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Proceedings Paper

Data compression in emitter location systems via sensor pairing and selection
Author(s): Xi Hu; Mark L. Fowler
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Paper Abstract

Data compression ideas can be extended to assess the data quality across multiple sensors to manage the network of sensors to optimize the location accuracy subject to communication constraints. From an unconstrained-resources viewpoint it is desirable to use the complete set of deployed sensors; however, that generally results in an excessive data volume. We have previously presented here results on selecting pre-paired sensors. We have now extended our results to enable optimal joint pairing/selection of sensors. Pairing and selecting sensors to participate in sensing is crucial to satisfying trade-offs between accuracy and time-line requirements. We propose two methods that use Fisher information to determine sensor pairing/selection. The first method optimally determines pairings as well as selections of pairs but with the constraint that no sensors are shared between pairs. The second method allows sensors to be shared between pairs. In the first method, it is simple to evaluate the Fisher information but is challenging to make the optimal selections of sensors. However, the opposite is true in the second method: it is more challenging to evaluate the Fisher information but is simple to make the optimal selections of sensors.

Paper Details

Date Published: 29 August 2008
PDF: 11 pages
Proc. SPIE 7075, Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications XI, 707502 (29 August 2008); doi: 10.1117/12.796196
Show Author Affiliations
Xi Hu, Binghamton Univ. (United States)
Mark L. Fowler, Binghamton Univ. (United States)


Published in SPIE Proceedings Vol. 7075:
Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications XI
Mark S. Schmalz; Gerhard X. Ritter; Junior Barrera; Jaakko T. Astola, Editor(s)

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