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Proceedings Paper

A near-optimal low complexity sensor fusion technique for accurate indoor localization based on ultrasound time of arrival measurements from low-quality sensors
Author(s): Stelios A. Mitilineos; Nick D. Argyreas; Stelios C. A. Thomopoulos
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Paper Abstract

A fusion-based localization technique for location-based services in indoor environments is introduced herein, based on ultrasound time-of-arrival measurements from multiple off-the-shelf range estimating sensors which are used in a market-available localization system. In-situ field measurements results indicated that the respective off-the-shelf system was unable to estimate position in most of the cases, while the underlying sensors are of low-quality and yield highly inaccurate range and position estimates. An extensive analysis is performed and a model of the sensor-performance characteristics is established. A low-complexity but accurate sensor fusion and localization technique is then developed, which consists inof evaluating multiple sensor measurements and selecting the one that is considered most-accurate based on the underlying sensor model. Optimality, in the sense of a genie selecting the optimum sensor, is subsequently evaluated and compared to the proposed technique. The experimental results indicate that the proposed fusion method exhibits near-optimal performance and, albeit being theoretically suboptimal, it largely overcomes most flaws of the underlying single-sensor system resulting in a localization system of increased accuracy, robustness and availability.

Paper Details

Date Published: 11 May 2009
PDF: 11 pages
Proc. SPIE 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII, 73360R (11 May 2009); doi: 10.1117/12.818109
Show Author Affiliations
Stelios A. Mitilineos, National Ctr. for Scientific Research Demokritos (Greece)
Nick D. Argyreas, National Ctr. for Scientific Research Demokritos (Greece)
Stelios C. A. Thomopoulos, National Ctr. for Scientific Research Demokritos (Greece)

Published in SPIE Proceedings Vol. 7336:
Signal Processing, Sensor Fusion, and Target Recognition XVIII
Ivan Kadar, Editor(s)

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