Computing budget allocation for optimization of sensor processing order in sequential multi-sensor fusion algorithms

Because target tracking is a stochastic process, comparison of different tracking algorithms or parameter sets within one algorithm relies on time-consuming and computationally demanding simulations. In this paper we present a method to minimize simulation time, yet to achieve a desirable confidence...

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Veröffentlicht in:Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148) Jg. 3; S. 1841 - 1847 vol.3
Hauptverfasser: Trailovic, L., Pao, L.Y.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 2001
Schlagworte:
Additive noise
Computational modeling
Computer simulation
Optimization methods
Position measurement
Sensor fusion
Sensor systems
State estimation
Stochastic processes
Target tracking
ISBN:9780780364950, 0780364953
ISSN:0743-1619
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Because target tracking is a stochastic process, comparison of different tracking algorithms or parameter sets within one algorithm relies on time-consuming and computationally demanding simulations. In this paper we present a method to minimize simulation time, yet to achieve a desirable confidence of the obtained results by applying ordinal optimization and computing budget allocation ideas and techniques. The developed method is applied to optimization of sensor processing order in sequential multisensor fusion algorithms.
ISBN:9780780364950
0780364953
ISSN:0743-1619
DOI:10.1109/ACC.2001.946004