Targets, sensors and infinite-horizon tracking optimality

Eric Feron; Christian Olivier

doi:10.1109/cdc.1990.204032

Targets, sensors and infinite-horizon tracking optimality

Eric Feron, Christian Olivier

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Scopus citations

Abstract

The problem of optimally scheduling various measurement sensors in a multiple-target tracking application is addressed. A short review of state filtering fundamentals using the Kalman filtering formalism is given. It is pointed out that the infinite-horizon optimality scheduling problem is closley related to the definition of some invariants and to the construction of a characteristic fractal set. Iteratively building an approximation of this set results in quasi-optimal finite-length sensor allocation sequences.

Original language	English (US)
Title of host publication	Proceedings of the IEEE Conference on Decision and Control
Publisher	Publ by IEEEPiscataway
Pages	2291-2292
Number of pages	2
DOIs	https://doi.org/10.1109/cdc.1990.204032
State	Published - Jan 1 1990
Externally published	Yes

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10.1109/cdc.1990.204032

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title = "Targets, sensors and infinite-horizon tracking optimality",

abstract = "The problem of optimally scheduling various measurement sensors in a multiple-target tracking application is addressed. A short review of state filtering fundamentals using the Kalman filtering formalism is given. It is pointed out that the infinite-horizon optimality scheduling problem is closley related to the definition of some invariants and to the construction of a characteristic fractal set. Iteratively building an approximation of this set results in quasi-optimal finite-length sensor allocation sequences.",

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N2 - The problem of optimally scheduling various measurement sensors in a multiple-target tracking application is addressed. A short review of state filtering fundamentals using the Kalman filtering formalism is given. It is pointed out that the infinite-horizon optimality scheduling problem is closley related to the definition of some invariants and to the construction of a characteristic fractal set. Iteratively building an approximation of this set results in quasi-optimal finite-length sensor allocation sequences.

AB - The problem of optimally scheduling various measurement sensors in a multiple-target tracking application is addressed. A short review of state filtering fundamentals using the Kalman filtering formalism is given. It is pointed out that the infinite-horizon optimality scheduling problem is closley related to the definition of some invariants and to the construction of a characteristic fractal set. Iteratively building an approximation of this set results in quasi-optimal finite-length sensor allocation sequences.

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U2 - 10.1109/cdc.1990.204032

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M3 - Conference contribution

SP - 2291

EP - 2292

BT - Proceedings of the IEEE Conference on Decision and Control

PB - Publ by IEEEPiscataway

ER -

Targets, sensors and infinite-horizon tracking optimality

Abstract

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