MIMO radar target classification using complex-valued BP learning algorithm

This article studies the multi-target classification issues of multiple-input multiple-output (MIMO) radar, a complexvalued back-propagation (CV-BP) network structure with the cross-entropy cost function is designed. The complexvalued echo signals captured by MIMO radar are pre-processed to provide more data for the classification, and then the pre-processed complex-valued data is directly selected as the recognition feature, combined with the CV-BP network to classify multiple targets. This scheme can not only effectively avoid the process of target feature extraction manually, but also improve the accuracy of classification by utilizing the amplitude and phase information of the target. The simulation results demonstrate the effectiveness and robustness of the CV-BP scheme under different SNRs.