Title :
PHD filters for nonstandard targets, I: Extended targets
Author_Institution :
MS2 Tactical Syst., Adv. Technol. Dept., Lockheed Martin, Eagan, MN, USA
Abstract :
The probability hypothesis density (PHD) and cardinalized PHD (CPHD) filters were introduced in 2000 and 2006, respectively, as approximations of the full multitarget Bayes detection and tracking filter. Both filters are based on the ldquostandardrdquo multitarget measurement model that underlies most multitarget tracking theory. This paper is one of a series of theoretical studies that address PHD and CPHD filters for nonstandard multitarget measurement models. In this paper I derive the measurement-update equations for a PHD filter that presumes a Poisson model for extended targets due to Gilholm, Godsill, Maskell, and Salmond.
Keywords :
Bayes methods; filtering theory; stochastic processes; target tracking; Poisson model; cardinalized PHD filters; multitarget Bayes detection; multitarget measurement model; multitarget tracking theory; nonstandard targets; probability hypothesis density filters; tracking filter; Bayesian methods; Filtering theory; Information filtering; Information filters; Measurement standards; Poisson equations; Probability distribution; Radar tracking; Target tracking; Wireless communication; CPHD filter; PHD filter; extended targets; multi-target tracking; point processes; random sets;
Conference_Titel :
Information Fusion, 2009. FUSION '09. 12th International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
978-0-9824-4380-4
