Multisensor-multitarget tracking algorithms are typically based on numerous statistical independence assumptions. This paper is the fifth in a series aimed at weakening such assumptions. It addresses the statistics of correlated, simultaneously evolving multitarget populations. The correlation between two multitarget popula-tions is approximately modeled using bivariate i.i.d.c. (independent, identically distributed cluster) distributions. Based on this, a joint tracking filter for such populations is devised, in analogy with the cardinalized probability hypothesis density (CPHD) filter.

Date Published: 17 May 2016
PDF: 12 pages
Proc. SPIE 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV, 98420C (17 May 2016); doi: 10.1117/12.2224640

Published in SPIE Proceedings Vol. 9842:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXV
Ivan Kadar, Editor(s)