LFM Signal Parameter Estimation Method Based on CNN-FRFT Under Impulsive Noise
The impulse noise destroys the fractional spectrum characteristics of linear frequency modulation(LFM)signal,so the parameter estimation method based on the fractional spectrum characteristics cannot esti-mate the parameters effectively.To solve this issue,a LFM signal parameter estimation method under impulsive noise environment was proposed based on CNN-FRFT.Firstly,the alpha-stable distribution was used to fit the random impulse noise,and the additive noisy signal was constructed and input into CNN for training and tes-ting.Secondly,the trained CNN model was used to denoise the signal,and the ability of denoising and generali-zation of CNN model was verified.Finally,the fractional spectrum of the denoised signal was established using FRFT,and the parameters of LFM signal were estimated by the position of the peak point.Experimental results showed that the proposed method had better accuracy and noise robustness in the strong impulsive noise environ-ment in comparison with the traditional method based on nonlinear function.The application of CNN made the proposed method a stronger generalization ability with the measured impulse noise.
impulse noiselinear frequency modulation signalparameter estimationconvolutional neural net-workfractional Fourier transform
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