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Method of Radar Detecting Small Signal Based on Genetic Algorithm and Neural Network

机译:基于遗传算法和神经网络的雷达检测方法

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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.
机译:为了在低SNR中执行有效的雷达小信号检测,建立了信号处理模型。在该模型中,利用白化过程和特征分解频率估计来定义区分小信号的特征因素,然后通过使用遗传算法和GA-RBF神经网络来优化RBF参数以实现分类,从而进行分类,从而进行小信号检测完成。仿真结果表明,检测概率大大增加以及分类的性能。

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