This study investigates the problem of tracking a satellite performing unknown continuous maneuvers. A new method is proposed for estimating both the state and maneuver acceleration of the satellite. The estimation of...This study investigates the problem of tracking a satellite performing unknown continuous maneuvers. A new method is proposed for estimating both the state and maneuver acceleration of the satellite. The estimation of the maneuver acceleration is obtained by the combination of an unbiased minimum-variance input and state estimation method and a low-pass filter. Then a threshold-based maneuver detection approach is developed to determinate the start and end time of the unknown maneuvers. During the maneuvering period, the estimation error of the maneuver acceleration is modeled as the sum of a fluctuation error and a sudden change error. A robust extended Kalman filter is developed for dealing with the acceleration estimate error and providing state estimation. Simulation results show that, compared with the Unbiased Minimum-variance Input and State Estimation(UMISE) method, the proposed method has the same position estimation accuracy, and the velocity estimation error is reduced by about 5 times during the maneuver period. Besides, the acceleration detection and estimation accuracy of the proposed method is much higher than that of the UMISE method.展开更多
A sequential processing is presented aiming at optimizing the direction of arrival(DOA)tracking performance.Firstly,current positions and Doppler frequency are estimated and a mathematical model is derived in order to...A sequential processing is presented aiming at optimizing the direction of arrival(DOA)tracking performance.Firstly,current positions and Doppler frequency are estimated and a mathematical model is derived in order to clarify the effect of Doppler frequency on the estimation.The Doppler effect is employed within subspace concept in order to refine the estimation of the target position.Secondly,a renewed weight factor that depends on target maneuver is employed in order to realize more accurate association and smoothing processes.Simulation results show that the presented method has high accuracy in DOA tracking.展开更多
基金supported by the National Natural Science Fund for Distinguished Young Scholars of China(No.11525208)
文摘This study investigates the problem of tracking a satellite performing unknown continuous maneuvers. A new method is proposed for estimating both the state and maneuver acceleration of the satellite. The estimation of the maneuver acceleration is obtained by the combination of an unbiased minimum-variance input and state estimation method and a low-pass filter. Then a threshold-based maneuver detection approach is developed to determinate the start and end time of the unknown maneuvers. During the maneuvering period, the estimation error of the maneuver acceleration is modeled as the sum of a fluctuation error and a sudden change error. A robust extended Kalman filter is developed for dealing with the acceleration estimate error and providing state estimation. Simulation results show that, compared with the Unbiased Minimum-variance Input and State Estimation(UMISE) method, the proposed method has the same position estimation accuracy, and the velocity estimation error is reduced by about 5 times during the maneuver period. Besides, the acceleration detection and estimation accuracy of the proposed method is much higher than that of the UMISE method.
文摘A sequential processing is presented aiming at optimizing the direction of arrival(DOA)tracking performance.Firstly,current positions and Doppler frequency are estimated and a mathematical model is derived in order to clarify the effect of Doppler frequency on the estimation.The Doppler effect is employed within subspace concept in order to refine the estimation of the target position.Secondly,a renewed weight factor that depends on target maneuver is employed in order to realize more accurate association and smoothing processes.Simulation results show that the presented method has high accuracy in DOA tracking.
