Fundamental Limits of Wideband Localization - Part I: A General Framework
Name
Shen-2010-Fundamental Limits I.pdf
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1.07 MB
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Adobe PDF
Checksum (MD5)
e65ea83e4ec7f129822d37cde2e25d77
Author(s)
Shen, Yuan
Win, Moe Z.
Date Issued
September 2010
Journal
IEEE Transactions on Information Theory
Publisher
Institute of Electrical and Electronics Engineers
Citation
Shen, Yuan, and Moe Z. Win. “Fundamental Limits of Wideband Localization Part I: A General Framework.” IEEE Transactions on Information Theory 56.10 (2010) : 4956-4980. © Copyright 2011 IEEE
Version
Final published version
Abstract
The availability of position information is of great importance in many commercial, public safety, and military applications. The coming years will see the emergence of location-aware networks with submeter accuracy, relying on accurate range measurements provided by wide bandwidth transmissions. In this two-part paper, we determine the fundamental limits of localization accuracy of wideband wireless networks in harsh multipath environments. We first develop a general framework to characterize the localization accuracy of a given node here and then extend our analysis to cooperative location-aware networks in Part II. In this paper, we characterize localization accuracy in terms of a performance measure called the squared position error bound (SPEB), and introduce the notion of equivalent Fisher information (EFI) to derive the SPEB in a succinct expression. This methodology provides insights into the essence of the localization problem by unifying localization information from individual anchors and that from a priori knowledge of the agent's position in a canonical form. Our analysis begins with the received waveforms themselves rather than utilizing only the signal metrics extracted from these waveforms, such as time-of-arrival and received signal strength. Hence, our framework exploits all the information inherent in the received waveforms, and the resulting SPEB serves as a fundamental limit of localization accuracy.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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DOI of Published Version
https://doi.org/10.1109/tit.2010.2060110
