Subband Maximum Eigenvalue Detection for Radar Moving Target in Sea Clutter

Abstract

In this letter, a cascade algorithm combined subband decomposition with an eigenvalue-based detection scheme is proposed to detect moving targets in sea clutter for the radar system with short pulses. Using a discrete Fourier transform-modulated filter bank, on the one hand, subband decomposition can effectively suppress clutter as well as increase the coherent integration time. On the other hand, it transforms the scene where the target spectrum is separated from the clutter spectrum into the scene where the target spectrum overlaps with the clutter spectrum. In the target subband, the noncoherent method using amplitude difference is more favorable for detection due to the nonobvious phase difference caused by the overlap of the target spectrum and the clutter spectrum. Considering that the maximum eigenvalue can reflect the signal intensity and capture the signal correlations well, the maximum eigenvalue of the covariance matrix is adopted to discriminate the target from the clutter. Finally, the simulation results show that the proposed algorithm achieves superior performance.