shen, Yunzhong; Li, Haojun
2017-04-01
Although DGNSS is widely used and PPP-GNSS is nowadays a viable precise positioning technology option, the major disadvantage of GNSS still remains: signal blockage due to obstructions in urban and built up environments, and extreme power attenuation of the signals when operated indoors. The combination of GNSS with other sensors, such as a self-contained inertial navigation system (INS), provides an ideal position and attitude determination solution which can not only mitigate the weakness of GNSS, but also bound the INS error that otherwise would grow with time when the INS operates alone. However, the navigation accuracy provided by GNSS/INS strongly depends on the quality and geometry of the GNSS observations, the quality of the INS technology used, and the integration model applied. There are two main types of coupled schemes for integration systems: loosely coupled integration and tightly coupled integration. In loosely coupled integration, position measurements are taken from both systems and combined optimally, usually in a Kalman filter. Tightly coupled integration directly combines the raw pseudorange or carrier phase measurements of GNSS with inertial measurements in an extended Kalman filter. The latter technique improves the ability to resolve ambiguities, i.e. allows a quicker recovery from outage events such as a loss of signal under vegetation. In recent years, tightly coupled differential carrier phase GNSS/INS integration has become popular, because it has the advantage of providing accurate position information even when GPS measurements are rank-deficient in stand-alone processing and is theoretically optimal in a filtering sense, especially in urban navigation applications. However, the heavier computational burden and sensor communication usually complicate the tightly coupled integration and reduce the system efficiency, compared with the loosely coupled integration. In this paper, it has been proved that the loosely coupled and tightly coupled algorithms are equivalent when following conditions are satisfied: 1) there is enough redundancy on the GNSS raw measurements; 2) only pseudorange measurements are used; 3) If differential carrier phase measurements are used, only the float solutions of the ambiguities are considered; 4) the covariance of the loosely coupled measurement model should come from the GNSS standalone solution instead of conventional pre-determined values. Based on the equivalence proof, a dual-step loosely coupled procedure is proposed to regenerate the equal ambiguity fixing solutions in tightly coupled procedure. Accordingly, the tightly coupled differential carrier phase or pseudorange GNSS/INS integration can be simplified, which will degrade to an equivalent loosely coupled integration when there are enough measurement redundancy and recover to a tightly coupled integration when GNSS measurements are rank-deficient. By this hybrid data fusion method, both the optimality of the tightly coupled algorithm and the efficiency of the loosely coupled algorithm can be conserved. Field test results confirm the effectiveness of the proposed method.
Space Shuttle Earth Observation sensors pointing and stabilization requirements study
NASA Technical Reports Server (NTRS)
1976-01-01
The shuttle orbiter inertial measurement unit (IMU), located in the orbiter cabin, is used to supply inertial attitude reference signals; and, in conjunction with the onboard navigation system, can provide a pointing capability of the navigation base accurate to within plus or minus 0.5 deg for earth viewing missions. This pointing accuracy can degrade to approximately plus or minus 2.0 deg for payloads located in the aft bay due to structural flexure of the shuttle vehicle, payload structural and mounting misalignments, and calibration errors with respect to the navigation base. Drawbacks to obtaining pointing accuracy by using the orbiter RCS jets are discussed. Supplemental electromechanical pointing systems are developed to provide independent pointing for individual sensors, or sensor groupings. The missions considered and the sensors required for these missions and the parameters of each sensor are described. Assumptions made to derive pointing and stabilization requirements are delineated.
LIDAR-Aided Inertial Navigation with Extended Kalman Filtering for Pinpoint Landing
NASA Technical Reports Server (NTRS)
Busnardo, David M.; Aitken, Matthew L.; Tolson, Robert H.; Pierrottet, Diego; Amzajerdian, Farzin
2011-01-01
In support of NASA s Autonomous Landing and Hazard Avoidance Technology (ALHAT) project, an extended Kalman filter routine has been developed for estimating the position, velocity, and attitude of a spacecraft during the landing phase of a planetary mission. The proposed filter combines measurements of acceleration and angular velocity from an inertial measurement unit (IMU) with range and Doppler velocity observations from an onboard light detection and ranging (LIDAR) system. These high-precision LIDAR measurements of distance to the ground and approach velocity will enable both robotic and manned vehicles to land safely and precisely at scientifically interesting sites. The filter has been extensively tested using a lunar landing simulation and shown to improve navigation over flat surfaces or rough terrain. Experimental results from a helicopter flight test performed at NASA Dryden in August 2008 demonstrate that LIDAR can be employed to significantly improve navigation based exclusively on IMU integration.
LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments
Tang, Jian; Chen, Yuwei; Niu, Xiaoji; Wang, Li; Chen, Liang; Liu, Jingbin; Shi, Chuang; Hyyppä, Juha
2015-01-01
A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies—INS and LiDAR SLAM—into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform—NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment. PMID:26184206
LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments.
Tang, Jian; Chen, Yuwei; Niu, Xiaoji; Wang, Li; Chen, Liang; Liu, Jingbin; Shi, Chuang; Hyyppä, Juha
2015-07-10
A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies-INS and LiDAR SLAM-into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform-NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment.
A celestial assisted INS initialization method for lunar explorers.
Ning, Xiaolin; Wang, Longhua; Wu, Weiren; Fang, Jiancheng
2011-01-01
The second and third phases of the Chinese Lunar Exploration Program (CLEP) are planning to achieve Moon landing, surface exploration and automated sample return. In these missions, the inertial navigation system (INS) and celestial navigation system (CNS) are two indispensable autonomous navigation systems which can compensate for limitations in the ground based navigation system. The accurate initialization of the INS and the precise calibration of the CNS are needed in order to achieve high navigation accuracy. Neither the INS nor the CNS can solve the above problems using the ground controllers or by themselves on the lunar surface. However, since they are complementary to each other, these problems can be solved by combining them together. A new celestial assisted INS initialization method is presented, in which the initial position and attitude of the explorer as well as the inertial sensors' biases are estimated by aiding the INS with celestial measurements. Furthermore, the systematic error of the CNS is also corrected by the help of INS measurements. Simulations show that the maximum error in position is 300 m and in attitude 40″, which demonstrates this method is a promising and attractive scheme for explorers on the lunar surface.
A Celestial Assisted INS Initialization Method for Lunar Explorers
Ning, Xiaolin; Wang, Longhua; Wu, Weiren; Fang, Jiancheng
2011-01-01
The second and third phases of the Chinese Lunar Exploration Program (CLEP) are planning to achieve Moon landing, surface exploration and automated sample return. In these missions, the inertial navigation system (INS) and celestial navigation system (CNS) are two indispensable autonomous navigation systems which can compensate for limitations in the ground based navigation system. The accurate initialization of the INS and the precise calibration of the CNS are needed in order to achieve high navigation accuracy. Neither the INS nor the CNS can solve the above problems using the ground controllers or by themselves on the lunar surface. However, since they are complementary to each other, these problems can be solved by combining them together. A new celestial assisted INS initialization method is presented, in which the initial position and attitude of the explorer as well as the inertial sensors’ biases are estimated by aiding the INS with celestial measurements. Furthermore, the systematic error of the CNS is also corrected by the help of INS measurements. Simulations show that the maximum error in position is 300 m and in attitude 40″, which demonstrates this method is a promising and attractive scheme for explorers on the lunar surface. PMID:22163998
Sanchez, Richard D.; Hothem, Larry D.
2002-01-01
High-resolution airborne and satellite image sensor systems integrated with onboard data collection based on the Global Positioning System (GPS) and inertial navigation systems (INS) may offer a quick and cost-effective way to gather accurate topographic map information without ground control or aerial triangulation. The Applanix Corporation?s Position and Orientation Solutions for Direct Georeferencing of aerial photography was used in this project to examine the positional accuracy of integrated GPS/INS for terrain mapping in Glen Canyon, Arizona. The research application in this study yielded important information on the usefulness and limits of airborne integrated GPS/INS data-capture systems for mapping.
Inertial navigation sensor integrated motion analysis for autonomous vehicle navigation
NASA Technical Reports Server (NTRS)
Roberts, Barry; Bhanu, Bir
1992-01-01
Recent work on INS integrated motion analysis is described. Results were obtained with a maximally passive system of obstacle detection (OD) for ground-based vehicles and rotorcraft. The OD approach involves motion analysis of imagery acquired by a passive sensor in the course of vehicle travel to generate range measurements to world points within the sensor FOV. INS data and scene analysis results are used to enhance interest point selection, the matching of the interest points, and the subsequent motion-based computations, tracking, and OD. The most important lesson learned from the research described here is that the incorporation of inertial data into the motion analysis program greatly improves the analysis and makes the process more robust.
2015-03-26
tracker, an Inertial Measurement Unit (IMU), and a barometric altimeter using an Extended Kalman Filter (EKF). Models of each of these components are...Positioning 15 2.5 Detector Device Improvement . . . . . . . . . . . . . . . 15 2.6 Kalman Filter . . . . . . . . . . . . . . . . . . . . . . . . 17 2.6.1...Extended Kalman Filter . . . . . . . . . . . . . 17 2.7 System Properties . . . . . . . . . . . . . . . . . . . . . 21 2.8 Sun Exitance
Strapdown system redundancy management flight demonstration. [vertical takeoff and landing aircraft
NASA Technical Reports Server (NTRS)
1978-01-01
The suitability of strapdown inertial systems in providing highly reliable short-term navigation for vertical take-off and landing (VTOL) aircraft operating in an intra-urban setting under all-weather conditions was assessed. A preliminary design configuration of a skewed sensor inertial reference system employing a redundancy management concept to achieve fail-operational, fail-operational performance, was developed.
Terrain matching image pre-process and its format transform in autonomous underwater navigation
NASA Astrophysics Data System (ADS)
Cao, Xuejun; Zhang, Feizhou; Yang, Dongkai; Yang, Bogang
2007-06-01
Underwater passive navigation technology is one of the important development orientations in the field of modern navigation. With the advantage of high self-determination, stealth at sea, anti-jamming and high precision, passive navigation is completely meet with actual navigation requirements. Therefore passive navigation has become a specific navigating method for underwater vehicles. The scientists and researchers in the navigating field paid more attention to it. The underwater passive navigation can provide accurate navigation information with main Inertial Navigation System (INS) for a long period, such as location and speed. Along with the development of micro-electronics technology, the navigation of AUV is given priority to INS assisted with other navigation methods, such as terrain matching navigation. It can provide navigation ability for a long period, correct the errors of INS and make AUV not emerge from the seabed termly. With terrain matching navigation technique, in the assistance of digital charts and ocean geographical characteristics sensors, we carry through underwater image matching assistant navigation to obtain the higher location precision, therefore it is content with the requirement of underwater, long-term, high precision and all-weather of the navigation system for Autonomous Underwater Vehicles. Tertian-assistant navigation (TAN) is directly dependent on the image information (map information) in the navigating field to assist the primary navigation system according to the path appointed in advance. In TAN, a factor coordinative important with the system operation is precision and practicability of the storable images and the database which produce the image data. If the data used for characteristics are not suitable, the system navigation precision will be low. Comparing with terrain matching assistant navigation system, image matching navigation system is a kind of high precision and low cost assistant navigation system, and its matching precision directly influences the final precision of integrated navigation system. Image matching assistant navigation is spatially matching and aiming at two underwater scenery images coming from two different sensors matriculating of the same scenery in order to confirm the relative displacement of the two images. In this way, we can obtain the vehicle's location in fiducial image known geographical relation, and the precise location information given from image matching location is transmitted to INS to eliminate its location error and greatly enhance the navigation precision of vehicle. Digital image data analysis and processing of image matching in underwater passive navigation is important. In regard to underwater geographic data analysis, we focus on the acquirement, disposal, analysis, expression and measurement of database information. These analysis items structure one of the important contents of underwater terrain matching and are propitious to know the seabed terrain configuration of navigation areas so that the best advantageous seabed terrain district and dependable navigation algorithm can be selected. In this way, we can improve the precision and reliability of terrain assistant navigation system. The pre-process and format transformation of digital image during underwater image matching are expatiated in this paper. The information of the terrain status in navigation areas need further study to provide the reliable data terrain characteristic and underwater overcast for navigation. Through realizing the choice of sea route, danger district prediction and navigating algorithm analysis, TAN can obtain more high location precision and probability, hence provide technological support for image matching of underwater passive navigation.
NASA Astrophysics Data System (ADS)
Gao, Chunfeng; Wei, Guo; Wang, Qi; Xiong, Zhenyu; Wang, Qun; Long, Xingwu
2016-10-01
As an indispensable equipment in inertial technology tests, the three-axis turntable is widely used in the calibration of various types inertial navigation systems (INS). In order to ensure the calibration accuracy of INS, we need to accurately measure the initial state of the turntable. However, the traditional measuring method needs a lot of exterior equipment (such as level instrument, north seeker, autocollimator, etc.), and the test processing is complex, low efficiency. Therefore, it is relatively difficult for the inertial measurement equipment manufacturers to realize the self-inspection of the turntable. Owing to the high precision attitude information provided by the laser gyro strapdown inertial navigation system (SINS) after fine alignment, we can use it as the attitude reference of initial state measurement of three-axis turntable. For the principle that the fixed rotation vector increment is not affected by measuring point, we use the laser gyro INS and the encoder of the turntable to provide the attitudes of turntable mounting plat. Through this way, the high accuracy measurement of perpendicularity error and initial attitude of the three-axis turntable has been achieved.
NASA Astrophysics Data System (ADS)
Markelov, V.; Shukalov, A.; Zharinov, I.; Kostishin, M.; Kniga, I.
2016-04-01
The use of the correction course option before aircraft take-off after inertial navigation system (INS) inaccurate alignment based on the platform attitude-and-heading reference system in azimuth is considered in the paper. A course correction is performed based on the track angle defined by the information received from the satellite navigation system (SNS). The course correction includes a calculated track error definition during ground taxiing along straight sections before take-off with its input in the onboard digital computational system like amendment for using in the current flight. The track error calculation is performed by the statistical evaluation of the track angle comparison defined by the SNS information with the current course measured by INS for a given number of measurements on the realizable time interval. The course correction testing results and recommendation application are given in the paper. The course correction based on the information from SNS can be used for improving accuracy characteristics for determining an aircraft path after making accelerated INS preparation concerning inaccurate initial azimuth alignment.
Absolute Positioning Using The Earth’s Magnetic Anomaly Field
2016-09-15
many of these limitations. We present a navigation filter which uses the Earth’s magnetic anomaly field as a navigation signal to aid an inertial...navigation system (INS) in an aircraft. The filter utilizes highly-accurate optically pumped cesium (OPC) magnetometers to make scalar intensity...measurements of the Earth’s magnetic field and compare them to a map using a marginalized particle filter approach. The accuracy of these mea- surements allows
Study on UKF based federal integrated navigation for high dynamic aviation
NASA Astrophysics Data System (ADS)
Zhao, Gang; Shao, Wei; Chen, Kai; Yan, Jie
2011-08-01
High dynamic aircraft is a very attractive new generation vehicles, in which provides near space aviation with large flight envelope both speed and altitude, for example the hypersonic vehicles. The complex flight environments for high dynamic vehicles require high accuracy and stability navigation scheme. Since the conventional Strapdown Inertial Navigation System (SINS) and Global Position System (GPS) federal integrated scheme based on EKF (Extended Kalman Filter) is invalidation in GPS single blackout situation because of high speed flight, a new high precision and stability integrated navigation approach is presented in this paper, in which the SINS, GPS and Celestial Navigation System (CNS) is combined as a federal information fusion configuration based on nonlinear Unscented Kalman Filter (UKF) algorithm. Firstly, the new integrated system state error is modeled. According to this error model, the SINS system is used as the navigation solution mathematic platform. The SINS combine with GPS constitute one error estimation filter subsystem based on UKF to obtain local optimal estimation, and the SINS combine with CNS constitute another error estimation subsystem. A non-reset federated configuration filter based on partial information is proposed to fuse two local optimal estimations to get global optimal error estimation, and the global optimal estimation is used to correct the SINS navigation solution. The χ 2 fault detection method is used to detect the subsystem fault, and the fault subsystem is isolation through fault interval to protect system away from the divergence. The integrated system takes advantages of SINS, GPS and CNS to an immense improvement for high accuracy and reliably high dynamic navigation application. Simulation result shows that federated fusion of using GPS and CNS to revise SINS solution is reasonable and availably with good estimation performance, which are satisfied with the demands of high dynamic flight navigation. The UKF is superior than EKF based integrated scheme, in which has smaller estimation error and quickly convergence rate.
Luo, Yong; Wu, Wenqi; Babu, Ravindra; Tang, Kanghua; Luo, Bing
2012-01-01
COMPASS is an indigenously developed Chinese global navigation satellite system and will share many features in common with GPS (Global Positioning System). Since the ultra-tight GPS/INS (Inertial Navigation System) integration shows its advantage over independent GPS receivers in many scenarios, the federated ultra-tight COMPASS/INS integration has been investigated in this paper, particularly, by proposing a simplified prefilter model. Compared with a traditional prefilter model, the state space of this simplified system contains only carrier phase, carrier frequency and carrier frequency rate tracking errors. A two-quadrant arctangent discriminator output is used as a measurement. Since the code tracking error related parameters were excluded from the state space of traditional prefilter models, the code/carrier divergence would destroy the carrier tracking process, and therefore an adaptive Kalman filter algorithm tuning process noise covariance matrix based on state correction sequence was incorporated to compensate for the divergence. The federated ultra-tight COMPASS/INS integration was implemented with a hardware COMPASS intermediate frequency (IF), and INS's accelerometers and gyroscopes signal sampling system. Field and simulation test results showed almost similar tracking and navigation performances for both the traditional prefilter model and the proposed system; however, the latter largely decreased the computational load. PMID:23012564
Yang, Yanqiang; Zhang, Chunxi; Lu, Jiazhen
2017-01-01
Strapdown inertial navigation system/celestial navigation system (SINS/CNS) integrated navigation is a fully autonomous and high precision method, which has been widely used to improve the hitting accuracy and quick reaction capability of near-Earth flight vehicles. The installation errors between SINS and star sensors have been one of the main factors that restrict the actual accuracy of SINS/CNS. In this paper, an integration algorithm based on the star vector observations is derived considering the star sensor installation error. Then, the star sensor installation error is accurately estimated based on Kalman Filtering (KF). Meanwhile, a local observability analysis is performed on the rank of observability matrix obtained via linearization observation equation, and the observable conditions are presented and validated. The number of star vectors should be greater than or equal to 2, and the times of posture adjustment also should be greater than or equal to 2. Simulations indicate that the star sensor installation error could be readily observable based on the maneuvering condition; moreover, the attitude errors of SINS are less than 7 arc-seconds. This analysis method and conclusion are useful in the ballistic trajectory design of near-Earth flight vehicles. PMID:28275211
NASA Technical Reports Server (NTRS)
Carpenter, J. Russell; Bishop, Robert H.
1996-01-01
A recently developed rendezvous navigation fusion filter that optimally exploits existing distributed filters for rendezvous and GPS navigation to achieve the relative and inertial state accuracies of both in a global solution is utilized here to process actual flight data. Space Shuttle Mission STS-69 was the first mission to date which gathered data from both the rendezvous and Global Positioning System filters allowing, for the first time, a test of the fusion algorithm with real flight data. Furthermore, a precise best estimate of trajectory is available for portions of STS-69, making possible a check on the performance of the fusion filter. In order to successfully carry out this experiment with flight data, two extensions to the existing scheme were necessary: a fusion edit test based on differences between the filter state vectors, and an underweighting scheme to accommodate the suboptimal perfect target assumption made by the Shuttle rendezvous filter. With these innovations, the flight data was successfully fused from playbacks of downlinked and/or recorded measurement data through ground analysis versions of the Shuttle rendezvous filter and a GPS filter developed for another experiment. The fusion results agree with the best estimate of trajectory at approximately the levels of uncertainty expected from the fusion filter's covariance matrix.
An Overview of Flight Test Results for a Formation Flight Autopilot
NASA Technical Reports Server (NTRS)
Hanson, Curtis E.; Ryan, Jack; Allen, Michael J.; Jacobson, Steven R.
2002-01-01
The first flight test phase of the NASA Dryden Flight Research Center Autonomous Formation Flight project has successfully demonstrated precision autonomous station-keeping of an F/A-18 research airplane with a second F/A-18 airplane. Blended inertial navigation system (INS) and global positioning system (GPS) measurements have been communicated across an air-to-air telemetry link and used to compute relative-position estimates. A precision research formation autopilot onboard the trailing airplane controls lateral and vertical spacing while the leading airplane operates under production autopilot control. Four research autopilot gain sets have been designed and flight-tested, and each exceeds the project design requirement of steady-state tracking accuracy within 1 standard deviation of 10 ft. Performance also has been demonstrated using single- and multiple-axis inputs such as step commands and frequency sweeps. This report briefly describes the experimental formation flight systems employed and discusses the navigation, guidance, and control algorithms that have been flight-tested. An overview of the flight test results of the formation autopilot during steady-state tracking and maneuvering flight is presented.
NASA Astrophysics Data System (ADS)
Changyong, Dou; Huadong, Guo; Chunming, Han; yuquan, Liu; Xijuan, Yue; Yinghui, Zhao
2014-03-01
Raw signal simulation is a useful tool for the system design, mission planning, processing algorithm testing, and inversion algorithm design of Synthetic Aperture Radar (SAR). Due to the wide and high frequent variation of aircraft's trajectory and attitude, and the low accuracy of the Position and Orientation System (POS)'s recording data, it's difficult to quantitatively study the sensitivity of the key parameters, i.e., the baseline length and inclination, absolute phase and the orientation of the antennas etc., of the airborne Interferometric SAR (InSAR) system, resulting in challenges for its applications. Furthermore, the imprecise estimation of the installation offset between the Global Positioning System (GPS), Inertial Measurement Unit (IMU) and the InSAR antennas compounds the issue. An airborne interferometric SAR (InSAR) simulation based on the rigorous geometric model and real navigation data is proposed in this paper, providing a way for quantitatively studying the key parameters and for evaluating the effect from the parameters on the applications of airborne InSAR, as photogrammetric mapping, high-resolution Digital Elevation Model (DEM) generation, and surface deformation by Differential InSAR technology, etc. The simulation can also provide reference for the optimal design of the InSAR system and the improvement of InSAR data processing technologies such as motion compensation, imaging, image co-registration, and application parameter retrieval, etc.
Autonomous navigation system. [gyroscopic pendulum for air navigation
NASA Technical Reports Server (NTRS)
Merhav, S. J. (Inventor)
1981-01-01
An inertial navigation system utilizing a servo-controlled two degree of freedom pendulum to obtain specific force components in the locally level coordinate system is described. The pendulum includes a leveling gyroscope and an azimuth gyroscope supported on a two gimbal system. The specific force components in the locally level coordinate system are converted to components in the geographical coordinate system by means of a single Euler transformation. The standard navigation equations are solved to determine longitudinal and lateral velocities. Finally, vehicle position is determined by a further integration.
Autonomous GPS/INS navigation experiment for Space Transfer Vehicle
NASA Technical Reports Server (NTRS)
Upadhyay, Triveni N.; Cotterill, Stephen; Deaton, A. W.
1993-01-01
An experiment to validate the concept of developing an autonomous integrated spacecraft navigation system using on board Global Positioning System (GPS) and Inertial Navigation System (INS) measurements is described. The feasibility of integrating GPS measurements with INS measurements to provide a total improvement in spacecraft navigation performance, i.e. improvement in position, velocity and attitude information, was previously demonstrated. An important aspect of this research is the automatic real time reconfiguration capability of the system designed to respond to changes in a spacecraft mission under the control of an expert system.
