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International Journal of Navigation and Observation
Volume 2012 (2012), Article ID 281592, 10 pages
Research Article

A Comparison of Parametric and Sample-Based Message Representation in Cooperative Localization

1Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
2Research Laboratory of Electronics, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
3Department of Computer Engineering, Thai-Nichi Institute of Technology, Bangkok 10250, Thailand
4Department of Signals and Systems, Chalmers University of Technology, Gothenburg 412 96, Sweden
5Laboratory for Information and Decision Systems, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA

Received 14 April 2012; Accepted 18 July 2012

Academic Editor: Elena Lohan

Copyright © 2012 Jaime Lien et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Location awareness is a key enabling feature and fundamental challenge in present and future wireless networks. Most existing localization methods rely on existing infrastructure and thus lack the flexibility and robustness necessary for large ad hoc networks. In this paper, we build upon SPAWN (sum-product algorithm over a wireless network), which determines node locations through iterative message passing, but does so at a high computational cost. We compare different message representations for SPAWN in terms of performance and complexity and investigate several types of cooperation based on censoring. Our results, based on experimental data with ultra-wideband (UWB) nodes, indicate that parametric message representation combined with simple censoring can give excellent performance at relatively low complexity.