Scan-by-scan averaging and adjacent detection merging to improve ship detection in HFSWR

High Frequency Surface Wave Radars (HFSWRs) play an important role in long-range ocean surveillance, with particular interest in reliable detection and tracking of far-distant ships. One of the biggest challenges in ship target detection in HFSWR is the non-homogeneous detection background. Depending on the chosen detection parameters, this non-homogeneous detection background leads to extensive false alarms or poor detection performance. This paper shows how scan-by-scan averaging can help to reduce a significant number of these false alarms. In addition the problem of target spreading and multiple detections of the same target is addressed by an Adjacent Detection Merging Algorithm (ADMA). Furthermore, it is shown how the result of the ADMA can be used to improve the estimation of target parameters, such as azimuth, Doppler and range.