A fuzzy-based angle-of-arrival estimation system (AES) using radiation pattern reconfigurable (RPR) antenna and modified gaussian membership function

Angle-of-arrival (AOA) estimation is an important factor in various wireless sensing applications, especially localization systems. This paper proposes a new type of AOA estimation sensor node, known as AOA-estimation system (AES) where the received signal strength indication (RSSI) from multiple ra...

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Main Authors: Jais, Mohd. Ilman, Sabapathy, Thennarasan, Jusoh, Muzammil, Ahmad, R. Badlishah, Jamaluddin, Mohd. Haizal, Kamarudin, Muhammad Ramlee, Ehkan, Phaklen, Loganathan, L. Murukesan, Soh, Ping Jack
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2019
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Online Access:http://eprints.utm.my/id/eprint/89070/1/MohdHaizalJamaluddin2019_AFuzzy-BasedAngle-of-ArrivalEstimationSystem.pdf
http://eprints.utm.my/id/eprint/89070/
http://dx.doi.org/10.1109/ACCESS.2019.2945789
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Summary:Angle-of-arrival (AOA) estimation is an important factor in various wireless sensing applications, especially localization systems. This paper proposes a new type of AOA estimation sensor node, known as AOA-estimation system (AES) where the received signal strength indication (RSSI) from multiple radiation pattern reconfigurable (RPR) antennas are used to calculate the AOA. In the proposed framework, three sets of RPR antennas have been used to provide a coverage of 15 regions of radiation patterns at different angles. The salient feature of this RPR-based AOA estimation is the use of Fuzzy Inferences System (FIS) to further enhance the number of estimation points. The introduction of a modified FIS membership function (MF) based on Gaussian function resulted in an improved 85% FIS aggregation percentage between the fuzzy input and output. This later resulted in a low AOA error (of less than 5%) and root-mean-square error (of less than 8°).