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      • Department of Electrical and Electronics Engineering
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      Fundamental limits and improved algorithms for linear least-squares wireless position estimation

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      Author
      Guvenc, I.
      Gezici, Sinan
      Sahinoglu Z.
      Date
      2010-09-22
      Source Title
      Wireless Communications and Mobile Computing
      Print ISSN
      1530-8669
      Publisher
      John Wiley & Sons
      Volume
      12
      Issue
      12
      Pages
      1037 - 1052
      Language
      English
      Type
      Article
      Item Usage Stats
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      128
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      Abstract
      In this paper, theoretical lower bounds on performance of linear least-squares (LLS) position estimators are obtained, and performance differences between LLS and nonlinear least-squares (NLS) position estimators are quantified. In addition, two techniques are proposed in order to improve the performance of the LLS approach. First, a reference selection algorithm is proposed to optimally select the measurement that is used for linearizing the other measurements in an LLS estimator. Then, a maximum likelihood approach is proposed, which takes correlations between different measurements into account in order to reduce average position estimation errors. Simulations are performed to evaluate the theoretical limits and to compare performance of various LLS estimators.
      Keywords
      Cramer-rao lower bound (CRLB)
      least-squares (LS) estimation
      Maximum likelihood (ML)
      Time-of-arrival (TOA)
      Wireless positioning
      Cramer-rao lower bound
      Least Square
      Linear least squares
      Lower bounds
      Maximum likelihood approaches
      Nonlinear least squares
      Position estimation
      Selection algorithm
      Theoretical limits
      Time-of-arrival
      Wireless positioning
      Algorithms
      Cramer-Rao bounds
      Maximum likelihood
      Estimation
      Permalink
      http://hdl.handle.net/11693/21360
      Published Version (Please cite this version)
      http://dx.doi.org/10.1002/wcm.1029
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      • Department of Electrical and Electronics Engineering 3597
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