Improved position estimation using hybrid TW-TOA and TDOA in cooperative networks
buir.contributor.author | Gezici, Sinan | |
dc.citation.epage | 3785 | en_US |
dc.citation.issueNumber | 7 | en_US |
dc.citation.spage | 3770 | en_US |
dc.citation.volumeNumber | 60 | en_US |
dc.contributor.author | Gholami, M. R. | en_US |
dc.contributor.author | Gezici, Sinan | en_US |
dc.contributor.author | Ström, E. G. | en_US |
dc.date.accessioned | 2016-02-08T09:45:55Z | |
dc.date.available | 2016-02-08T09:45:55Z | |
dc.date.issued | 2012-04-13 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description.abstract | This paper addresses the problem of positioning multiple target nodes in a cooperative wireless sensor network in the presence of unknown turn-around times. In this type of cooperative networks, two different reference sensors, namely, primary and secondary nodes, measure two-way time-of-arrival (TW-TOA) and time-difference-of-arrival (TDOA), respectively. Motivated by the role of secondary nodes, we extend the role of target nodes such that they can be considered as pseudo secondary nodes. By modeling turn-around times as nuisance parameters, we derive a maximum likelihood estimator (MLE) that poses a difficult global optimization problem due to its nonconvex objective function. To avoid drawbacks in solving the MLE, we linearize the measurements using two different techniques, namely, nonlinear processing and first-order Taylor series, and obtain linear models based on unknown parameters. The proposed linear estimator is implemented in three steps. In the first step, a coarse position estimate is obtained for each target node, and it is refined through steps two and three. To evaluate the performance of different methods, we derive the Cramér-Rao lower bound (CRLB). Simulation results show that the cooperation technique provides considerable improvements in positioning accuracy compared to the noncooperative scenario, especially for low signal-to-noise-ratios. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T09:45:55Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2012 | en |
dc.identifier.doi | 10.1109/TSP.2012.2194705 | en_US |
dc.identifier.issn | 1053-587X | |
dc.identifier.uri | http://hdl.handle.net/11693/21409 | |
dc.language.iso | English | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/TSP.2012.2194705 | en_US |
dc.source.title | IEEE Transactions on Signal Processing | en_US |
dc.subject | Cooperative positioning | en_US |
dc.subject | Cramér-Rao lower bound (CRLB) | en_US |
dc.subject | Linear estimator | en_US |
dc.subject | Maximum-likelihood estimator (MLE) | en_US |
dc.subject | Time-difference-of-arrival (TDOA) | en_US |
dc.subject | Time-of-arrival (TOA) | en_US |
dc.subject | Two-way time-of-arrival (TW-TOA) | en_US |
dc.subject | Wireless sensor network | en_US |
dc.subject | Cooperative positioning | en_US |
dc.subject | Linear estimators | en_US |
dc.subject | Lower bounds | en_US |
dc.subject | Maximum-likelihood estimator (MLE) | en_US |
dc.subject | Time-difference-of-arrival | en_US |
dc.subject | Time-of-arrival | en_US |
dc.subject | Maximum likelihood estimation | en_US |
dc.subject | Wireless sensor networks | en_US |
dc.subject | Sensor nodes | en_US |
dc.title | Improved position estimation using hybrid TW-TOA and TDOA in cooperative networks | en_US |
dc.type | Article | en_US |
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