Ecolocation: a sequence based technique for RF localization in wireless sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Statistical location detection with sensor networks
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
MoteTrack: a robust, decentralized approach to RF-based location tracking
Personal and Ubiquitous Computing
Relative location estimation in wireless sensor networks
IEEE Transactions on Signal Processing
Model-free probabilistic localization of wireless sensor network nodes in indoor environments
MELT'09 Proceedings of the 2nd international conference on Mobile entity localization and tracking in GPS-less environments
Statistical anomaly detection with sensor networks
ACM Transactions on Sensor Networks (TOSN)
Posture detection with body area networks
Proceedings of the 6th International Conference on Body Area Networks
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We present a robust localization system allowing wireless sensor networks to determine the physical location of their nodes. The coverage area is partitioned into regions and we seek to identify the region of a sensor based on observations by stationary clusterheads. Observations (e.g., signal strength) are assumed random. We pose the localization problem as a composite multihypothesis testing problem, develop the requisite theory, and address the problem of optimally placing clusterheads. We show that localization decisions can be distributed by appropriate in-network processing. The approach is validated in a testbed yielding promising results.