27 April 2018 Enabling self-configuration of fusion networks via scalable opportunistic sensor calibration
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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.
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Murat Uney, Murat Uney, Keith Copsey, Keith Copsey, Scott Page, Scott Page, Bernard Mulgrew, Bernard Mulgrew, Paul Thomas, Paul Thomas, } "Enabling self-configuration of fusion networks via scalable opportunistic sensor calibration", Proc. SPIE 10646, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII, 106460P (27 April 2018); doi: 10.1117/12.2303964; https://doi.org/10.1117/12.2303964
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