DocumentCode
2018592
Title
Maximizing multi-sensor system dependability
Author
Brooks, R.R. ; Iyengar, S.S.
Author_Institution
Commun. Sci. & Technol. Center, California State Univ., Seaside, CA, USA
fYear
1996
fDate
8-11 Dec 1996
Firstpage
1
Lastpage
8
Abstract
This paper considers distributed sensor systems and finds redundant configurations which maximize dependability while insuring the system remains within cost or weight constraints. Given different sensor modules which fulfil the system´s operational requirements but have different dependability and cost parameters, efficient methods are used to find maximum dependability configurations. These methods limit the search to a constrained subspace of the problem space. It is shown that this region must contain the optimal configuration. Three heuristics: genetic algorithms, simulated annealing and tabu search are used. Experimental results are presented with dependability gains of between 10 and 15%. These test cases compare results from all methods and verify that in most cases the simulated annealing heuristic provides the best solutions
Keywords
genetic algorithms; redundancy; search problems; sensor fusion; simulated annealing; cost constraints; distributed sensor systems; genetic algorithms; maximum dependability configurations; multi-sensor system dependability; operational requirements; redundant configurations; simulated annealing; tabu search; weight constraints; Communications technology; Computer science; Costs; Intelligent sensors; Nuclear magnetic resonance; Redundancy; Sensor fusion; Sensor systems; Sensor systems and applications; Simulated annealing;
fLanguage
English
Publisher
ieee
Conference_Titel
Multisensor Fusion and Integration for Intelligent Systems, 1996. IEEE/SICE/RSJ International Conference on
Conference_Location
Washington, DC
Print_ISBN
0-7803-3700-X
Type
conf
DOI
10.1109/MFI.1996.568492
Filename
568492
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