Poisson multi-Bernoulli conjugate prior for multiple extended object filtering

Understand

This paper presents a Poisson multi-Bernoulli mixture (PMBM) conjugate prior for multiple extended object filtering.

• A Poisson point process is used to describe the existence of yet undetected targets, while a multi-Bernoulli mixture describes the distribution of the targets that have been detected.
• The prediction and update equations are presented for the standard transition density and measurement likelihood.
• Both the prediction and the update preserve the PMBM form of the density, and in this sense the PMBM density is a conjugate prior.