Prolonging Network Lifetime for Target Coverage in Sensor Networks
WASA '08 Proceedings of the Third International Conference on Wireless Algorithms, Systems, and Applications
Surveillance with wireless sensor networks in obstruction: Breach paths as watershed contours
Computer Networks: The International Journal of Computer and Telecommunications Networking
IEEE Transactions on Wireless Communications
Error analysis of non-collaborative wireless localization in circular-shaped regions
Computer Networks: The International Journal of Computer and Telecommunications Networking
Mobile element assisted cooperative localization for wireless sensor networks with obstacles
IEEE Transactions on Wireless Communications
A grid-based coverage approach for target tracking in hybrid sensor networks
Journal of Systems and Software
Employing energy-efficient patterns for coverage problem to extend the network lifetime
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part IV
International Journal of Ad Hoc and Ubiquitous Computing
Sensing task assignment via sensor selection for maximum target coverage in WSNs
Journal of Network and Computer Applications
ACM Transactions on Embedded Computing Systems (TECS) - Special issue on embedded systems for interactive multimedia services (ES-IMS)
Primal and dual-based algorithms for sensing range adjustment in WSNs
The Journal of Supercomputing
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Target tracking and localization are important applications in wireless sensor networks. Although the coverage problem for target detection has been intensively studied, few consider the coverage problem from the perspective of target localization. In this paper, we propose two methods to estimate the lower bound of sensor density to guarantee a bounded localization error over the sensing field. We first convert the coverage problem for localization to a conventional disk coverage problem, where the sensing area is a disk centered at the sensor. Our results show that the disk coverage model requires 4 times more sensors for localization compared to detection applications. We then introduce the idea of sector coverage to tighten the lower bound. The lower bound derived through sector coverage is 2 times less than through disk coverage. A distributed sector coverage algorithm is then proposed in this paper. Compared to disk coverage, sector coverage requires more computations. However, it provides more accurate density estimations than the disk model. Numerical evaluations show that the density bound derived through our sector coverage model is tight.