Source localization based on field signatures:Laboratory ultrasonic validationOA
Source localization based on field signatures:Laboratory ultrasonic validation
Location awareness in wireless networks is essential for emergency services,navigation,gaming,and many other applications.This article presents a method for source localization based on measuring the amplitude-phase distribution of the field at the base station.The existing scatterers in the target area create unique scattered field interference at each source location.The unique field interference at each source location results in a unique field signature at the base station which is used for source localization.In the proposed method,the target area is divided into a grid with a step of less than half the wavelength.Each grid node is characterized by its field signature at the base station.Field signatures corresponding to all nodes are normalized and stored in the base station as fingerprints for source localization.The normalization of the field signatures avoids the need for time synchronization between the base station and the source.When a source transmits signals,the generated field signature at the base station is normalized and then correlated with the stored fingerprints.The maximum correlation value is given by the node to which the source is the closest.Numerical simulations and results of experiments on ultrasonic waves in the air show that the ultrasonic source is correctly localized using broadband field signatures with one base station and without time synchronization.The proposed method is potentially applicable for indoor localization and navigation of mobile robots.
Mahmoud Eissa;Dmitry Sukhanov
Department of Radiophysics,Tomsk State University,Tomsk,634050,Russia||Higher Institute for Applied Sciences and Technology(HIAST),Damascus,31983,SyriaDepartment of Radiophysics,Tomsk State University,Tomsk,634050,Russia
Base stationField signatureFingerprintsLocalizationUltrasonic frequencies
《电子科技学刊》 2024 (003)
47-56 / 10
This work was supported by the Tomsk State University Competitiveness Improvement Program under Grant No.2.4.2.23 IG.
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