DocumentCode :
875427
Title :
"Statistics 101" for multisensor, multitarget data fusion
Author :
Mahler, Ronald P S
Author_Institution :
Lockheed Martin NE&SS Tactical Syst., Eagan, MN, USA
Volume :
19
Issue :
1
fYear :
2004
Firstpage :
53
Lastpage :
64
Abstract :
This tutorial summarizes the motivations, concepts, techniques, and applications of finite-set statistics (FISST), a system-level, "top-down" direct generalization of ordinary single-sensor, single-target engineering statistics to the multisensor, multitarget realm. FISST provides powerful new conceptual and computational methods for dealing with multisensor, multitarget, and multi-evidence data fusion problems. The paper begins with a broad-brush overview of the basic concepts of FISST. It describes how conventional single-sensor, single-target formal Bayesian modeling is carefully extended to general data fusion problems. We examine a simple example: joint detection and tracking of a possibly non-existent maneuvering target in heavy clutter. The tutorial concludes with a commentary on certain criticisms of FISST.
Keywords :
Bayes methods; probability; radar clutter; sensor fusion; target tracking; tracking filters; Statistics 101 concepts; finite-set statistics; formal Bayesian modeling; heavy clutter; joint detection and tracking; multievidence data fusion; multisensor multitarget data fusion; possibly nonexistent maneuvering target; system-level top-down direct generalization; tutorial; Algorithm design and analysis; Bayesian methods; Data engineering; Power engineering and energy; Power engineering computing; Reliability engineering; Signal processing; Signal processing algorithms; Statistics; Target tracking;
fLanguage :
English
Journal_Title :
Aerospace and Electronic Systems Magazine, IEEE
Publisher :
ieee
ISSN :
0885-8985
Type :
jour
DOI :
10.1109/MAES.2004.1263231
Filename :
1263231
Link To Document :
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