Nonparametric obstruction detection for UWB localization
Paper i proceeding, 2009

Ultra-wide bandwidth (UWB) transmission is a promising technology for indoor localization due to its fine delay resolution and obstacle-penetration capabilities. However, the presence of walls and other obstacles introduces a positive bias in distance estimates, severely degrading localization accuracy. We have performed an extensive indoor measurement campaign with FCC-compliant UWB radios to quantify the effect of non-line-of-sight (NLOS) propagation. Based on this campaign, we extract key features that allow us to distinguish between NLOS and LOS conditions. We then propose a nonparametric approach based on support vector machines for NLOS identification, and compare it with existing parametric (i.e., model-based) approaches. Finally, we evaluate the impact on localization through Monte Carlo simulation. Our results show that it is possible to improve positioning accuracy relying solely on the received UWB signal.

Support vector machine


NLOS identification


Stefano Maranò

Eidgenössische Technische Hochschule Zürich (ETH)

Wesley Gifford

Massachusetts Institute of Technology (MIT)

Henk Wymeersch

Chalmers, Signaler och system, Kommunikation, Antenner och Optiska Nätverk

Moe Win

Massachusetts Institute of Technology (MIT)

2009 IEEE Global Telecommunications Conference, GLOBECOM 2009; Honolulu, HI; United States; 30 November 2009 through 4 December 2009

978-142444148-8 (ISBN)


Elektroteknik och elektronik





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