DocumentCode :
2620799
Title :
Stochastic approximation for optimal observer trajectory planning
Author :
Singh, Sumeetpal ; Vo, Ba-Ngu ; Doucet, Arnaud ; Evans, Robin
Author_Institution :
Dept. of Electr. & Electron. Eng., Melbourne Univ., Vic., Australia
Volume :
6
fYear :
2003
fDate :
9-12 Dec. 2003
Firstpage :
6313
Abstract :
A maneuvering target is to be tracked based on noise corrupted measurements of the target´s state that are received by a moving observer. Additionally, the quality of the target state observations can be improved by the appropriate positioning of the observer relative to the target during tracking. The bearings-only tracking problem is an example of this scenario. The question of optimal observer trajectory planning naturally arises, i.e. how should the observer maneuver relative to the target in order to optimise the tracking performance? In this paper, we formulate this problem as a discrete-time stochastic optimal control problem and present a novel stochastic approximation algorithm for designing the observer trajectory. Numerical examples are presented to demonstrate the utility of the proposed methodology.
Keywords :
approximation theory; discrete time systems; observers; optimal control; path planning; stochastic systems; target tracking; discrete-time stochastic optimal control; maneuvering target; optimal observer trajectory planning; stochastic approximation; Approximation algorithms; Artificial intelligence; Electric variables measurement; Equations; Noise measurement; Observers; Signal processing; Stochastic processes; Target tracking; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
ISSN :
0191-2216
Print_ISBN :
0-7803-7924-1
Type :
conf
DOI :
10.1109/CDC.2003.1272313
Filename :
1272313
Link To Document :
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