Background-Dependent Adaptive Composite CFAR Detector for Compact High Frequency Surface Wave Radars

Nowadays, most ship surveillance systems utilize phased-array systems. However, majority of employed HFSWRs are of compact type and are mostly used for ocean parameters estimation. This paper covers the development of a ship or vessel detection scheme for compact high frequency surface wave radars configured for remote ocean sensing. The proposed detector exploits the background information generated from a background segmentation process to select which CFAR variant yields optimum performance. A merging algorithm for adjacent detections combined with a local peak detection technique is employed to mitigate the effects of target spreading which is common in radars with long integration time. Preliminary results show that the proposed detector detects possible targets even with severe spreading.