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Sensors 2019, 19(1), 202; https://doi.org/10.3390/s19010202 (registering DOI)

“Statistics 103” for Multitarget Tracking

Random Sets LLC, Eagan, MN 55122, USA
Received: 3 December 2018 / Revised: 24 December 2018 / Accepted: 24 December 2018 / Published: 8 January 2019
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PDF [379 KB, uploaded 18 January 2019]

Abstract

The finite-set statistics (FISST) foundational approach to multitarget tracking and information fusion was introduced in the mid-1990s and extended in 2001. FISST was devised to be as “engineering-friendly” as possible by avoiding avoidable mathematical abstraction and complexity—and, especially, by avoiding measure theory and measure-theoretic point process (p.p.) theory. Recently, however, an allegedly more general theoretical foundation for multitarget tracking has been proposed. In it, the constituent components of FISST have been systematically replaced by mathematically more complicated concepts—and, especially, by the very measure theory and measure-theoretic p.p.’s that FISST eschews. It is shown that this proposed alternative is actually a mathematical paraphrase of part of FISST that does not correctly address the technical idiosyncrasies of the multitarget tracking application. View Full-Text
Keywords: multitarget tracking; random finite set; point process; finite-set statistics multitarget tracking; random finite set; point process; finite-set statistics
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Mahler, R. “Statistics 103” for Multitarget Tracking. Sensors 2019, 19, 202.

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