Probabilistic Framework for Sensor Management

A probabilistic sensor management framework is introduced, which maximizes the utility of sensor systems with many different sensing modalities by dynamically configuring the sensor system in the most beneficial way. For this purpose, techniques from stochastic control and Bayesian estimation are co...

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Bibliographic Details
Main Author: Huber, Marco (auth)
Format: Book Chapter
Published: KIT Scientific Publishing 2009
Subjects:
Online Access:Get Fullteks
DOAB: description of the publication
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001 doab_20_500_12854_57004
005 20210211
020 |a KSP/1000012224 
020 |a 9783866444058 
024 7 |a 10.5445/KSP/1000012224  |c doi 
041 0 |a English 
042 |a dc 
100 1 |a Huber, Marco  |4 auth 
245 1 0 |a Probabilistic Framework for Sensor Management 
260 |b KIT Scientific Publishing  |c 2009 
300 |a 1 electronic resource (VI, 159 p. p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a A probabilistic sensor management framework is introduced, which maximizes the utility of sensor systems with many different sensing modalities by dynamically configuring the sensor system in the most beneficial way. For this purpose, techniques from stochastic control and Bayesian estimation are combined such that long-term effects of possible sensor configurations and stochastic uncertainties resulting from noisy measurements can be incorporated into the sensor management decisions. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by-nc-nd/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ 
546 |a English 
653 |a Bayesian estimation 
653 |a decision theory 
653 |a sensor management 
653 |a information theory 
653 |a Gaussian mixtures 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/57004  |7 0  |z DOAB: description of the publication