Ship-based AIS And SAR Synchronous Detection And Synchronization

With the development of economy and society, maritime voyage become more and more frequen.so that, maritime security threats are increasing. Monitoring the vessels become an important effective protection of maritime security. Data are based on AIS and satellite exist many defects:The experiment is collecting vessel data in Dalian Bay area through both systems. There is a time difference between acquiring AIS Information and shooting satellite image. Although the vessel can be fully gotten by AIS, some vessels fail to install the system. Therefore it could not get all boats data; Vessel data from S AR image is comprehensive but incomplete. Due to the presence of image noise, much vessel feature information is not accurate. Current literatures on AIS and satellite images of vessels information fusion algorithms are less, mainly BP neural network algorithm, DR algorithm, the weighted average algorithm, fuzzy fusion algorithm and the evidence synthesis method. This paper analyzes the actual situation and resolves the following issues:characteristics of vessels are not accurate caused by image noise; fuzzy fusion algorithm is not efficient; lack analysis of suspicious vessels.The experiment easily gets vessel information which is round Dalian Bay with using ship AIS equipment. Satellite captures this regional image, making image geometric correction; after that, building a common eigenvectors set. Due to the impact of factors such as image distortion exists, it is a necessary to recalculate image vessel length, location and other characteristics. Then calculate the ratio between the various characteristics boats similarity value basing on the similarity of the formula. After that, improve Fuzzy Fusion:limit Fusion range; select the key feature; make integrate decision. The suspicious vessels are defined as ship that does appear in SAR image and but doesn’t or not precisely find in AIS. Collecting and analyzing the relationship between vessel type and vessel length or width at different period in Dalian Bay. Through performing the new fusion algorithm, the suspicious vessels can be found. These suspicious ships are analyzed and classified by statistical sailing 。vessel data.With the improved fuzzy fusion algorithm, this experiment achieves good results. The experiment fuses a total of thirteen boats and finds five suspicious boats, consistent with the actual situation. Five suspicious vessels are classified. The results are better. The algorithm has been well verified.