Research And System Implementation Of AIS And ARPA Trajectory Fusion Method For Fishing Vessel

Fishing vessels are important maritime operation facilities.With the increasing number of maritime operations and the increasing complexity of maritime traffic,illegal operations of fishing vessels occur from time to time.Only through a single fishing vessel trajectory data detection device can no longer meet the management of relevant law enforcement for Marine fishery vessel fishing.Automatic Identification System(AIS)and Automatic Radar Plotting Aid(ARPA)are the detection equipment mainly used to obtain the trajectories of fishing vessels.In order to obtain accurate and complete trajectories of target fishing vessels,analyze their behaviors and provide important basis for the supervision.In this paper,the method of information fusion between AIS and ARPA of fishing vessels is studied in depth.The main research work is as follows:1.AIS trajectory and ARPA trajectory matching of fishing vessels based on temporal spatial constraints and triangle iterative partitioning: The existing trajectory matching algorithms are high complexity and low efficiency for AIS trajectory and ARPA trajectory matching of fishing vessels.In order to solve this problem,a trajectory matching algorithm TSC-TIP(Temporal and Spatial Constraint-Triangle Iterative Partitioning)based on temporal spatial constraint and triangle iterative partitioning is proposed.Firstly,the temporal and spatial constraint algorithm is applied to filter the AIS data within the same spatio-temporal area with the ARPA data.Secondly,the triangle similarity algorithm is used to select the APRA trajectories including the same feature points with the AIS data.Finally,sub-trajectories iterative partitioning algorithm is designed to determine the matched trajectory in which each trajectory is divided into two sub-trajectories and the sub-trajectories are selected iteratively with the triangle similarity algorithm.The experiments on actual AIS trajectory data and ARPA trajectory data are designed to test the performance of the proposed algorithm.The results show that the matching time of the TSC-TIP algorithm reduces95% compared with that of the classical distance-based similarity measurement method without affecting accuracy.2.Trajectory fusion algorithm of AIS and ARPA for fishing vessel based on extended Kalman filter: The existing trajectory fusion methods cause trajectory distortion when trajectory data is lost.A trajectories fusion algorithm of AIS and ARPA for fishing vessels based on extended Kalman filter is proposed.Firstly,a simple fusion structure is used to unify the AIS trajectory and ARPA trajectory onto the same time line,realizing the stitching of the AIS trajectory and ARPA trajectory,and solving the problem of data loss of a single trajectory;Secondly,on the basis of simple fusion,the missing points are filled by linear interpolation,and a complete observation trajectory with equal time interval is fitted.Finally,the kinematic model of the fishing vessel was established,and the extended Kalman filter was used to make full use of the heading and speed information of the fishing vessel trajectory information to correct the observed trajectory,so as to reduce the error caused by the original AIS trajectory points,the original ARPA trajectory points and the linear interpolation points in the simple fusion.The experimental results show that the proposed algorithm can effectively solve the trajectory fusion problem caused by the local loss of AIS and ARPA trajectory data,and has good robustness.3.A trajectory fusion system of AIS and ARPA for fishing vessels based on Spring boot and Vue: At present,most of the fishing vessel trajectory platforms only use AIS trajectory data as the source of fishing vessel trajectory data.When the trajectory data of this device is missing,the target fishing vessel will be lost.To solve this problem,a trajectory fusion system of AIS and ARPA for fishing vessels based on Spring Boot and Vue was designed.In order to make the system have better stability and scalability,the front-end architecture of the system uses Vue framework,and the back-end architecture uses Spring boot framework.The system uses the fishing vessel trajectory matching and trajectory fusion algorithm to take the fused trajectory as the trajectory of the target fishing vessel,so as to solve the problem that the target fishing vessel will be lost when the detection data is partially missing.In order to provide data for regulators more conveniently,based on the fusion of AIS and ARPA trajectories of fishing vessels,the functions of visual operation such as the display of current position of fishing vessels,the query of detailed information of fishing vessels and the display of historical trajectories of fishing vessels are added.