Improved TQWT for marine moving target detection

Under the conditions of strong sea clutter and complex moving targets, it is extremely difficult to detect moving targets in the maritime surface. This paper proposes a new algorithm named improved tunable Q-factor wavelet transform (TQWT) for moving target detection. Firstly, this paper establishes a moving target model and sparsely compensates the Doppler migration of the moving target in the fractional Fourier transform (FRFT) domain. Then, TQWT is adopted to decompose the signal based on the discrimination between the sea clutter and the target's oscillation characteristics, using the basis pursuit denoising (BPDN) algorithm to get the wavelet coefficients. Furthermore, an energy selection method based on the optimal distribution of sub-bands energy is proposed to sparse the coefficients and reconstruct the target. Finally, experiments on the Council for Scientific and Industrial Research (CSIR) dataset indicate the performance of the proposed method and provide the basis for subsequent target detection.