The strapdown inertial navigation system (SINS)/two-antenna GPS integrated navigation system is discussed. Corresponding error and the measurement models are built, especially the double differenced GPS carrier phas...The strapdown inertial navigation system (SINS)/two-antenna GPS integrated navigation system is discussed. Corresponding error and the measurement models are built, especially the double differenced GPS carrier phase model. The extended Kalman filtering is proposed. And the hardware composition and connection are designed to simulate the SINS/two-antenna GPS integrated navigation system. Results show that the performances of the system, the precision of the navigation and the positioning, the reliability and the practicability are im proved.展开更多
An interval Kalman filter (IKF) algorithm based on the interval conditional expectation is applied to an integrated global positioning system/inertial navigation system (GPS/INS). Because the IKF algorithm is applica...An interval Kalman filter (IKF) algorithm based on the interval conditional expectation is applied to an integrated global positioning system/inertial navigation system (GPS/INS). Because the IKF algorithm is applicable only to linear interval systems, the extended interval Kalman filter (EIKF) algorithm for non linear integrated systems is developed. A high dynamic aircraft trajectory is designed to test the algorithm developed. The results of computer simulation indicate that the EIKF algorithm is consistent with the traditional SKF scheme, and is also effective for uncertain non linear integrated system.展开更多
A fast U D factorization based Kalman filter for the 21 state integrated global positioning system and inertial navigation system (GPS/INS) is developed from the point of engineering implementation. The conventio...A fast U D factorization based Kalman filter for the 21 state integrated global positioning system and inertial navigation system (GPS/INS) is developed from the point of engineering implementation. The conventional Kalman filter is widely used for integration of GPS/INS, however, due to the model and numerical computation errors, the Kalman filter may diverge in engineering implementation. In order to solve this problem, an extended Kalman filter based on the U D factorization is proposed. Moreover, the high order integrated system suffers from the problem of long computation time, leading to difficulties in real time applications. An algorithmic approach is developed to improve the computational speed. A typical aircraft trajectory is simulated to compare the improvement in the computational speed and the navigation accuracy using the conventional Kalman filter and the fast Kalman filter based on the U D factorization. The results indicate that the methods proposed in this paper are very effective in overcoming these problems for the high dynamic integrated GPS/INS system.展开更多
A land vehicle tracking and monitoring system based on the integration of differential global position system (DGPS), dead-reckoning (DR), and map matched technology is studied. In this paper, from the economic point ...A land vehicle tracking and monitoring system based on the integration of differential global position system (DGPS), dead-reckoning (DR), and map matched technology is studied. In this paper, from the economic point of view, a new scheme using the one-way directional communication link, is presented. Moreover, 8-state Kalman filter is proposed for integrated DGPS/DR system. When field tests are carried out using two C/A code GARMIN GPS receiver, the positioning accuracy less than 5 m (1σ) is achieved.展开更多
This article deals with a problem of the robot localization in the outdoor environment by using the GPS (global positioning system) data. In order to navigate the robot, it is necessary to transform the global posit...This article deals with a problem of the robot localization in the outdoor environment by using the GPS (global positioning system) data. In order to navigate the robot, it is necessary to transform the global position into the local map in the form of two-dimensional Cartesian coordinate system. The transformation is based on the model of the Earth-WGS 84 reference ellipsoid. The aim of this article is to experimentally evaluate a set of low-cost GPS receivers applicable as position sensors for small outdoor mobile robots. The evaluation is based on series of measurements executed in different times and places. The measured data is processed by given procedure and acquired positions are transformed into the local coordinate system. Accordingly the accuracy of the measured positions is statistically evaluated. The evaluation of used GPS receivers is done by comparison with data acquired by high-end geodetic GPS system Leica 1200, which is used as a reference GPS system.展开更多
Traditional beamformers need to know the incident angle of the desired signal leading while its abili-ty to handle interference is limited.In this paper,the constrained steer vector of linearly constrained min-imum-va...Traditional beamformers need to know the incident angle of the desired signal leading while its abili-ty to handle interference is limited.In this paper,the constrained steer vector of linearly constrained min-imum-variance(LCMV)beamformer is modified to make sidelobe null to direction of powerful jammer.Inaddition,the state-space concept is used to describe the anti-jammer filter,and Kalman filter algorithm isdeduced by building the observation model and measurement equation.The new method is more efficient oncomputation and more robust to survive environment with large scale variation in interference strength.Fi-nally,simulation results shows that the new approach can form the null with its depth in proportion to powerin direction of jammer,and has steady convergence process.The novel method can effectively improve thesignal-to-jammer-plus-noise power ratio(SJNR)of GPS signals to make the correlation peak easy to track.展开更多
Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typical...Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive.For the inherent shortcomings of general particle filter(the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it.Based on improvement a distributed localization algorithm named WC-IPF(weighted centroid algorithm improved particle filter) has been proposed for localization.In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm.Then the accurate position can be gotten via improved particle filter recursively.The extend simulation results show that the proposed algorithm is efficient for most condition.展开更多
文摘The strapdown inertial navigation system (SINS)/two-antenna GPS integrated navigation system is discussed. Corresponding error and the measurement models are built, especially the double differenced GPS carrier phase model. The extended Kalman filtering is proposed. And the hardware composition and connection are designed to simulate the SINS/two-antenna GPS integrated navigation system. Results show that the performances of the system, the precision of the navigation and the positioning, the reliability and the practicability are im proved.
