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 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
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
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 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.