Autonomous GPS/INS navigation experiment for Space Transfer Vehicle (STV)
NASA Technical Reports Server (NTRS)
Upadhyay, Triveni N.; Cotterill, Stephen; Deaton, A. Wayne
1991-01-01
An experiment to validate the concept of developing an autonomous integrated spacecraft navigation system using on board Global Positioning System (GPS) and Inertial Navigation System (INS) measurements is described. The feasibility of integrating GPS measurements with INS measurements to provide a total improvement in spacecraft navigation performance, i.e. improvement in position, velocity and attitude information, was previously demonstrated. An important aspect of this research is the automatic real time reconfiguration capability of the system designed to respond to changes in a spacecraft mission under the control of an expert system.
Autonomous GPS/INS navigation experiment for Space Transfer Vehicle
NASA Astrophysics Data System (ADS)
Upadhyay, Triveni N.; Cotterill, Stephen; Deaton, A. W.
1993-07-01
An experiment to validate the concept of developing an autonomous integrated spacecraft navigation system using on board Global Positioning System (GPS) and Inertial Navigation System (INS) measurements is described. The feasibility of integrating GPS measurements with INS measurements to provide a total improvement in spacecraft navigation performance, i.e. improvement in position, velocity and attitude information, was previously demonstrated. An important aspect of this research is the automatic real time reconfiguration capability of the system designed to respond to changes in a spacecraft mission under the control of an expert system.
A systematic review of gait analysis methods based on inertial sensors and adaptive algorithms.
Caldas, Rafael; Mundt, Marion; Potthast, Wolfgang; Buarque de Lima Neto, Fernando; Markert, Bernd
2017-09-01
The conventional methods to assess human gait are either expensive or complex to be applied regularly in clinical practice. To reduce the cost and simplify the evaluation, inertial sensors and adaptive algorithms have been utilized, respectively. This paper aims to summarize studies that applied adaptive also called artificial intelligence (AI) algorithms to gait analysis based on inertial sensor data, verifying if they can support the clinical evaluation. Articles were identified through searches of the main databases, which were encompassed from 1968 to October 2016. We have identified 22 studies that met the inclusion criteria. The included papers were analyzed due to their data acquisition and processing methods with specific questionnaires. Concerning the data acquisition, the mean score is 6.1±1.62, what implies that 13 of 22 papers failed to report relevant outcomes. The quality assessment of AI algorithms presents an above-average rating (8.2±1.84). Therefore, AI algorithms seem to be able to support gait analysis based on inertial sensor data. Further research, however, is necessary to enhance and standardize the application in patients, since most of the studies used distinct methods to evaluate healthy subjects. Copyright © 2017 Elsevier B.V. All rights reserved.
3D indoor modeling using a hand-held embedded system with multiple laser range scanners
NASA Astrophysics Data System (ADS)
Hu, Shaoxing; Wang, Duhu; Xu, Shike
2016-10-01
Accurate three-dimensional perception is a key technology for many engineering applications, including mobile mapping, obstacle detection and virtual reality. In this article, we present a hand-held embedded system designed for constructing 3D representation of structured indoor environments. Different from traditional vehicle-borne mobile mapping methods, the system presented here is capable of efficiently acquiring 3D data while an operator carrying the device traverses through the site. It consists of a simultaneous localization and mapping(SLAM) module, a 3D attitude estimate module and a point cloud processing module. The SLAM is based on a scan matching approach using a modern LIDAR system, and the 3D attitude estimate is generated by a navigation filter using inertial sensors. The hardware comprises three 2D time-flight laser range finders and an inertial measurement unit(IMU). All the sensors are rigidly mounted on a body frame. The algorithms are developed on the frame of robot operating system(ROS). The 3D model is constructed using the point cloud library(PCL). Multiple datasets have shown robust performance of the presented system in indoor scenarios.
The ship-borne infrared searching and tracking system based on the inertial platform
NASA Astrophysics Data System (ADS)
Li, Yan; Zhang, Haibo
2011-08-01
As a result of the radar system got interferenced or in the state of half silent ,it can cause the guided precision drop badly In the modern electronic warfare, therefore it can lead to the equipment depended on electronic guidance cannot strike the incoming goals exactly. It will need to rely on optoelectronic devices to make up for its shortcomings, but when interference is in the process of radar leading ,especially the electro-optical equipment is influenced by the roll, pitch and yaw rotation ,it can affect the target appear outside of the field of optoelectronic devices for a long time, so the infrared optoelectronic equipment can not exert the superiority, and also it cannot get across weapon-control system "reverse bring" missile against incoming goals. So the conventional ship-borne infrared system unable to track the target of incoming quickly , the ability of optoelectronic rivalry declines heavily.Here we provide a brand new controlling algorithm for the semi-automatic searching and infrared tracking based on inertial navigation platform. Now it is applying well in our XX infrared optoelectronic searching and tracking system. The algorithm is mainly divided into two steps: The artificial mode turns into auto-searching when the deviation of guide exceeds the current scene under the course of leading for radar.When the threshold value of the image picked-up is satisfied by the contrast of the target in the searching scene, the speed computed by using the CA model Least Square Method feeds back to the speed loop. And then combine the infrared information to accomplish the closed-loop control of the infrared optoelectronic system tracking. The algorithm is verified via experiment. Target capturing distance is 22.3 kilometers on the great lead deviation by using the algorithm. But without using the algorithm the capturing distance declines 12 kilometers. The algorithm advances the ability of infrared optoelectronic rivalry and declines the target capturing time by using semi-automatic searching and reliable capturing-tracking, when the lead deviation of the radar is great.
PDR with a Foot-Mounted IMU and Ramp Detection
Jiménez, Antonio R.; Seco, Fernando; Zampella, Francisco; Prieto, José C.; Guevara, Jorge
2011-01-01
The localization of persons in indoor environments is nowadays an open problem. There are partial solutions based on the deployment of a network of sensors (Local Positioning Systems or LPS). Other solutions only require the installation of an inertial sensor on the person’s body (Pedestrian Dead-Reckoning or PDR). PDR solutions integrate the signals coming from an Inertial Measurement Unit (IMU), which usually contains 3 accelerometers and 3 gyroscopes. The main problem of PDR is the accumulation of positioning errors due to the drift caused by the noise in the sensors. This paper presents a PDR solution that incorporates a drift correction method based on detecting the access ramps usually found in buildings. The ramp correction method is implemented over a PDR framework that uses an Inertial Navigation algorithm (INS) and an IMU attached to the person’s foot. Unlike other approaches that use external sensors to correct the drift error, we only use one IMU on the foot. To detect a ramp, the slope of the terrain on which the user is walking, and the change in height sensed when moving forward, are estimated from the IMU. After detection, the ramp is checked for association with one of the existing in a database. For each associated ramp, a position correction is fed into the Kalman Filter in order to refine the INS-PDR solution. Drift-free localization is achieved with positioning errors below 2 meters for 1,000-meter-long routes in a building with a few ramps. PMID:22163701
Nonlinear calibration for petroleum water content measurement using PSO
NASA Astrophysics Data System (ADS)
Li, Mingbao; Zhang, Jiawei
2008-10-01
A new algorithmic for strapdown inertial navigation system (SINS) state estimation based on neural networks is introduced. In training strategy, the error vector and its delay are introduced. This error vector is made of the position and velocity difference between the estimations of system and the outputs of GPS. After state prediction and state update, the states of the system are estimated. After off-line training, the network can approach the status switching of SINS and after on-line training, the state estimate precision can be improved further by reducing network output errors. Then the network convergence is discussed. In the end, several simulations with different noise are given. The results show that the neural network state estimator has lower noise sensitivity and better noise immunity than Kalman filter.
Assessment of modern smartphone sensors performance on vehicle localization in urban environments
NASA Astrophysics Data System (ADS)
Lazarou, Theodoros; Danezis, Chris
2017-09-01
The advent of Global Navigation Satellite Systems (GNSS) initiated a revolution in Positioning, Navigation and Timing (PNT) applications. Besides the enormous impact on geospatial data acquisition and reality capture, satellite navigation has penetrated everyday life, a fact which is proved by the increasing degree of human reliance on GNSS-enabled smart devices to perform casual activities. Nevertheless, GNSS does not perform well in all cases. Specifically, in GNSS-challenging environments, such as urban canyons or forested areas, navigation performance may be significantly degraded or even nullified. Consequently, positioning is achieved by combining GNSS with additional heterogeneous information or sensors, such as inertial sensors. To date, most smartphones are equipped with at least accelerometers and gyroscopes, besides GNSS chipsets. In the frame of this research, difficult localization scenarios were investigated to assess the performance of these low-cost inertial sensors with respect to higher grade GNSS and IMU systems. Four state-of-the-art smartphones were mounted on a specifically designed on-purpose build platform along with reference equipment. The platform was installed on top of a vehicle, which was driven by a predefined trajectory that included several GNSS-challenging parts. Consequently, positioning and inertial readings were acquired by smartphones and compared to the information collected by the reference equipment. The results indicated that although the smartphone GNSS receivers have increased sensitivity, they were unable to produce an acceptable solution for more than 30% of the driven course. However, all smartphones managed to identify, up to a satisfactory degree, distinct driving features, such as curves or bumps.
PEG Enhancement for EM1 and EM2+ Missions
NASA Technical Reports Server (NTRS)
Von der Porten, Paul; Ahmad, Naeem; Hawkins, Matt
2018-01-01
NASA is currently building the Space Launch System (SLS) Block-1 launch vehicle for the Exploration Mission 1 (EM-1) test flight. The next evolution of SLS, the Block-1B Exploration Mission 2 (EM-2), is currently being designed. The Block-1 and Block-1B vehicles will use the Powered Explicit Guidance (PEG) algorithm. Due to the relatively low thrust-to-weight ratio of the Exploration Upper Stage (EUS), certain enhancements to the Block-1 PEG algorithm are needed to perform Block-1B missions. In order to accommodate mission design for EM-2 and beyond, PEG has been significantly improved since its use on the Space Shuttle program. The current version of PEG has the ability to switch to different targets during Core Stage (CS) or EUS flight, and can automatically reconfigure for a single Engine Out (EO) scenario, loss of communication with the Launch Abort System (LAS), and Inertial Navigation System (INS) failure. The Thrust Factor (TF) algorithm uses measured state information in addition to a priori parameters, providing PEG with an improved estimate of propulsion information. This provides robustness against unknown or undetected engine failures. A loft parameter input allows LAS jettison while maximizing payload mass. The current PEG algorithm is now able to handle various classes of missions with burn arcs much longer than were seen in the shuttle program. These missions include targeting a circular LEO orbit with a low-thrust, long-burn-duration upper stage, targeting a highly eccentric Trans-Lunar Injection (TLI) orbit, targeting a disposal orbit using the low-thrust Reaction Control System (RCS), and targeting a hyperbolic orbit. This paper will describe the design and implementation of the TF algorithm, the strategy to handle EO in various flight regimes, algorithms to cover off-nominal conditions, and other enhancements to the Block-1 PEG algorithm. This paper illustrates challenges posed by the Block-1B vehicle, and results show that the improved PEG algorithm is capable for use on the SLS Block 1-B vehicle as part of the Guidance, Navigation, and Control System.
Sampling and Control Circuit Board for an Inertial Measurement Unit
NASA Technical Reports Server (NTRS)
Chelmins, David T (Inventor); Sands, Obed (Inventor); Powis, Richard T., Jr. (Inventor)
2016-01-01
A circuit board that serves as a control and sampling interface to an inertial measurement unit ("IMU") is provided. The circuit board is also configured to interface with a local oscillator and an external trigger pulse. The circuit board is further configured to receive the external trigger pulse from an external source that time aligns the local oscillator and initiates sampling of the inertial measurement device for data at precise time intervals based on pulses from the local oscillator. The sampled data may be synchronized by the circuit board with other sensors of a navigation system via the trigger pulse.
Spoofing Detection Using GNSS/INS/Odometer Coupling for Vehicular Navigation
Broumandan, Ali; Lachapelle, Gérard
2018-01-01
Location information is one of the most vital information required to achieve intelligent and context-aware capability for various applications such as driverless cars. However, related security and privacy threats are a major holdback. With increasing focus on using Global Navigation Satellite Systems (GNSS) for autonomous navigation and related applications, it is important to provide robust navigation solutions, yet signal spoofing for illegal or covert transportation and misleading receiver timing is increasing and now frequent. Hence, detection and mitigation of spoofing attacks has become an important topic. Several contributions on spoofing detection have been made, focusing on different layers of a GNSS receiver. This paper focuses on spoofing detection utilizing self-contained sensors, namely inertial measurement units (IMUs) and vehicle odometer outputs. A spoofing detection approach based on a consistency check between GNSS and IMU/odometer mechanization is proposed. To detect a spoofing attack, the method analyses GNSS and IMU/odometer measurements independently during a pre-selected observation window and cross checks the solutions provided by GNSS and inertial navigation solution (INS)/odometer mechanization. The performance of the proposed method is verified in real vehicular environments. Mean spoofing detection time and detection performance in terms of receiver operation characteristics (ROC) in sub-urban and dense urban environments are evaluated. PMID:29695064
Spoofing Detection Using GNSS/INS/Odometer Coupling for Vehicular Navigation.
Broumandan, Ali; Lachapelle, Gérard
2018-04-24
Location information is one of the most vital information required to achieve intelligent and context-aware capability for various applications such as driverless cars. However, related security and privacy threats are a major holdback. With increasing focus on using Global Navigation Satellite Systems (GNSS) for autonomous navigation and related applications, it is important to provide robust navigation solutions, yet signal spoofing for illegal or covert transportation and misleading receiver timing is increasing and now frequent. Hence, detection and mitigation of spoofing attacks has become an important topic. Several contributions on spoofing detection have been made, focusing on different layers of a GNSS receiver. This paper focuses on spoofing detection utilizing self-contained sensors, namely inertial measurement units (IMUs) and vehicle odometer outputs. A spoofing detection approach based on a consistency check between GNSS and IMU/odometer mechanization is proposed. To detect a spoofing attack, the method analyses GNSS and IMU/odometer measurements independently during a pre-selected observation window and cross checks the solutions provided by GNSS and inertial navigation solution (INS)/odometer mechanization. The performance of the proposed method is verified in real vehicular environments. Mean spoofing detection time and detection performance in terms of receiver operation characteristics (ROC) in sub-urban and dense urban environments are evaluated.
Chiang, Kai-Wei; Lin, Cheng-An; Kuo, Chung-Yen
2015-01-01
The integration of the Strapdown Inertial Navigation System and Global Navigation Satellite System (SINS/GNSS) has been implemented for land-based gravimetry and has been proven to perform well in estimating gravity. Based on the mGal-level gravimetry results, this research aims to construct and develop a land-based SINS/GNSS gravimetry device containing a navigation-grade Inertial Measurement Unit. This research also presents a feasibility analysis for groundwater resource detection. A preliminary comparison of the kinematic velocities and accelerations using multi-combination of GNSS data including Global Positioning System, Global Navigation Satellite System, and BeiDou Navigation Satellite System, indicates that three-system observations performed better than two-system data in the computation. A comparison of gravity derived from SINS/GNSS and measured using a relative gravimeter also shows that both agree reasonably well with a mean difference of 2.30 mGal. The mean difference between repeat measurements of gravity disturbance using SINS/GNSS is 2.46 mGal with a standard deviation of 1.32 mGal. The gravity variation because of the groundwater at Pingtung Plain, Taiwan could reach 2.72 mGal. Hence, the developed land-based SINS/GNSS gravimetry can sufficiently and effectively detect groundwater resources. PMID:26426019
Chiang, Kai-Wei; Lin, Cheng-An; Kuo, Chung-Yen
2015-09-29
The integration of the Strapdown Inertial Navigation System and Global Navigation Satellite System (SINS/GNSS) has been implemented for land-based gravimetry and has been proven to perform well in estimating gravity. Based on the mGal-level gravimetry results, this research aims to construct and develop a land-based SINS/GNSS gravimetry device containing a navigation-grade Inertial Measurement Unit. This research also presents a feasibility analysis for groundwater resource detection. A preliminary comparison of the kinematic velocities and accelerations using multi-combination of GNSS data including Global Positioning System, Global Navigation Satellite System, and BeiDou Navigation Satellite System, indicates that three-system observations performed better than two-system data in the computation. A comparison of gravity derived from SINS/GNSS and measured using a relative gravimeter also shows that both agree reasonably well with a mean difference of 2.30 mGal. The mean difference between repeat measurements of gravity disturbance using SINS/GNSS is 2.46 mGal with a standard deviation of 1.32 mGal. The gravity variation because of the groundwater at Pingtung Plain, Taiwan could reach 2.72 mGal. Hence, the developed land-based SINS/GNSS gravimetry can sufficiently and effectively detect groundwater resources.
BOREAS Level-0 C-130 Navigation Data
NASA Technical Reports Server (NTRS)
Strub, Richard; Newcomer, Jeffrey A.; Domingues, Roseanne; Hall, Forrest G. (Editor)
2000-01-01
The level-0 C-130 navigation data files contain aircraft attitude and position information acquired during the digital image and photographic data collection missions over the BOReal Ecosystem-Atmosphere Study (BOREAS) study areas. Various portions of the navigation data were collected at 1, 10, and 30 Hz. The level-0 C-130 navigation data collected for BOREAS in 1994 were improved over previous years in that the C-130 onboard navigation system was upgraded to output inertial navigation parameters every 1/30th of a second (i.e., 30 Hz). This upgrade was encouraged by users of the aircraft scanner data with the hope of improving the relative geometric positioning of the collected images.
Evaluation on real-time dynamic performance of BDS in PPP, RTK, and INS tightly aided modes
NASA Astrophysics Data System (ADS)
Gao, Zhouzheng; Li, Tuan; Zhang, Hongping; Ge, Maorong; Schuh, Harald
2018-05-01
Since China's BeiDou satellite navigation system (BDS) began to provide regional navigation service for Asia-Pacific region after 2012, more new generation BDS satellites have been launched to further expand BDS's coverage to be global. In this contribution, precise positioning models based on BDS and the corresponding mathematical algorithms are presented in detail. Then, an evaluation on BDS's real-time dynamic positioning and navigation performance is presented in Precise Point Positioning (PPP), Real-time Kinematic (RTK), Inertial Navigation System (INS) tightly aided PPP and RTK modes by processing a set of land-borne vehicle experiment data. Results indicate that BDS positioning Root Mean Square (RMS) in north, east, and vertical components are 2.0, 2.7, and 7.6 cm in RTK mode and 7.8, 14.7, and 24.8 cm in PPP mode, which are close to GPS positioning accuracy. Meanwhile, with the help of INS, about 38.8%, 67.5%, and 66.5% improvements can be obtained by using PPP/INS tight-integration mode. Such enhancements in RTK/INS tight-integration mode are 14.1%, 34.0%, and 41.9%. Moreover, the accuracy of velocimetry and attitude determination can be improved to be better than 1 cm/s and 0.1°, respectively. Besides, the continuity and reliability of BDS in both PPP and RTK modes can also be ameliorated significantly by INS during satellite signal missing periods.
A low-cost inertial smoothing system for landing approach guidance
NASA Technical Reports Server (NTRS)
Niessen, F. R.
1973-01-01
Accurate position and velocity information with low noise content for instrument approaches and landings is required for both control and display applications. In a current VTOL automatic instrument approach and landing research program, radar-derived landing guidance position reference signals, which are noisy, have been mixed with acceleration information derived from low-cost onboard sensors to provide high-quality position and velocity information. An in-flight comparison of signal quality and accuracy has shown good agreement between the low-cost inertial smoothing system and an aided inertial navigation system. Furthermore, the low-cost inertial smoothing system has been proven to be satisfactory in control and display system applications for both automatic and pilot-in-the-loop instrument approaches and landings.
Achievements and perspectives of fiber gyros
NASA Astrophysics Data System (ADS)
Boehm, Manfred
1986-01-01
After evaluating the development history and current status of fiber-optic gyros employing the Sagnac effect, attention is given to a novel class of inertial fiber-optic motion devices having their basis in the Kennedy-Thorndike (1932) interferometry experiments. These devices promise high performance strapdown inertial navigation systems that dispense with accelerometers. The prospective performance of such devices is discussed in light of an analysis of Sagnac, Michelson, and Kennedy-Thorndike interferometers.
Evaluation on the impact of IMU grades on BDS + GPS PPP/INS tightly coupled integration
NASA Astrophysics Data System (ADS)
Gao, Zhouzheng; Ge, Maorong; Shen, Wenbin; Li, You; Chen, Qijin; Zhang, Hongping; Niu, Xiaoji
2017-09-01
The unexpected observing environments in dynamic applications may lead to partial and/or complete satellite signal outages frequently, which can definitely impact on the positioning performance of the Precise Point Positioning (PPP) in terms of decreasing available satellite numbers, breaking the continuity of observations, and degrading PPP's positioning accuracy. Generally, both the Inertial Navigation System (INS) and the multi-constellation Global Navigation Satellite System (GNSS) can be used to enhance the performance of PPP. This paper introduces the mathematical models of the multi-GNSS PPP/INS Tightly Coupled Integration (TCI), and investigates its performance from several aspects. Specifically, it covers (1) the use of the BDS/GPS PPP, PPP/INS, and their combination; (2) three positioning modes including PPP, PPP/INS TCI, and PPP/INS Loosely Coupled Integration (LCI); (3) the use of four various INS systems named navigation grade, tactical grade, auto grade, and Micro-Electro-Mechanical-Sensors (MEMS) one; (4) three PPP observation scenarios including PPP available, partially available, and fully outage. According to the statistics results, (1) the positioning performance of the PPP/INS (either TCI or LCI) mode is insignificantly depended on the grade of inertial sensor, when there are enough available satellites; (2) after the complete GNSS outages, the TCI mode expresses both higher convergence speed and more accurate positioning solutions than the LCI mode. Furthermore, in the TCI mode, using a higher grade inertial sensor is beneficial for the PPP convergence; (3) under the partial GNSS outage situations, the PPP/INS TCI mode position divergence speed is also restrained significantly; and (4) the attitude determination accuracy of the PPP/INS integration is highly correlated with the grade of inertial sensor.
FORTRAN program for analyzing ground-based radar data: Usage and derivations, version 6.2
NASA Technical Reports Server (NTRS)
Haering, Edward A., Jr.; Whitmore, Stephen A.
1995-01-01
A postflight FORTRAN program called 'radar' reads and analyzes ground-based radar data. The output includes position, velocity, and acceleration parameters. Air data parameters are also provided if atmospheric characteristics are input. This program can read data from any radar in three formats. Geocentric Cartesian position can also be used as input, which may be from an inertial navigation or Global Positioning System. Options include spike removal, data filtering, and atmospheric refraction corrections. Atmospheric refraction can be corrected using the quick White Sands method or the gradient refraction method, which allows accurate analysis of very low elevation angle and long-range data. Refraction properties are extrapolated from surface conditions, or a measured profile may be input. Velocity is determined by differentiating position. Accelerations are determined by differentiating velocity. This paper describes the algorithms used, gives the operational details, and discusses the limitations and errors of the program. Appendices A through E contain the derivations for these algorithms. These derivations include an improvement in speed to the exact solution for geodetic altitude, an improved algorithm over earlier versions for determining scale height, a truncation algorithm for speeding up the gradient refraction method, and a refinement of the coefficients used in the White Sands method for Edwards AFB, California. Appendix G contains the nomenclature.
