Ground Moving Target Identification Based on Neural Network

With the development of science and chip technology, more and more attention is taken on more accurate and more intelligent recognition of the complex targets. Target identification is studied based on neural network method in this paper. Firstly, Wavelet analysis method is used for target feature extraction. 4 layers of wavelet decomposition and reconstruction are done for multiple signals, several groups of feature vectors have been obtained and they constitute the neural network learning sample set. Secondly, by analyzing and comparing a variety of BP algorithm, the resilient BP method is finally selected. Only 16 steps of training are needed to meet the error requirement by the resilient BP learning algorithm. Then, Bp neural network is designed and trained according to the signal characteristics. Finally, a recognition test is carried out. The test results show the recognition rate of 90% for the vehicles and 80% for the personnel.