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在电扫描或机械扫描雷达中均可利用Kalman滤波方法进行跟踪。Kalman滤波形成的跟踪回路是对目标进行偏零跟踪,它与伺服跟踪回路并联工作。Kalman滤波的状态估计作为雷达测得的座标输出,同时还作为伺服系统复合控制信号,实现计算机辅助跟踪。 为了提高精度和解决模型设计与目标实际运动的差异而引起的问题,文中提出用均值和方差联合检测及直接修改增益矩阵的自适应方法,经实验性相控阵雷达飞行试验表明,这种方法比不用自适应的常系数跟踪系统具有更好的效果。
Kalman filtering can be used for tracking both in electro-scanning or mechanical scanning radars. The tracking loop formed by Kalman filtering is a zero-tracking of the target, which works in parallel with the servo tracking loop. Kalman filter state estimation as the radar output measured by the coordinates, but also as a composite servo system control signals to achieve computer-aided tracking. In order to improve the accuracy and solve the problem caused by the difference between the model design and the actual target movement, this paper presents a joint detection of mean and variance and the adaptive method of directly modifying the gain matrix. The experimental phased array radar flight test shows that this method Compared with the constant coefficient tracking system without self-adaption, it has a better effect.