A Long-Term Performance Enhancement Method for FOG-Based Measurement While Drilling
Zhang, Chunxi; Lin, Tie
2016-01-01
In the oil industry, the measurement-while-drilling (MWD) systems are usually used to provide the real-time position and orientation of the bottom hole assembly (BHA) during drilling. However, the present MWD systems based on magnetic surveying technology can barely ensure good performance because of magnetic interference phenomena. In this paper, a MWD surveying system based on a fiber optic gyroscope (FOG) was developed to replace the magnetic surveying system. To accommodate the size of the downhole drilling conditions, a new design method is adopted. In order to realize long-term and high position precision and orientation surveying, an integrated surveying algorithm is proposed based on inertial navigation system (INS) and drilling features. In addition, the FOG-based MWD error model is built and the drilling features are analyzed. The state-space system model and the observation updates model of the Kalman filter are built. To validate the availability and utility of the algorithm, the semi-physical simulation is conducted under laboratory conditions. The results comparison with the traditional algorithms show that the errors were suppressed and the measurement precision of the proposed algorithm is better than the traditional ones. In addition, the proposed method uses a lot less time than the zero velocity update (ZUPT) method. PMID:27483270
A Long-Term Performance Enhancement Method for FOG-Based Measurement While Drilling.
Zhang, Chunxi; Lin, Tie
2016-07-28
In the oil industry, the measurement-while-drilling (MWD) systems are usually used to provide the real-time position and orientation of the bottom hole assembly (BHA) during drilling. However, the present MWD systems based on magnetic surveying technology can barely ensure good performance because of magnetic interference phenomena. In this paper, a MWD surveying system based on a fiber optic gyroscope (FOG) was developed to replace the magnetic surveying system. To accommodate the size of the downhole drilling conditions, a new design method is adopted. In order to realize long-term and high position precision and orientation surveying, an integrated surveying algorithm is proposed based on inertial navigation system (INS) and drilling features. In addition, the FOG-based MWD error model is built and the drilling features are analyzed. The state-space system model and the observation updates model of the Kalman filter are built. To validate the availability and utility of the algorithm, the semi-physical simulation is conducted under laboratory conditions. The results comparison with the traditional algorithms show that the errors were suppressed and the measurement precision of the proposed algorithm is better than the traditional ones. In addition, the proposed method uses a lot less time than the zero velocity update (ZUPT) method.
An approach for finding long period elliptical orbits for precursor SEI missions
NASA Technical Reports Server (NTRS)
Fraietta, Michael F.; Bond, Victor R.
1993-01-01
Precursors for Solar System Exploration Initiative (SEI) missions may require long period elliptical orbits about a planet. These orbits will typically have periods on the order of tens to hundreds of days. Some potential uses for these orbits may include the following: studying the effects of galactic cosmic radiation, parking orbits for engineering and operational test of systems, and ferrying orbits between libration points and low altitude orbits. This report presents an approach that can be used to find these orbits. The approach consists of three major steps. First, it uses a restricted three-body targeting algorithm to determine the initial conditions which satisfy certain desired final conditions in a system of two massive primaries. Then the initial conditions are transformed to an inertial coordinate system for use by a special perturbation method. Finally, using the special perturbation method, other perturbations (e.g., sun third body and solar radiation pressure) can be easily incorporated to determine their effects on the nominal trajectory. An algorithm potentially suitable for on-board guidance will also be discussed. This algorithm uses an analytic method relying on Chebyshev polynomials to compute the desired position and velocity of the satellite as a function of time. Together with navigation updates, this algorithm can be implemented to predict the size and timing for AV corrections.
Mars Aerobraking Spacecraft State Estimation by Processing Inertial Measurement Unit Data
NASA Technical Reports Server (NTRS)
Jah, Moriba K.; Lisano, Michael E.,, II; Born, George H.; Axelrad, Penina
2006-01-01
Aerobraking is an efficient technique for orbit adjustment of planetary spacecraft, such as Magellan (Venus), Mars Global Surveyor, and Mars Odyssey. Determination of the vehicle state during the aerobraking phase has conventionally been performed using only radiometric tracking data prior to and following the atmospheric drag pass. This approach is sufficiently accurate and timely to meet current mission operational requirements; however, it is expensive in terms of ground support and leads to delayed results because ofthe need for post-drag pass data. This research presents a new approach to estimation of the vehicle state during the atmospheric pass that sequentially incorporates observations from an Inertial Measurement Unit (IMU) and models of the vehicle and environment. The approach, called Inertial Measurements for Aerobraking Navigation (IMAN), is shown to perform at a level comparable to the conventional methods in terms of navigation accuracy and superior to them in terms of availability of the results immediately after completion ofthe pass. Furthermore, the research shows that IMAN can be used to reliably predict subsequent periapsis times and locations over all aerobraking regimes. IMAN also yields accurate peak dynamic pressure and heating rates, critical for a successful corridor control strategy, comparable to navigation team reconstructed values. This research also provides the first instance of the utilization of the Unscented Kalman Filter for the purpose of estimating an actual spacecraft trajectory arc about another planet.
Mars aerobraking spacecraft state estimation by processing inertial measurement unit data
NASA Astrophysics Data System (ADS)
Jah, Moriba Kemessia
Aerobraking is an efficient technique for orbit adjustment of planetary spacecraft such as Magellan (Venus), Mars Global Surveyor, and Mars Odyssey. Determination of the vehicle state during the Aerobraking phase has conventionally been performed using only radiometric tracking data prior to and following the atmospheric drag pass. This approach is sufficiently accurate and timely to meet current mission operational requirements; however, it is expensive in terms of ground support and leads to delayed results because of the need for post drag pass data. This dissertation presents a new approach to estimation of the vehicle state during the atmospheric pass that sequentially incorporates observations from an Inertial Measurement Unit (IMU) and models of the vehicle and environment. The approach, called Inertial Measurements for Aerobraking Navigation (IMAN), is shown to perform at a level comparable to the conventional methods in terms of navigation accuracy and superior to them in terms of availability of the results immediately after completion of the pass. Furthermore, the research shows that IMAN can be used to reliably predict subsequent periapsis times and locations over all aerobraking regimes. IMAN also yields accurate peak dynamic pressure and heating rates, critical for a successful corridor control strategy, comparable to navigation team reconstructed values. This research also provides the first instance of the utilization of the Unscented Kalman Filter for the purpose of estimating an actual spacecraft trajectory arc about another planet.
NASA Astrophysics Data System (ADS)
Napoli, Jay
2016-05-01
Precision fiber optic gyroscopes (FOGs) are critical components for an array of platforms and applications ranging from stabilization and pointing orientation of payloads and platforms to navigation and control for unmanned and autonomous systems. In addition, FOG-based inertial systems provide extremely accurate data for geo-referencing systems. Significant improvements in the performance of FOGs and FOG-based inertial systems at KVH are due, in large part, to advancements in the design and manufacture of optical fiber, as well as in manufacturing operations and signal processing. Open loop FOGs, such as those developed and manufactured by KVH Industries, offer tactical-grade performance in a robust, small package. The success of KVH FOGs and FOG-based inertial systems is due to innovations in key fields, including the development of proprietary D-shaped fiber with an elliptical core, and KVH's unique ThinFiber. KVH continually improves its FOG manufacturing processes and signal processing, which result in improved accuracies across its entire FOG product line. KVH acquired its FOG capabilities, including its patented E•Core fiber, when the company purchased Andrew Corporation's Fiber Optic Group in 1997. E•Core fiber is unique in that the light-guiding core - critical to the FOG's performance - is elliptically shaped. The elliptical core produces a fiber that has low loss and high polarization-maintaining ability. In 2010, KVH developed its ThinFiber, a 170-micron diameter fiber that retains the full performance characteristics of E•Core fiber. ThinFiber has enabled the development of very compact, high-performance open-loop FOGs, which are also used in a line of FOG-based inertial measurement units and inertial navigation systems.
NASA Astrophysics Data System (ADS)
Umadevi, P.; Navas, A.; Karuturi, Kesavabrahmaji; Shukkoor, A. Abdul; Kumar, J. Krishna; Sreekumar, Sreejith; Basim, A. Mohammed
2017-12-01
This work presents the configuration of Inertial Navigation System (INS) used in India's Reusable Launch Vehicle-Technology Demonstrator (RLV-TD) Program. In view of the specific features and requirements of the RLV-TD, specific improvements and modifications were required in the INS. A new system was designed, realised and qualified meeting the mission requirements of RLV-TD, at the same time taking advantage of the flight heritage attained in INS through various Launch vehicle Missions of the country. The new system has additional redundancy in acceleration channel, in-built inclinometer based bias update scheme for acceleration channels and sign conventions as employed in an aircraft. Data acquisition in micro cycle periodicity (10 ms) was incorporated which was required to provide rate and attitude information at higher sampling rate for ascent phase control. Provision was incorporated for acquisition of rate and acceleration data with high resolution for aerodynamic characterisation and parameter estimation. GPS aided navigation scheme was incorporated to meet the stringent accuracy requirements of the mission. Navigation system configuration for RLV-TD, specific features incorporated to meet the mission requirements, various tests carried out and performance during RLV-TD flight are highlighted.
Performance analysis of an IMU-augmented GNSS tracking system on board the MAIUS-1 sounding rocket
NASA Astrophysics Data System (ADS)
Braun, Benjamin; Grillenberger, Andreas; Markgraf, Markus
2018-05-01
Satellite navigation receivers are adequate tracking sensors for range safety of both orbital launch vehicles and suborbital sounding rockets. Due to high accuracy and its low system complexity, satellite navigation is seen as well-suited supplement or replacement of conventional tracking systems like radar. Having the well-known shortcomings of satellite navigation like deliberate or unintentional interferences in mind, it is proposed to augment the satellite navigation receiver by an inertial measurement unit (IMU) to enhance continuity and availability of localization. The augmented receiver is thus enabled to output at least an inertial position solution in case of signal outages. In a previous study, it was shown by means of simulation using the example of Ariane 5 that the performance of a low-grade microelectromechanical IMU is sufficient to bridge expected outages of some ten seconds, and still meeting the range safety requirements in effect. In this publication, these theoretical findings shall be substantiated by real flight data that were recorded on MAIUS-1, a sounding rocket launched from Esrange, Sweden, in early 2017. The analysis reveals that the chosen representative of a microelectromechanical IMU is suitable to bridge outages of up to thirty seconds.
NA-241_Quarterly Report_SBLibby - 12.31.2017_v2
DOE Office of Scientific and Technical Information (OSTI.GOV)
Libby, Stephen B.
This is an evaluation of candidate navigation solutions for GPS free inspection tools that can be used in tours of large building interiors. In principle, COTS portable inertial motion unit (IMU) sensors with satisfactory accuracy, SWAP (size, weight, power), low error, and bias drift can provide sufficiently accurate dead reckoning navigation in a large building in the absence of GPS. To explore this assumption, the capabilities of representative IMU navigation sensors to meet these requirements will be evaluated, starting with a market survey, and then carrying out a basic analysis of these sensors using LLNL’s navigation codes.
Kotiadis, D; Hermens, H J; Veltink, P H
2010-05-01
An Inertial Gait Phase Detection system was developed to replace heel switches and footswitches currently being used for the triggering of drop foot stimulators. A series of four algorithms utilising accelerometers and gyroscopes individually and in combination were tested and initial results are shown. Sensors were positioned on the outside of the upper shank. Tests were performed on data gathered from a subject, sufferer of stroke, implanted with a drop foot stimulator and triggered with the current trigger, the heel switch. Data tested includes a variety of activities representing everyday life. Flat surface walking, rough terrain and carpet walking show 100% detection and the ability of the algorithms to ignore non-gait events such as weight shifts. Timing analysis is performed against the current triggering method, the heel switch. After evaluating the heel switch timing against a reference system, namely the Vicon 370 marker and force plates system. Initial results show a close correlation between the current trigger detection and the inertial sensor based triggering algorithms. Algorithms were tested for stairs up and stairs down. Best results are observed for algorithms using gyroscope data. Algorithms were designed using threshold techniques for lowest possible computational load and with least possible sensor components to minimize power requirements and to allow for potential future implantation of sensor system.
Dual-use micromechanical inertial sensors
NASA Astrophysics Data System (ADS)
Elwell, John M., Jr.
1995-03-01
A new industry, which will provide low-cost silicon-based inertial sensors to the commercial and military markets. is being created. Inertial measurement units are used extensively in military systems, and new versions are expected to find their way into commercial products, such as automobiles, as production costs fall as technology advances. An automotive inertial measurement unit can be expected to perform a complete range of control, diagnostic, and navigation functions. These functions are expected to provide significant active safety, performance, comfort, convenience, and fuel economy advantages to the automotive consumer. An inertial measurement unit applicable to the automobile industry would meet many of the performance requirements for the military in important areas, such as antenna and image stabilization, autopilot control, and the guidance of smart weapons. Such a new industrial base will significantly reduce the acquisition cost of many future tactical weapons systems. An alliance, consisting of the Charles Stark Draper Laboratory and Rockwell International, has been created to develop inertial products for this new industry.
An integrated autonomous rendezvous and docking system architecture using Centaur modern avionics
NASA Technical Reports Server (NTRS)
Nelson, Kurt
1991-01-01
The avionics system for the Centaur upper stage is in the process of being modernized with the current state-of-the-art in strapdown inertial guidance equipment. This equipment includes an integrated flight control processor with a ring laser gyro based inertial guidance system. This inertial navigation unit (INU) uses two MIL-STD-1750A processors and communicates over the MIL-STD-1553B data bus. Commands are translated into load activation through a Remote Control Unit (RCU) which incorporates the use of solid state relays. Also, a programmable data acquisition system replaces separate multiplexer and signal conditioning units. This modern avionics suite is currently being enhanced through independent research and development programs to provide autonomous rendezvous and docking capability using advanced cruise missile image processing technology and integrated GPS navigational aids. A system concept was developed to combine these technologies in order to achieve a fully autonomous rendezvous, docking, and autoland capability. The current system architecture and the evolution of this architecture using advanced modular avionics concepts being pursued for the National Launch System are discussed.
A Short Tutorial on Inertial Navigation System and Global Positioning System Integration
NASA Technical Reports Server (NTRS)
Smalling, Kyle M.; Eure, Kenneth W.
2015-01-01
The purpose of this document is to describe a simple method of integrating Inertial Navigation System (INS) information with Global Positioning System (GPS) information for an improved estimate of vehicle attitude and position. A simple two dimensional (2D) case is considered. The attitude estimates are derived from sensor data and used in the estimation of vehicle position and velocity through dead reckoning within the INS. The INS estimates are updated with GPS estimates using a Kalman filter. This tutorial is intended for the novice user with a focus on bringing the reader from raw sensor measurements to an integrated position and attitude estimate. An application is given using a remotely controlled ground vehicle operating in assumed 2D environment. The theory is developed first followed by an illustrative example.
Lakshmanan, Shanmugam; Prakash, Mani; Lim, Chee Peng; Rakkiyappan, Rajan; Balasubramaniam, Pagavathigounder; Nahavandi, Saeid
2018-01-01
In this paper, synchronization of an inertial neural network with time-varying delays is investigated. Based on the variable transformation method, we transform the second-order differential equations into the first-order differential equations. Then, using suitable Lyapunov-Krasovskii functionals and Jensen's inequality, the synchronization criteria are established in terms of linear matrix inequalities. Moreover, a feedback controller is designed to attain synchronization between the master and slave models, and to ensure that the error model is globally asymptotically stable. Numerical examples and simulations are presented to indicate the effectiveness of the proposed method. Besides that, an image encryption algorithm is proposed based on the piecewise linear chaotic map and the chaotic inertial neural network. The chaotic signals obtained from the inertial neural network are utilized for the encryption process. Statistical analyses are provided to evaluate the effectiveness of the proposed encryption algorithm. The results ascertain that the proposed encryption algorithm is efficient and reliable for secure communication applications.
2010-03-01
in this paper. Velocity sensing can be accomplished in the optical domain with laser Doppler radar (i.e. LIDAR ), through RF band or ultrasonic... Doppler radar. Reference [34] discusses an example of a LIDAR based velocimeter, used to furnish landing speed information for spacecraft terminal descent...in military (and commercial) capabilities: the Ring Laser Gyro (since ~1975), Fiber Optic Gyros (since ~1985), and MEMS (since ~1995). RLGs enabled
NASA Technical Reports Server (NTRS)
Lee, Shinhak; Ortiz, Gerry G.
2003-01-01
We discuss use of inertial sensors to facilitate deep space optical communications. Implementation of this concept requires accurate and wide bandwidth inertial sensors. In this presentation, the principal concept and algorithm using linear accelerometers will be given along with the simulation and experimental results.
Performance Thresholds for Application of MEMS Inertial Sensors in Space
NASA Technical Reports Server (NTRS)
Smit, Geoffrey N.
1995-01-01
We review types of inertial sensors available and current usage of inertial sensors in space and the performance requirements for these applications. We then assess the performance available from micro-electro-mechanical systems (MEMS) devices, both in the near and far term. Opportunities for the application of these devices are identified. A key point is that although the performance available from MEMS inertial sensors is significantly lower than that achieved by existing macroscopic devices (at least in the near term), the low cost, low size, and power of the MEMS devices opens up a number of applications. In particular, we show that there are substantial benefits to using MEMS devices to provide vibration, and for some missions, attitude sensing. In addition, augmentation for global positioning system (GPS) navigation systems holds much promise.
Diaz-Estrella, Antonio; Reyes-Lecuona, Arcadio; Langley, Alyson; Brown, Michael; Sharples, Sarah
2018-01-01
Inertial sensors offer the potential for integration into wireless virtual reality systems that allow the users to walk freely through virtual environments. However, owing to drift errors, inertial sensors cannot accurately estimate head and body orientations in the long run, and when walking indoors, this error cannot be corrected by magnetometers, due to the magnetic field distortion created by ferromagnetic materials present in buildings. This paper proposes a technique, called EHBD (Equalization of Head and Body Directions), to address this problem using two head- and shoulder-located magnetometers. Due to their proximity, their distortions are assumed to be similar and the magnetometer measurements are used to detect when the user is looking straight forward. Then, the system corrects the discrepancies between the estimated directions of the head and the shoulder, which are provided by gyroscopes and consequently are affected by drift errors. An experiment is conducted to evaluate the performance of this technique in two tasks (navigation and navigation plus exploration) and using two different locomotion techniques: (1) gaze-directed mode (GD) in which the walking direction is forced to be the same as the head direction, and (2) decoupled direction mode (DD) in which the walking direction can be different from the viewing direction. The obtained results show that both locomotion modes show similar matching of the target path during the navigation task, while DD’s path matches the target path more closely than GD in the navigation plus exploration task. These results validate the EHBD technique especially when allowing different walking and viewing directions in the navigation plus exploration tasks, as expected. While the proposed method does not reach the accuracy of optical tracking (ideal case), it is an acceptable and satisfactory solution for users and is much more compact, portable and economical. PMID:29621298
Precision Landing and Hazard Avoidance Doman
NASA Technical Reports Server (NTRS)
Robertson, Edward A.; Carson, John M., III
2016-01-01
The Precision Landing and Hazard Avoidance (PL&HA) domain addresses the development, integration, testing, and spaceflight infusion of sensing, processing, and GN&C functions critical to the success and safety of future human and robotic exploration missions. PL&HA sensors also have applications to other mission events, such as rendezvous and docking. Autonomous PL&HA builds upon the core GN&C capabilities developed to enable soft, controlled landings on the Moon, Mars, and other solar system bodies. Through the addition of a Terrain Relative Navigation (TRN) function, precision landing within tens of meters of a map-based target is possible. The addition of a 3-D terrain mapping lidar sensor improves the probability of a safe landing via autonomous, real-time Hazard Detection and Avoidance (HDA). PL&HA significantly improves the probability of mission success and enhances access to sites of scientific interest located in challenging terrain. PL&HA can also utilize external navigation aids, such as navigation satellites and surface beacons. Advanced Lidar Sensors High precision ranging, velocimetry, and 3-D terrain mapping Terrain Relative Navigation (TRN) TRN compares onboard reconnaissance data with real-time terrain imaging data to update the S/C position estimate Hazard Detection and Avoidance (HDA) Generates a high-resolution, 3-D terrain map in real-time during the approach trajectory to identify safe landing targets Inertial Navigation During Terminal Descent High precision surface relative sensors enable accurate inertial navigation during terminal descent and a tightly controlled touchdown within meters of the selected safe landing target.
Deep data fusion method for missile-borne inertial/celestial system
NASA Astrophysics Data System (ADS)
Zhang, Chunxi; Chen, Xiaofei; Lu, Jiazhen; Zhang, Hao
2018-05-01
Strap-down inertial-celestial integrated navigation system has the advantages of autonomy and high precision and is very useful for ballistic missiles. The star sensor installation error and inertial measurement error have a great influence for the system performance. Based on deep data fusion, this paper establishes measurement equations including star sensor installation error and proposes the deep fusion filter method. Simulations including misalignment error, star sensor installation error, IMU error are analyzed. Simulation results indicate that the deep fusion method can estimate the star sensor installation error and IMU error. Meanwhile, the method can restrain the misalignment errors caused by instrument errors.
Gravity Compensation Using EGM2008 for High-Precision Long-Term Inertial Navigation Systems
Wu, Ruonan; Wu, Qiuping; Han, Fengtian; Liu, Tianyi; Hu, Peida; Li, Haixia
2016-01-01
The gravity disturbance vector is one of the major error sources in high-precision and long-term inertial navigation applications. Specific to the inertial navigation systems (INSs) with high-order horizontal damping networks, analyses of the error propagation show that the gravity-induced errors exist almost exclusively in the horizontal channels and are mostly caused by deflections of the vertical (DOV). Low-frequency components of the DOV propagate into the latitude and longitude errors at a ratio of 1:1 and time-varying fluctuations in the DOV excite Schuler oscillation. This paper presents two gravity compensation methods using the Earth Gravitational Model 2008 (EGM2008), namely, interpolation from the off-line database and computing gravity vectors directly using the spherical harmonic model. Particular attention is given to the error contribution of the gravity update interval and computing time delay. It is recommended for the marine navigation that a gravity vector should be calculated within 1 s and updated every 100 s at most. To meet this demand, the time duration of calculating the current gravity vector using EGM2008 has been reduced to less than 1 s by optimizing the calculation procedure. A few off-line experiments were conducted using the data of a shipborne INS collected during an actual sea test. With the aid of EGM2008, most of the low-frequency components of the position errors caused by the gravity disturbance vector have been removed and the Schuler oscillation has been attenuated effectively. In the rugged terrain, the horizontal position error could be reduced at best 48.85% of its regional maximum. The experimental results match with the theoretical analysis and indicate that EGM2008 is suitable for gravity compensation of the high-precision and long-term INSs. PMID:27999351
Gravity Compensation Using EGM2008 for High-Precision Long-Term Inertial Navigation Systems.
