Aiming at the problems that the radar tracking and occupies data processing resources are affected by the residual clutter after target detection,a radar clutter suppression method based on genetic algorithm (GA) optimized back propagation (BP) neural network is proposed.By analyzing the differentiated features of radar target plots and clutter plots,multi-dimensional features are selected as input independent variables,and BP neural network classifier model is designed to classify radar target plots and clutter plots,so as to filter clutter.During the data input, genetic algorithm is used to optimize the input independent variables of neural network to reduce the dimension of input data and shorten the modeling time.During the neural network training process,GA is used to optimize the initial weights and thresholds of BP neural network to improve the network convergence speed and recognition accuracy.Tests on radar measured data show that:the BP neural network optimized by genetic algorithm has a 1.5% increase in the recognition rate of radar clutter plots and a 20.4% reduction in recognition time compared with the traditional BP neural network.