Marine Radar Image Sequence Target Detection Based on Space–Time Adaptive Filtering and Hough Transform

The performance of marine radar target detection is largely affected by the intricate and dynamic space–time variations of sea clutter signals, which cause substantial numbers of false and missed alarms. To improve the target detection performance of rotating scanning marine radar, this study proposes a marine radar image sequence target detection algorithm based on space–time adaptive filtering and the Hough transform algorithm. The algorithm adopts a two-stage approach of coarse detection followed by precise detection. During the coarse detection stage, the sea clutter energy in the 3-D frequency–wavenumber spectrum of the marine radar image sequence is suppressed by a sea clutter suppression algorithm in the space–time domain, space–time clutter suppression (STCS). Subsequently, moving targets are extracted from the image sequence using a target energy extraction method based on the Hough transform algorithm in the 3-D frequency–wavenumber domain. The result is a processed image sequence with sea clutter signal reduction and target signal extraction. The precise detection stage detects the target point in this processed image sequence using a constant false alarm rate method based on a real clutter background distribution model. During verification tests on real X-band marine radar data, the detection probability of the proposed method reaches 99.89% under low sea state, 95.34% under medium sea state, and 94.44% under high sea state. Compared with the WHOS-CFAR and GMOS-CFAR, the average improvement is 10.1% and 16.6%, respectively. Furthermore, compared to the STCS, there is a maximum improvement of 3.7%. The enhancement in detection performance is significant.