Based on fractional Fourier transform-tunable Q-factor wavelet transform moving target detection technology

Abstract

Aiming at the problem that sea clutter suppression in the detection of accelerant and weak targets, a Fractional Fourier Transform-Tunable Q-factor Wavelet Transform (FRFT-TQWT) algorithm is proposed. A search criterion based on the maximum standard deviation is proposed to obtain the optimal pout of FRFT, and then the echo signal is processed by optimal FRFT and inverse Fourier transform. The signal is decomposed into different sub-bands through TQWT for optimizing the wavelet coefficients, and an Ikurt feature selection method is used to extract the wavelet coefficients for reconstruction, so as to achieve the separation of the target from sea clutter. Finally, simulation experiments with measured data from IPIX are carried out to verify the effectiveness of the proposed method. Results show that the algorithm proposed in this paper can improve signal-to-clutter ratio (SCR) and effectively detect the marine moving target in a sea clutter environment.