基于CRPF的MIMO雷达目标检测前跟踪算法

A tracking before detecting algorithm based on CRPF with MIMO radar

摘要:

在对机动弱目标进行检测过程中，由于回波信号含有杂波、干扰等噪声，其统计特性未知，难以对回波信号进行数学建模，无法得到后验概率密度函数，传统的粒子滤波算法性能大幅下降。针对此问题，提出了基于代价参考粒子滤波的MIMO雷达目标检测前跟踪算法。该算法无需背景噪声的统计特性，只需利用目标状态的估计值与真实值之间的差值计算各粒子的代价和权值，避免了通过对噪声进行建模来求得后验概率密度的问题。实验仿真证明，当噪声统计特性未知时，所提算法检测跟踪性能明显优于传统粒子滤波算法。

Abstract:

In the detection of maneuvering weak targets, the statistical characteristics are unknown and the echo signal is difficult to model for the clutter and interference in the echo signal, so the posterior probability density function can’t be obtained and the performance of traditional particle filter algorithm decreases. Aiming at this problem, target detection before track algorithm with MIMO radar based on cost reference particle filter. The algorithm does not require of the statistical characteristics of the background noise. The difference between the true value and the estimated value of the target state is used to calculate the cost and weight of each particle, the posterior probability density doesn’t require the model of noise. Simulation results show that the proposed algorithm is superior to the traditional particle filter algorithm when the noise statistics are unknown.