The Application of Alterable Parameter Genetic Algorithm and Neural Network in Artillery Locating Radar Detecting Small Signal

摘要：

　　To perform effective radar small signal detection in low SNR,a signal-processing model is established.In the model,the feature factors that distinguish small signal from noise are defined with whitening process and feature decomposition frequency estimation,then the RBF parameters are optimized by using genetic algorithm and APGA-RBF neural network is formed to realize classification,thereby the small signal detection is completed.Results of simulation show that the detection probability is greatly increased as well as the performance of classification.

关键词： Signal detection Alterable parameter genetic algorithm Neural network Feature extraction

作者: Shangguo Tan Ruidong Hou Wei Pan

作者单位: Electric Detection Department, Shenyang Artillery Academy, Shenyang 110162, China

会议类型: 国际会议

会议名称: 2013 International Conference on Intelligent System,Applied Materials and Control Technology(GSAMCT2013)(2013年智能系统、应用材料和控制技术国际会议)

会议地点: 太原

会议语种:英文

页码: 259-262

在线出版日期: 2013-01-13（万方平台首次上网日期，不代表论文的发表时间）