Introduction - If you have any usage issues, please Google them yourself
The probabilistic multihypothesis tracker (PMHT) is a
target tracking algorithm of considerable theoretical elegance.
In practice, its performance turns out to be at best similar
to that of the probabilistic data association filter (PDAF)
and since the implementation of the PDAF is less intense
numerically the PMHT has been having a hard time finding
acceptance. The PMHT’s problems of nonadaptivity, narcissism,
and over-hospitality to clutter are elicited in this work. The
PMHT’s main selling-point is its flexible and easily modifiable
model, which we use to develop the “homothetic” PMHT
maneuver-based PMHTs, including those with separate and
joint homothetic measurement models a modified PMHT whose
measurement/target association model is more similar to that
of the PDAF and PMHTs with eccentric and/or estimated
measurement models.