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Performance Evaluation of Non-GPS Based Localization Techniques under Shadowing Effects

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posted on 2024-11-15, 14:10 authored by Ngoc M Nguyen, Le Chung TranLe Chung Tran, Farzad Safaei, Son Lam PhungSon Lam Phung, Peter VialPeter Vial, Nam Huynh, Anne CoxAnne Cox, Theresa HaradaTheresa Harada, Johan BarthelemyJohan Barthelemy
Non-GPS localization has gained much interest from researchers and industries recently because GPS might fail to meet the accuracy requirements in shadowing environments. The two most common range-based non-GPS localization methods, namely Received Signal Strength Indicator (RSSI) and Angle-of-Arrival (AOA), have been intensively mentioned in the literature over the last decade. However, an in-depth analysis of the weighted combination methods of AOA and RSSI in shadowing environments is still missing in the state-of-the-art. This paper proposes several weighted combinations of the two RSSI and AOA components in the form of pAOA + qRSSI, devises the mathematical model for analyzing shadowing effects, and evaluates these weighted combination localization methods from both accuracy and precision perspectives. Our simulations show that increasing the number of anchors does not necessarily improve the precision and accuracy, that the AOA component is less susceptible to shadowing than the RSSI one, and that increasing the weight of the AOA component and reducing that of the RSSI component help improve the accuracy and precision at high Signal-to-Noise Ratios (SNRs). This observation suggests that some power control algorithm could be used to increase automatically the transmitted power when the channel experiences large shadowing to maintain a high SNR, thus guaranteeing both accuracy and precision of the weighted combination localization techniques.

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Citation

N. Mai. Nguyen, L. Tran, F. Safaei, S. Lam. Phung, P. Vial, N. Huynh, A. Cox, T. Harada & J. Barthelemy, "Performance Evaluation of Non-GPS Based Localization Techniques under Shadowing Effects," Sensors, vol. 19, pp. 2633-1-2633-21, 2019.

Journal title

Sensors (Switzerland)

Volume

19

Issue

11

Language

English

RIS ID

136223

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