Research On Multi-component Signal Extraction And Reconstruction Based On Time-frequency Distribution

With the increasingly complex electromagnetic environment in the battlefield,the intercepted radar signal is increasingly complicated.The complexity is reflected in the superimposed components which is modulated differently.To obtain the type and parameters of each component in the complex signals is the key factor of correct identification and efficient interference to each radiation source in strategic decision.To correctly analyze the intercepted multi-component radar signal,component extraction and reconstruction it is inevitable processes.This paper focuses on the extraction and reconstruction of multi-component signals based on the time-frequency representation(TFR)of signals.Firstly,the time-frequency characteristics and sparse characteristics of radar signals are summarized.In addition,the laws of time-frequency analysis of multi-component radar signals is carried out.The inevitable balance between the interference suppression and signal fuzzification in the time-frequency analysis is found.Thus the adaptive direction quadratic TFR is introduced by adaptively selecting the optimal ambiguity domain direction kernel,the ideal equilibrium is achieved between interference suppression and signal fuzzification.Secondly,in order to obtain the component structure of the signal,the instantaneous frequency(IF)estimation algorithm of the signal is studied.It is found that the existing algorithms may be wrong when the cross component exists.Therefore,the gradient rotation method is introduced to enhance the TFR image,and then a connection method based on endpoint gradient and cur ve fitting is proposed.Not only the IF tracking error of the component is eliminated,But also the estimation error is reduced.Finally,based on the estimated IF,the time-varying filtering method is used to separate and reconstruct the individual compon ent.It is found that the time-varying filtering has large distortion at the intersection of the components.Therefore,the amplitude correction algorithm is introduced and a time-varying filtering algorithm based on time-varying order Short-time Fractional Fourier Transform is proposed.The proposed algorithm significantly improves the signal separation and reconstruction performance,especially for the nonlinear frequency modulated signal.In this paper,the adaptive direction TFR algorithm is obtained to deal with the contradiction between cross-term interference and signal-term ambiguity,which achieved a relatively ideal TFR.Then the enhancement algorithm based on rotated gradient and segment connection followed with curve-fitting are proposed to overcome the track error of IF estimation.Finally,a time-varying order Fractional Fourier Transform based time-varying filtering algorithm is proposed to reconstruct the time domain waveform.This paper decomposes the signal separation and reconstruction into four steps: signal modeling,time-frequency analysis,IF extraction and time-varying filtering,which constitutes a complete and effective multi-component radar signal separation and reconstruction scheme.