基于稀疏恢复的 MIMO-STAP干扰样本检测方法

针对机载多输入多输出(MIMO)雷达空时自适应处理(STAP)技术在训练样本存在有源干扰时杂波抑制性能严重下降的问题,提出了一种干扰样本检测方法。首先使用正则化FOCUSS算法估计出各原子的空时功率谱值,接着设置谱值门限将谱值较大的原子取出,然后确定扫描带对空时二维平面进行扫描,最后根据进入扫描带最大原子数占总原子数的比例判别训练样本是否存在干扰。仿真实验表明,该方法可有效检测出训练样本中的干扰,使用该方法挑选出的无干扰训练样本恢复杂波谱可保证空时滤波器的杂波抑制性能,提升稀疏算法求解杂波谱时涉及到的样本的可靠性。

Sample with Jamming Detection Method of MIMO STAP Based on Sparse Recovery

Aimed at the problem that the clutter suppression performance of multiple input multiple output radar space time adaptive processing technology is greatly degraded when the training samples are in jam, a jamming detection method is proposed. This method firstly uses the regularized FOCUSS algorithm to estimate the space time power spectrum of each atom. Next, the spectrum threshold is set to pick up atoms with large values. Then, the scanning band is determined to scan the space time two dimensional plane. Finally, according to the ratio of the maximum number of atoms entering the scanning band to the total number of atoms, a determination can be made whether there is jamming in the training sample. The simulation results show that this method can effectively detect the jamming in the training samples, and the clutter suppression performance of space time filter can be guaranteed by using the training samples selected by this method.