Vessel target detection based on fusion range-Doppler image for dual-frequency high-frequency surface wave radar

被引:14
作者
Ji, Yonggang [1 ,2 ,3 ]
Zhang, Jie [1 ,2 ,3 ]
Wang, Yiming [1 ,2 ,3 ]
Chu, Xiaoliang [1 ,4 ]
机构
[1] SOA, Inst Oceanog 1, Lab Marine Phys & Remote Sensing, Qingdao, Peoples R China
[2] State Ocean Adm, Ocean Telemetry Engn & Technol Res Ctr, Qingdao, Peoples R China
[3] China Aerosp Sci & Technol Corp, Qingdao, Peoples R China
[4] Ocean Univ China, Coll Informat Sci & Engn, Qingdao, Peoples R China
关键词
object detection; Doppler radar; radar imaging; radar detection; marine radar; image fusion; vessel target detection; fusion range-Doppler image; dual-frequency high-frequency surface wave radar; dual-frequency HFSWR; sea clutter; proper threshold values; range-velocity-bearing dimension; R-D fusion image; TRACKING;
D O I
10.1049/iet-rsn.2015.0190
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
High-frequency surface wave radars (HFSWRs) have been used to monitor moving vessel targets within large areas of the coastal ocean. Moreover, a dual-frequency HFSWR can overcome the negative effect of sea clutter on vessel target detection. As only the information of point targets are used in the traditional point association method of dual-frequency HFSWR, it is difficult to select proper threshold values to obtain correct association and fusion results, which will increase the false alarm or miss rate. In this study, it is found that a moving vessel target is shown as an area target rather than a point target in range-Doppler (R-D) image. First, from the characteristic analyses of a vessel target in R-D fusion image, it is concluded that the two constant false alarm rate points of a single vessel target should locate within the same area target in the fusion image when it is detected by both frequencies. Then a new detection method of dual-frequency HFSWR was proposed on a fusion R-D image level. Finally, the proposed method is validated with the measured HFSWR data, and the results show that it can obtain more reliable association results than the traditional point association method.
引用
收藏
页码:333 / 340
页数:8
相关论文
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