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Design of MIMO radar waveform covariance matrix for Clutter and Jamming suppression based on space time adaptive processing

机译:基于空时自适应处理的杂波抑制干扰MIMO雷达波形协方差矩阵设计

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This paper studies the optimization of waveform covariance matrix (WCM) for airborne multiple-input-multiple-output (MIMO) radar systems in the presence of clutter and jamming. The goal is to enhance the target detection performance by suppressing the clutter and jamming based on space time adaptive processing (STAP). We employ the signal-to-interference-plus-noise ratio (S1NR) as the figure of merit. Assuming a known target steering vector, we recast the WCM design problem into a convex optimization problem. Through a max-min approach, we also make the designed WCM robust to the target steering vector, i.e., we develop a method to design WCM that maximizes the worst-case SINR associated with an uncertainty set. We explicitly derive the target steering vector corresponding to the worst-case SINR and solve the robust design of WCM via convex optimization. Finally, we provide several numerical examples to demonstrate the superiority of the proposed algorithms over the existing methods.
机译:本文研究了在杂波和干扰情况下机载多输入多输出(MIMO)雷达系统的波形协方差矩阵(WCM)的优化。目的是通过基于空时自适应处理(STAP)抑制杂波和干扰来增强目标检测性能。我们采用信号干扰加噪声比(S1NR)作为品质因数。假定目标转向矢量已知,我们将WCM设计问题重铸为凸优化问题。通过最大-最小方法,我们还使设计的WCM对目标转向矢量具有鲁棒性,即,我们开发了一种设计WCM的方法,该方法可以最大化与不确定性集相关的最坏情况SINR。我们显式地得出对应于最坏情况SINR的目标转向矢量,并通过凸优化解决WCM的鲁棒设计。最后,我们提供了几个数值示例来证明所提出的算法优于现有方法的优越性。

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