Received signal strength localization with an unknown path loss exponent
Received Signal Strength (RSS) measurements obtained at locations in the vicinity of an emitter can be used to estimate the emitter location given a suitable path loss model. For commonly used propagation models, the RSS has a dependence on the emitter to sensor separation, d, of the form P ∝ d -α ,...
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Published in | 2011 24th Canadian Conference on Electrical and Computer Engineering(CCECE) pp. 000456 - 000459 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.05.2011
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Subjects | |
Online Access | Get full text |
ISBN | 9781424497881 1424497884 |
ISSN | 0840-7789 |
DOI | 10.1109/CCECE.2011.6030492 |
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Abstract | Received Signal Strength (RSS) measurements obtained at locations in the vicinity of an emitter can be used to estimate the emitter location given a suitable path loss model. For commonly used propagation models, the RSS has a dependence on the emitter to sensor separation, d, of the form P ∝ d -α , where the path loss exponent, α, is typically between 2 and 4 depending on the terrain. This uncertainty is a problem since a solution for the emitter location obtained using a suboptimal choice of α will suffer from degraded accuracy. To resolve this issue, a near maximum likelihood (ML) estimator for both α and emitter position (x,y) has been developed. By expressing (x,y) in terms of α and substituting the results into the ML-function, the 3-D minimization problem is simplified to 1-D. A simple search in α then gives the (α,x,y) estimates. Simulation experiments corroborate the proposed approach and demonstrate estimation accuracy close to the Cramer-Rao Lower Bound. |
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AbstractList | Received Signal Strength (RSS) measurements obtained at locations in the vicinity of an emitter can be used to estimate the emitter location given a suitable path loss model. For commonly used propagation models, the RSS has a dependence on the emitter to sensor separation, d, of the form P ∝ d -α , where the path loss exponent, α, is typically between 2 and 4 depending on the terrain. This uncertainty is a problem since a solution for the emitter location obtained using a suboptimal choice of α will suffer from degraded accuracy. To resolve this issue, a near maximum likelihood (ML) estimator for both α and emitter position (x,y) has been developed. By expressing (x,y) in terms of α and substituting the results into the ML-function, the 3-D minimization problem is simplified to 1-D. A simple search in α then gives the (α,x,y) estimates. Simulation experiments corroborate the proposed approach and demonstrate estimation accuracy close to the Cramer-Rao Lower Bound. |
Author | Chan, F. Lee, B. H. Inkol, R. Chan, Y. T. |
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Snippet | Received Signal Strength (RSS) measurements obtained at locations in the vicinity of an emitter can be used to estimate the emitter location given a suitable... |
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SubjectTerms | Cramer-Rao bounds Fading Geometry Localization Maximum likelihood estimation received signal strength Receivers Simulation Wireless sensor networks |
Title | Received signal strength localization with an unknown path loss exponent |
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