Theoretical Optimization of Sensing Area Shape for Target Detection, Barrier Coverage, and Path Coverage
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E99-B No.9 pp.1967-1979
- Publication Date
- 2016/09/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2016SNP0005
- Type of Manuscript
- Special Section PAPER (Special Section on Integration Technologies of Ambient Intelligence and Sensor Networks)
- Category
Authors
Hiroshi SAITO
NTT Corporation
Keyword
Latest Issue
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Hiroshi SAITO, "Theoretical Optimization of Sensing Area Shape for Target Detection, Barrier Coverage, and Path Coverage" in IEICE TRANSACTIONS on Communications,
vol. E99-B, no. 9, pp. 1967-1979, September 2016, doi: 10.1587/transcom.2016SNP0005.
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.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2016SNP0005/_p
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@ARTICLE{e99-b_9_1967,
author={Hiroshi SAITO, },
journal={IEICE TRANSACTIONS on Communications},
title={Theoretical Optimization of Sensing Area Shape for Target Detection, Barrier Coverage, and Path Coverage},
year={2016},
volume={E99-B},
number={9},
pages={1967-1979},
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.},
keywords={},
doi={10.1587/transcom.2016SNP0005},
ISSN={1745-1345},
month={September},}
Copy
TY - JOUR
TI - Theoretical Optimization of Sensing Area Shape for Target Detection, Barrier Coverage, and Path Coverage
T2 - IEICE TRANSACTIONS on Communications
SP - 1967
EP - 1979
AU - Hiroshi SAITO
PY - 2016
DO - 10.1587/transcom.2016SNP0005
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E99-B
IS - 9
JA - IEICE TRANSACTIONS on Communications
Y1 - September 2016
AB - 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.
ER -
English
