研究在线性调频波形下把径向速度(多普勒)测量引入Kalman滤波的新方法，分析了距离和径向速度测量的统计特性以及距离-多普勒耦合引起的偏差，给出了位置测量噪声与径向速度测量噪声的协方差，导出了一个等价的径向速度测量方程，其测量噪声与位置测量噪声统计是不相关的，由此得到一个序贯处理的滤波算法。蒙特卡罗仿真表明，通过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，大大提高状态估计的精度，而且其估计性能优于传统的推广Kalman滤波。

A new algorithm is developed to incorporate the radial velocity measurement into Kalman filter for LFM waveform. An analysis is given about the statistical property of the range and radial velocity measurements. The covariance of position measurement noises and radial velocity measurement noises is given. An equivalent radial velocity measurement equation is derived and associated measurement noise is uncorrelated with position measurement noises. Monte Carlo simulation results show that the new algorithm can not only remove the bias caused by the range-Doppler coupling but also improve estimation accuracy and its performance is superior to conventional EKF.

TN953