多普勒雷达测量数据的Kalman滤波器设计

Design of a Kalman Filter with Doppler Radar Measurements

研究把多普勒雷达测量数据引入Kalman滤波的新方法.根据测量噪声协方差矩阵的分解导出一种理想的线性测量方程的等价形式,在方向余弦估计和误差补偿的基础上,给出可实现的测量方程及其对应的序贯处理的滤波方程.这种序贯处理结构有助于方向余弦继承位置测量更新带来的性能改善,从而减小其估计误差.蒙特卡罗仿真表明,这种序贯滤波算法,不但可以提高状态估计精度,而且其性能优于传统的推广Kalman滤波.

A new algorithm is developed to incorporate Doppler radar measurements into the Kalman filter. An equivalent formulation of the ideal linear measurement equations is derived from the decomposition of measurement noise covariance matrix. Based on the direction cosines estimation and error compensation, a practical measurement equation and sequential filtering equations are given. This sequential process structure can inherit in the direction cosines a performance improvement from updating position measurements and thus reduce its estimation error. Monte Carlo simulation results show that the sequential filtering algorithm can not only improve the estimation accuracy and its performance is superior to conventional extended Kalman filter.