Research on Optimization Algorithm of Low-Resolution Radar Target Recognition Based on Neural Network

Radar target recognition is an important research direction in the field of radar information processing. Low resolution radar ground target classification and recognition still has broad application prospects in modern military and civil fields. Convolutional neural network (CNN) has attracted more and more attention in the field of radar automatic target recognition, because it does not need Feature Engineering and has superior classification performance. The optimization algorithm of neural network is proposed, and the effects of different network structures on the recognition effect are compared, in this paper. The results show that the multi-scale wide residual network multi-target classification algorithm based on optimized auto-encoder has better recognition effect in low resolution radar target recognition.