Abstract
There is a large error in the actual radar trajectory tracking process. Track initiation is the primary problem in trajectory tracking and the first step in target tracking. The current track initiation algorithms are greatly affected by heavy clutter environments, so it is necessary to propose an algorithm to solve the problem of low track initiation efficiency. This paper presents a track initiation algorithm using a residual threshold in heavy clutter environments. The falling probability of measured value and decision threshold are used to determine the correlation window. The angle limiting condition is added to establish the track association, and the residual threshold is used to further eliminate the false tracks. The initial track experiment with the trajectory data in the sea near Rizhao Port shows that the algorithm is superior to the traditional logic method and Kalman filter method in track quality. The experiment uses the AIS buffer zone to calculate track initiation probability and uses the multi-region AIS trajectory data for verification. The experimental result shows that track initiation probability with the proposed algorithm in this paper can reach 92.31%.
Highlights
In recent years, a large amount of information contained in trajectories has attracted more and more attention with the development of trajectory information collection technology
The track initiation algorithm will consume a lot of time if there are a large number of stationary ships; on the other hand, it refers to other noises in the acquisition process of radar signals, such as ground signals, ocean signals, and signals generated by atmospheric scattering, which have no relation with ship data
The result shows that it has an initial probability of 92.31%, while the traditional logic method has an initial probability of 89%, which indicates the track initiation accuracy can be improved
Summary
A large amount of information contained in trajectories has attracted more and more attention with the development of trajectory information collection technology. To improve the above situation, Sedehi et al proposed an improved M/N logic method [8], which added a restriction to the measured value falling into the correlation window to eliminate the measured points that are V-shaped with the tracks in the state of track initiation It optimizes the track initiation procedure and can be used to detect fast-moving observation targets, reducing the false alarm probability effectively. It decides trajectory quality and starting time by selecting the appropriate transformation equation parameters [9] This method is suitable for the targets in clutter environments, but it is difficult to initialize the tracks of the maneuvering targets due to the characteristics of the algorithm itself. The innovation of the algorithm is that after the track association is established, the residual threshold is added to remove the false tracks that do not meet the conditions, ensuring the quality and accuracy of the track initiation
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