Phased Array Diagnostics by TR-MUSIC Approach by a Reduced Set of Measurements

Mario Del Prete
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Abstract

In this paper, the problem of planar phased array antenna diagnostics from near-field measurements is addressed by a Time Reversal-MUltiple SIgnal Classification (TR-MUSIC) based algorithm using a steering diversity. It is shown that the number of degrees of freedom limits the diagnostic scenarios in which the TR-MUSIC works. A difference model allows to overcome this limitation and at the same time can reduce the data required for diagnostics. Finally, numerical examples show the effectiveness of the proposed method.
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基于简化测量集的TR-MUSIC相控阵诊断方法
针对平面相控阵天线的近场诊断问题,提出了一种基于时间反向多信号分类(TR-MUSIC)的转向分集算法。结果表明,自由度的数量限制了TR-MUSIC工作的诊断场景。差异模型可以克服这一限制,同时可以减少诊断所需的数据。最后,通过数值算例验证了该方法的有效性。
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