Performance Analysis of Centroid and SVD Features for Personnel Recognition Using Multistatic Micro-Doppler


During this letter, we tend to investigate the utilization of micro-Doppler signatures experimentally recorded by a multistatic radar system to perform recognition of folks walking. 3 different sets of features are tested, taking under consideration the impact on the classification performance of parameters, like facet angle, types of classifier, different values of signal-to-noise ratio, and totally different ways that of exploiting multistatic info. High classification accuracy of on top of 98% is reported for the most favorable aspect angle, and the benefit of using multistatic data at less favorable angles is discussed.

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