Abstract:

Target occlusion is a common problem in multiple extended target tracking.When the distance between targets is close or there are unknown obstacles within the scanning range of the sensor,the phenomenon of partial or complete occlusion of the target will occur,resulting in underestimation of the target quantity.Aiming at the problem that the existing Poisson multi-Bernoulli mixture(PMBM) filtering algorithms cannot perform stable tracking in occlusion scenarios,this paper proposes a GP-PMBM algorithm incorporating fuzzy inference.First,based on the random set target tracking framework,the corresponding extended target occlusion model is given according to different occlusion scenarios.On this basis,the state space of the GP-PMBM filter is expanded,and the influence of occlusion on the target state is taken into account in the filtering steps of the algorithm by adding variable detection probability.Finally,a fuzzy inference system that can estimate the target occlusion probability is constructed and combined with the GP-PMBM algorithm,and the accurate estimation of the target in occlusion scenarios is achieved with the help of the description ability of the fuzzy system and the good tracking performance of the PMBM filter.Simulation results show that the tracking performance of the proposed algorithm in target occlusion scenarios is better than that of the existing PMBM filtering algorithms.

Key words: poisson multi-Bernoulli mixture filtering, fuzzy inference, occlusion scenario, target tracking