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Labeled random finite sets vs. trajectory random finite sets

Ronald Mahler

TL;DR

This paper summarizes and augments the main findings of [12], [13]--specifcally, why SoT, PMBM, and TPMBM are physically and mathematically erroneous.

Abstract

The paper [12] discussed two approaches for multitarget tracking (MTT): the generalized labeled multi-Bernoulli (GLMB) filter and three Poisson multi-Bernoulli mixture (PMBM) filters. The paper [13] discussed two frameworks for multitarget trajectory representation--labeled random finite set (LRFS) and set of trajectories (SoT)--and the merging of SoT and PMBM into trajectory PMBM (TPMBM) theory. This paper summarizes and augments the main findings of [12], [13]--specifcally, why SoT, PMBM, and TPMBM are physically and mathematically erroneous.

Labeled random finite sets vs. trajectory random finite sets

TL;DR

This paper summarizes and augments the main findings of [12], [13]--specifcally, why SoT, PMBM, and TPMBM are physically and mathematically erroneous.

Abstract

The paper [12] discussed two approaches for multitarget tracking (MTT): the generalized labeled multi-Bernoulli (GLMB) filter and three Poisson multi-Bernoulli mixture (PMBM) filters. The paper [13] discussed two frameworks for multitarget trajectory representation--labeled random finite set (LRFS) and set of trajectories (SoT)--and the merging of SoT and PMBM into trajectory PMBM (TPMBM) theory. This paper summarizes and augments the main findings of [12], [13]--specifcally, why SoT, PMBM, and TPMBM are physically and mathematically erroneous.
Paper Structure (16 sections, 4 equations)