Development of the Multi-target Tracking Scheme Using Particle Filter

Authors:
Yang Weon Lee
Affiliations:
Department of Information and Communication Engineering, Honam University, Seobongdong, Gwangsangu, Gwangju, 506-714, South Korea
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Year:
2007

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Abstract

This paper introduces a particle filter algorithm determining the measurement-track association problem in multi-target tracking. This scheme is important in providing a computationally feasible alternative to complete enumeration of JPDA which is intractable. We have proved that given an artificial measurement and track's configuration, particle filter scheme converges to a proper plot in a finite number of iterations. Also, a proper plot which is not the global solution can be corrected by re-initializing one or more times. In this light, even if the performance is enhanced by using the particle filter, we also note that the difficulty in tuning the parameters of the particle filter is critical aspect of this scheme. The difficulty can, however, be overcome by developing suitable automatic instruments that will iteratively verify convergence as the network parameters vary.