数据采集与处理2013，Vol.28Issue(2)：207-212,6.
基于平方根UKF双向滤波的单站无源定位算法
Single-Observer Passive Location Algorithm Based on Square-Root UKF with Forward-Backward Filtering
摘要
Abstract
The observability and measurement accuracy are low in single observer passive location, so the initial error is usually large. As the unscented Kalman filtering (UKF) in single observer passive location is sensitive to the initial value and its result will divergent because of numerical calculation error, an improved forward-backward smoothing algorithm based on square-root unscented Kalman filter (SRUKF) is presented. To guarantee the stability of the filter, the algorithm uses the covariance square root matrix instead of the covariance matrix in the process of estimation. And the algorithm utilizes backward smoothing to get a more accurate state estimate as an initial condition to improve the robustness of the initial value. Simulation results show that the algorithm has better performance, compared with UFK and SRUKF in the filter's stability, convergence velocity, positioning precision and the robustness to the initial value.关键词
单站无源定位/平方根UKF/后向平滑/非线性滤波Key words
single observer passive location/ square-root unscented Kalman filter/ backward-smoothing/ nonlinear filtering分类
信息技术与安全科学引用本文复制引用
黄耀光,高博,李建新,黄山奇..基于平方根UKF双向滤波的单站无源定位算法[J].数据采集与处理,2013,28(2):207-212,6.基金项目
国家自然科学基金(41174006,61171108)资助项目. （41174006,61171108）
