Echo Detection of LFM Signal under Strong Reverberation Background Based on Blind Source Extraction

In the detection of submerged and buried targets in shallow sea area by active sonar, bottom reverberation is the main background interference, which seriously affects the detection of LFM signal echo. Pre-whitening algorithm based on Autoregressive (AR) model can adapt to matching detection, but the detection effect is not ideal at low signal-to-reverberation ratio. Fractional domain filtering algorithm based on fractional Fourier transform (FRFT) can suppress reverberation, but the detection performance decreases rapidly with the enhancement of reverberation. An improved blind source extraction algorithm based on linear prediction (LP-BSE) is proposed in this paper. By utilizing the prior knowledge of strong correlation between the Signal to be extracted and the transmitted signal, the parameters of the corresponding linear predictor are estimated and fixed by the least square method. Then, by constructing the minimum mean square prediction error criterion, the de-mixing vector is iteratively obtained to extract the desired echo for matching detection. The simulation results show that the algorithm has better matching detection effect and is more robust. Combining LP-BSE with FRFT to form a joint method, the matching detection effect is further improved.