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Proceedings Paper

Enabling self-configuration of fusion networks via scalable opportunistic sensor calibration
Author(s): Murat Uney; Keith Copsey; Scott Page; Bernard Mulgrew; Paul Thomas
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Paper Abstract

The range of applications in which sensor networks can be deployed depends heavily on the ease with which sensor locations/orientations can be registered and the accuracy of this process. We present a scalable strategy for algorithmic network calibration using sensor measurements from non-cooperative objects. Specifically, we use recently developed separable likelihoods in order to scale with the number of sensors whilst capturing the overall uncertainties. We demonstrate the efficacy of our self-configuration solution using a real network of radar and lidar sensors for perimeter protection and compare the accuracy achieved to manual calibration.

Paper Details

Date Published: 27 April 2018
PDF: 13 pages
Proc. SPIE 10646, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII, 106460P (27 April 2018); doi: 10.1117/12.2303964
Show Author Affiliations
Murat Uney, The Univ. of Edinburgh (United Kingdom)
Keith Copsey, Cubica Technology Ltd. (United Kingdom)
Scott Page, Cubica Technology Ltd. (United Kingdom)
Bernard Mulgrew, The Univ. of Edinburgh (United Kingdom)
Paul Thomas, Defence Science and Technology Lab. (United Kingdom)

Published in SPIE Proceedings Vol. 10646:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII
Ivan Kadar, Editor(s)

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