卡尔曼滤波在雷达偏差估计应用中的改进

为实时跟踪整个雷达网内各雷达的方位偏差和测距偏差的幅度变化，可利用卡尔曼滤波数据存储量小、便于实时处理的特点，用卡尔曼滤波算法对雷达方位偏差和测距偏差幅度进行实时跟踪，并在实际处理的过程中改进噪声计算方法，克服噪声线性化的问题，对实时估计雷达方位偏差和测距偏差非常有效。通过MATLAB仿真得到验证，改进后的雷达方位偏差和测距偏差的估计值比改进前更精确，并且收敛速度提高了2倍，结果表明，此方法既简单又快速、估计值更精确。

Improving Kalman Filter Method in Application to Radar Error Estimation

In order to track the change of each radar＇s azimuth error and distance error of radar network in real time, from the feature of small storage volume in Kalman filter, We select Kalman filter algorithm to track the changing magnitude of each radar＇s azimuth error and distance error, and we improve noise data calcula- tion method in the process of calculation, so as to solve the problem during noise linearization. Simulation proves that the estimation of improved Kalman filter method is more accurate than that of old estimation method, and a very important feature is that the convergence rate of the algorithms is increased by two times.