摘要
研究在LFM信号波形下把径向速度测量引入Kalman滤波的新方法,分析了LFM信号波形下距离和径向速度测量的统计特性.在分析位置测量更新后状态估计误差与径向速度测量噪声统计相关性的基础上,导出了等价的径向速度测量方程,其测量噪声与位置测量更新后的状态滤波误差统计不相关,由此而得到序贯处理的EKF算法.蒙特卡罗仿真结果表明,采用这一新算法引入径向速度测量,可以有效地消除距离-多普勒耦合引起的偏差,提高状态估计精度,而且其估计性能优于传统的EKF.
A new algorithm is developed to incorporate radial velocity measurement into a Kalman filter for the LFM signal waveform. An analysis is given about the statistical properties of the range and radial velocity measurements. Based on statistical correlation analysis of the radial velocity measurement noise and state estimation errors after position measurements updating, an equivalent radial velocity measurement equation is derived where corresponding measurement noise is uncorrelated with state estimation errors thus obtaining a sequential EKF algorithm. Monte Carlo simulation results show that the new algorithm not only effectively removes the bias caused by the rangeDoppler coupling, but also improves the estimation accuracy and is superior to conventional EKF in its estimation performance.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2002年第6期754-756,777,共4页
Transactions of Beijing Institute of Technology
基金
国防预研项目
