并行MIMO雷达无训练数据的超对称自适应目标检测

Haifeng Yang, Yongliang Wang, W. Xie, Yuanshui Di
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引用次数: 3

摘要

针对对称间隔线阵并置多输入多输出(MIMO)雷达中的自适应目标检测问题,提出了一种基于广义似然比检验(GLRT)准则的自适应检测器。该检测器不需要训练数据,利用了接收信号中的超对称结构。仿真结果表明,在发射波形采样数量适中的情况下,该检测器的性能明显优于传统检测器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Persymmetric adaptive target detection without training data in collocated MIMO radar
For adaptive target detection in a collocated Multiple-input multiple-output (MIMO) radar with a symmetrical spaced linear array, we propose an adaptive detector according to the generalized likelihood ratio test (GLRT) criterion. The proposed detector does not need training data and exploits the persymmetric structures in the receive signal. Simulation results show that the proposed detector significantly outperforms the conventional detectors when the number of the transmit waveform samples is moderate.
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