Improved global optimal association algorithm for ships track

Abstract

For solving the problem of ship track association using data from High Frequency Surface Wave Radar (HFSWR) and Automatic Identification System (AIS), an improved global optimal algorithm is proposed in this paper. In order to increase association tracks from HFSWR more, a HFSWR tracks error correction method is used first. Then the associable tracks set is formed by initial match, which data from these two sensors associated using three parameters. Through these steps, the amount of computation in global optimization algorithm can be reduced, and this also made the algorithm more effective. Furthermore, the one to one track is associated accurately by using global optimal algorithm to associate tracks from HFSWR and AIS. Finally measured data in October 31, 2011 are employed to compare with nearest neighbor (NN) track association algorithm and this improved global optimal algorithm. The result shows that improved global optimal algorithm track association get more associations, and it has better stability than nearest neighbor algorithm especially in more complex situations.