Bearing estimation of low SNR linear frequency-modulated signal

The linear frequency-modulated (LFM) signal is a type of pulse compression signal widely used in the active sonar system. The bearing estimation of the LFM signal is important in the field of underwater acoustic signal processing. While there are strong interferences and background noise, the signal to noise ratio (SNR) of LFM signal may be so low that its bearing cannot be estimated correctly. Aiming to solve this problem, the concise fractional Fourier transform (CFRFT) filter is proposed to combine with the conventional beamforming (CBF) in this paper. The CFRFT can gather energy of the LFM signal in certain frequency as a pulse peak in specific angle. Thus, by transforming the signal received by sensors of horizontal array with CFRFT and filtering the pulse peak out of CFRFT spectrum in an extremely narrow bandwidth, the interference and the background noise can be dislodged partly. And then, the new time domain signal can be obtained after transforming the filtered pulse peak with inverse CFRFT. With this method, the SNR of target signal in the new time domain can be improved efficiently; therefore, the bearing estimation result of LFM signal can be more accurate. Numerical simulation and experimental results show that, the proposed method has better performance in eliminating the interference and the background noise mangled with the LFM signal so that the efficient bearing estimation result can be obtained.