Subband adaptive GLRT-LTD for weak moving targets in sea clutter

Abstract

In this paper, the subband detection scheme, a frequency division tactic to decompose received time series into low-rate subband time series, and the generalized likelihood ratio test linear threshold detector (GLRT-LTD) are combined to form a subband adaptive detector to find weak moving targets in sea clutter by lengthened integration time. To alleviate the conflict between the large number of integrated pulses and limited reference cells constrained by spatial inhomogeneity of sea clutter, a discrete Fourier transform modulated filter bank is used to decompose high-rate sea clutter into low-rate subband clutters. Subband clutters exhibit diversity of non-Gaussianity, and subbands are grouped into noise-dominated subbands of approximate Gaussianity, clutter-noise-mixed subbands of non-Gaussianity, and clutter-dominated subbands of strong non-Gaussianity. The subband compound-Gaussian (CG) model with inverse gamma texture is presented to characterize subband clutters, and a bipercentile method is given to estimate the shape and scale parameters of subband amplitude distributions. The GLRT-LTDs specified by the subband parameters are imposed on individual subbands to optimize detection performance. The experiments show that the subband adaptive GLRT-LTD attains better performance than the subband adaptive normalized matched filter detector, owing to the full exploitation of the subband diversity of the non-Gaussianity of sea clutter.