Distributed GGIW-CPHD-Based Extended Target Tracking Over a Sensor Network

Multiple extended target tracking (METT) is a common and challenging problem. Various solutions for METT have been proposed, however, most of them focus on the single-sensor or centralized multi-sensor scenarios. In this letter, we explore the multi-sensor METT problem in a distributed fusion framework. Specifically, there are two stages in the implementation process: 1) to perform a
Gamma Gaussian Inverse Wishart Cardinalized Probability Hypothesis Density
(GGIW-CPHD) filter for each sensor node, and 2) to perform a fusion by resorting to the so-called
Generalized Covariance Intersection
(GCI) fusion rule. In the fusion stage, we derive an approximate GGIW mixture form of the fused spatial density. Lastly, simulation experiments via a consensus sensor network are provided to verify the effectiveness of the proposed approach.