Simultaneous Localization, Calibration, and Tracking in an ad Hoc Sensor Network
MASSACHUSETTS INST OF TECH CAMBRIDGE COMPUTER SCIENCE AND ARTIFICIAL INTELLIGENCE LAB
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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.
- Operations Research
- Computer Programming and Software
- Target Direction, Range and Position Finding
- Statistics and Probability