Wu, Ruonan; Wu, Qiuping; Han, Fengtian; Liu, Tianyi; Hu, Peida; Li, Haixia
2016-12-18
The gravity disturbance vector is one of the major error sources in high-precision and long-term inertial navigation applications. Specific to the inertial navigation systems (INSs) with high-order horizontal damping networks, analyses of the error propagation show that the gravity-induced errors exist almost exclusively in the horizontal channels and are mostly caused by deflections of the vertical (DOV). Low-frequency components of the DOV propagate into the latitude and longitude errors at a ratio of 1:1 and time-varying fluctuations in the DOV excite Schuler oscillation. This paper presents two gravity compensation methods using the Earth Gravitational Model 2008 (EGM2008), namely, interpolation from the off-line database and computing gravity vectors directly using the spherical harmonic model. Particular attention is given to the error contribution of the gravity update interval and computing time delay. It is recommended for the marine navigation that a gravity vector should be calculated within 1 s and updated every 100 s at most. To meet this demand, the time duration of calculating the current gravity vector using EGM2008 has been reduced to less than 1 s by optimizing the calculation procedure. A few off-line experiments were conducted using the data of a shipborne INS collected during an actual sea test. With the aid of EGM2008, most of the low-frequency components of the position errors caused by the gravity disturbance vector have been removed and the Schuler oscillation has been attenuated effectively. In the rugged terrain, the horizontal position error could be reduced at best 48.85% of its regional maximum. The experimental results match with the theoretical analysis and indicate that EGM2008 is suitable for gravity compensation of the high-precision and long-term INSs.
Intelligent Behavioral Action Aiding for Improved Autonomous Image Navigation
2012-09-13
odometry, SICK laser scanning unit ( Lidar ), Inertial Measurement Unit (IMU) and ultrasonic distance measurement system (Figure 32). The Lidar , IMU...2010, July) GPS world. [Online]. http://www.gpsworld.com/tech-talk- blog/gnss-independent-navigation-solution-using-integrated- lidar -data-11378 [4...Milford, David McKinnon, Michael Warren, Gordon Wyeth, and Ben Upcroft, "Feature-based Visual Odometry and Featureless Place Recognition for SLAM in
Unstructured Facility Navigation by Applying the NIST 4D/RCS Architecture
2006-07-01
control, and the planner); wire- less data and emergency stop radios; GPS receiver; inertial navigation unit; dual stereo cameras; infrared sensors...current Actuators Wheel motors, camera controls Scale & filter signals status commands commands commands GPS Antenna Dual stereo cameras...used in the sensory processing module include the two pairs of stereo color cameras, the physical bumper and infrared bumper sensors, the motor
Guidance, navigation, and control systems performance analysis: Apollo 13 mission report
NASA Technical Reports Server (NTRS)
1970-01-01
The conclusions of the analyses of the inflight performance of the Apollo 13 spacecraft guidance, navigation, and control equipment are presented. The subjects discussed are: (1) the command module systems, (2) the lunar module inertial measurement unit, (3) the lunar module digital autopilot, (4) the lunar module abort guidance system, (5) lunar module optical alignment checks, and (6) spacecraft component separation procedures.
Chen, Guoliang; Meng, Xiaolin; Wang, Yunjia; Zhang, Yanzhe; Tian, Peng; Yang, Huachao
2015-09-23
Because of the high calculation cost and poor performance of a traditional planar map when dealing with complicated indoor geographic information, a WiFi fingerprint indoor positioning system cannot be widely employed on a smartphone platform. By making full use of the hardware sensors embedded in the smartphone, this study proposes an integrated approach to a three-dimensional (3D) indoor positioning system. First, an improved K-means clustering method is adopted to reduce the fingerprint database retrieval time and enhance positioning efficiency. Next, with the mobile phone's acceleration sensor, a new step counting method based on auto-correlation analysis is proposed to achieve cell phone inertial navigation positioning. Furthermore, the integration of WiFi positioning with Pedestrian Dead Reckoning (PDR) obtains higher positional accuracy with the help of the Unscented Kalman Filter algorithm. Finally, a hybrid 3D positioning system based on Unity 3D, which can carry out real-time positioning for targets in 3D scenes, is designed for the fluent operation of mobile terminals.
Planetary Probe Entry Atmosphere Estimation Using Synthetic Air Data System
NASA Technical Reports Server (NTRS)
Karlgaard, Chris; Schoenenberger, Mark
2017-01-01
This paper develops an atmospheric state estimator based on inertial acceleration and angular rate measurements combined with an assumed vehicle aerodynamic model. The approach utilizes the full navigation state of the vehicle (position, velocity, and attitude) to recast the vehicle aerodynamic model to be a function solely of the atmospheric state (density, pressure, and winds). Force and moment measurements are based on vehicle sensed accelerations and angular rates. These measurements are combined with an aerodynamic model and a Kalman-Schmidt filter to estimate the atmospheric conditions. The new method is applied to data from the Mars Science Laboratory mission, which landed the Curiosity rover on the surface of Mars in August 2012. The results of the new estimation algorithm are compared with results from a Flush Air Data Sensing algorithm based on onboard pressure measurements on the vehicle forebody. The comparison indicates that the new proposed estimation method provides estimates consistent with the air data measurements, without the use of pressure measurements. Implications for future missions such as the Mars 2020 entry capsule are described.
Integrated WiFi/PDR/Smartphone Using an Unscented Kalman Filter Algorithm for 3D Indoor Localization
Chen, Guoliang; Meng, Xiaolin; Wang, Yunjia; Zhang, Yanzhe; Tian, Peng; Yang, Huachao
2015-01-01
Because of the high calculation cost and poor performance of a traditional planar map when dealing with complicated indoor geographic information, a WiFi fingerprint indoor positioning system cannot be widely employed on a smartphone platform. By making full use of the hardware sensors embedded in the smartphone, this study proposes an integrated approach to a three-dimensional (3D) indoor positioning system. First, an improved K-means clustering method is adopted to reduce the fingerprint database retrieval time and enhance positioning efficiency. Next, with the mobile phone’s acceleration sensor, a new step counting method based on auto-correlation analysis is proposed to achieve cell phone inertial navigation positioning. Furthermore, the integration of WiFi positioning with Pedestrian Dead Reckoning (PDR) obtains higher positional accuracy with the help of the Unscented Kalman Filter algorithm. Finally, a hybrid 3D positioning system based on Unity 3D, which can carry out real-time positioning for targets in 3D scenes, is designed for the fluent operation of mobile terminals. PMID:26404314
Airborne LIDAR point cloud tower inclination judgment
NASA Astrophysics Data System (ADS)
liang, Chen; zhengjun, Liu; jianguo, Qian
2016-11-01
Inclined transmission line towers for the safe operation of the line caused a great threat, how to effectively, quickly and accurately perform inclined judgment tower of power supply company safety and security of supply has played a key role. In recent years, with the development of unmanned aerial vehicles, unmanned aerial vehicles equipped with a laser scanner, GPS, inertial navigation is one of the high-precision 3D Remote Sensing System in the electricity sector more and more. By airborne radar scan point cloud to visually show the whole picture of the three-dimensional spatial information of the power line corridors, such as the line facilities and equipment, terrain and trees. Currently, LIDAR point cloud research in the field has not yet formed an algorithm to determine tower inclination, the paper through the existing power line corridor on the tower base extraction, through their own tower shape characteristic analysis, a vertical stratification the method of combining convex hull algorithm for point cloud tower scarce two cases using two different methods for the tower was Inclined to judge, and the results with high reliability.
Optimization-Based Sensor Fusion of GNSS and IMU Using a Moving Horizon Approach
Girrbach, Fabian; Hol, Jeroen D.; Bellusci, Giovanni; Diehl, Moritz
2017-01-01
The rise of autonomous systems operating close to humans imposes new challenges in terms of robustness and precision on the estimation and control algorithms. Approaches based on nonlinear optimization, such as moving horizon estimation, have been shown to improve the accuracy of the estimated solution compared to traditional filter techniques. This paper introduces an optimization-based framework for multi-sensor fusion following a moving horizon scheme. The framework is applied to the often occurring estimation problem of motion tracking by fusing measurements of a global navigation satellite system receiver and an inertial measurement unit. The resulting algorithm is used to estimate position, velocity, and orientation of a maneuvering airplane and is evaluated against an accurate reference trajectory. A detailed study of the influence of the horizon length on the quality of the solution is presented and evaluated against filter-like and batch solutions of the problem. The versatile configuration possibilities of the framework are finally used to analyze the estimated solutions at different evaluation times exposing a nearly linear behavior of the sensor fusion problem. PMID:28534857
Optimization-Based Sensor Fusion of GNSS and IMU Using a Moving Horizon Approach.
Girrbach, Fabian; Hol, Jeroen D; Bellusci, Giovanni; Diehl, Moritz
2017-05-19
The rise of autonomous systems operating close to humans imposes new challenges in terms of robustness and precision on the estimation and control algorithms. Approaches based on nonlinear optimization, such as moving horizon estimation, have been shown to improve the accuracy of the estimated solution compared to traditional filter techniques. This paper introduces an optimization-based framework for multi-sensor fusion following a moving horizon scheme. The framework is applied to the often occurring estimation problem of motion tracking by fusing measurements of a global navigation satellite system receiver and an inertial measurement unit. The resulting algorithm is used to estimate position, velocity, and orientation of a maneuvering airplane and is evaluated against an accurate reference trajectory. A detailed study of the influence of the horizon length on the quality of the solution is presented and evaluated against filter-like and batch solutions of the problem. The versatile configuration possibilities of the framework are finally used to analyze the estimated solutions at different evaluation times exposing a nearly linear behavior of the sensor fusion problem.
INS integrated motion analysis for autonomous vehicle navigation
NASA Technical Reports Server (NTRS)
Roberts, Barry; Bazakos, Mike
1991-01-01
The use of inertial navigation system (INS) measurements to enhance the quality and robustness of motion analysis techniques used for obstacle detection is discussed with particular reference to autonomous vehicle navigation. The approach to obstacle detection used here employs motion analysis of imagery generated by a passive sensor. Motion analysis of imagery obtained during vehicle travel is used to generate range measurements to points within the field of view of the sensor, which can then be used to provide obstacle detection. Results obtained with an INS integrated motion analysis approach are reviewed.
Adaptive Estimation and Heuristic Optimization of Nonlinear Spacecraft Attitude Dynamics
2016-09-15
Algorithm GPS Global Positioning System HOUF Higher Order Unscented Filter IC initial conditions IMM Interacting Multiple Model IMU Inertial Measurement Unit ...sources ranging from inertial measurement units to star sensors are used to construct observations for attitude estimation algorithms. The sensor...parameters. A single vector measurement will provide two independent parameters, as a unit vector constraint removes a DOF making the problem underdetermined
NASA Astrophysics Data System (ADS)
Klein, Tony
2017-10-01
Used these days in inertial navigation, ring lasers are also used in recording the tiniest variations in the Earth's spin, as well in detecting earthquakes and even the drift of continents. How did it all begin?
NASA Astrophysics Data System (ADS)
Wang, Lin; Wu, Wenqi; Wei, Guo; Lian, Junxiang; Yu, Ruihang
2018-05-01
The shipboard redundant rotational inertial navigation system (RINS) configuration, including a dual-axis RINS and a single-axis RINS, can satisfy the demand of marine INSs of especially high reliability as well as achieving trade-off between position accuracy and cost. Generally, the dual-axis RINS is the master INS, and the single-axis RINS is the hot backup INS for high reliability purposes. An integrity monitoring system performs a fault detection function to ensure sailing safety. However, improving the accuracy of the backup INS in case of master INS failure has not been given enough attention. Without the aid of any external information, a systematic bias collaborative measurement method based on an augmented Kalman filter is proposed for the redundant RINSs. Estimates of inertial sensor biases can be used by the built-in integrity monitoring system to monitor the RINS running condition. On the other hand, a position error prediction model is designed for the single-axis RINS to estimate the systematic error caused by its azimuth gyro bias. After position error compensation, the position information provided by the single-axis RINS still remains highly accurate, even if the integrity monitoring system detects a dual-axis RINS fault. Moreover, use of a grid frame as a navigation frame makes the proposed method applicable in any area, including the polar regions. Semi-physical simulation and experiments including sea trials verify the validity of the method.
NASA Astrophysics Data System (ADS)
Zhang, Xian; Zhou, Binquan; Li, Hong; Zhao, Xinghua; Mu, Weiwei; Wu, Wenfeng
2017-10-01
Navigation technology is crucial to the national defense and military, which can realize the measurement of orientation, positioning, attitude and speed for moving object. Inertial navigation is not only autonomous, real-time, continuous, hidden, undisturbed but also no time-limited and environment-limited. The gyroscope is the core component of the inertial navigation system, whose precision and size are the bottleneck of the performance. However, nuclear magnetic resonance gyroscope is characteristic of the advantage of high precision and small size. Nuclear magnetic resonance gyroscope can meet the urgent needs of high-tech weapons and equipment development of new generation. This paper mainly designs a set of photoelectric signal processing system for nuclear magnetic resonance gyroscope based on FPGA, which process and control the information of detecting laser .The photoelectric signal with high frequency carrier is demodulated by in-phase and quadrature demodulation method. Finally, the processing system of photoelectric signal can compensate the residual magnetism of the shielding barrel and provide the information of nuclear magnetic resonance gyroscope angular velocity.
Hierarchical information fusion for global displacement estimation in microsensor motion capture.
Meng, Xiaoli; Zhang, Zhi-Qiang; Wu, Jian-Kang; Wong, Wai-Choong
2013-07-01
This paper presents a novel hierarchical information fusion algorithm to obtain human global displacement for different gait patterns, including walking, running, and hopping based on seven body-worn inertial and magnetic measurement units. In the first-level sensor fusion, the orientation for each segment is achieved by a complementary Kalman filter (CKF) which compensates for the orientation error of the inertial navigation system solution through its error state vector. For each foot segment, the displacement is also estimated by the CKF, and zero velocity update is included for the drift reduction in foot displacement estimation. Based on the segment orientations and left/right foot locations, two global displacement estimates can be acquired from left/right lower limb separately using a linked biomechanical model. In the second-level geometric fusion, another Kalman filter is deployed to compensate for the difference between the two estimates from the sensor fusion and get more accurate overall global displacement estimation. The updated global displacement will be transmitted to left/right foot based on the human lower biomechanical model to restrict the drifts in both feet displacements. The experimental results have shown that our proposed method can accurately estimate human locomotion for the three different gait patterns with regard to the optical motion tracker.
Navigation in Difficult Environments: Multi-Sensor Fusion Techniques
2010-03-01
Hwang , Introduction to Random Signals and Applied Kalman Filtering, 3rd ed., John Wiley & Sons, Inc., New York, 1997. [17] J. L. Farrell, “GPS/INS...nav solution Navigation outputs Estimation of inertial errors ( Kalman filter) Error estimates Core sensor Incoming signal INS Estimates of signal...the INS drift terms is performed using the mechanism of a complementary Kalman filter. The idea is that a signal parameter can be generally
NASA Technical Reports Server (NTRS)
Bochsler, Daniel C.
1988-01-01
The preliminary version of expert knowledge for the Onboard Navigation (ONAV) Ground Based Expert Trainer Ascent system for the space shuttle is presented. Included is some brief background information along with the information describing the knowledge the system will contain. Information is given on rules and heuristics, telemetry status, landing sites, inertial measurement units, and a high speed trajectory determinator (HSTD) state vector.
Inertial Navigation System/Doppler Velocity Log (INS/DVL) Fusion with Partial DVL Measurements
Tal, Asaf; Klein, Itzik; Katz, Reuven
2017-01-01
The Technion autonomous underwater vehicle (TAUV) is an ongoing project aiming to develop and produce a small AUV to carry on research missions, including payload dropping, and to demonstrate acoustic communication. Its navigation system is based on an inertial navigation system (INS) aided by a Doppler velocity log (DVL), magnetometer, and pressure sensor (PS). In many INSs, such as the one used in TAUV, only the velocity vector (provided by the DVL) can be used for aiding the INS, i.e., enabling only a loosely coupled integration approach. In cases of partial DVL measurements, such as failure to maintain bottom lock, the DVL cannot estimate the vehicle velocity. Thus, in partial DVL situations no velocity data can be integrated into the TAUV INS, and as a result its navigation solution will drift in time. To circumvent that problem, we propose a DVL-based vehicle velocity solution using the measured partial raw data of the DVL and additional information, thereby deriving an extended loosely coupled (ELC) approach. The implementation of the ELC approach requires only software modification. In addition, we present the TAUV six degrees of freedom (6DOF) simulation that includes all functional subsystems. Using this simulation, the proposed approach is evaluated and the benefit of using it is shown. PMID:28241410
Inertial Navigation System/Doppler Velocity Log (INS/DVL) Fusion with Partial DVL Measurements.
Tal, Asaf; Klein, Itzik; Katz, Reuven
2017-02-22
The Technion autonomous underwater vehicle (TAUV) is an ongoing project aiming to develop and produce a small AUV to carry on research missions, including payload dropping, and to demonstrate acoustic communication. Its navigation system is based on an inertial navigation system (INS) aided by a Doppler velocity log (DVL), magnetometer, and pressure sensor (PS). In many INSs, such as the one used in TAUV, only the velocity vector (provided by the DVL) can be used for aiding the INS, i.e., enabling only a loosely coupled integration approach. In cases of partial DVL measurements, such as failure to maintain bottom lock, the DVL cannot estimate the vehicle velocity. Thus, in partial DVL situations no velocity data can be integrated into the TAUV INS, and as a result its navigation solution will drift in time. To circumvent that problem, we propose a DVL-based vehicle velocity solution using the measured partial raw data of the DVL and additional information, thereby deriving an extended loosely coupled (ELC) approach. The implementation of the ELC approach requires only software modification. In addition, we present the TAUV six degrees of freedom (6DOF) simulation that includes all functional subsystems. Using this simulation, the proposed approach is evaluated and the benefit of using it is shown.
NASA Technical Reports Server (NTRS)
Hruby, R. J.; Bjorkman, W. S.; Schmidt, S. F.; Carestia, R. A.
1979-01-01
Algorithms were developed that attempt to identify which sensor in a tetrad configuration has experienced a step failure. An algorithm is also described that provides a measure of the confidence with which the correct identification was made. Experimental results are presented from real-time tests conducted on a three-axis motion facility utilizing an ortho-skew tetrad strapdown inertial sensor package. The effects of prediction errors and of quantization on correct failure identification are discussed as well as an algorithm for detecting second failures through prediction.
Brückner, Hans-Peter; Spindeldreier, Christian; Blume, Holger
2013-01-01
A common approach for high accuracy sensor fusion based on 9D inertial measurement unit data is Kalman filtering. State of the art floating-point filter algorithms differ in their computational complexity nevertheless, real-time operation on a low-power microcontroller at high sampling rates is not possible. This work presents algorithmic modifications to reduce the computational demands of a two-step minimum order Kalman filter. Furthermore, the required bit-width of a fixed-point filter version is explored. For evaluation real-world data captured using an Xsens MTx inertial sensor is used. Changes in computational latency and orientation estimation accuracy due to the proposed algorithmic modifications and fixed-point number representation are evaluated in detail on a variety of processing platforms enabling on-board processing on wearable sensor platforms.
Inertial Sensor-Based Touch and Shake Metaphor for Expressive Control of 3D Virtual Avatars
Patil, Shashidhar; Chintalapalli, Harinadha Reddy; Kim, Dubeom; Chai, Youngho
2015-01-01
In this paper, we present an inertial sensor-based touch and shake metaphor for expressive control of a 3D virtual avatar in a virtual environment. An intuitive six degrees-of-freedom wireless inertial motion sensor is used as a gesture and motion control input device with a sensor fusion algorithm. The algorithm enables user hand motions to be tracked in 3D space via magnetic, angular rate, and gravity sensors. A quaternion-based complementary filter is implemented to reduce noise and drift. An algorithm based on dynamic time-warping is developed for efficient recognition of dynamic hand gestures with real-time automatic hand gesture segmentation. Our approach enables the recognition of gestures and estimates gesture variations for continuous interaction. We demonstrate the gesture expressivity using an interactive flexible gesture mapping interface for authoring and controlling a 3D virtual avatar and its motion by tracking user dynamic hand gestures. This synthesizes stylistic variations in a 3D virtual avatar, producing motions that are not present in the motion database using hand gesture sequences from a single inertial motion sensor. PMID:26094629
Failure Detection of a Pseudolite-Based Reference System Using Residual Monitoring
2009-03-01
inertial measurements contain white Gaussian noise, wfins and w ! ins. f bins = f b + abias + w f ins (2.3) !bibins = ! b ib + !bias + w ! ins (2.4) A...type of IMU being used and the length of navigation. For a more accurate model the bias can estimated as a drift, shown as abias and !bias. The drift...to be estimated inside a Kalman lter. _abias = abias T + wabias (2.5) where T is the time constant. The strapdown mechanization for raw inertial
Inertial Sensor Characterization for Inertial Navigation and Human Motion Tracking Applications
2012-06-01
sensor to the pendulum. The time he took to design this part in SolidWorks so that I could have it printed on a 3D printer was greatly appreciated...I would also like to thank Daniel Sakoda for his quick turnaround in printing the mounting bracket using a 3D printer . Lastly, I would like to...sensors provide three-dimensional ( 3D ) orientation, acceleration, rate of turn, and magnetic field information. Manufacturers specify both static and
a Method for the Positioning and Orientation of Rail-Bound Vehicles in Gnss-Free Environments
NASA Astrophysics Data System (ADS)
Hung, R.; King, B. A.; Chen, W.
2016-06-01
Mobile Mapping System (MMS) are increasingly applied for spatial data collection to support different fields because of their efficiencies and the levels of detail they can provide. The Position and Orientation System (POS), which is conventionally employed for locating and orienting MMS, allows direct georeferencing of spatial data in real-time. Since the performance of a POS depends on both the Inertial Navigation System (INS) and the Global Navigation Satellite System (GNSS), poor GNSS conditions, such as in long tunnels and underground, introduce the necessity for post-processing. In above-ground railways, mobile mapping technology is employed with high performance sensors for finite usage, which has considerable potential for enhancing railway safety and management in real-time. In contrast, underground railways present a challenge for a conventional POS thus alternative configurations are necessary to maintain data accuracy and alleviate the need for post-processing. This paper introduces a method of rail-bound navigation to replace the role of GNSS for railway applications. The proposed method integrates INS and track alignment data for environment-independent navigation and reduces the demand of post-processing. The principle of rail-bound navigation is presented and its performance is verified by an experiment using a consumer-grade Inertial Measurement Unit (IMU) and a small-scale railway model. The method produced a substantial improvement in position and orientation for a poorly initialised system in centimetre positional accuracy. The potential improvements indicated by, and limitations of rail-bound navigation are also considered for further development in existing railway systems.
A novel artificial fish swarm algorithm for recalibration of fiber optic gyroscope error parameters.
Gao, Yanbin; Guan, Lianwu; Wang, Tingjun; Sun, Yunlong
2015-05-05
The artificial fish swarm algorithm (AFSA) is one of the state-of-the-art swarm intelligent techniques, which is widely utilized for optimization purposes. Fiber optic gyroscope (FOG) error parameters such as scale factors, biases and misalignment errors are relatively unstable, especially with the environmental disturbances and the aging of fiber coils. These uncalibrated error parameters are the main reasons that the precision of FOG-based strapdown inertial navigation system (SINS) degraded. This research is mainly on the application of a novel artificial fish swarm algorithm (NAFSA) on FOG error coefficients recalibration/identification. First, the NAFSA avoided the demerits (e.g., lack of using artificial fishes' pervious experiences, lack of existing balance between exploration and exploitation, and high computational cost) of the standard AFSA during the optimization process. To solve these weak points, functional behaviors and the overall procedures of AFSA have been improved with some parameters eliminated and several supplementary parameters added. Second, a hybrid FOG error coefficients recalibration algorithm has been proposed based on NAFSA and Monte Carlo simulation (MCS) approaches. This combination leads to maximum utilization of the involved approaches for FOG error coefficients recalibration. After that, the NAFSA is verified with simulation and experiments and its priorities are compared with that of the conventional calibration method and optimal AFSA. Results demonstrate high efficiency of the NAFSA on FOG error coefficients recalibration.
