杂波先验知识未确知场景下 MIMO雷达收发联合优化
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TN911. 23

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国家自然科学基金(61401526)、河南省科技攻关项目(192102210239)资助


Joint optimization of MIMO radar transmit code and receive weight with the imperfect clutter prior knowledge
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    摘要:

    针对杂波初始估计误差导致多输入多输出(MIMO)雷达检测稳健性较差的问题,提出了发射波形与接收权联合优化方 法以改善 MIMO 雷达检测稳健性。 杂波误差凸集、波形恒模特性和相似约束下,基于最大化输出信干噪比准则,首先构建了改 善最差情况下 MIMO 雷达检测性能的极大极小联合优化问题;而后,为求解所得 NP-hard 问题,将其分解为内外层子问题,并交 替迭代求解。 与不相关信号、非稳健及现有稳健方法相比,数值仿真验证了所提方法的有效性。

    Abstract:

    Aiming at the issue of poor robustness of multiple-input multiple-output (MIMO) radar detection caused by the initial clutter estimation error, a joint robust optimization approach of transmitted waveform and received weight is proposed here to improve MIMO radar detection robustness. With the constraints of clutter error convex set, the transmitted waveform constant envelop characteristic and the similarity, the min-max joint optimization problem can be firstly constructed to improve the worst-case detection performance of MIMO radar on the basis of the criterion of maximizing the output signal to interference noise ratio (SINR); After that, in order to solve the resultant NP-hard problem, this issue is decomposed into the internal and external sub-problems, and these two sub-problems can be solved alternately. In comparison with the non-robust and existing robust algorithms as well as unrelated signals, numerical simulation verifies the efficacy of the developed approach.

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姚 遥,夏长林,李 琼.杂波先验知识未确知场景下 MIMO雷达收发联合优化[J].电子测量与仪器学报,2020,34(6):117-123

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  • 在线发布日期: 2023-11-20
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