Distributed online localization in sensor networks using a moving target
Proceedings of the 3rd international symposium on Information processing in sensor networks
Simultaneous localization, calibration, and tracking in an ad hoc sensor network
Proceedings of the 5th international conference on Information processing in sensor networks
Simultaneous adaptive localization of a wireless sensor network
ACM SIGMOBILE Mobile Computing and Communications Review
A collaborative approach to in-place sensor calibration
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
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Starting with a randomly distributed sensor array with unknown sensor orientations, array calibration is needed before target localization and tracking can be performed using classical triangulation methods. We assume that the sensors are only capable of accurate direction of arrival (DOA) estimation. The calibration problem cannot be completely solved given the DOA estimates alone, since the problem is not only rotationally symmetric but also includes a range ambiguity. Our approach to calibration is based on tracking a single target moving at a constant velocity. In this case, the sensor array can be calibrated from target tracks generated by an extended Kalman filter (EKF) at each sensor. A simple algorithm based on geometrical matching of similar triangles aligns the separate tracks and determines the sensor positions and orientations relative to a reference sensor. Computer simulations show that the algorithm performs well even with noisy DOA estimates at the sensors.