The inertial attitude augmentation for ambiguity resolution in SF/SE-GNSS attitude determination.
Zhu, Jiancheng; Hu, Xiaoping; Zhang, Jingyu; Li, Tao; Wang, Jinling; Wu, Meiping
2014-06-26
The Unaided Single Frequency/Single Epoch Global Navigation Satellite System (SF/SE GNSS) model is the most challenging scenario for ambiguity resolution in the GNSS attitude determination application. To improve the performance of SF/SE-GNSS ambiguity resolution without excessive cost, the Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS-IMU) is a proper choice for the auxiliary sensor that carries out the inertial attitude augmentation. Firstly, based on the SF/SE-GNSS compass model, the Inertial Derived Baseline Vector (IDBV) is defined to connect the MEMS-IMU attitude measurement with the SF/SE-GNSS ambiguity search space, and the mechanism of inertial attitude augmentation is revealed from the perspective of geometry. Then, through the quantitative description of model strength by Ambiguity Dilution of Precision (ADOP), two ADOPs are specified for the unaided SF/SE-GNSS compass model and its inertial attitude augmentation counterparts, respectively, and a sufficient condition is proposed for augmenting the SF/SE-GNSS model strength with inertial attitude measurement. Finally, in the framework of an integer aperture estimator with fixed failure rate, the performance of SF/SE-GNSS ambiguity resolution with inertial attitude augmentation is analyzed when the model strength is varying from strong to weak. The simulation results show that, in the SF/SE-GNSS attitude determination application, MEMS-IMU can satisfy the requirements of ambiguity resolution with inertial attitude augmentation.
The Inertial Attitude Augmentation for Ambiguity Resolution in SF/SE-GNSS Attitude Determination
Zhu, Jiancheng; Hu, Xiaoping; Zhang, Jingyu; Li, Tao; Wang, Jinling; Wu, Meiping
2014-01-01
The Unaided Single Frequency/Single Epoch Global Navigation Satellite System (SF/SE GNSS) model is the most challenging scenario for ambiguity resolution in the GNSS attitude determination application. To improve the performance of SF/SE-GNSS ambiguity resolution without excessive cost, the Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS-IMU) is a proper choice for the auxiliary sensor that carries out the inertial attitude augmentation. Firstly, based on the SF/SE-GNSS compass model, the Inertial Derived Baseline Vector (IDBV) is defined to connect the MEMS-IMU attitude measurement with the SF/SE-GNSS ambiguity search space, and the mechanism of inertial attitude augmentation is revealed from the perspective of geometry. Then, through the quantitative description of model strength by Ambiguity Dilution of Precision (ADOP), two ADOPs are specified for the unaided SF/SE-GNSS compass model and its inertial attitude augmentation counterparts, respectively, and a sufficient condition is proposed for augmenting the SF/SE-GNSS model strength with inertial attitude measurement. Finally, in the framework of an integer aperture estimator with fixed failure rate, the performance of SF/SE-GNSS ambiguity resolution with inertial attitude augmentation is analyzed when the model strength is varying from strong to weak. The simulation results show that, in the SF/SE-GNSS attitude determination application, MEMS-IMU can satisfy the requirements of ambiguity resolution with inertial attitude augmentation. PMID:24971472
Error Modelling for Multi-Sensor Measurements in Infrastructure-Free Indoor Navigation
Ruotsalainen, Laura; Kirkko-Jaakkola, Martti; Rantanen, Jesperi; Mäkelä, Maija
2018-01-01
The long-term objective of our research is to develop a method for infrastructure-free simultaneous localization and mapping (SLAM) and context recognition for tactical situational awareness. Localization will be realized by propagating motion measurements obtained using a monocular camera, a foot-mounted Inertial Measurement Unit (IMU), sonar, and a barometer. Due to the size and weight requirements set by tactical applications, Micro-Electro-Mechanical (MEMS) sensors will be used. However, MEMS sensors suffer from biases and drift errors that may substantially decrease the position accuracy. Therefore, sophisticated error modelling and implementation of integration algorithms are key for providing a viable result. Algorithms used for multi-sensor fusion have traditionally been different versions of Kalman filters. However, Kalman filters are based on the assumptions that the state propagation and measurement models are linear with additive Gaussian noise. Neither of the assumptions is correct for tactical applications, especially for dismounted soldiers, or rescue personnel. Therefore, error modelling and implementation of advanced fusion algorithms are essential for providing a viable result. Our approach is to use particle filtering (PF), which is a sophisticated option for integrating measurements emerging from pedestrian motion having non-Gaussian error characteristics. This paper discusses the statistical modelling of the measurement errors from inertial sensors and vision based heading and translation measurements to include the correct error probability density functions (pdf) in the particle filter implementation. Then, model fitting is used to verify the pdfs of the measurement errors. Based on the deduced error models of the measurements, particle filtering method is developed to fuse all this information, where the weights of each particle are computed based on the specific models derived. The performance of the developed method is tested via two experiments, one at a university’s premises and another in realistic tactical conditions. The results show significant improvement on the horizontal localization when the measurement errors are carefully modelled and their inclusion into the particle filtering implementation correctly realized. PMID:29443918
NASA Technical Reports Server (NTRS)
Edwards, F. G.; Foster, J. D.
1973-01-01
Unpowered automatic approaches and landings with a CV990 aircraft were conducted to study navigation, guidance, and control problems associated with terminal area approach and landing for the space shuttle. The flight tests were designed to study from 11,300 m to touchdown the performance of a navigation and guidance concept which utilized blended radio/inertial navigation using VOR, DME, and ILS as the ground navigation aids. In excess of fifty automatic approaches and landings were conducted. Preliminary results indicate that this concept may provide sufficient accuracy to accomplish automatic landing of the shuttle orbiter without air-breathing engines on a conventional size runway.
Fusion of Imaging and Inertial Sensors for Navigation
2006-09-01
combat operations. The Global Positioning System (GPS) was fielded in the 1980’s and first used for precision navigation and targeting in combat...equations [37]. Consider the homogeneous nonlinear differential equation ẋ(t) = f [x(t),u(t), t] ; x(t0) = x0 (2.4) For a given input function , u0(t...differential equation is a time-varying probability density function . The Kalman filter derivation assumes Gaussian distributions for all random
Lane-Level Vehicle Positioning : Integrating Diverse Systems for Precision and Reliability
DOT National Transportation Integrated Search
2013-05-13
Integrated global positioning system/inertial navigation system (GPS/INS) technology, the backbone of vehicle positioning systems, cannot provide the precision and reliability needed for vehicle-based, lane-level positioning in all driving environmen...
Autonomous orbital navigation using Kepler's equation
NASA Technical Reports Server (NTRS)
Boltz, F. W.
1974-01-01
A simple method of determining the six elements of elliptic satellite orbits has been developed for use aboard manned and unmanned spacecraft orbiting the earth, moon, or any planet. The system requires the use of a horizon sensor or other device for determining the local vertical, a precision clock or timing device, and Apollo-type navigation equipment including an inertial measurement unit (IMU), a digital computer, and a coupling data unit. The three elements defining the in-plane motion are obtained from simultaneous measurements of central angle traversed around the planet and elapsed flight time using a linearization of Kepler's equation about a reference orbit. It is shown how Kalman filter theory may also be used to determine the in-plane orbital elements. The three elements defining the orbit orientation are obtained from position angles in celestial coordinates derived from the IMU with the spacecraft vertically oriented after alignment of the IMU to a known inertial coordinate frame.
NASA Technical Reports Server (NTRS)
Oliver, B. M.; Gower, J. F. R.
1977-01-01
A data acquisition system using a Litton LTN-51 inertial navigation unit (INU) was tested and used for aircraft track recovery and for location and tracking from the air of targets at sea. The characteristic position drift of the INU is compensated for by sighting landmarks of accurately known position at discrete time intervals using a visual sighting system in the transparent nose of the Beechcraft 18 aircraft used. For an aircraft altitude of about 300 m, theoretical and experimental tests indicate that calculated aircraft and/or target positions obtained from the interpolated INU drift curve will be accurate to within 10 m for landmarks spaced approximately every 15 minutes in time. For applications in coastal oceanography, such as surface current mapping by tracking artificial targets, the system allows a broad area to be covered without use of high altitude photography and its attendant needs for large targets and clear weather.
Detecting inertial effects with airborne matter-wave interferometry
Geiger, R.; Ménoret, V.; Stern, G.; Zahzam, N.; Cheinet, P.; Battelier, B.; Villing, A.; Moron, F.; Lours, M.; Bidel, Y.; Bresson, A.; Landragin, A.; Bouyer, P.
2011-01-01
Inertial sensors relying on atom interferometry offer a breakthrough advance in a variety of applications, such as inertial navigation, gravimetry or ground- and space-based tests of fundamental physics. These instruments require a quiet environment to reach their performance and using them outside the laboratory remains a challenge. Here we report the first operation of an airborne matter-wave accelerometer set up aboard a 0g plane and operating during the standard gravity (1g) and microgravity (0g) phases of the flight. At 1g, the sensor can detect inertial effects more than 300 times weaker than the typical acceleration fluctuations of the aircraft. We describe the improvement of the interferometer sensitivity in 0g, which reaches 2 x 10-4 ms-2 / √Hz with our current setup. We finally discuss the extension of our method to airborne and spaceborne tests of the Universality of free fall with matter waves. PMID:21934658
SLS Navigation Model-Based Design Approach
NASA Technical Reports Server (NTRS)
Oliver, T. Emerson; Anzalone, Evan; Geohagan, Kevin; Bernard, Bill; Park, Thomas
2018-01-01
The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and management of design requirements to the development of usable models, model requirements, and model verification and validation efforts. The models themselves are represented in C/C++ code and accompanying data files. Under the idealized process, potential ambiguity in specification is reduced because the model must be implementable versus a requirement which is not necessarily subject to this constraint. Further, the models are shown to emulate the hardware during validation. For models developed by the Navigation Team, a common interface/standalone environment was developed. The common environment allows for easy implementation in design and analysis tools. Mechanisms such as unit test cases ensure implementation as the developer intended. The model verification and validation process provides a very high level of component design insight. The origin and implementation of the SLS variant of Model-based Design is described from the perspective of the SLS Navigation Team. The format of the models and the requirements are described. The Model-based Design approach has many benefits but is not without potential complications. Key lessons learned associated with the implementation of the Model Based Design approach and process from infancy to verification and certification are discussed
Real-time full-motion color Flash lidar for target detection and identification
NASA Astrophysics Data System (ADS)
Nelson, Roy; Coppock, Eric; Craig, Rex; Craner, Jeremy; Nicks, Dennis; von Niederhausern, Kurt
2015-05-01
Greatly improved understanding of areas and objects of interest can be gained when real time, full-motion Flash LiDAR is fused with inertial navigation data and multi-spectral context imagery. On its own, full-motion Flash LiDAR provides the opportunity to exploit the z dimension for improved intelligence vs. 2-D full-motion video (FMV). The intelligence value of this data is enhanced when it is combined with inertial navigation data to produce an extended, georegistered data set suitable for a variety of analysis. Further, when fused with multispectral context imagery the typical point cloud now becomes a rich 3-D scene which is intuitively obvious to the user and allows rapid cognitive analysis with little or no training. Ball Aerospace has developed and demonstrated a real-time, full-motion LIDAR system that fuses context imagery (VIS to MWIR demonstrated) and inertial navigation data in real time, and can stream these information-rich geolocated/fused 3-D scenes from an airborne platform. In addition, since the higher-resolution context camera is boresighted and frame synchronized to the LiDAR camera and the LiDAR camera is an array sensor, techniques have been developed to rapidly interpolate the LIDAR pixel values creating a point cloud that has the same resolution as the context camera, effectively creating a high definition (HD) LiDAR image. This paper presents a design overview of the Ball TotalSight™ LIDAR system along with typical results over urban and rural areas collected from both rotary and fixed-wing aircraft. We conclude with a discussion of future work.
State estimation for autonomous flight in cluttered environments
NASA Astrophysics Data System (ADS)
Langelaan, Jacob Willem
Safe, autonomous operation in complex, cluttered environments is a critical challenge facing autonomous mobile systems. The research described in this dissertation was motivated by a particularly difficult example of autonomous mobility: flight of a small Unmanned Aerial Vehicle (UAV) through a forest. In cluttered environments (such as forests or natural and urban canyons) signals from navigation beacons such as GPS may frequently be occluded. Direct measurements of vehicle position are therefore unavailable, and information required for flight control, obstacle avoidance, and navigation must be obtained using only on-board sensors. However, payload limitations of small UAVs restrict both the mass and physical dimensions of sensors that can be carried. This dissertation describes the development and proof-of-concept demonstration of a navigation system that uses only a low-cost inertial measurement unit and a monocular camera. Micro electromechanical inertial measurements units are well suited to small UAV applications and provide measurements of acceleration and angular rate. However, they do not provide information about nearby obstacles (needed for collision avoidance) and their noise and bias characteristics lead to unbounded growth in computed position. A monocular camera can provide bearings to nearby obstacles and landmarks. These bearings can be used both to enable obstacle avoidance and to aid navigation. Presented here is a solution to the problem of estimating vehicle state (position, orientation and velocity) as well as positions of obstacles in the environment using only inertial measurements and bearings to obstacles. This is a highly nonlinear estimation problem, and standard estimation techniques such as the Extended Kalman Filter are prone to divergence in this application. In this dissertation a Sigma Point Kalman Filter is implemented, resulting in an estimator which is able to cope with the significant nonlinearities in the system equations and uncertainty in state estimates while remaining tractable for real-time operation. In addition, the issues of data association and landmark initialization are addressed. Estimator performance is examined through Monte Carlo simulations in both two and three dimensions for scenarios involving UAV flight in cluttered environments. Hardware tests and simulations demonstrate navigation through an obstacle-strewn environment by a small Unmanned Ground Vehicle.
Dai, Erpeng; Zhang, Zhe; Ma, Xiaodong; Dong, Zijing; Li, Xuesong; Xiong, Yuhui; Yuan, Chun; Guo, Hua
2018-03-23
To study the effects of 2D navigator distortion and noise level on interleaved EPI (iEPI) DWI reconstruction, using either the image- or k-space-based method. The 2D navigator acquisition was adjusted by reducing its echo spacing in the readout direction and undersampling in the phase encoding direction. A POCS-based reconstruction using image-space sampling function (IRIS) algorithm (POCSIRIS) was developed to reduce the impact of navigator distortion. POCSIRIS was then compared with the original IRIS algorithm and a SPIRiT-based k-space algorithm, under different navigator distortion and noise levels. Reducing the navigator distortion can improve the reconstruction of iEPI DWI. The proposed POCSIRIS and SPIRiT-based algorithms are more tolerable to different navigator distortion levels, compared to the original IRIS algorithm. SPIRiT may be hindered by low SNR of the navigator. Multi-shot iEPI DWI reconstruction can be improved by reducing the 2D navigator distortion. Different reconstruction methods show variable sensitivity to navigator distortion or noise levels. Furthermore, the findings can be valuable in applications such as simultaneous multi-slice accelerated iEPI DWI and multi-slab diffusion imaging. © 2018 International Society for Magnetic Resonance in Medicine.
A Personal Navigation System Based on Inertial and Magnetic Field Measurements
2010-09-01
MATLAB IMPLEMENTATION.................................................................74 G. A MODEL FOR PENDULUM MOTION SENSOR DATA...76 1. Pendulum Model for MATLAB Simulation....................................76 2. Sensor Data Generated with the Pendulum Model... PENDULUM ..................................................................................................88 I. FILTER PERFORMANCE WITH REAL PENDULUM DATA
On-Board Perception System For Planetary Aerobot Balloon Navigation
NASA Technical Reports Server (NTRS)
Balaram, J.; Scheid, Robert E.; T. Salomon, Phil
1996-01-01
NASA's Jet Propulsion Laboratory is implementing the Planetary Aerobot Testbed to develop the technology needed to operate a robotic balloon aero-vehicle (Aerobot). This earth-based system would be the precursor for aerobots designed to explore Venus, Mars, Titan and other gaseous planetary bodies. The on-board perception system allows the aerobot to localize itself and navigate on a planet using information derived from a variety of celestial, inertial, ground-imaging, ranging, and radiometric sensors.
AGARD (Advisory Group for Aerospace Research & Development) Index of Publications, 1986-1988
1989-08-01
measurements are used in forming the navigation and the baro-inertial loop as well The system communicates with equations to solve for the user position...processing techniques in the tracking ROBERT P. DENARO and G JEFFREY GEIER In AGARD, The loops . and later in the navigation processing ot the Kalman...avionics investigations to predict the dynamic structural response of flexible assessment. The current status of real time, pilot-in-the- loop flight
Precision Positioning and Inertial Guidance Sensors. Technology and Operational Aspects
1981-03-01
Ueberlingen, GE EVALUATION D’UN SYSTEME EUROPEEN DE NAVIGATION HYBRIDE A - - GYROLASER POUR HELICOPTERE: "SEXTAN" by D Regnault, Centre d’Essais en Vol de...NAVIGATION SYSTEM AND STANDARD STATE ELEMENT DEVIATIONMEASUREMENT SOURCES( Dead-reckoning with position fxP fy 5000 En ]TAS, heading and wind scale...Reproduction Ltd ilarford House. 7-9 Charlotte St. London. WIP JIHD [i Ii THEME A new class of precision positioning systems , including GPS (Global
Piao, Jin-Chun; Kim, Shin-Dug
2017-11-07
Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual-inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual-inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual-inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual-inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method.
Proceedings of the 20th International Symposium on Space Flight Dynamics
NASA Technical Reports Server (NTRS)
Woodard, Mark (Editor); Stengle, Tom (Editor)
2007-01-01
Topics include: Measuring Image Navigation and Registration Performance at the 3-Sigma Level Using Platinum Quality Landmarks; Flight Dynamics Performances of the MetOp A Satellite during the First Months of Operations; Visual Navigation - SARE Mission; Determining a Method of Enabling and Disabling the Integral Torque in the SDO Science and Inertial Mode Controllers; Guaranteeing Pointing Performance of the SDO Sun-Pointing Controllers in Light of Nonlinear Effects; SDO Delta H Mode Design and Analysis; Observing Mode Attitude Controller for the Lunar Reconnaissance Orbiter; Broken-Plane Maneuver Applications for Earth to Mars Trajectories; ExoMars Mission Analysis and Design - Launch, Cruise and Arrival Analyses; Mars Reconnaissance Orbiter Aerobraking Daily Operations and Collision Avoidance; Mars Reconnaissance Orbiter Interplanetary Cruise Navigation; Motion Parameters Determination of the SC and Phobos in the Project Phobos-Grunt; GRAS NRT Precise Orbit Determination: Operational Experience; Orbit Determination of LEO Satellites for a Single Pass through a Radar: Comparison of Methods; Orbit Determination System for Low Earth Orbit Satellites; Precise Orbit Determination for ALOS; Anti-Collision Function Design and Performances of the CNES Formation Flying Experiment on the PRISMA Mission; CNES Approaching Guidance Experiment within FFIORD; Maneuver Recovery Analysis for the Magnetospheric Multiscale Mission; SIMBOL-X: A Formation Flying Mission on HEO for Exploring the Universe; Spaceborne Autonomous and Ground Based Relative Orbit Control for the TerraSAR-X/TanDEM-X Formation; First In-Orbit Experience of TerraSAR-X Flight Dynamics Operations; Automated Target Planning for FUSE Using the SOVA Algorithm; Space Technology 5 Post-Launch Ground Attitude Estimation Experience; Standardizing Navigation Data: A Status Update; and A Study into the Method of Precise Orbit Determination of a HEO Orbiter by GPS and Accelerometer.
Improving geolocation and spatial accuracies with the modular integrated avionics group (MIAG)
NASA Astrophysics Data System (ADS)
Johnson, Einar; Souter, Keith
1996-05-01
The modular integrated avionics group (MIAG) is a single unit approach to combining position, inertial and baro-altitude/air data sensors to provide optimized navigation, guidance and control performance. Lear Astronics Corporation is currently working within the navigation community to upgrade existing MIAG performance with precise GPS positioning mechanization tightly integrated with inertial, baro and other sensors. Among the immediate benefits are the following: (1) accurate target location in dynamic conditions; (2) autonomous launch and recovery using airborne avionics only; (3) precise flight path guidance; and (4) improved aircraft and payload stability information. This paper will focus on the impact of using the MIAG with its multimode navigation accuracies on the UAV targeting mission. Gimbaled electro-optical sensors mounted on a UAV can be used to determine ground coordinates of a target at the center of the field of view by a series of vector rotation and scaling computations. The accuracy of the computed target coordinates is dependent on knowing the UAV position and the UAV-to-target offset computation. Astronics performed a series of simulations to evaluate the effects that the improved angular and position data available from the MIAG have on target coordinate accuracy.
Beacons for supporting lunar landing navigation
NASA Astrophysics Data System (ADS)
Theil, Stephan; Bora, Leonardo
2017-03-01
Current and future planetary exploration missions involve a landing on the target celestial body. Almost all of these landing missions are currently relying on a combination of inertial and optical sensor measurements to determine the current flight state with respect to the target body and the desired landing site. As soon as an infrastructure at the landing site exists, the requirements as well as conditions change for vehicles landing close to this existing infrastructure. This paper investigates the options for ground-based infrastructure supporting the onboard navigation system and analyzes the impact on the achievable navigation accuracy. For that purpose, the paper starts with an existing navigation architecture based on optical navigation and extends it with measurements to support navigation with ground infrastructure. A scenario of lunar landing is simulated and the provided functions of the ground infrastructure as well as the location with respect to the landing site are evaluated. The results are analyzed and discussed.
Analysis of a novel device-level SINS/ACFSS deeply integrated navigation method
NASA Astrophysics Data System (ADS)
Zhang, Hao; Qin, Shiqiao; Wang, Xingshu; Jiang, Guangwen; Tan, Wenfeng; Wu, Wei
2017-02-01
The combination of the strap-down inertial navigation system(SINS) and the celestial navigation system(CNS) is one of the popular measures to constitute the integrated navigation system. A star sensor(SS) is used as a precise attitude determination device in CNS. To solve the problem that the star image obtained by SS is motion-blurred under dynamic conditions, the attitude-correlated frames(ACF) approach is presented and the star sensor which works based on ACF approach is named ACFSS. Depending on the ACF approach, a novel device-level SINS/ACFSS deeply integrated navigation method is proposed in this paper. Feedback to the ACF process from the error of the gyro is one of the typical characters of the SINS/CNS deeply integrated navigation method. Herein, simulation results have verified its validity and efficiency in improving the accuracy of gyro and it can be proved that this method is feasible.
Redundancy management of multiple KT-70 inertial measurement units applicable to the space shuttle
NASA Technical Reports Server (NTRS)
Cook, L. J.
