Abstract:

Due to the complex marine environment and the dense sea-surface targets,radars often face the tough tracking scenarios with a high false alarm rate and high target density.The measurement points originating from clutter and multiple closely-spaced targets appear densely in the detection space.The traditional tracking methods only use the position information,which cannot distinguish the specific source of the measurement well,resulting in serious degradation of the tracking performance.Target returns features can be used to solve the problem without increasing the complexity of the algorithm,but the generalization ability of the features is low.It is necessary to select suitable features according to different radar systems,working scenes and requirements.In this paper,the test statistic and the target radial velocity measurement are used as the target returns features,and the tracking equation is reconstructed so that features can be fully applied in all aspects of tracking.In addition,this paper adopts a "two-level" tracking process,which divides track and candidate track according to track quality.Experimental results show that the proposed method can achieve robust target tracking in the complex multi-target scenarios on the sea surface.

Key words: feature-aided tracking, target tracking, sea clutter, target returns features, tracking systems