We introduce Simultaneous Localization and Tracking (SLAT), the problem of tracking a target in a sensor network while simultaneously localizing and calibrating the nodes of the network. Our proposed solution, LaSLAT, is a Bayesian filter providing on-line probabilistic estimates of sensor locations and target tracks. It does not require globally accessible beacon signals or accurate ranging between the nodes. When applied to a network of 27 sensor nodes, our algorithm can localize the nodes to within one or two centimeters.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/30541 |
| Date | 26 April 2005 |
| Creators | Taylor, Christopher, Rahimi, Ali, Bachrach, Jonathan, Shrobe, Howard |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Format | 18 p., 40655574 bytes, 2128443 bytes, application/postscript, application/pdf |
| Relation | Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory |
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