1975-01-01
Results of an investigation of velocity failure detection and isolation for 3 inertial measuring units (IMU) and 2 inertial measuring units (IMU) configurations are presented. The failure detection and isolation algorithm performance was highly successful and most types of velocity errors were detected and isolated. The failure detection and isolation algorithm also included attitude FDI but was not evaluated because of the lack of time and low resolution in the gimbal angle synchro outputs. The shuttle KT-70 IMUs will have dual-speed resolvers and high resolution gimbal angle readouts. It was demonstrated by these tests that a single computer utilizing a serial data bus can successfully control a redundant 3-IMU system and perform FDI.
Prognostic Modeling and Experimental Techniques for Electrolytic Capacitor Health Monitoring
2011-09-01
result in errors in the Inertial Navigation ( INAV ) computations of position and heading, causing the aircraft to fly off course [2, 3]. Chetan... Science Instruments, 2010. 21) IEC 60384-4-1 Fixed capacitors for use in electronic equipment
NASA Technical Reports Server (NTRS)
Garcia-Gorriz, E.; Candela, J.; Font, J.
1998-01-01
The Acoustic Doppler Current Profiler (ADCP) combined with accurate navigation provides absolute current velocities which include information from all the frequencies which have a dynamical presence in the ocean.
A Robust Self-Alignment Method for Ship's Strapdown INS Under Mooring Conditions
Sun, Feng; Lan, Haiyu; Yu, Chunyang; El-Sheimy, Naser; Zhou, Guangtao; Cao, Tong; Liu, Hang
2013-01-01
Strapdown inertial navigation systems (INS) need an alignment process to determine the initial attitude matrix between the body frame and the navigation frame. The conventional alignment process is to compute the initial attitude matrix using the gravity and Earth rotational rate measurements. However, under mooring conditions, the inertial measurement unit (IMU) employed in a ship's strapdown INS often suffers from both the intrinsic sensor noise components and the external disturbance components caused by the motions of the sea waves and wind waves, so a rapid and precise alignment of a ship's strapdown INS without any auxiliary information is hard to achieve. A robust solution is given in this paper to solve this problem. The inertial frame based alignment method is utilized to adapt the mooring condition, most of the periodical low-frequency external disturbance components could be removed by the mathematical integration and averaging characteristic of this method. A novel prefilter named hidden Markov model based Kalman filter (HMM-KF) is proposed to remove the relatively high-frequency error components. Different from the digital filters, the HMM-KF barely cause time-delay problem. The turntable, mooring and sea experiments favorably validate the rapidness and accuracy of the proposed self-alignment method and the good de-noising performance of HMM-KF. PMID:23799492
Vibration Noise Modeling for Measurement While Drilling System Based on FOGs
Zhang, Chunxi; Wang, Lu; Gao, Shuang; Lin, Tie; Li, Xianmu
2017-01-01
Aiming to improve survey accuracy of Measurement While Drilling (MWD) based on Fiber Optic Gyroscopes (FOGs) in the long period, the external aiding sources are fused into the inertial navigation by the Kalman filter (KF) method. The KF method needs to model the inertial sensors’ noise as the system noise model. The system noise is modeled as white Gaussian noise conventionally. However, because of the vibration while drilling, the noise in gyros isn’t white Gaussian noise any more. Moreover, an incorrect noise model will degrade the accuracy of KF. This paper developed a new approach for noise modeling on the basis of dynamic Allan variance (DAVAR). In contrast to conventional white noise models, the new noise model contains both the white noise and the color noise. With this new noise model, the KF for the MWD was designed. Finally, two vibration experiments have been performed. Experimental results showed that the proposed vibration noise modeling approach significantly improved the estimated accuracies of the inertial sensor drifts. Compared the navigation results based on different noise model, with the DAVAR noise model, the position error and the toolface angle error are reduced more than 90%. The velocity error is reduced more than 65%. The azimuth error is reduced more than 50%. PMID:29039815
Vibration Noise Modeling for Measurement While Drilling System Based on FOGs.
Zhang, Chunxi; Wang, Lu; Gao, Shuang; Lin, Tie; Li, Xianmu
2017-10-17
Aiming to improve survey accuracy of Measurement While Drilling (MWD) based on Fiber Optic Gyroscopes (FOGs) in the long period, the external aiding sources are fused into the inertial navigation by the Kalman filter (KF) method. The KF method needs to model the inertial sensors' noise as the system noise model. The system noise is modeled as white Gaussian noise conventionally. However, because of the vibration while drilling, the noise in gyros isn't white Gaussian noise any more. Moreover, an incorrect noise model will degrade the accuracy of KF. This paper developed a new approach for noise modeling on the basis of dynamic Allan variance (DAVAR). In contrast to conventional white noise models, the new noise model contains both the white noise and the color noise. With this new noise model, the KF for the MWD was designed. Finally, two vibration experiments have been performed. Experimental results showed that the proposed vibration noise modeling approach significantly improved the estimated accuracies of the inertial sensor drifts. Compared the navigation results based on different noise model, with the DAVAR noise model, the position error and the toolface angle error are reduced more than 90%. The velocity error is reduced more than 65%. The azimuth error is reduced more than 50%.
Spacecraft Alignment Determination and Control for Dual Spacecraft Precision Formation Flying
NASA Technical Reports Server (NTRS)
Calhoun, Philip; Novo-Gradac, Anne-Marie; Shah, Neerav
2017-01-01
Many proposed formation flying missions seek to advance the state of the art in spacecraft science imaging by utilizing precision dual spacecraft formation flying to enable a virtual space telescope. Using precision dual spacecraft alignment, very long focal lengths can be achieved by locating the optics on one spacecraft and the detector on the other. Proposed science missions include astrophysics concepts with spacecraft separations from 1000 km to 25,000 km, such as the Milli-Arc-Second Structure Imager (MASSIM) and the New Worlds Observer, and Heliophysics concepts for solar coronagraphs and X-ray imaging with smaller separations (50m-500m). All of these proposed missions require advances in guidance, navigation, and control (GNC) for precision formation flying. In particular, very precise astrometric alignment control and estimation is required for precise inertial pointing of the virtual space telescope to enable science imaging orders of magnitude better than can be achieved with conventional single spacecraft instruments. This work develops design architectures, algorithms, and performance analysis of proposed GNC systems for precision dual spacecraft astrometric alignment. These systems employ a variety of GNC sensors and actuators, including laser-based alignment and ranging systems, optical imaging sensors (e.g. guide star telescope), inertial measurement units (IMU), as well as microthruster and precision stabilized platforms. A comprehensive GNC performance analysis is given for Heliophysics dual spacecraft PFF imaging mission concept.
Spacecraft Alignment Determination and Control for Dual Spacecraft Precision Formation Flying
NASA Technical Reports Server (NTRS)
Calhoun, Philip C.; Novo-Gradac, Anne-Marie; Shah, Neerav
2017-01-01
Many proposed formation flying missions seek to advance the state of the art in spacecraft science imaging by utilizing precision dual spacecraft formation flying to enable a virtual space telescope. Using precision dual spacecraft alignment, very long focal lengths can be achieved by locating the optics on one spacecraft and the detector on the other. Proposed science missions include astrophysics concepts with spacecraft separations from 1000 km to 25,000 km, such as the Milli-Arc-Second Structure Imager (MASSIM) and the New Worlds Observer, and Heliophysics concepts for solar coronagraphs and X-ray imaging with smaller separations (50m 500m). All of these proposed missions require advances in guidance, navigation, and control (GNC) for precision formation flying. In particular, very precise astrometric alignment control and estimation is required for precise inertial pointing of the virtual space telescope to enable science imaging orders of magnitude better than can be achieved with conventional single spacecraft instruments. This work develops design architectures, algorithms, and performance analysis of proposed GNC systems for precision dual spacecraft astrometric alignment. These systems employ a variety of GNC sensors and actuators, including laser-based alignment and ranging systems, optical imaging sensors (e.g. guide star telescope), inertial measurement units (IMU), as well as micro-thruster and precision stabilized platforms. A comprehensive GNC performance analysis is given for Heliophysics dual spacecraft PFF imaging mission concept.
Estimating Position of Mobile Robots From Omnidirectional Vision Using an Adaptive Algorithm.
Li, Luyang; Liu, Yun-Hui; Wang, Kai; Fang, Mu
2015-08-01
This paper presents a novel and simple adaptive algorithm for estimating the position of a mobile robot with high accuracy in an unknown and unstructured environment by fusing images of an omnidirectional vision system with measurements of odometry and inertial sensors. Based on a new derivation where the omnidirectional projection can be linearly parameterized by the positions of the robot and natural feature points, we propose a novel adaptive algorithm, which is similar to the Slotine-Li algorithm in model-based adaptive control, to estimate the robot's position by using the tracked feature points in image sequence, the robot's velocity, and orientation angles measured by odometry and inertial sensors. It is proved that the adaptive algorithm leads to global exponential convergence of the position estimation errors to zero. Simulations and real-world experiments are performed to demonstrate the performance of the proposed algorithm.
New approach for processing data provided by an INS/GPS system onboard a vehicle
NASA Astrophysics Data System (ADS)
Dumitrascu, Ana; Serbanescu, Ionut; Tamas, Razvan D.; Danisor, Alin; Caruntu, George; Ticu, Ionela
2016-12-01
Due to the technology development, navigation systems are widely used in ground vehicle applications such as position prediction, safety of life, etc. It is known that a hybrid navigation system consisting of a GPS and inertial navigation system (INS) can provide a more accurate position prediction. By applying a Method of Moments (MoM) approach on the acquired data with INS/GPS we can extract both the coordinate and important information concerning safety of life. This kind of system will be cost effective and can also be used as a black box on boats, cars, submersible ships and even on small aircrafts.
Deng, Zhi-An; Wang, Guofeng; Hu, Ying; Cui, Yang
2016-01-01
This paper proposes a novel heading estimation approach for indoor pedestrian navigation using the built-in inertial sensors on a smartphone. Unlike previous approaches constraining the carrying position of a smartphone on the user’s body, our approach gives the user a larger freedom by implementing automatic recognition of the device carrying position and subsequent selection of an optimal strategy for heading estimation. We firstly predetermine the motion state by a decision tree using an accelerometer and a barometer. Then, to enable accurate and computational lightweight carrying position recognition, we combine a position classifier with a novel position transition detection algorithm, which may also be used to avoid the confusion between position transition and user turn during pedestrian walking. For a device placed in the trouser pockets or held in a swinging hand, the heading estimation is achieved by deploying a principal component analysis (PCA)-based approach. For a device held in the hand or against the ear during a phone call, user heading is directly estimated by adding the yaw angle of the device to the related heading offset. Experimental results show that our approach can automatically detect carrying positions with high accuracy, and outperforms previous heading estimation approaches in terms of accuracy and applicability. PMID:27187391
Hellmers, Hendrik; Kasmi, Zakaria; Norrdine, Abdelmoumen; Eichhorn, Andreas
2018-01-04
In recent years, a variety of real-time applications benefit from services provided by localization systems due to the advent of sensing and communication technologies. Since the Global Navigation Satellite System (GNSS) enables localization only outside buildings, applications for indoor positioning and navigation use alternative technologies. Ultra Wide Band Signals (UWB), Wireless Local Area Network (WLAN), ultrasonic or infrared are common examples. However, these technologies suffer from fading and multipath effects caused by objects and materials in the building. In contrast, magnetic fields are able to pass through obstacles without significant propagation errors, i.e. in Non-Line of Sight Scenarios (NLoS). The aim of this work is to propose a novel indoor positioning system based on artificially generated magnetic fields in combination with Inertial Measurement Units (IMUs). In order to reach a better coverage, multiple coils are used as reference points. A basic algorithm for three-dimensional applications is demonstrated as well as evaluated in this article. The established system is then realized by a sensor fusion principle as well as a kinematic motion model on the basis of a Kalman filter. Furthermore, a pressure sensor is used in combination with an adaptive filtering method to reliably estimate the platform's altitude.
An Evaluation of the Measurement Requirements for an In-Situ Wake Vortex Detection System
NASA Technical Reports Server (NTRS)
Fuhrmann, Henri D.; Stewart, Eric C.
1996-01-01
Results of a numerical simulation are presented to determine the feasibility of estimating the location and strength of a wake vortex from imperfect in-situ measurements. These estimates could be used to provide information to a pilot on how to avoid a hazardous wake vortex encounter. An iterative algorithm based on the method of secants was used to solve the four simultaneous equations describing the two-dimensional flow field around a pair of parallel counter-rotating vortices of equal and constant strength. The flow field information used by the algorithm could be derived from measurements from flow angle sensors mounted on the wing-tip of the detecting aircraft and an inertial navigation system. The study determined the propagated errors in the estimated location and strength of the vortex which resulted from random errors added to theoretically perfect measurements. The results are summarized in a series of charts and a table which make it possible to estimate these propagated errors for many practical situations. The situations include several generator-detector airplane combinations, different distances between the vortex and the detector airplane, as well as different levels of total measurement error.
Navigable points estimation for mobile robots using binary image skeletonization
NASA Astrophysics Data System (ADS)
Martinez S., Fernando; Jacinto G., Edwar; Montiel A., Holman
2017-02-01
This paper describes the use of image skeletonization for the estimation of all the navigable points, inside a scene of mobile robots navigation. Those points are used for computing a valid navigation path, using standard methods. The main idea is to find the middle and the extreme points of the obstacles in the scene, taking into account the robot size, and create a map of navigable points, in order to reduce the amount of information for the planning algorithm. Those points are located by means of the skeletonization of a binary image of the obstacles and the scene background, along with some other digital image processing algorithms. The proposed algorithm automatically gives a variable number of navigable points per obstacle, depending on the complexity of its shape. As well as, the way how the algorithm can change some of their parameters in order to change the final number of the resultant key points is shown. The results shown here were obtained applying different kinds of digital image processing algorithms on static scenes.
Theoretical Limits of Lunar Vision Aided Navigation with Inertial Navigation System
2015-03-26
camera model. Light reflected or projected from objects in the scene of the outside world is taken in by the aperture (or opening) shaped as a double...model’s analog aspects with an analog-to-digital interface converting raw images of the outside world scene into digital information a computer can use to...Figure 2.7. Digital Image Coordinate System. Used with permission [30]. Angular Field of View. The angular field of view is the angle of the world scene
A new method for determining which stars are near a star sensor field-of-view
NASA Technical Reports Server (NTRS)
Yates, Russell E., Jr.; Vedder, John D.
1991-01-01
A new method is described for determining which stars in a navigation star catalog are near a star sensor field of view (FOV). This method assumes that an estimate of spacecraft inertial attitude is known. Vector component ranges for the star sensor FOV are computed, so that stars whose vector components lie within these ranges are near the star sensor FOV. This method requires no presorting of the navigation star catalog, and is more efficient than tradition methods.
1981-03-01
Instrarf.ent Landing System (IT,S) f. Microwave Landing System (MLS) . Marker Beacon 2. OPEiRA’TiONAL :. Gen ~eral • b. Navigation (1) inertial (2...system with integrated navigation course guidance. 5. ENVIRONMENT. The pressurization, air conditioning, ox,- gen and liqhting must be suitable for...8217) ,nStruments, ~s s t-r se drsoal, cuae~ area covc. ace and I* i0n to + 1/4 inch. Thie com.uica i on systems must be fanc - i n I lv s imulated ( i. e
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.
How Funding Instability Affects Army Programs
2007-01-01
rocket motor, aerodynamic vane controls, and inertial guidance to navigate to an intercept point. Shortly before arrival at the intercept point, the...responsiveness. Significant features of the C-17 include: super-critical wing design and winglets to reduce drag and increase fuel efficiency and
How Funding Instability Affects Army Programs
2007-01-01
missile uses a solid-pro- pellant rocket motor, aerodynamic vane controls, and inertial guidance to navigate to an intercept point. Shortly before arrival...that significantly improves airlift responsiveness. Significant features of the C-17 include: super-critical wing design and winglets to reduce drag
Performance analysis of device-level SINS/ACFSS deeply integrated navigation method
NASA Astrophysics Data System (ADS)
Zhang, Hao; Qin, Shiqiao; Wang, Xingshu; Jiang, Guangwen; Tan, Wenfeng
2016-10-01
The Strap-Down Inertial Navigation System (SINS) is a widely used navigation system. The combination of SINS and the Celestial Navigation System (CNS) is one of the popular measures to constitute the integrated navigation system. A Star Sensor (SS) is used as a precise attitude determination device in CNS. To solve the problem that the star image obtained by SS under dynamic conditions is motion-blurred, the Attitude Correlated Frames (ACF) is presented and the star sensor which works based on ACF approach is named ACFSS. Depending on the ACF approach, a novel device-level SINS/ACFSS deeply integrated navigation method is proposed in this paper. Feedback to the ACF process from the error of the gyro is one of the typical characters of the SINS/CNS deeply integrated navigation method. Herein, simulation results have verified its validity and efficiency in improving the accuracy of gyro and it can be proved that this method is feasible in theory.
Inertial modes in a rotating triaxial ellipsoid
Vantieghem, S.
2014-01-01
In this work, we present an algorithm that enables computation of inertial modes and their corresponding frequencies in a rotating triaxial ellipsoid. The method consists of projecting the inertial mode equation onto finite-dimensional bases of polynomial vector fields. It is shown that this leads to a well-posed eigenvalue problem, and hence, that eigenmodes are of polynomial form. Furthermore, these results shed new light onto the question whether the eigenmodes form a complete basis, i.e. whether any arbitrary velocity field can be expanded in a sum of inertial modes. Finally, we prove that two intriguing integral properties of inertial modes in rotating spheres and spheroids also extend to triaxial ellipsoids. PMID:25104908
Ground truth and benchmarks for performance evaluation
NASA Astrophysics Data System (ADS)
Takeuchi, Ayako; Shneier, Michael; Hong, Tsai Hong; Chang, Tommy; Scrapper, Christopher; Cheok, Geraldine S.
2003-09-01
Progress in algorithm development and transfer of results to practical applications such as military robotics requires the setup of standard tasks, of standard qualitative and quantitative measurements for performance evaluation and validation. Although the evaluation and validation of algorithms have been discussed for over a decade, the research community still faces a lack of well-defined and standardized methodology. The range of fundamental problems include a lack of quantifiable measures of performance, a lack of data from state-of-the-art sensors in calibrated real-world environments, and a lack of facilities for conducting realistic experiments. In this research, we propose three methods for creating ground truth databases and benchmarks using multiple sensors. The databases and benchmarks will provide researchers with high quality data from suites of sensors operating in complex environments representing real problems of great relevance to the development of autonomous driving systems. At NIST, we have prototyped a High Mobility Multi-purpose Wheeled Vehicle (HMMWV) system with a suite of sensors including a Riegl ladar, GDRS ladar, stereo CCD, several color cameras, Global Position System (GPS), Inertial Navigation System (INS), pan/tilt encoders, and odometry . All sensors are calibrated with respect to each other in space and time. This allows a database of features and terrain elevation to be built. Ground truth for each sensor can then be extracted from the database. The main goal of this research is to provide ground truth databases for researchers and engineers to evaluate algorithms for effectiveness, efficiency, reliability, and robustness, thus advancing the development of algorithms.
Applying FastSLAM to Articulated Rovers
NASA Astrophysics Data System (ADS)
Hewitt, Robert Alexander
This thesis presents the navigation algorithms designed for use on Kapvik, a 30 kg planetary micro-rover built for the Canadian Space Agency; the simulations used to test the algorithm; and novel techniques for terrain classification using Kapvik's LIDAR (Light Detection And Ranging) sensor. Kapvik implements a six-wheeled, skid-steered, rocker-bogie mobility system. This warrants a more complicated kinematic model for navigation than a typical 4-wheel differential drive system. The design of a 3D navigation algorithm is presented that includes nonlinear Kalman filtering and Simultaneous Localization and Mapping (SLAM). A neural network for terrain classification is used to improve navigation performance. Simulation is used to train the neural network and validate the navigation algorithms. Real world tests of the terrain classification algorithm validate the use of simulation for training and the improvement to SLAM through the reduction of extraneous LIDAR measurements in each scan.
New vision system and navigation algorithm for an autonomous ground vehicle
NASA Astrophysics Data System (ADS)
Tann, Hokchhay; Shakya, Bicky; Merchen, Alex C.; Williams, Benjamin C.; Khanal, Abhishek; Zhao, Jiajia; Ahlgren, David J.
2013-12-01
Improvements were made to the intelligence algorithms of an autonomously operating ground vehicle, Q, which competed in the 2013 Intelligent Ground Vehicle Competition (IGVC). The IGVC required the vehicle to first navigate between two white lines on a grassy obstacle course, then pass through eight GPS waypoints, and pass through a final obstacle field. Modifications to Q included a new vision system with a more effective image processing algorithm for white line extraction. The path-planning algorithm adopted the vision system, creating smoother, more reliable navigation. With these improvements, Q successfully completed the basic autonomous navigation challenge, finishing tenth out of over 50 teams.
DOT National Transportation Integrated Search
2013-06-03
"Integrated Global Positioning System and Inertial Navigation Unit (GPS/INU) Simulator for Enhanced Traffic Safety," is a project awarded to Ohio State University to integrate different simulation models to accurately study the relationship between v...
Development of the German A-4 guidance and control system, 1939 - 1945: A memoir
NASA Technical Reports Server (NTRS)
Steinhoff, E. A.
1977-01-01
The development by 1943 of a fully inertial navigational system for the German A-4 (V-2) missile is detailed. This flight control system used a triple-axis stabilized platform with two longitudinal accelerometers and one lateral accelerometer.
Application of Mobile Laser Scanning for Lean and Rapid Highway Maintenance and Construction
DOT National Transportation Integrated Search
2015-08-28
Mobile Terrestrial Laser Scanning (MTLS) is an emerging technology that combines the use of a laser scanner(s), the Global Navigation Satellite System (GNSS), and an Inertial Measurement Unit (IMU) on a vehicle to collect geo-spatial data. The overal...
NASA Technical Reports Server (NTRS)
Eberlein, A. J.; Lahm, T. G.
1976-01-01
The degree to which flight-critical failures in a strapdown laser gyro tetrad sensor assembly can be isolated in short-haul aircraft after a failure occurrence has been detected by the skewed sensor failure-detection voting logic is investigated along with the degree to which a failure in the tetrad computer can be detected and isolated at the computer level, assuming a dual-redundant computer configuration. The tetrad system was mechanized with two two-axis inertial navigation channels (INCs), each containing two gyro/accelerometer axes, computer, control circuitry, and input/output circuitry. Gyro/accelerometer data is crossfed between the two INCs to enable each computer to independently perform the navigation task. Computer calculations are synchronized between the computers so that calculated quantities are identical and may be compared. Fail-safe performance (identification of the first failure) is accomplished with a probability approaching 100 percent of the time, while fail-operational performance (identification and isolation of the first failure) is achieved 93 to 96 percent of the time.
NASA Astrophysics Data System (ADS)
Ou, Yangwei; Zhang, Hongbo; Li, Bin
2018-04-01
The purpose of this paper is to show that absolute orbit determination can be achieved based on spacecraft formation. The relative position vectors expressed in the inertial frame are used as measurements. In this scheme, the optical camera is applied to measure the relative line-of-sight (LOS) angles, i.e., the azimuth and elevation. The LIDAR (Light radio Detecting And Ranging) or radar is used to measure the range and we assume that high-accuracy inertial attitude is available. When more deputies are included in the formation, the formation configuration is optimized from the perspective of the Fisher information theory. Considering the limitation on the field of view (FOV) of cameras, the visibility of spacecraft and the installation of cameras are investigated. In simulations, an extended Kalman filter (EKF) is used to estimate the position and velocity. The results show that the navigation accuracy can be enhanced by using more deputies and the installation of cameras significantly affects the navigation performance.
