基于概率数据关联的雷达导引头抗速度拖引干扰算法

针对在速度拖引干扰下, 脉冲多普勒雷达导引头无法精确跟踪、制导目标的问题, 提出了基于概率数据关联的抗速度拖引干扰算法。对于雷达导引头角度测量信息和Doppler测量信息, 采用序贯扩展卡尔曼滤波算法进行目标状态估计。根据Doppler信息强非线性的特点构建了伪量测信息, 并提出了在Doppler量测更新滤波估计阶段，采用概率数据关联算法进行抗速度拖引干扰。给出了算法的推导过程, 并进行了数值仿真验证。仿真结果表明, 采用该算法能够稳定跟踪释放多重速度拖引干扰的目标, 有效抑制速度拖引干扰对制导信息估计的影响, 改善导弹的制导精度。

Algorithm for countering velocity gate pull-off jamming of radar seeker based on probability data association

Considering the problem that pulse Doppler(PD)radar seeker could not track and guide target precisely in the presence of velocity gate pull-off(VGPO)jamming,an algorithm for countering VGPO based on probability data association(PDA)is proposed.For the angle and Doppler measurements of radar seeker,the sequential extended Kalman filter(SEKF)is used to estimate the target state.According to the strong nonlinear characteristics of Doppler measurement,the pseudo-measurement information is constructed,and the method of using the probability data association algorithm to counter VGPO in the phase of Doppler measurement update is proposed.The derivation process of the algorithm is given and the algorithm is verified by numerical simulation.The simulation results show that the algorithm proposed can track the target stably under multiple VGPO jamming,suppress the influence of VGPO on guidance information estimation effectively,and improve the guidance accuracy of the missile.