WSN Localization in Smart Cities Using Hybrid (TDOA & RSSI) Localization Techniques with Extended Kalman Filter
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885-907
Digital Object Identifier:
10.58578/ajstea.v2i6.4109
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Authors:Ishiwu Ifeanyichukwu Jude1, Oshiga Omotayo2, Tologon Karataev3, Peter Igba Awunde4, Nusaiba Bashir Kurfi5, Michael Paul Okpe6, Ollor Abee Ejire7, Odivwofene Excel Ogheneovo8
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Abstract
In the context of smart cities, localization technologies are essential for tracking objects in both indoor and outdoor environments. The characteristics of urban settings such as building density, signal interference, and multipath propagation significantly impact the accuracy of localization algorithms. This paper reviews existing localization techniques, categorizing them into range-based and range-free methods, and discusses key algorithms including trilateration, multilateration, and triangulation. We propose a hybrid localization framework that combines Time Difference of Arrival (TDOA) and Received Signal Strength Indicator (RSSI) techniques, enhanced by an Extended Kalman Filter (EKF) for improved accuracy and robustness. Additionally, we present a design architecture for a transmitter and receiver system utilizing Long Range (LoRa) technology, facilitating the development of low-cost, low-power tracking devices that operate independently of Global Positioning System (GPS). Our approach aims to enhance the efficacy of localization in smart city applications, ultimately contributing to improved urban management and safety.
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Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
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