Fundamental limits and improved algorithms for linear least-squares wireless position estimation
buir.contributor.author | Gezici, Sinan | |
dc.citation.epage | 1052 | en_US |
dc.citation.issueNumber | 12 | en_US |
dc.citation.spage | 1037 | en_US |
dc.citation.volumeNumber | 12 | en_US |
dc.contributor.author | Guvenc, I. | en_US |
dc.contributor.author | Gezici, Sinan | en_US |
dc.contributor.author | Sahinoglu Z. | en_US |
dc.date.accessioned | 2016-02-08T09:45:15Z | |
dc.date.available | 2016-02-08T09:45:15Z | |
dc.date.issued | 2010-09-22 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description.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. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T09:45:15Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2012 | en |
dc.identifier.doi | 10.1002/wcm.1029 | en_US |
dc.identifier.issn | 1530-8669 | |
dc.identifier.uri | http://hdl.handle.net/11693/21360 | |
dc.language.iso | English | en_US |
dc.publisher | John Wiley & Sons | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1002/wcm.1029 | en_US |
dc.source.title | Wireless Communications and Mobile Computing | en_US |
dc.subject | Cramer-rao lower bound (CRLB) | en_US |
dc.subject | least-squares (LS) estimation | en_US |
dc.subject | Maximum likelihood (ML) | en_US |
dc.subject | Time-of-arrival (TOA) | en_US |
dc.subject | Wireless positioning | en_US |
dc.subject | Cramer-rao lower bound | en_US |
dc.subject | Least Square | en_US |
dc.subject | Linear least squares | en_US |
dc.subject | Lower bounds | en_US |
dc.subject | Maximum likelihood approaches | en_US |
dc.subject | Nonlinear least squares | en_US |
dc.subject | Position estimation | en_US |
dc.subject | Selection algorithm | en_US |
dc.subject | Theoretical limits | en_US |
dc.subject | Time-of-arrival | en_US |
dc.subject | Wireless positioning | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Cramer-Rao bounds | en_US |
dc.subject | Maximum likelihood | en_US |
dc.subject | Estimation | en_US |
dc.title | Fundamental limits and improved algorithms for linear least-squares wireless position estimation | en_US |
dc.type | Article | en_US |
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