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"Target Detection in Passive MIMO Radar Networks Based on Moments Space" by Bin Li, Jun Li et al.

This work deals with the issue of target detection in passive multiple-input and multiple-output (MIMO) radar networks. Compared to distributed detection, centralized detection offers better performance but at the cost of high communication and computational costs. To address this issue, we propose a novel moments space based centralized detection method, where the moments of received signal amplitudes are computed as their features, and a low complexity moments space log-likelihood ratio test is proposed. As only the moments need to be sent to the fusion center, the proposed method enjoys low communication and computational costs. Numerical results demonstrate that the proposed method significantly outperforms existing methods in various scenarios. ....

Feature Fusion , Likelihood Ratio Test , Moments Space , Assive Mimo Radar ,