Abstract
We present a novel scheme for node localization in a Delay-Tolerant Sensor Network (DTN). In a DTN, sensor devices are often organized in network clusters that may be mutually disconnected. Some mobile-robots may be used for data collection from the network clusters. The key idea in our scheme is to use this robot to perform location estimation for the sensor nodes it passes by based on the signal strength of radio messages received from them. Thus we eliminate the processing constraints of static sensor nodes and the need for static reference beacons. Our mathematical contribution is the use of a Robust Extended Kalman Filter (REKF) based state estimator to solve the localization. Compared to the standard extended Kalman filter, REKF is computationally efficient and also more robust, since it does not make any assumptions about the measurement noise. Finally, we have implemented our localization scheme on a hybrid sensor network testbed, and show that it can achieve node localization accuracy within 1m in a large indoor setting.
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Pathirana, P.N., Bulusu, N., Savkin, A.V., Jha, S., Dang, T.X. (2007). Node Localization Using Mobile Robots in Delay-Tolerant Sensor Networks. In: Poovendran, R., Roy, S., Wang, C. (eds) Secure Localization and Time Synchronization for Wireless Sensor and Ad Hoc Networks. Advances in Information Security, vol 30. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-46276-9_4
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DOI: https://doi.org/10.1007/978-0-387-46276-9_4
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