Cooperative Localization in Wireless Sensor Networks With AOA Measurements
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| Název: | Cooperative Localization in Wireless Sensor Networks With AOA Measurements |
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| Autoři: | Wang, Shengchu, Jiang, Xianbo, Wymeersch, Henk, 1976 |
| Zdroj: | IEEE Transactions on Wireless Communications. 21(8):6760-6773 |
| Témata: | expectation maximization, Approximate message passing, cooperative localization, least square |
| Popis: | This paper researches the cooperative localization in wireless sensor networks (WSNs) with 2 pi/pi-periodic angle-of-arrival (AOA) measurements. Two types of localizers are developed from the perspectives of Bayesian inference and convex optimization. When the orientation angles are known, the positioning problem is resolved by a phase-only generalized approximate message passing (POG-AMP) algorithm with importance sampling mechanism. From the perspective of convex optimization, the positioning problem under 2 pi/pi-periodic AOAs is converted as a least square (LS) problem and then resolved by the gradient-descent/projected gradient-descent method named as TYpe-I LS localizer. When the orientations are unknown, expectation-maximization (EM) mechanism is introduced into the POG-AMP localizer, where node positions and orientations are alternatively updated through exchanging their statistical confidences. Type-II LS localizer is constructed by alternatively executing Type-I LS and a maximum-likelihood (ML) estimator of orientation. Cramer-Rao lower bounds (CRLBs) are derived for the proposed localizers. Simulation results validate that the proposed AMP-type and LS-type localizers outperform existing localizers, AMP-type localizers successfully handle nonlinear quantization losses, and EM-framework and ML estimator handle unknown orientation problem. AMP-type localizers outperform LS-type ones, and can approach to the CRLBs even under high noise contaminations. |
| Přístupová URL adresa: | https://research.chalmers.se/publication/531848 |
| Databáze: | SwePub |
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Nájsť tento článok vo Web of Science | Abstrakt: | This paper researches the cooperative localization in wireless sensor networks (WSNs) with 2 pi/pi-periodic angle-of-arrival (AOA) measurements. Two types of localizers are developed from the perspectives of Bayesian inference and convex optimization. When the orientation angles are known, the positioning problem is resolved by a phase-only generalized approximate message passing (POG-AMP) algorithm with importance sampling mechanism. From the perspective of convex optimization, the positioning problem under 2 pi/pi-periodic AOAs is converted as a least square (LS) problem and then resolved by the gradient-descent/projected gradient-descent method named as TYpe-I LS localizer. When the orientations are unknown, expectation-maximization (EM) mechanism is introduced into the POG-AMP localizer, where node positions and orientations are alternatively updated through exchanging their statistical confidences. Type-II LS localizer is constructed by alternatively executing Type-I LS and a maximum-likelihood (ML) estimator of orientation. Cramer-Rao lower bounds (CRLBs) are derived for the proposed localizers. Simulation results validate that the proposed AMP-type and LS-type localizers outperform existing localizers, AMP-type localizers successfully handle nonlinear quantization losses, and EM-framework and ML estimator handle unknown orientation problem. AMP-type localizers outperform LS-type ones, and can approach to the CRLBs even under high noise contaminations. |
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| ISSN: | 15582248 15361276 |
| DOI: | 10.1109/TWC.2022.3152426 |