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DOA estimation for sub-array MIMO radar with limited samples

机译:子阵列MIMO雷达的DOA估计有限的样品

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摘要

The problem of DOA estimation for sub-array multiple-input multiple-output radar is concerned. Employing compressive sampling concept and the minimum mean-square error (MMSE) technology, the proposed algorithm alternates between updating sample covariance matrix and the MMSE filter bank values until convergence. Simplified array manifolds are considered to decrease the computational complexity. The core idea of the algorithm is to determine the DOA by calculating the spatial distribution of signal power adaptively. Simulation results show that the new algorithm performs well both in a wide SNR range and limited samples, compared with the MUSIC, PIAA-APES, and OGSBI algorithms. The most outstanding advantage of the new algorithm is that it can maintain high estimation accuracy under limited samples without knowing the number of targets.
机译:涉及子阵列多输入多输出雷达的DOA估计问题。采用压缩采样概念和最小均方误差(MMSE)技术,所提出的算法在更新样本协方差矩阵和MMSE滤波器组值之间交替,直到收敛。简化的阵列歧管被认为是降低计算复杂度。算法的核心思想是通过自适应地计算信号功率的空间分布来确定DOA。仿真结果表明,与音乐,PIAA-APES和OGSBI算法相比,新算法在宽的SNR范围和有限的样品中表现良好。新算法最出色的优势是它可以在有限的样本下保持高估计精度,而不知道目标的数量。

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  • 来源
    《The Journal of Engineering》 |2019年第20期|6413-6416|共4页
  • 作者单位

    AVIC Leihua Elect Technol Res Inst Wuxi Jiangsu Peoples R China;

    AVIC Leihua Elect Technol Res Inst Wuxi Jiangsu Peoples R China;

    AVIC Leihua Elect Technol Res Inst Wuxi Jiangsu Peoples R China;

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  • 正文语种 eng
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