摘要
针对一般测量精度下初始状态估计误差大,导致滤波易发散的问题,提出了一种基于解析推导和Leven-berg-Marquardt算法的初始状态估计方法,能够在目标参数测量精度不高的情况下获得比较精确的初始值;针对滤波过程计算量太大、收敛速度慢的问题,结合精确的初始状态估计值和扩展卡尔曼滤波(EKF)实现了前向散射雷达三维目标的精确跟踪.通过仿真和比较分析表明,EKF算法跟踪精度高,收敛速度快,且计算量小.
Aiming to the problem of filtering divergence easily caused by large error of initial state estimation,an accurate initial state estimation approach based on analytic derivation and Levenberg-Marquardt algorithm is presented,which can improve the accuracy of initial state estimation under low accuracy of target parameters measurement.In order to reduce the computation of filtering process and speed up the filtering convergence rate,the combination of accurate initial state estimation and extended Kalman filter(EKF) algorithm is implemented,therefore,a precise 3D target tracking in forward scattering radar(FSR) could be achieved.Through comparative analysis of simulation results,the validity of proposed accurate tracking method is verified.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2012年第9期942-948,共7页
Transactions of Beijing Institute of Technology
基金
国家自然科学基金资助项目(61172177)