摘要
针对双基地前向散射栅栏雷达运动参数估计精度低、易发散的问题,在扩展卡尔曼滤波和不敏卡尔曼滤波基础上,提出了一种新的滤波跟踪算法U EKF.该算法利用不敏卡尔曼滤波对初始误差不敏感的特点实现目标初始捕捉,克服了扩展卡尔曼滤波由于初始估计误差较大而引起的发散问题;然后采用扩展卡尔曼滤波进行目标跟踪保持,克服了目标穿越雷达基线时不敏卡尔曼滤波由于对系统模型的误差敏感而引起估计精度低的问题.
Concerning the problem of low precision and easy divergence in estimation of the moving parameters for objects in the Bistatic Forward Scattering Barrier Radar, a new tracking filter algorithm is presented based on the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). The new filter applies insensitiveness of UKF to initial estimation error to catch the object, which avoids the divergence due to the big error in initial estimation when using EKF, and then uses EKF to keep the tracking of objects,which avoids low precision and divergence due to sensitiveness of UKF to the system model error when the objects traverse the base line. Simulation results show the validity of the algorithm proposed in the paper.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2007年第1期54-58,91,共6页
Journal of Xidian University
基金
国家部委科技预研资助项目(57.7.2.10)
关键词
卡尔曼滤波
前向散射
运动参数估计
Kalman filter
forward scattering
estimation of moving parameters