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提出了基于混沌理论的混响中目标回波提取新方法。该方法主要得益于一种新的预测模型,该模型基于径向基函数神经网络,综合利用了时间序列的前向和后向预测,解释了该模型用于混沌信号分离的基本原理,用几种混沌时间序列分析了该模型用于混沌信号建模和谐波信号提取的性能。该方法用于湖试混响中目标回波提取的结果表明:该模型可以用于提取信混比不小于1dB的目标回波。
A new method of target echo extraction in reverberation based on chaos theory is proposed. The method is mainly due to a new prediction model based on radial basis function neural network, making use of forward and backward prediction of time series, explains the basic principle of the model for chaotic signal separation, using Several chaotic time series analyzes the performance of the model for chaotic signal modeling and harmonic signal extraction. The proposed method can be used to extract target echoes from the reverberant test. The results show that the proposed method can be used to extract target echoes with a signal-to-noise ratio of no less than 1dB.