火力与指挥控制Issue(3)：116-120,5.
基于改进平方根UKF双向滤波的单站无源定位算法
Forward-Backward Filter Based on Improved Square Root UKF for Single Observer Passive Location
摘要
Abstract
Because of the low observability and the high noise in single observer passive location, the performance of the positioning accuracy,stability and convergence velocity is poor. Based on the Square-Root Unscented Kalman Filter (SRUKF)and the backward smoothing method,a forward-backward filter based on improved SRUKF is presented. To improve the stability and the calculate efficiency of the algorithm,the Q-R decomposition is adopted,and the covariance square-root matrix is used instead of the covariance matrix. Meanwhile,the state vector is augmented. The process noise and measurement noise are propagated through the nonlinearity system. The negative influence of noise on the filtering accuracy is decreased. The more accurate initial value for the next filtering process was obtain by the use of the current filtering results,based on the Rauch-Tung-Striebel(RTS)backward smoothing method. The positioning accuracy and the convergence velocity is improved. Simulation results indicated that the novel algorithm improved the single observer passive location performance while keeping the real-time characteristic.关键词
单站无源定位/平方根无迹卡尔曼滤波/后向平滑/Q-R分解/扩维Key words
single observer passive location/square root unscented kalman filter/backward smoothing/Q-R decomposition/augmented分类
信息技术与安全科学引用本文复制引用
张智,姜秋喜,孙志勇..基于改进平方根UKF双向滤波的单站无源定位算法[J].火力与指挥控制,2015,(3):116-120,5.
