Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Exposure in wireless Ad-Hoc sensor networks
Proceedings of the 7th annual international conference on Mobile computing and networking
Distributed Detection and Data Fusion
Distributed Detection and Data Fusion
A coverage-preserving node scheduling scheme for large wireless sensor networks
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Lightweight time synchronization for sensor networks
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
IEEE Transactions on Computers
Vulnerability of Sensor Networks to Unauthorized Traversal and Monitoring
IEEE Transactions on Computers
Wireless Sensor Networks: An Information Processing Approach
Wireless Sensor Networks: An Information Processing Approach
Spatio-temporal correlation: theory and applications for wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: In memroy of Olga Casals
Probabilistic Coverage in Wireless Sensor Networks
LCN '05 Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary
The coverage problem in a wireless sensor network
Mobile Networks and Applications
Exact distribution of the max/min of two Gaussian random variables
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
The good, bad and ugly: distributed detection of a known signal in dependent Gaussian noise
IEEE Transactions on Signal Processing
Asymptotic locally optimal detector for large-scale sensor networks under the Poisson regime
IEEE Transactions on Signal Processing
IEEE Communications Magazine
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One of the main applications of Wireless Sensor Networks (WSNs) is area monitoring (e.g., environmental monitoring). In such problems, it is desirable to maximize the area coverage which can be achieved by appropriately positioning the sensors (if possible) and/or by increasing the detection range of the sensors. This paper considers the latter. The emphasis is on pairs of closely spaced sensors that can collaborate in order to increase their collective area coverage. The main contribution of this work is to investigate collaborative detection schemes between a pair of sensor nodes and show that the area coverage achieved by each scheme depends on the distance between the two sensors. For closely spaced sensors, we propose the Enhanced Covariance Detector (ECD) that combines the energy and the covariance information from the two nodes by utilizing two different thresholds (one for the energy test statistic and another for the covariance).