Time-frequency diagram denoising method for frequency-hopping signals based on local energy thresholding
Traditional denoising methods for frequency-hopping(FH)signals parameter estimation often fail to effectively preserve the boundaries of FH signals in the time-frequency graph,resulting in low accuracy in estimating the time parameters of FH signals.To address this,a denoising method for FH signals time-frequency graphs based on local energy thresholding is proposed.Firstly,to increase the energy proportion of FH signals in the time-frequency graph after short-time Fourier transform,instantaneous frequency operators are used to mark and remove time-frequency coefficients that do not match the frequency of the FH signals as noise.Then,to avoid losing the energy of the FH signals during denoising,a search window is set to locate the area with the highest energy density in the time-frequency graph,and thresholds are adaptively set for denoising based on the energy distribution in different areas.Finally,a synchronous compression method is used to compress the time-frequency coefficients to the position of the local energy centroid,making the boundaries of the FH signals in the time-frequency graph clearer.Experimental results show that this method can simultaneously improve the accuracy of time and frequency parameter estimation of FH signals when the signal-to-noise ratio is greater than-5 dB,with normalized mean square errors below 0.1 and 0.2,respectively.
frequency hopping signalslocal thresholddenoisinginstantaneous frequency operator
万方数据
维普
