引入测速信息的雷达导引头无偏转换跟踪方法

为了满足先进地空导弹对精确弹目交会信息的需求,基于自适应卡尔曼滤波算法,提出了一种引入测速信息的雷达导引头无偏转换跟踪方法。在当前统计模型的基础上,利用递推遗忘最小二乘法估计当前加速度,得到了状态方程。在雷达测量模型的基础上,分析了极坐标系下与笛卡尔坐标系下位置、速度信息的无偏转换关系,推导了无偏转换量测误差协方差矩阵真实值和利用量测信息估计真实值的表达式,得到了量测方程。通过滤波得到的状态和误差估计信息,改进了真实无偏转换量测协方差矩阵的估计算法。仿真结果验证了所提跟踪方法在滤波精度和跟踪速度上的良好性能。

Unbiased converted tracking method of radar seeker with velocity information

For the advanced surface-to-air missile, the accurate information of missile-target encounter is required. Based on the adaptive Kalman filter algorithm, an unbiased converted tracking method of radar seeker with velocity information is proposed. According to the current statistical model, the current acceleration is estimated by recursive least square algorithm with forgetting factor, and the state equation is obtained. By analyzing the unbiased conversion relations of position and velocity information from polar coordinates to Cartesian coordinates, the true unbiased converted measurement covariance and its estimation using measurements are deduced. And the measurement equation is acquired. With the state and error estimation result of filter, the estimation algorithm of the true unbiased converted measurement covariance is improved. The simulation results prove the good performance of the tracking method in both filtering accuracy and tracking speed.