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Proceedings Paper

Sensor array calibration via tracking with the extended Kalman filter
Author(s): Volkan Cevher; James H. McClellan
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Paper Abstract

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. In this paper, 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 will align the separate tracks and determine the sensor positions and orientations relative to a reference sensor. Computer simulations show that the algorithm performs well even with noisy DOA estimates at sensors.

Paper Details

Date Published: 22 March 2001
PDF: 10 pages
Proc. SPIE 4385, Sensor Fusion: Architectures, Algorithms, and Applications V, (22 March 2001); doi: 10.1117/12.421122
Show Author Affiliations
Volkan Cevher, Georgia Institute of Technology (United States)
James H. McClellan, Georgia Institute of Technology (United States)


Published in SPIE Proceedings Vol. 4385:
Sensor Fusion: Architectures, Algorithms, and Applications V
Belur V. Dasarathy, Editor(s)

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