An antenna subset selection algorithm in distributed MIMO radar for target localization via convolutional neural network

Abstract Since the distributed MIMO radar (DMR) has widely spread transmitters and receivers, it can provide higher target detection probability, as well superior tracking localization performance than monostatic/bistatic systems. An effective resource allocation scheme optimise DMR system parameter obtain better performance. In this paper, a critical but limited is optimised, that is, select subset of active antennas. scenario, convolutional neural network antenna selection for (LCNN‐ASS) algorithm in proposed based on two free switching policies. The immune to failure single policy selects subsets from entire sets with remarkable computational speed. Therefore, increases flexibility scheduling over traditional algorithms. Simulation experiments analysis demonstrate LCNN‐ASS algorithm.