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Azimuth Sidelobe Suppression Technique for Near Field MIMO Radar Imaging

机译:用于近场MIMO雷达成像的方位角旁瓣抑制技术

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Multiple-input multiple-output (MIMO) radar is getting more and more applications over the last decade. In near field imaging using a linear MIMO array, the azimuth sampling is non-uniform, resulting in spatially variant point spread function (PSF) over a large imaging zone. In this work, an azimuth sidelobe suppression technique is proposed where apodization or complex amplitude weighting is applied to the multiple channel data prior to image reconstruction. For best sidelobe suppression, the optimal channel weights w_(opt) are obtained through mathematical optimization. The overall process mainly includes three steps. Firstly, the expression of PSF in azimuth is acquired by the azimuth focusing process; Secondly, based on the fact that, for an ideal PSF the maximum value of the mainlobe should be one and the values of sidelobes should be zeros, the problem of finding w_(opt), is mathematically fomulated as an optimization problem; Lastly, by setting proper mainlobe width and sidelobe level, the optimal weights can be solved through convex optimization algorithm. Simulations of a MIMO radar system where channel amplitude-phase error and antenna elements position deviation exist are presented and the performance of the proposed technique is studied.
机译:在过去的十年中,多输入多输出(MIMO)雷达得到越来越多的应用。在使用线性MIMO阵列的近场成像中,方位角采样是不均匀的,从而导致在较大成像区域上出现空间变异点扩展函数(PSF)。在这项工作中,提出了一种方位旁瓣抑制技术,其中在图像重建之前将切趾或复振幅加权应用于多通道数据。为了获得最佳的旁瓣抑制,可通过数学优化获得最佳信道权重w_(opt)。整个过程主要包括三个步骤。首先,通过方位聚焦过程获得方位角中PSF的表达。其次,基于以下事实:对于理想的PSF,主瓣的最大值应为1,旁瓣的值应为零,因此找到w_(opt)的问题在数学上被视为优化问题;最后,通过设置合适的主瓣宽度和旁瓣水平,可以通过凸优化算法求解最优权重。给出了存在信道幅度相位误差和天线元件位置偏差的MIMO雷达系统的仿真,并研究了该技术的性能。

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