Analysis of Multipath Effects on Accuracy of Range Estimation Using Received Signal Strength Indicator

Chen, Ming; Xia, Aiming; Zeng, Yi

doi:10.1109/csnt.2014.69

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…Consequently, the measured RSSI values had high uncertainty and fluctuation. To realise accurate localisation, preprocessing of the RSSI values had to be considered [21–23].…”

Section: Uhf Rssi Values Preprocessingmentioning

confidence: 99%

Intelligent learning approach for UHF partial discharge localisation in air‐insulated substations

et al. 2020

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To achieve comprehensive insulation deterioration motoring of power equipment and early fault warning in air‐insulated substations, a data‐driven partial discharge (PD) source localisation method employing noisy ultra‐high frequency (UHF) received signal strength indicator (RSSI) and particle filter is proposed in this study. Compared with the existing UHF time‐difference‐based techniques, UHF wireless sensor arrays and RSSI‐based methods provide an economical and high‐adaptability solution. However, owing to the multi‐pathing and shadowing effects, UHF signal attenuation cannot be modelled. Therefore, a Kalman filter was employed to smoothen the RSSI signal. Furthermore, a semi‐parametric regression model is proposed to achieve a more accurate relationship between the RSSI and the transmission distance. Finally, in contrast to traditional localisation algorithms directly based on the RSSI ranging model, a particle filter was used to achieve higher accuracy. It predicted the best distribution of the position of PD by learning and considering all the system states of the previous moment. The laboratory test was performed within an area of 6 m × 6 m, and the results demonstrate that the mean PD source localisation error was 1.16 m, which gives a potential application for the identification of power equipment with insulation deterioration in a substation, while the accuracy is still needed to be verified further by field tests.

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“…Consequently, the measured RSSI values had high uncertainty and fluctuation. To realise accurate localisation, preprocessing of the RSSI values had to be considered [21–23].…”

Section: Uhf Rssi Values Preprocessingmentioning

confidence: 99%

Intelligent learning approach for UHF partial discharge localisation in air‐insulated substations

et al. 2020

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“…The simplest principle measures the receive-signal strength (RSS), which decreases with increasing transmitter-receiver distance. Unfortunately, the constructive and destructive superposition of multipath propagation results in strong variations of the RSS and, hence, the localization accuracy is poor [5].…”

Section: Introductionmentioning

confidence: 99%

Exchanging Bandwidth With Aperture Size in Wireless Indoor Localization - Or Why 5G/6G Systems With Antenna Arrays Can Outperform UWB Solutions

Sippel

Geiß

Brückner

et al. 2021

IEEE Open J. Veh. Technol.

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The localization of wireless devices in indoor scenarios presents a major challenge because of multipath propagation. Hence, the majority of the research community has focused on increasing the available bandwidth of localization systems, leading to the emergence of the ultra wide band (UWB) radar. However, the hardware implementation of UWB transceivers is challenging itself and, hence, their utilization in commercial low-cost wireless devices is not to be expected in the near future. Hence, instead of evaluating frequency dependent phases via UWB, the measurement of spatially distributed phases represents a valuable alternative. Therefore, this article presents a comparison of phase-difference-of-arrival (PDOA) and time-of-arrival (TOA) systems. For this purpose, we compare the measurement sensitivity, the effects of multipath propagation, and the hardware complexity. Based on the results, the applicability of typical position estimators is discussed. Thereby, we argue that PDOA-based localization with large receiver arrays appears to be the better choice to localize wireless devices, because it enables highly accurate positioning using narrow band signals without elaborated transmitter-receiver synchronization. To validate this, indoor localization measurements are presented and compared with UWB results in extant literature.

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Post Disaster Indoor Position Tracking Device with Pulse Detection in Wireless Sensor Networks

Magwili

Linsangan

Marasigan

et al. 2021

2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environ

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Analysis of Multipath Effects on Accuracy of Range Estimation Using Received Signal Strength Indicator

Cited by 3 publications

References 2 publications

Intelligent learning approach for UHF partial discharge localisation in air‐insulated substations

Intelligent learning approach for UHF partial discharge localisation in air‐insulated substations

Exchanging Bandwidth With Aperture Size in Wireless Indoor Localization - Or Why 5G/6G Systems With Antenna Arrays Can Outperform UWB Solutions

Post Disaster Indoor Position Tracking Device with Pulse Detection in Wireless Sensor Networks

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