For an airborne passive radar with impure reference signals, the clutter caused by multipath (MP) signals involved in the reference channel (MP clutter) corrupts the space–time adaptive processing performances. To eliminate the influence of the MP clutter, two clutter suppression methods based on reduced-dimension (RD) transformation are proposed herein. RD transformation is exploited to reduce the size of the sparse recovery dictionary. Subsequently, the sparse recovery problem is revised, and the MP clutter is suppressed using the least mean square (LMS) algorithm and the exponentially forgetting window LMS algorithm. Compared with the existing L1-based recursive least square algorithm, the proposed algorithms significantly reduce computational complexity without degrading the MP clutter suppression performance. In addition, the proposed algorithms provide more robust characteristics to the errors in prior knowledge than the modified blind equalization method. A range of simulations is conducted to test the proposed algorithms.

中文翻译：

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基于降维变换的不纯参考信号机载无源雷达杂波抑制方法

对于具有不正确参考信号的机载无源雷达，参考通道中涉及的多径（MP）信号引起的杂波（MP杂波）会破坏时空自适应处理性能。为了消除MP杂波的影响，提出了两种基于降维（RD）变换的杂波抑制方法。利用RD转换来减少稀疏恢复字典的大小。随后，修正了稀疏恢复问题，并使用最小均方（LMS）算法和指数遗忘窗口LMS算法抑制了MP混乱。与现有的基于L1的递归最小二乘算法相比，所提出的算法在不降低MP杂波抑制性能的情况下，显着降低了计算复杂度。此外，与改进的盲均衡方法相比，所提出的算法为先验知识中的错误提供了更鲁棒的特性。进行了一系列仿真以测试所提出的算法。