%0 Journal Article %T 基于分段时空约束航迹匹配算法的海上目标信息特征分析算法研究及在围填海监管中的应用
Research on Algorithm for Maritime Target Information Feature Analysis Based on Segmented Spatio-Temporal Constraint Trajectory Matching and Its Application in Sea Reclamation Supervision %A 张莉 %A 谭萌 %A 陈烽 %A 徐晓玮 %A 崔凤娟 %J Adances in Marine Sciences %P 246-254 %@ 2376-4279 %D 2024 %I Hans Publishing %R 10.12677/ams.2024.114027 %X 针对新形势下海洋围填海监管需要,通过对岸基小目标雷达数据和AIS数据原始数据前期处理,建设海上目标原始数据库。在入库数据基础上开展岸基小目标雷达数据和AIS数据融合算法研究,形成24小时为单位的海上目标轨迹融合数据。最后通过对海洋围填海监管高风险区域内海上目标轨迹的特征分析算法研究,甄别异常轨迹船舶,实现对海洋围填海监管高风险区的海上目标连续监管,填补当前山东省海洋围填海监管领域空白。
In response to the needs of marine reclamation supervision under the new situation, a raw database of maritime targets has been established through preliminary processing of shore-based small target radar data and AIS data. Based on the data stored in the database, research has been conducted on data fusion algorithms for shore-based small target radar data and AIS data, resulting in 24-hour maritime target trajectory fusion data. Finally, through research on algorithms for analyzing the characteristics of maritime target trajectories within high-risk areas for marine reclamation supervision, ships with abnormal trajectories are identified, enabling continuous supervision of maritime targets in high-risk areas for marine reclamation supervision and filling the gap in the field of marine reclamation supervision in Shandong Province. %K 分段时空约束航迹匹配算法, %K 海上目标信息特征分析算法, %K 数据融合算法, %K 围填海监管
Segmented Spatio-Temporal Constraint Trajectory Matching Algorithm %K Maritime Target Information Feature Analysis Algorithm %K Data Fusion Algorithm %K Marine Reclamation Supervision %U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=103941