Flight results from a study of aided inertial navigation applied to landing operations
NASA Technical Reports Server (NTRS)
Mcgee, L. A.; Smith, G. L.; Hegarty, D. M.; Carson, T. M.; Merrick, R. B.; Schmidt, S. F.; Conrad, B.
1973-01-01
An evaluation is presented of the approach and landing performance of a Kalman filter aided inertial navigation system using flight data obtained from a series of approaches and landings of the CV-340 aircraft at an instrumented test area. A description of the flight test is given, in which data recorded included: (1) accelerometer signals from the platform of an INS; (2) three ranges from the Ames-Cubic Precision Ranging System; and (3) radar and barometric altimeter signals. The method of system evaluation employed was postflight processing of the recorded data using a Kalman filter which was designed for use on the XDS920 computer onboard the CV-340 aircraft. Results shown include comparisons between the trajectories as estimated by the Kalman filter aided system and as determined from cinetheodolite data. Data start initialization of the Kalman filter, operation at a practical data rate, postflight modeling of sensor errors and operation under the adverse condition of bad data are illustrated.
Mapping of sea ice and measurement of its drift using aircraft synthetic aperture radar images
NASA Technical Reports Server (NTRS)
Leberl, F.; Bryan, M. L.; Elachi, C.; Farr, T.; Campbell, W.
1979-01-01
Side-looking radar images of Arctic sea ice were obtained as part of the Arctic Ice Dynamics Joint Experiment. Repetitive coverages of a test site in the Arctic were used to measure sea ice drift, employing single images and blocks of overlapping radar image strips; the images were used in conjunction with data from the aircraft inertial navigation and altimeter. Also, independently measured, accurate positions of a number of ground control points were available. Initial tests of the method were carried out with repeated coverages of a land area on the Alaska coast (Prudhoe). Absolute accuracies achieved were essentially limited by the accuracy of the inertial navigation data. Errors of drift measurements were found to be about + or - 2.5 km. Relative accuracy is higher; its limits are set by the radar image geometry and the definition of identical features in sequential images. The drift of adjacent ice features with respect to one another could be determined with errors of less than + or - 0.2 km.
Piao, Jin-Chun; Kim, Shin-Dug
2017-01-01
Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual–inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual–inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual–inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual–inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method. PMID:29112143
A systems concept of the vestibular organs
NASA Technical Reports Server (NTRS)
Mayne, R.
1974-01-01
A comprehensive model of vestibular organ function is presented. The model is based on an analogy with the inertial guidance systems used in navigation. Three distinct operations are investigated: angular motion sensing, linear motion sensing, and computation. These operations correspond to the semicircular canals, the otoliths, and central processing respectively. It is especially important for both an inertial guidance system and the vestibular organs to distinguish between attitude with respect to the vertical on the one hand, and linear velocity and displacement on the other. The model is applied to various experimental situations and found to be corroborated by them.
Results from a GPS Shuttle Training Aircraft flight test
NASA Technical Reports Server (NTRS)
Saunders, Penny E.; Montez, Moises N.; Robel, Michael C.; Feuerstein, David N.; Aerni, Mike E.; Sangchat, S.; Rater, Lon M.; Cryan, Scott P.; Salazar, Lydia R.; Leach, Mark P.
1991-01-01
A series of Global Positioning System (GPS) flight tests were performed on a National Aeronautics and Space Administration's (NASA's) Shuttle Training Aircraft (STA). The objective of the tests was to evaluate the performance of GPS-based navigation during simulated Shuttle approach and landings for possible replacement of the current Shuttle landing navigation aid, the Microwave Scanning Beam Landing System (MSBLS). In particular, varying levels of sensor data integration would be evaluated to determine the minimum amount of integration required to meet the navigation accuracy requirements for a Shuttle landing. Four flight tests consisting of 8 to 9 simulation runs per flight test were performed at White Sands Space Harbor in April 1991. Three different GPS receivers were tested. The STA inertial navigation, tactical air navigation, and MSBLS sensor data were also recorded during each run. C-band radar aided laser trackers were utilized to provide the STA 'truth' trajectory.
Space shuttle entry and landing navigation analysis
NASA Technical Reports Server (NTRS)
Jones, H. L.; Crawford, B. S.
1974-01-01
A navigation system for the entry phase of a Space Shuttle mission which is an aided-inertial system which uses a Kalman filter to mix IMU data with data derived from external navigation aids is evaluated. A drag pseudo-measurement used during radio blackout is treated as an additional external aid. A comprehensive truth model with 101 states is formulated and used to generate detailed error budgets at several significant time points -- end-of-blackout, start of final approach, over runway threshold, and touchdown. Sensitivity curves illustrating the effect of variations in the size of individual error sources on navigation accuracy are presented. The sensitivity of the navigation system performance to filter modifications is analyzed. The projected overall performance is shown in the form of time histories of position and velocity error components. The detailed results are summarized and interpreted, and suggestions are made concerning possible software improvements.
a Fast and Flexible Method for Meta-Map Building for Icp Based Slam
NASA Astrophysics Data System (ADS)
Kurian, A.; Morin, K. W.
2016-06-01
Recent developments in LiDAR sensors make mobile mapping fast and cost effective. These sensors generate a large amount of data which in turn improves the coverage and details of the map. Due to the limited range of the sensor, one has to collect a series of scans to build the entire map of the environment. If we have good GNSS coverage, building a map is a well addressed problem. But in an indoor environment, we have limited GNSS reception and an inertial solution, if available, can quickly diverge. In such situations, simultaneous localization and mapping (SLAM) is used to generate a navigation solution and map concurrently. SLAM using point clouds possesses a number of computational challenges even with modern hardware due to the shear amount of data. In this paper, we propose two strategies for minimizing the cost of computation and storage when a 3D point cloud is used for navigation and real-time map building. We have used the 3D point cloud generated by Leica Geosystems's Pegasus Backpack which is equipped with Velodyne VLP-16 LiDARs scanners. To improve the speed of the conventional iterative closest point (ICP) algorithm, we propose a point cloud sub-sampling strategy which does not throw away any key features and yet significantly reduces the number of points that needs to be processed and stored. In order to speed up the correspondence finding step, a dual kd-tree and circular buffer architecture is proposed. We have shown that the proposed method can run in real time and has excellent navigation accuracy characteristics.
Hou, Bowen; He, Zhangming; Li, Dong; Zhou, Haiyin; Wang, Jiongqi
2018-05-27
Strap-down inertial navigation system/celestial navigation system ( SINS/CNS) integrated navigation is a high precision navigation technique for ballistic missiles. The traditional navigation method has a divergence in the position error. A deeply integrated mode for SINS/CNS navigation system is proposed to improve the navigation accuracy of ballistic missile. The deeply integrated navigation principle is described and the observability of the navigation system is analyzed. The nonlinearity, as well as the large outliers and the Gaussian mixture noises, often exists during the actual navigation process, leading to the divergence phenomenon of the navigation filter. The new nonlinear Kalman filter on the basis of the maximum correntropy theory and unscented transformation, named the maximum correntropy unscented Kalman filter, is deduced, and the computational complexity is analyzed. The unscented transformation is used for restricting the nonlinearity of the system equation, and the maximum correntropy theory is used to deal with the non-Gaussian noises. Finally, numerical simulation illustrates the superiority of the proposed filter compared with the traditional unscented Kalman filter. The comparison results show that the large outliers and the influence of non-Gaussian noises for SINS/CNS deeply integrated navigation is significantly reduced through the proposed filter.
NASA Astrophysics Data System (ADS)
Retscher, Guenther; Obex, Franz
2015-12-01
Location-based Services (LBS) influence nowadays every individual's life due to the emerging market penetration of smartphones and other mobile devices. For smartphone Apps localization technologies are developed ranging from GNSS beyond to other alternative ubiquitous positioning methods as well as the use of the in-built inertial sensors, such as accelerometers, gyroscopes, magnetometer, barometer, etc. Moreover, signals-of-opportunity which are not intended for positioning at the first sight but are receivable in many environments such as in buildings and public spaces are more and more utilized for positioning and navigation. The use of Wi-Fi (Wireless Fidelity) is a typical example. These technologies, however, have become very powerful tools as the enable to track an individual or even a group of users. Most technical researchers imply that it is mainly about further enhancing technologies and algorithms including the development of new advanced Apps to improve personal navigation and to deliver location oriented information just in time to a single LBS user or group of users. The authors claim that there is a need that ethical and political issues have to be addressed within our research community from the very beginning. Although there is a lot of research going on in developing algorithms to keep ones data and LBS search request in private, researchers can no longer keep their credibility without cooperating with ethical experts or an ethical committee. In a study called InKoPoMoVer (Cooperative Positioning for Real-time User Assistance and Guidance at Multi-modal Public Transit Junctions) a cooperation with social scientists was initiated for the first time at the Vienna University of Technology, Austria, in this context. The major aims of this study in relation to ethical questions are addressed in this paper.
NASA Technical Reports Server (NTRS)
Gay, Robert S.; Holt, Greg N.; Zanetti, Renato
2016-01-01
This paper details the post-flight navigation performance assessment of the Orion Exploration Flight Test-1 (EFT-1). Results of each flight phase are presented: Ground Align, Ascent, Orbit, and Entry Descent and Landing. This study examines the on-board Kalman Filter uncertainty along with state deviations relative to the Best Estimated Trajectory (BET). Overall the results show that the Orion Navigation System performed as well or better than expected. Specifically, the Global Positioning System (GPS) measurement availability was significantly better than anticipated at high altitudes. In addition, attitude estimation via processing GPS measurements along with Inertial Measurement Unit (IMU) data performed very well and maintained good attitude throughout the mission.
A novel visual-inertial monocular SLAM
NASA Astrophysics Data System (ADS)
Yue, Xiaofeng; Zhang, Wenjuan; Xu, Li; Liu, JiangGuo
2018-02-01
With the development of sensors and computer vision research community, cameras, which are accurate, compact, wellunderstood and most importantly cheap and ubiquitous today, have gradually been at the center of robot location. Simultaneous localization and mapping (SLAM) using visual features, which is a system getting motion information from image acquisition equipment and rebuild the structure in unknown environment. We provide an analysis of bioinspired flights in insects, employing a novel technique based on SLAM. Then combining visual and inertial measurements to get high accuracy and robustness. we present a novel tightly-coupled Visual-Inertial Simultaneous Localization and Mapping system which get a new attempt to address two challenges which are the initialization problem and the calibration problem. experimental results and analysis show the proposed approach has a more accurate quantitative simulation of insect navigation, which can reach the positioning accuracy of centimeter level.
Lu, Hao; Zhao, Kaichun; Wang, Xiaochu; You, Zheng; Huang, Kaoli
2016-01-01
Bio-inspired imaging polarization navigation which can provide navigation information and is capable of sensing polarization information has advantages of high-precision and anti-interference over polarization navigation sensors that use photodiodes. Although all types of imaging polarimeters exist, they may not qualify for the research on the imaging polarization navigation algorithm. To verify the algorithm, a real-time imaging orientation determination system was designed and implemented. Essential calibration procedures for the type of system that contained camera parameter calibration and the inconsistency of complementary metal oxide semiconductor calibration were discussed, designed, and implemented. Calibration results were used to undistort and rectify the multi-camera system. An orientation determination experiment was conducted. The results indicated that the system could acquire and compute the polarized skylight images throughout the calibrations and resolve orientation by the algorithm to verify in real-time. An orientation determination algorithm based on image processing was tested on the system. The performance and properties of the algorithm were evaluated. The rate of the algorithm was over 1 Hz, the error was over 0.313°, and the population standard deviation was 0.148° without any data filter. PMID:26805851
Laser-based Relative Navigation Using GPS Measurements for Spacecraft Formation Flying
NASA Astrophysics Data System (ADS)
Lee, Kwangwon; Oh, Hyungjik; Park, Han-Earl; Park, Sang-Young; Park, Chandeok
2015-12-01
This study presents a precise relative navigation algorithm using both laser and Global Positioning System (GPS) measurements in real time. The measurement model of the navigation algorithm between two spacecraft is comprised of relative distances measured by laser instruments and single differences of GPS pseudo-range measurements in spherical coordinates. Based on the measurement model, the Extended Kalman Filter (EKF) is applied to smooth the pseudo-range measurements and to obtain the relative navigation solution. While the navigation algorithm using only laser measurements might become inaccurate because of the limited accuracy of spacecraft attitude estimation when the distance between spacecraft is rather large, the proposed approach is able to provide an accurate solution even in such cases by employing the smoothed GPS pseudo-range measurements. Numerical simulations demonstrate that the errors of the proposed algorithm are reduced by more than about 12% compared to those of an algorithm using only laser measurements, as the accuracy of angular measurements is greater than 0.001° at relative distances greater than 30 km.
Tightly Coupled Inertial Navigation System/Global Positioning System (TCMIG)
NASA Technical Reports Server (NTRS)
Watson, Michael D.; Jackson, Kurt (Technical Monitor)
2002-01-01
Many NASA applications planned for execution later this decade are seeking high performance, miniaturized, low power Inertial Management Units (IMU). Much research has gone into Micro-Electro-Mechanical System (MEMS) over the past decade as a solution to these needs. While MEMS devices have proven to provide high accuracy acceleration measurements, they have not yet proven to have the accuracy required by many NASA missions in rotational measurements. Therefore, a new solution has been formulated integrating the best of all IMU technologies to address these mid-term needs in the form of a Tightly Coupled Micro Inertial Navigation System (INS)/Global Positioning System (GPS) (TCMIG). The TCMIG consists of an INS and a GPS tightly coupled by a Kalman filter executing on an embedded Field Programmable Gate Array (FPGA) processor. The INS consists of a highly integrated Interferometric Fiber Optic Gyroscope (IFOG) and a MEMS accelerometer. The IFOG utilizes a tightly wound fiber coil to reduce volume and the high level of integration and advanced optical components to reduce power. The MEMS accelerometer utilizes a newly developed deep etch process to increase the proof mass and yield a highly accurate accelerometer. The GPS receiver consists of a low power miniaturized version of the Blackjack receiver. Such an IMU configuration is ideal to meet the mid-term needs of the NASA Science Enterprises and the new launch vehicles being developed for the Space Launch Initiative (SLI).
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
X-ray Pulsar Navigation Algorithms and Testbed for SEXTANT
NASA Technical Reports Server (NTRS)
Winternitz, Luke M. B.; Hasouneh, Monther A.; Mitchell, Jason W.; Valdez, Jennifer E.; Price, Samuel R.; Semper, Sean R.; Yu, Wayne H.; Ray, Paul S.; Wood, Kent S.; Arzoumanian, Zaven;
2015-01-01
The Station Explorer for X-ray Timing and Navigation Technology (SEXTANT) is a NASA funded technologydemonstration. SEXTANT will, for the first time, demonstrate real-time, on-board X-ray Pulsar-based Navigation (XNAV), a significant milestone in the quest to establish a GPS-like navigation capability available throughout our Solar System and beyond. This paper describes the basic design of the SEXTANT system with a focus on core models and algorithms, and the design and continued development of the GSFC X-ray Navigation Laboratory Testbed (GXLT) with its dynamic pulsar emulation capability. We also present early results from GXLT modeling of the combined NICER X-ray timing instrument hardware and SEXTANT flight software algorithms.
Loosely Coupled GPS-Aided Inertial Navigation System for Range Safety
NASA Technical Reports Server (NTRS)
Heatwole, Scott; Lanzi, Raymond J.
2010-01-01
The Autonomous Flight Safety System (AFSS) aims to replace the human element of range safety operations, as well as reduce reliance on expensive, downrange assets for launches of expendable launch vehicles (ELVs). The system consists of multiple navigation sensors and flight computers that provide a highly reliable platform. It is designed to ensure that single-event failures in a flight computer or sensor will not bring down the whole system. The flight computer uses a rules-based structure derived from range safety requirements to make decisions whether or not to destroy the rocket.
Pilot-Assisted Inertial Navigation System Aiding Using Bearings-Only Measurements Taken Over Time
2015-03-26
δψ̇ ≈ −ω(n)in ×ψ + δω (n) in −Cnb δω (b) ib (11) Velocity error equation dynamics are expressed as Equation (12). Where the Coriolis effect comes into...navigation were effectively neglected due to the accuracy and technology development associated with GPS integration. The dependence on GPS was driven by the...bearing measurements used are more effective with high Signal-to-Noise Ratio (SNR) Line of Sight (LOS) measurements in a low Geometric Dilution of
2009-03-01
the research objectives for this study are presented. It should be noted that sensor cost was not considered for this study. Additionally, further...development costs ) for gravity compensation require- ments of its trident submarine inertial navigation systems and by the Air Force Geo- physics...52]: T (r, φ, λ) = GM ae Nmax∑ n=2 n∑ m=0 (a r )n+1 (Cnm cosmλ+ Snm sinmλ)P nm(cos φ) (31) 44 where r, φ, λ are the geocentric distance, lattitude and
Vision Aided Inertial Navigation System Augmented with a Coded Aperture
2011-03-24
as the change in blur at different distances from the pixel plane can be inferred. Cameras with a micro lens array (called plenoptic cameras...images from 8 slightly different perspectives [14,43]. Dappled photography is a similar to the plenoptic camera approach except that a cosine mask
NASA Astrophysics Data System (ADS)
Chu, Chien-Hsun; Chiang, Kai-Wei
2016-06-01
The early development of mobile mapping system (MMS) was restricted to applications that permitted the determination of the elements of exterior orientation from existing ground control. Mobile mapping refers to a means of collecting geospatial data using mapping sensors that are mounted on a mobile platform. Research works concerning mobile mapping dates back to the late 1980s. This process is mainly driven by the need for highway infrastructure mapping and transportation corridor inventories. In the early nineties, advances in satellite and inertial technology made it possible to think about mobile mapping in a different way. Instead of using ground control points as references for orienting the images in space, the trajectory and attitude of the imager platform could now be determined directly. Cameras, along with navigation and positioning sensors are integrated and mounted on a land vehicle for mapping purposes. Objects of interest can be directly measured and mapped from images that have been georeferenced using navigation and positioning sensors. Direct georeferencing (DG) is the determination of time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using the Global Navigation Satellite System (GNSS) and inertial navigation using an Inertial Measuring Unit (IMU). Although either technology used along could in principle determine both position and orientation, they are usually integrated in such a way that the IMU is the main orientation sensor, while the GNSS receiver is the main position sensor. However, GNSS signals are obstructed due to limited number of visible satellites in GNSS denied environments such as urban canyon, foliage, tunnel and indoor that cause the GNSS gap or interfered by reflected signals that cause abnormal measurement residuals thus deteriorates the positioning accuracy in GNSS denied environments. This study aims at developing a novel method that uses ground control points to maintain the positioning accuracy of the MMS in GNSS denied environments. At last, this study analyses the performance of proposed method using about 20 check-points through DG process.
Development of a Two-Wheel Contingency Mode for the MAP Spacecraft
NASA Technical Reports Server (NTRS)
Starin, Scott R.; ODonnell, James R., Jr.; Bauer, Frank H. (Technical Monitor)
2002-01-01
In the event of a failure of one of MAP's three reaction wheel assemblies (RWAs), it is not possible to achieve three-axis, full-state attitude control using the remaining two wheels. Hence, two of the attitude control algorithms implemented on the MAP spacecraft will no longer be usable in their current forms: Inertial Mode, used for slewing to and holding inertial attitudes, and Observing Mode, which implements the nominal dual-spin science mode. This paper describes the effort to create a complete strategy for using software algorithms to cope with a RWA failure. The discussion of the design process will be divided into three main subtopics: performing orbit maneuvers to reach and maintain an orbit about the second Earth-Sun libration point in the event of a RWA failure, completing the mission using a momentum-bias two-wheel science mode, and developing a new thruster-based mode for adjusting the inertially fixed momentum bias. In this summary, the philosophies used in designing these changes is shown; the full paper will supplement these with algorithm descriptions and testing results.
Hand-writing motion tracking with vision-inertial sensor fusion: calibration and error correction.
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.
Development of a Novel Locomotion Algorithm for Snake Robot
NASA Astrophysics Data System (ADS)
Khan, Raisuddin; Masum Billah, Md; Watanabe, Mitsuru; Shafie, A. A.
2013-12-01
A novel algorithm for snake robot locomotion is developed and analyzed in this paper. Serpentine is one of the renowned locomotion for snake robot in disaster recovery mission to overcome narrow space navigation. Several locomotion for snake navigation, such as concertina or rectilinear may be suitable for narrow spaces, but is highly inefficient if the same type of locomotion is used even in open spaces resulting friction reduction which make difficulties for snake movement. A novel locomotion algorithm has been proposed based on the modification of the multi-link snake robot, the modifications include alterations to the snake segments as well elements that mimic scales on the underside of the snake body. Snake robot can be able to navigate in the narrow space using this developed locomotion algorithm. The developed algorithm surmount the others locomotion limitation in narrow space navigation.
Magellan radar to reveal secrets of enshrouded Venus
NASA Technical Reports Server (NTRS)
Saunders, R. Stephen
1990-01-01
Imaging Venus with a synthetic aperture radar (SAR) with 70 percent global coverage at 1-km optical line-pair resolution to provide a detailed global characterization of the volcanic land-forms on Venus by an integration of image data with altimetry is discussed. The Magellan radar system uses navigation predictions to preset the radar data collection parameters. The data are collected in such a way as to preserve the Doppler signature of surface elements and later they are transmitted to the earth for processing into high-resolution radar images. To maintain high accuracy, a complex on-board filter algorithm allows the altitude control logic to respond only to a narrow range of expected photon intensity levels and only to signals that occur within a small predicted interval of time. Each mapping pass images a swath of the planet that varies in width from 20 to 25 km. Since the orbital plane of the spacecraft remains fixed in the inertial space, the slow rotation of Venus continually brings new areas into view of the spacecraft.
DAQ: Software Architecture for Data Acquisition in Sounding Rockets
NASA Technical Reports Server (NTRS)
Ahmad, Mohammad; Tran, Thanh; Nichols, Heidi; Bowles-Martinez, Jessica N.
2011-01-01
A multithreaded software application was developed by Jet Propulsion Lab (JPL) to collect a set of correlated imagery, Inertial Measurement Unit (IMU) and GPS data for a Wallops Flight Facility (WFF) sounding rocket flight. The data set will be used to advance Terrain Relative Navigation (TRN) technology algorithms being researched at JPL. This paper describes the software architecture and the tests used to meet the timing and data rate requirements for the software used to collect the dataset. Also discussed are the challenges of using commercial off the shelf (COTS) flight hardware and open source software. This includes multiple Camera Link (C-link) based cameras, a Pentium-M based computer, and Linux Fedora 11 operating system. Additionally, the paper talks about the history of the software architecture's usage in other JPL projects and its applicability for future missions, such as cubesats, UAVs, and research planes/balloons. Also talked about will be the human aspect of project especially JPL's Phaeton program and the results of the launch.
Study Navigator: An Algorithmically Generated Aid for Learning from Electronic Textbooks
ERIC Educational Resources Information Center
Agrawal, Rakesh; Gollapudi, Sreenivas; Kannan, Anitha; Kenthapadi, Krishnaram
2014-01-01
We present "study navigator," an algorithmically-generated aid for enhancing the experience of studying from electronic textbooks. The study navigator for a section of the book consists of helpful "concept references" for understanding this section. Each concept reference is a pair consisting of a concept phrase explained…
A fast bilinear structure from motion algorithm using a video sequence and inertial sensors.
