On point processes in multitarget tracking
Ronald Mahler

TL;DR
This paper critically examines the foundations of point process methods in multitarget tracking, revealing that non-RFS approaches are flawed, and clarifies the relationship between FISST and other purported frameworks, exposing misattributions and errors.
Contribution
It demonstrates that non-RFS point processes are incorrect for multitarget tracking and clarifies that the so-called point process approach is essentially a rephrasing of FISST with misattributions.
Findings
Non-RFS point processes are phenomenologically incorrect for multitarget tracking.
Most equations and concepts in JAIF appeared originally in FISST publications.
FISST is not due to Moyal and the point process approach is a rephrasing of FISST.
Abstract
The finite-set statistics (FISST) approach to multitarget tracking was introduced in the mid-1990s. Its current extended form dates from 2001. In 2008, an "elementary" alternative to FISST was proposed, based on "finite point processes" rather than RFS's. This was accompanied by single-sensor and multisensor versions of a claimed generalization of the PHD filter, the "iFilter." Then in 2013 in the Journal of Advances in Information Fusion (JAIF) and elsewhere, the same author went on to claim that the FISST p.g.fl./functional derivative approach is actually "due to" (a "corollary" of) a 50-year-old pure-mathematics paper by Moyal; and described a "point process" p.g.fl./functional derivative approach to multitarget tracking supposedly based on it. In this paper it is shown that: (1)non-RFS point processes are a phenomenologically erroneous foundation for multitarget tracking; (2) nearly…
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Taxonomy
TopicsTarget Tracking and Data Fusion in Sensor Networks · Time Series Analysis and Forecasting · Water Systems and Optimization
