In multitarget scenarios, the masking of small targets by large targets nearby may severely deteriorate radar detectability due to the range and Doppler sidelobes. In this article, a 2-D joint iterative adaptive filtering (2-D JIAF) method is proposed, by adopting the reiterative minimum mean square error (RMMSE) criterion to the outputs of a 2-D matched filter. The main advantages of the proposed method over the state-of-the-art (SOTA) methods, including modified adaptive multipulse compression and iterative adaptive approach, are twofold: 1) it is able to suppress the sidelobes in both range and Doppler dimensions and thus obtain an improved range-Doppler image; 2) the computational complexity is significantly reduced by adopting a small processing window in both range and Doppler dimensions. The derivation of 2-D JIAF is detailed and an efficient two-stage implementation is outlined. The performance of 2-D JIAF is validated with simulation results over a wide range of scenarios and compared with two SOTA approaches. The impacts of different parameters, including the number of iterations and the choice of the size of the processing window, are also extensively studied with Monte Carlo trials.

中文翻译：

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基于二维联合迭代自适应滤波的快速旁瓣抑制


在多目标场景中，由于距离和多普勒旁瓣，附近大目标对小目标的掩盖可能会严重降低雷达的可探测性。本文提出了一种二维联合迭代自适应滤波（2-D JIAF）方法，对二维匹配滤波器的输出采用迭代最小均方误差（RMMSE）准则。与最先进的（SOTA）方法（包括改进的自适应多脉冲压缩和迭代自适应方法）相比，所提出的方法的主要优点有两个：1）它能够抑制距离和多普勒维度上的旁瓣，并且从而获得改进的距离多普勒图像； 2）通过在距离和多普勒维度上采用较小的处理窗口，显着降低了计算复杂度。详细介绍了 2-D JIAF 的推导，并概述了高效的两阶段实现。 2-D JIAF 的性能通过各种场景的仿真结果进行了验证，并与两种 SOTA 方法进行了比较。不同参数的影响，包括迭代次数和处理窗口大小的选择，也通过蒙特卡罗试验进行了广泛的研究。