Integral track association for laser triangulation sensor in a dense target environment

Correct track association is a prerequisite to a successful track fusion. The association problem may be very diffcult in dense target environments due to the existence of furcation, combination and cross-tracks. After analyzing the physical background of the three cases, an integral track association approach for laser triangulation sensor in the dense target environment is derived. The algorithm makes the association judgment only be performed between the sensor tracks and the system tracks, which greatly reduce the number of the track pairs needed to be judged, and improve the effciency of track association algorithm. The difference degree of two tracks is acquired based on integral idea during the association judgment period, then the track with minimum difference degree is selected as the associated pair, which has considered of the historical and current data and improves association accuracy in the dense target environment. Finally, the algorithm is implemented in the multi-sensor and multi-target environment and the simulation results show the effectiveness and strong robustness of the algorithm in challenging scenarios.