Sidelobes and Ghost Targets Mitigation Technique for High-Resolution Forward-Looking MIMO-SAR

Adnan Albaba;Marc Bauduin;Adham Sakhnini;Hichem Sahli;André Bourdoux
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Abstract

We propose and analyze an image reconstruction algorithm for high angular resolution with a forward-looking multiple-input multiple-output synthetic aperture radar (FL-MIMO-SAR). This algorithm achieves significant attenuation levels of the sidelobes (SL) and ghosts such as grating lobes (GL) and Doppler left-right ambiguity (DLRA). Aspects such as SAR image reconstruction, high SLs in SAR images, the formation of GLs, DLRA, and the overlapping between DLRA ghosts and nearby GLs are investigated. In addition, different imaging scenarios are simulated using a frequency-modulated continuous wave (FMCW) radar simulator and validated with real measurements using different time-division multiplexing MIMO FMCW radars. The simulation and experimental results show that the proposed algorithm manages to significantly enhance the SAR image by attenuating the SLs and canceling ghosts and ambiguities. Furthermore, the proposed algorithm results in true targets with narrower response patterns, which improves the detectability of targets in the SAR image.
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高分辨率前向瞄准多输入多输出合成孔径雷达(MIMO-SAR)的侧斜和幽灵目标消减技术
我们提出并分析了一种利用前视多输入多输出合成孔径雷达(FL-MIMO-SAR)实现高角度分辨率的图像重建算法。该算法可显著衰减侧叶(SL)和重影,如光栅裂片(GL)和多普勒左右模糊(DLRA)。研究了 SAR 图像重建、SAR 图像中的高 SL、GL 的形成、DLRA 以及 DLRA 重影与附近 GL 的重叠等问题。此外,还使用频率调制连续波(FMCW)雷达模拟器模拟了不同的成像场景,并使用不同的时分复用 MIMO FMCW 雷达进行了实际测量验证。仿真和实验结果表明,所提出的算法能够通过衰减 SL、消除重影和模糊来显著增强合成孔径雷达图像。此外,所提出的算法还能得到具有更窄响应模式的真实目标,从而提高合成孔径雷达图像中目标的可探测性。
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