13 April 2009 Target tracking for randomly varying number of targets and sensors using random finite set theory
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Abstract
Variation in the number of targets and sensors needs to be addressed in any realistic sensor system. Targets may come in or out of a region or may suddenly stop emitting detectable signal. Sensors can be subject to failure for many reasons. We derive a tracking algorithm with a model that includes these variations using Random Finite Set Theory (RFST). RFST is a generalization of standard probability theory into the finite set theory domain. This generalization does come with additional mathematical complexity. However, many of the manipulations in RSFT are similar in behavior and intuition to those of standard probability theory.
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Andreas M. Ali, Ralph E. Hudson, Kung Yao, "Target tracking for randomly varying number of targets and sensors using random finite set theory", Proc. SPIE 7345, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2009, 73450L (13 April 2009); doi: 10.1117/12.820425; https://doi.org/10.1117/12.820425
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KEYWORDS
Sensors

Failure analysis

Motion models

Probability theory

Signal detection

Picosecond phenomena

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