文摘An interval Kalman filter (IKF) algorithm based on the interval conditional expectation is applied to an integrated global positioning system/inertial navigation system (GPS/INS). Because the IKF algorithm is applicable only to linear interval systems, the extended interval Kalman filter (EIKF) algorithm for non linear integrated systems is developed. A high dynamic aircraft trajectory is designed to test the algorithm developed. The results of computer simulation indicate that the EIKF algorithm is consistent with the traditional SKF scheme, and is also effective for uncertain non linear integrated system.
文摘A fast U D factorization based Kalman filter for the 21 state integrated global positioning system and inertial navigation system (GPS/INS) is developed from the point of engineering implementation. The conventional Kalman filter is widely used for integration of GPS/INS, however, due to the model and numerical computation errors, the Kalman filter may diverge in engineering implementation. In order to solve this problem, an extended Kalman filter based on the U D factorization is proposed. Moreover, the high order integrated system suffers from the problem of long computation time, leading to difficulties in real time applications. An algorithmic approach is developed to improve the computational speed. A typical aircraft trajectory is simulated to compare the improvement in the computational speed and the navigation accuracy using the conventional Kalman filter and the fast Kalman filter based on the U D factorization. The results indicate that the methods proposed in this paper are very effective in overcoming these problems for the high dynamic integrated GPS/INS system.
文摘A land vehicle tracking and monitoring system based on the integration of differential global position system (DGPS), dead-reckoning (DR), and map matched technology is studied. In this paper, from the economic point of view, a new scheme using the one-way directional communication link, is presented. Moreover, 8-state Kalman filter is proposed for integrated DGPS/DR system. When field tests are carried out using two C/A code GARMIN GPS receiver, the positioning accuracy less than 5 m (1σ) is achieved.
文摘This article deals with a problem of the robot localization in the outdoor environment by using the GPS (global positioning system) data. In order to navigate the robot, it is necessary to transform the global position into the local map in the form of two-dimensional Cartesian coordinate system. The transformation is based on the model of the Earth-WGS 84 reference ellipsoid. The aim of this article is to experimentally evaluate a set of low-cost GPS receivers applicable as position sensors for small outdoor mobile robots. The evaluation is based on series of measurements executed in different times and places. The measured data is processed by given procedure and acquired positions are transformed into the local coordinate system. Accordingly the accuracy of the measured positions is statistically evaluated. The evaluation of used GPS receivers is done by comparison with data acquired by high-end geodetic GPS system Leica 1200, which is used as a reference GPS system.
基金Supported by the National High Technology Research and Development Programme of China (No. 2006AA701108)
文摘Traditional beamformers need to know the incident angle of the desired signal leading while its abili-ty to handle interference is limited.In this paper,the constrained steer vector of linearly constrained min-imum-variance(LCMV)beamformer is modified to make sidelobe null to direction of powerful jammer.Inaddition,the state-space concept is used to describe the anti-jammer filter,and Kalman filter algorithm isdeduced by building the observation model and measurement equation.The new method is more efficient oncomputation and more robust to survive environment with large scale variation in interference strength.Fi-nally,simulation results shows that the new approach can form the null with its depth in proportion to powerin direction of jammer,and has steady convergence process.The novel method can effectively improve thesignal-to-jammer-plus-noise power ratio(SJNR)of GPS signals to make the correlation peak easy to track.
文摘Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive.For the inherent shortcomings of general particle filter(the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it.Based on improvement a distributed localization algorithm named WC-IPF(weighted centroid algorithm improved particle filter) has been proposed for localization.In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm.Then the accurate position can be gotten via improved particle filter recursively.The extend simulation results show that the proposed algorithm is efficient for most condition.