Ramachandran, Mahesh; Veeraraghavan, Ashok; Chellappa, Rama
2011-01-01
In this paper, we study the benefits of the availability of a specific form of additional information—the vertical direction (gravity) and the height of the camera, both of which can be conveniently measured using inertial sensors and a monocular video sequence for 3D urban modeling. We show that in the presence of this information, the SfM equations can be rewritten in a bilinear form. This allows us to derive a fast, robust, and scalable SfM algorithm for large scale applications. The SfM algorithm developed in this paper is experimentally demonstrated to have favorable properties compared to the sparse bundle adjustment algorithm. We provide experimental evidence indicating that the proposed algorithm converges in many cases to solutions with lower error than state-of-art implementations of bundle adjustment. We also demonstrate that for the case of large reconstruction problems, the proposed algorithm takes lesser time to reach its solution compared to bundle adjustment. We also present SfM results using our algorithm on the Google StreetView research data set.
Standardized strapdown inertial component modularity study, volume 2
NASA Technical Reports Server (NTRS)
Feldman, J.
1974-01-01
To obtain cost effective strapdown navigation, guidance and stabilization systems to meet anticipated future needs a standardized modularized strapdown system concept is proposed. Three performance classes, high, medium and low, are suggested to meet the range of applications. Candidate inertial instruments are selected and analyzed for interface compatibility. Electronic packaging and processing, materials and thermal considerations applying to the three classes are discussed and recommendations advanced. Opportunities for automatic fault detection and redundancy are presented. The smallest gyro and accelerometer modules are projected as requiring a volume of 26 cubic inches and 23.6 cubic inches, respectively. Corresponding power dissipation is projected as 5 watts, and 2.6 watts respectively.
The research of a new data glove based on MARG sensor and magnetic localization technology
NASA Astrophysics Data System (ADS)
Ding, Yi; Gao, Tongyue; Wu, Ye; Zhu, Shihao
2018-04-01
The human hand gesture can record and reproduce the posture and action information of the hand, which is of great significance to people's production and life. This paper has improved the existing data gloves based on micro inertial technology, and integrates the magnetic field localization method into finger gesture measurements. The strap down inertial navigation technology and the magnetic localization technology are combined in this paper to make the advantages complement each other, and a low cost and high degree of freedom of data gloves are put forward to realize the way of data gloves in the past.
Ilyas, Muhammad; Hong, Beomjin; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok
2016-01-01
This paper provides algorithms to fuse relative and absolute microelectromechanical systems (MEMS) navigation sensors, suitable for micro planetary rovers, to provide a more accurate estimation of navigation information, specifically, attitude and position. Planetary rovers have extremely slow speed (~1 cm/s) and lack conventional navigation sensors/systems, hence the general methods of terrestrial navigation may not be applicable to these applications. While relative attitude and position can be tracked in a way similar to those for ground robots, absolute navigation information is hard to achieve on a remote celestial body, like Moon or Mars, in contrast to terrestrial applications. In this study, two absolute attitude estimation algorithms were developed and compared for accuracy and robustness. The estimated absolute attitude was fused with the relative attitude sensors in a framework of nonlinear filters. The nonlinear Extended Kalman filter (EKF) and Unscented Kalman filter (UKF) were compared in pursuit of better accuracy and reliability in this nonlinear estimation problem, using only on-board low cost MEMS sensors. Experimental results confirmed the viability of the proposed algorithms and the sensor suite, for low cost and low weight micro planetary rovers. It is demonstrated that integrating the relative and absolute navigation MEMS sensors reduces the navigation errors to the desired level. PMID:27223293
Ilyas, Muhammad; Hong, Beomjin; Cho, Kuk; Baeg, Seung-Ho; Park, Sangdeok
2016-05-23
This paper provides algorithms to fuse relative and absolute microelectromechanical systems (MEMS) navigation sensors, suitable for micro planetary rovers, to provide a more accurate estimation of navigation information, specifically, attitude and position. Planetary rovers have extremely slow speed (~1 cm/s) and lack conventional navigation sensors/systems, hence the general methods of terrestrial navigation may not be applicable to these applications. While relative attitude and position can be tracked in a way similar to those for ground robots, absolute navigation information is hard to achieve on a remote celestial body, like Moon or Mars, in contrast to terrestrial applications. In this study, two absolute attitude estimation algorithms were developed and compared for accuracy and robustness. The estimated absolute attitude was fused with the relative attitude sensors in a framework of nonlinear filters. The nonlinear Extended Kalman filter (EKF) and Unscented Kalman filter (UKF) were compared in pursuit of better accuracy and reliability in this nonlinear estimation problem, using only on-board low cost MEMS sensors. Experimental results confirmed the viability of the proposed algorithms and the sensor suite, for low cost and low weight micro planetary rovers. It is demonstrated that integrating the relative and absolute navigation MEMS sensors reduces the navigation errors to the desired level.
Development of a two wheeled self balancing robot with speech recognition and navigation algorithm
NASA Astrophysics Data System (ADS)
Rahman, Md. Muhaimin; Ashik-E-Rasul, Haq, Nowab. Md. Aminul; Hassan, Mehedi; Hasib, Irfan Mohammad Al; Hassan, K. M. Rafidh
2016-07-01
This paper is aimed to discuss modeling, construction and development of navigation algorithm of a two wheeled self balancing mobile robot in an enclosure. In this paper, we have discussed the design of two of the main controller algorithms, namely PID algorithms, on the robot model. Simulation is performed in the SIMULINK environment. The controller is developed primarily for self-balancing of the robot and also it's positioning. As for the navigation in an enclosure, template matching algorithm is proposed for precise measurement of the robot position. The navigation system needs to be calibrated before navigation process starts. Almost all of the earlier template matching algorithms that can be found in the open literature can only trace the robot. But the proposed algorithm here can also locate the position of other objects in an enclosure, like furniture, tables etc. This will enable the robot to know the exact location of every stationary object in the enclosure. Moreover, some additional features, such as Speech Recognition and Object Detection, are added. For Object Detection, the single board Computer Raspberry Pi is used. The system is programmed to analyze images captured via the camera, which are then processed through background subtraction, followed by active noise reduction.
Image registration of naval IR images
NASA Astrophysics Data System (ADS)
Rodland, Arne J.
1996-06-01
In a real world application an image from a stabilized sensor on a moving platform will not be 100 percent stabilized. There will always be a small unknown error in the stabilization due to factors such as dynamic deformations in the structure between sensor and reference Inertial Navigation Unit, servo inaccuracies, etc. For a high resolution imaging sensor this stabilization error causes the image to move several pixels in unknown direction between frames. TO be able to detect and track small moving objects from such a sensor, this unknown movement of the sensor image must be estimated. An algorithm that searches for land contours in the image has been evaluated. The algorithm searches for high contrast points distributed over the whole image. As long as moving objects in the scene only cover a small area of the scene, most of the points are located on solid ground. By matching the list of points from frame to frame, the movement of the image due to stabilization errors can be estimated and compensated. The point list is searched for points with diverging movement from the estimated stabilization error. These points are then assumed to be located on moving objects. Points assumed to be located on moving objects are gradually exchanged with new points located in the same area. Most of the processing is performed on the list of points and not on the complete image. The algorithm is therefore very fast and well suited for real time implementation. The algorithm has been tested on images from an experimental IR scanner. Stabilization errors were added artificially to the image such that the output from the algorithm could be compared with the artificially added stabilization errors.
The Additional Error of Inertial Sensors Induced by Hypersonic Flight Conditions
Karachun, Volodimir; Mel’nick, Viktorij; Korobiichuk, Igor; Nowicki, Michał; Szewczyk, Roman; Kobzar, Svitlana
2016-01-01
The emergence of hypersonic technology pose a new challenge for inertial navigation sensors, widely used in aerospace industry. The main problems are: extremely high temperatures, vibration of the fuselage, penetrating acoustic radiation and shock N-waves. The nature of the additional errors of the gyroscopic inertial sensor with hydrostatic suspension components under operating conditions generated by forced precession of the movable part of the suspension due to diffraction phenomena in acoustic fields is explained. The cause of the disturbing moments in the form of the Coriolis inertia forces during the transition of the suspension surface into the category of impedance is revealed. The boundaries of occurrence of the features on the resonance wave match are described. The values of the “false” angular velocity as a result of the elastic-stress state of suspension in the acoustic fields are determined. PMID:26927122
A Comparison Between Three IMUs for Strapdown Airborne Gravimetry
NASA Astrophysics Data System (ADS)
Ayres-Sampaio, Diogo; Deurloo, Richard; Bos, Machiel; Magalhães, Américo; Bastos, Luísa
2015-07-01
Strapdown airborne gravimetry relies on the combination of an inertial measuring unit (IMU) and a global navigation satellite system (GNSS) to measure the Earth's gravity field. Early results with navigation-grade IMUs showed similar accuracies to those obtained with scalar gravimetric systems in the down component. This paper investigates the accuracy of three IMUs used for strapdown airborne gravimetry under the same flight conditions. The three systems considered were navigation-grade IMUs, iXSea AIRINS and iMAR iNAV-FMS, and a tactical-grade Litton LN-200. The data were collected in 2010 over the Island of Madeira, Portugal, in the scope of GEOid over MADeira campaign. The coordinates and orientation of the aircraft were computed using an extended Kalman filter based on the inertial navigation approach. GNSS position and velocity observations were used to update the filter, and the gravity disturbance was considered to be a stochastic process and was part of the state vector. A new crossover point-based serial tuning was introduced to deal with the uncertainty of choosing the filter's a priori information. The results show that with the iXSea accuracies of 2.1 and 1.6 mGal can be obtained for 1.7 and 5.0 km of spatial resolution (half-wavelength), respectively. iMAR's results were significantly affected by a nonlinear drift, which led to lower accuracies of 4.1-5.5 mGal. Remarkably, Litton showed very consistent results and achieved an accuracy of about 4.5 mGal at 5 km of spatial resolution (half-wavelength).
Image-based path planning for automated virtual colonoscopy navigation
NASA Astrophysics Data System (ADS)
Hong, Wei
2008-03-01
Virtual colonoscopy (VC) is a noninvasive method for colonic polyp screening, by reconstructing three-dimensional models of the colon using computerized tomography (CT). In virtual colonoscopy fly-through navigation, it is crucial to generate an optimal camera path for efficient clinical examination. In conventional methods, the centerline of the colon lumen is usually used as the camera path. In order to extract colon centerline, some time consuming pre-processing algorithms must be performed before the fly-through navigation, such as colon segmentation, distance transformation, or topological thinning. In this paper, we present an efficient image-based path planning algorithm for automated virtual colonoscopy fly-through navigation without the requirement of any pre-processing. Our algorithm only needs the physician to provide a seed point as the starting camera position using 2D axial CT images. A wide angle fisheye camera model is used to generate a depth image from the current camera position. Two types of navigational landmarks, safe regions and target regions are extracted from the depth images. Camera position and its corresponding view direction are then determined using these landmarks. The experimental results show that the generated paths are accurate and increase the user comfort during the fly-through navigation. Moreover, because of the efficiency of our path planning algorithm and rendering algorithm, our VC fly-through navigation system can still guarantee 30 FPS.
GPS navigation algorithms for Autonomous Airborne Refueling of Unmanned Air Vehicles
NASA Astrophysics Data System (ADS)
Khanafseh, Samer Mahmoud
Unmanned Air Vehicles (UAVs) have recently generated great interest because of their potential to perform hazardous missions without risking loss of life. If autonomous airborne refueling is possible for UAVs, mission range and endurance will be greatly enhanced. However, concerns about UAV-tanker proximity, dynamic mobility and safety demand that the relative navigation system meets stringent requirements on accuracy, integrity, and continuity. In response, this research focuses on developing high-performance GPS-based navigation architectures for Autonomous Airborne Refueling (AAR) of UAVs. The AAR mission is unique because of the potentially severe sky blockage introduced by the tanker. To address this issue, a high-fidelity dynamic sky blockage model was developed and experimentally validated. In addition, robust carrier phase differential GPS navigation algorithms were derived, including a new method for high-integrity reacquisition of carrier cycle ambiguities for recently-blocked satellites. In order to evaluate navigation performance, world-wide global availability and sensitivity covariance analyses were conducted. The new navigation algorithms were shown to be sufficient for turn-free scenarios, but improvement in performance was necessary to meet the difficult requirements for a general refueling mission with banked turns. Therefore, several innovative methods were pursued to enhance navigation performance. First, a new theoretical approach was developed to quantify the position-domain integrity risk in cycle ambiguity resolution problems. A mechanism to implement this method with partially-fixed cycle ambiguity vectors was derived, and it was used to define tight upper bounds on AAR navigation integrity risk. A second method, where a new algorithm for optimal fusion of measurements from multiple antennas was developed, was used to improve satellite coverage in poor visibility environments such as in AAR. Finally, methods for using data-link extracted measurements as an additional inter-vehicle ranging measurement were also introduced. The algorithms and methods developed in this work are generally applicable to realize high-performance GPS-based navigation in partially obstructed environments. Navigation performance for AAR was quantified through covariance analysis, and it was shown that the stringent navigation requirements for this application are achievable. Finally, a real-time implementation of the algorithms was developed and successfully validated in autopiloted flight tests.
A Context-Recognition-Aided PDR Localization Method Based on the Hidden Markov Model
Lu, Yi; Wei, Dongyan; Lai, Qifeng; Li, Wen; Yuan, Hong
2016-01-01
Indoor positioning has recently become an important field of interest because global navigation satellite systems (GNSS) are usually unavailable in indoor environments. Pedestrian dead reckoning (PDR) is a promising localization technique for indoor environments since it can be implemented on widely used smartphones equipped with low cost inertial sensors. However, the PDR localization severely suffers from the accumulation of positioning errors, and other external calibration sources should be used. In this paper, a context-recognition-aided PDR localization model is proposed to calibrate PDR. The context is detected by employing particular human actions or characteristic objects and it is matched to the context pre-stored offline in the database to get the pedestrian’s location. The Hidden Markov Model (HMM) and Recursive Viterbi Algorithm are used to do the matching, which reduces the time complexity and saves the storage. In addition, the authors design the turn detection algorithm and take the context of corner as an example to illustrate and verify the proposed model. The experimental results show that the proposed localization method can fix the pedestrian’s starting point quickly and improves the positioning accuracy of PDR by 40.56% at most with perfect stability and robustness at the same time. PMID:27916922
A Hybrid FPGA/Tilera Compute Element for Autonomous Hazard Detection and Navigation
NASA Technical Reports Server (NTRS)
Villalpando, Carlos Y.; Werner, Robert A.; Carson, John M., III; Khanoyan, Garen; Stern, Ryan A.; Trawny, Nikolas
2013-01-01
To increase safety for future missions landing on other planetary or lunar bodies, the Autonomous Landing and Hazard Avoidance Technology (ALHAT) program is developing an integrated sensor for autonomous surface analysis and hazard determination. The ALHAT Hazard Detection System (HDS) consists of a Flash LIDAR for measuring the topography of the landing site, a gimbal to scan across the terrain, and an Inertial Measurement Unit (IMU), along with terrain analysis algorithms to identify the landing site and the local hazards. An FPGA and Manycore processor system was developed to interface all the devices in the HDS, to provide high-resolution timing to accurately measure system state, and to run the surface analysis algorithms quickly and efficiently. In this paper, we will describe how we integrated COTS components such as an FPGA evaluation board, a TILExpress64, and multi-threaded/multi-core aware software to build the HDS Compute Element (HDSCE). The ALHAT program is also working with the NASA Morpheus Project and has integrated the HDS as a sensor on the Morpheus Lander. This paper will also describe how the HDS is integrated with the Morpheus lander and the results of the initial test flights with the HDS installed. We will also describe future improvements to the HDSCE.
A hybrid FPGA/Tilera compute element for autonomous hazard detection and navigation
NASA Astrophysics Data System (ADS)
Villalpando, C. Y.; Werner, R. A.; Carson, J. M.; Khanoyan, G.; Stern, R. A.; Trawny, N.
To increase safety for future missions landing on other planetary or lunar bodies, the Autonomous Landing and Hazard Avoidance Technology (ALHAT) program is developing an integrated sensor for autonomous surface analysis and hazard determination. The ALHAT Hazard Detection System (HDS) consists of a Flash LIDAR for measuring the topography of the landing site, a gimbal to scan across the terrain, and an Inertial Measurement Unit (IMU), along with terrain analysis algorithms to identify the landing site and the local hazards. An FPGA and Manycore processor system was developed to interface all the devices in the HDS, to provide high-resolution timing to accurately measure system state, and to run the surface analysis algorithms quickly and efficiently. In this paper, we will describe how we integrated COTS components such as an FPGA evaluation board, a TILExpress64, and multi-threaded/multi-core aware software to build the HDS Compute Element (HDSCE). The ALHAT program is also working with the NASA Morpheus Project and has integrated the HDS as a sensor on the Morpheus Lander. This paper will also describe how the HDS is integrated with the Morpheus lander and the results of the initial test flights with the HDS installed. We will also describe future improvements to the HDSCE.
Flight Test of an Adaptive Configuration Optimization System for Transport Aircraft
NASA Technical Reports Server (NTRS)
Gilyard, Glenn B.; Georgie, Jennifer; Barnicki, Joseph S.
1999-01-01
A NASA Dryden Flight Research Center program explores the practical application of real-time adaptive configuration optimization for enhanced transport performance on an L-1011 aircraft. This approach is based on calculation of incremental drag from forced-response, symmetric, outboard aileron maneuvers. In real-time operation, the symmetric outboard aileron deflection is directly optimized, and the horizontal stabilator and angle of attack are indirectly optimized. A flight experiment has been conducted from an onboard research engineering test station, and flight research results are presented herein. The optimization system has demonstrated the capability of determining the minimum drag configuration of the aircraft in real time. The drag-minimization algorithm is capable of identifying drag to approximately a one-drag-count level. Optimizing the symmetric outboard aileron position realizes a drag reduction of 2-3 drag counts (approximately 1 percent). Algorithm analysis of maneuvers indicate that two-sided raised-cosine maneuvers improve definition of the symmetric outboard aileron drag effect, thereby improving analysis results and consistency. Ramp maneuvers provide a more even distribution of data collection as a function of excitation deflection than raised-cosine maneuvers provide. A commercial operational system would require airdata calculations and normal output of current inertial navigation systems; engine pressure ratio measurements would be optional.
Li, Hong; Liu, Mingyong; Zhang, Feihu
2017-01-01
This paper presents a multi-objective evolutionary algorithm of bio-inspired geomagnetic navigation for Autonomous Underwater Vehicle (AUV). Inspired by the biological navigation behavior, the solution was proposed without using a priori information, simply by magnetotaxis searching. However, the existence of the geomagnetic anomalies has significant influence on the geomagnetic navigation system, which often disrupts the distribution of the geomagnetic field. An extreme value region may easily appear in abnormal regions, which makes AUV lost in the navigation phase. This paper proposes an improved bio-inspired algorithm with behavior constraints, for sake of making AUV escape from the abnormal region. First, the navigation problem is considered as the optimization problem. Second, the environmental monitoring operator is introduced, to determine whether the algorithm falls into the geomagnetic anomaly region. Then, the behavior constraint operator is employed to get out of the abnormal region. Finally, the termination condition is triggered. Compared to the state-of- the-art, the proposed approach effectively overcomes the disturbance of the geomagnetic abnormal. The simulation result demonstrates the reliability and feasibility of the proposed approach in complex environments.
Li, Hong; Liu, Mingyong; Zhang, Feihu
2017-01-01
This paper presents a multi-objective evolutionary algorithm of bio-inspired geomagnetic navigation for Autonomous Underwater Vehicle (AUV). Inspired by the biological navigation behavior, the solution was proposed without using a priori information, simply by magnetotaxis searching. However, the existence of the geomagnetic anomalies has significant influence on the geomagnetic navigation system, which often disrupts the distribution of the geomagnetic field. An extreme value region may easily appear in abnormal regions, which makes AUV lost in the navigation phase. This paper proposes an improved bio-inspired algorithm with behavior constraints, for sake of making AUV escape from the abnormal region. First, the navigation problem is considered as the optimization problem. Second, the environmental monitoring operator is introduced, to determine whether the algorithm falls into the geomagnetic anomaly region. Then, the behavior constraint operator is employed to get out of the abnormal region. Finally, the termination condition is triggered. Compared to the state-of- the-art, the proposed approach effectively overcomes the disturbance of the geomagnetic abnormal. The simulation result demonstrates the reliability and feasibility of the proposed approach in complex environments. PMID:28747884
Mission and Navigation Design for the 2009 Mars Science Laboratory Mission
NASA Technical Reports Server (NTRS)
D'Amario, Louis A.
2008-01-01
NASA s Mars Science Laboratory mission will launch the next mobile science laboratory to Mars in the fall of 2009 with arrival at Mars occurring in the summer of 2010. A heat shield, parachute, and rocket-powered descent stage, including a sky crane, will be used to land the rover safely on the surface of Mars. The direction of the atmospheric entry vehicle lift vector will be controlled by a hypersonic entry guidance algorithm to compensate for entry trajectory errors and counteract atmospheric and aerodynamic dispersions. The key challenges for mission design are (1) develop a launch/arrival strategy that provides communications coverage during the Entry, Descent, and Landing phase either from an X-band direct-to-Earth link or from a Ultra High Frequency link to the Mars Reconnaissance Orbiter for landing latitudes between 30 deg North and 30 deg South, while satisfying mission constraints on Earth departure energy and Mars atmospheric entry speed, and (2) generate Earth-departure targets for the Atlas V-541 launch vehicle for the specified launch/arrival strategy. The launch/arrival strategy employs a 30-day baseline launch period and a 27-day extended launch period with varying arrival dates at Mars. The key challenges for navigation design are (1) deliver the spacecraft to the atmospheric entry interface point (Mars radius of 3522.2 km) with an inertial entry flight path angle error of +/- 0.20 deg (3 sigma), (2) provide knowledge of the entry state vector accurate to +/- 2.8 km (3 sigma) in position and +/- 2.0 m/s (3 sigma) in velocity for initializing the entry guidance algorithm, and (3) ensure a 99% probability of successful delivery at Mars with respect to available cruise stage propellant. Orbit determination is accomplished via ground processing of multiple complimentary radiometric data types: Doppler, range, and Delta-Differential One-way Ranging (a Very Long Baseline Interferometry measurement). The navigation strategy makes use of up to five interplanetary trajectory correction maneuvers to achieve entry targeting requirements. The requirements for cruise propellant usage and atmospheric entry targeting and knowledge are met with ample margins.
An Analysis of Navigation Algorithms for Smartphones Using J2ME
NASA Astrophysics Data System (ADS)
Santos, André C.; Tarrataca, Luís; Cardoso, João M. P.
Embedded systems are considered one of the most potential areas for future innovations. Two embedded fields that will most certainly take a primary role in future innovations are mobile robotics and mobile computing. Mobile robots and smartphones are growing in number and functionalities, becoming a presence in our daily life. In this paper, we study the current feasibility of a smartphone to execute navigation algorithms. As a test case, we use a smartphone to control an autonomous mobile robot. We tested three navigation problems: Mapping, Localization and Path Planning. For each of these problems, an algorithm has been chosen, developed in J2ME, and tested on the field. Results show the current mobile Java capacity for executing computationally demanding algorithms and reveal the real possibility of using smartphones for autonomous navigation.