Abstract
In order to solve the problem that asynchronous multi-source multi-track cannot be correlated effectively, a trajectory similarity model for asynchronous multi-source multi-track and a track correlation algorithm based on this model are proposed in this paper. Based on the idea of searching potential matched data points under spatial and temporal constraints, the optimal matched point is determined from the sets of nearly matched points by setting spatial and temporal thresholds, and the similarity measure between multi-source trajectories is obtained. The spatial and temporal relation between potential matched points from multi-source trajectories has been totally considered. The temporal slots between potential mapped points are allowed, reducing the complexity sharply and ensuring the trajectory mapping accuracy. Simulated experiment results shows that when applied to a simulated complex multi-target scenario, performance of the proposed algorithm is better than existing methods. Also the proposed algorithm has been applied to bias estimation of sea surveillance radars.
Published Version
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