Research on Tunable Q-Factor Wavelet Transform Sea Clutter Suppression Algorithm Based on Sparse Representation

摘要

Due to the complex physical mechanism of sea clutter, the detection of maritime targets becomes a problem. To solve the problem, tunable Q-factor wavelet transform (TQWT) sea clutter suppression algorithm based on sparse representation is proposed. The method first uses TQWT to sparsely represent the echo signals and obtains the wavelet coefficients. Then, the basis pursuit clutter suppression algorithm is used to transform it into the optimization problem. And the wavelet coefficients are optimized by the split augmented Lagrangian shrinkage algorithm (SALSA). Finally, the energy selection method is used to select the wavelet coefficients for target reconstruction so as to achieve the purpose of suppressing clutter. Experiments were conducted on the CSIR public data set. The results verified the performance of the algorithm and improved the output signal-to-clutter ratio (SCR).