Method of radar detecting small signal based on genetic algorithm and neural network

被引：0
|
作者：
Lv, Q [1 ]
Li, JX [1 ]
Ma, XY [1 ]
机构：
[1] Acad Armored Force Engn, Beijing 100072, Peoples R China
来源：
ICEMI 2005: Conference Proceedings of the Seventh International Conference on Electronic Measurement & Instruments, Vol 4 | 2005年
关键词：
signal detection; genetic algorithm; neural network; feature extraction; NONSTATIONARY ENVIRONMENT; CLUTTER; CLASSIFICATION;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
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 GA-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.
引用
收藏
页码：390 / 395
页数：6
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