Title :
Method of radar detecting small signal based on adaptive genetic algorithm and neural network
Author :
Baojing, Sun ; Ziran, Wang ; Wei, Pan
Author_Institution :
Electr. Detection Dept., Shenyang Artillery Acad., Shenyang, China
Abstract :
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 AGA-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.
Keywords :
frequency estimation; genetic algorithms; radar computing; radar detection; radial basis function networks; AGA-RBF neural network; adaptive genetic algorithm; classification performance; detection probability; feature decomposition frequency estimation; radar signal detection; signal-processing model; whitening process; Adaptive signal detection; Background noise; Biological neural networks; Frequency; Genetic algorithms; Jamming; Neural networks; Radar detection; Signal detection; Signal processing; Adaptive genetic algorithm; Feature extraction; Neural network; Signal detection;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5192893
