Paper Info
Title
Theoretical Optimization Of Sensing Area Shape For Target Detection, Barrier Coverage, And Path Coverage
Abstract
This paper investigates target detection, barrier coverage, and path coverage with randomly deployed sensors and analyzes the performance of target detection, barrier coverage, and path coverage using integral geometry. Explicit formulas of their performance are derived. The optimal convex sensing area shape with a power consumption constraint is derived from the explicit formulas. Surprisingly, the optimal convex sensing area for target detection in a convex surveillance area can be different from that for barrier coverage. A slender sensing area is optimal for the former, but a disk-shaped sensing area can be optimal for the latter. Similar results are obtained with the Boolean and probabilistic detection models. A slender sensing area is optimal for the Boolean detection model and one of the probabilistic detection models, whereas the disk-shaped sensing area is optimal for another probabilistic detection model. This paper also derives the most difficult path and target to be detected.
Year
DOI
Venue
2016
10.1587/transcom.2016SNP0005
IEICE TRANSACTIONS ON COMMUNICATIONS
Keywords
Field
DocType
sensor, coverage, integral geometry
Computer science,Path coverage,Computational science,Integral geometry,Distributed computing
Journal
Volume
Issue
ISSN
E99B
9
0916-8516
Citations 
PageRank 
References 
1
0.36
33
Authors
1
Name
Order
Citations
PageRank
Hiroshi Saito116416.39