Joint multi-target tracking and parameter estimation with the second-order factorial cumulant filter

摘要

This paper presents a low computational complexity solution to the problem of joint multi-target tracking and parameter estimation. The multi-target filtering approach is based on the linear-complexity factorial cumulant filter presented in this conference last year, and the parameter estimation approach is based on the single-cluster point process method for joint multi-object estimation and parameter estimation. The joint multitarget and measurement process is approximated at each step with a Panjer point process, which permits the low cost solution. It is shown in simulated studies the paper that the approach is more robust than using a Poisson point process prior since second-order information is retained and propagated.