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UAM-RDE: an uncertainty analysis method for RSSI-based distance estimation in wireless sensor networks

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Abstract

Distance estimation between sensor nodes is crucial to localization and object tracking in a wireless sensor network. The received signal strength indicator is widely used for wireless distance estimation, because of its advantages, including availability, low cost, flexibility, and so on. As is well known, RSSI measurement values are extremely susceptible to the surroundings, resulting in uncertain distance estimations. Without confidential information, the distance estimation results could not provide valuable priori information for follow-up processing methods and applications, such as localization, navigation, and guidance. In this paper, we propose a new uncertainty analysis method for RSSI-based distance estimation (UAM-RDE) to study the uncertainty propagation in RSSI-based distance estimations. In UAM-RDE, we explore the uncertainty propagation mechanism from the input to the output of the RSSI-based distance estimation, including uncertainty factor analysis, sensitivity analysis, propagation, and synthesis of uncertainty. The simulations and experimental results validate and demonstrate the feasibility of UAM-RDE.

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Abbreviations

UAM-RDE:

Uncertainty analysis method for RSSI-based distance estimation

WSNs:

Wireless sensor networks

RSSI:

Received signal strength indicator

TOA:

Time of arrival

TDOA:

Time difference of arrival

AOA:

Angle of arrival

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Acknowledgements

This work is partly supported by the National Natural Science Foundation of China (61671174, 61601142, and 51909039), the Natural Science Foundation of Shandong Province of China (ZR2015FM027, ZR2014FM023), Weihai Research Program of Science and Technology, the key lab of Weihai, the engineering center of Shandong province, the Laboratory of Satellite Navigation System and Equipment Technology (EX166840037, EX166840044), the Guangxi Key Laboratory of Automatic Detecting Technology and Instruments (YQ14205, YQ15203), the Natural Scientific Research Innovation Foundation of the Harbin Institute of Technology (HIT.NSRIF.2015122, HIT.NSRIF.201721), the Space Science and Technology Foundation (2017-HT-HG-16), and the Discipline Construction Guiding Foundation in Harbin Institute of Technology (Weihai) (WH20150211).

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Authors and Affiliations

  1. School of Information Science and Engineering, Harbin Institute of Technology at Weihai, No. 2 Wenhua West Road, Weihai, 264209, Shandong Province, China

    Xiaozhen Yan, Pengtai Zhou & Qinghua Luo

  2. The Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin University of Electronic Technology, Guilin, 541004, Guangxi Province, China

    Xiaozhen Yan, Pengtai Zhou, Qinghua Luo & Cong Hu

  3. State Key Laboratory of Satellite Navigation Engineering Technology, Shijiazhuang, China

    Xiaozhen Yan, Pengtai Zhou & Qinghua Luo

  4. The Auto Test and Control Institute, Shandong Institute of Shipping, No. 2 Wenhua West Road, Weihai, 264209, Shandong Province, China

    Xiaozhen Yan, Pengtai Zhou & Qinghua Luo

  5. Shandong New Beiyang Information Technology Co., Ltd., Weihai, 264203, Shandong Province, China

    Qinghua Luo, Chuntao Wang & Jinfeng Ding

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  1. Xiaozhen Yan
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  2. Pengtai Zhou
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  3. Qinghua Luo
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  4. Chuntao Wang
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  5. Jinfeng Ding
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  6. Cong Hu
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Correspondence to Xiaozhen Yan or Qinghua Luo.

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Yan, X., Zhou, P., Luo, Q. et al. UAM-RDE: an uncertainty analysis method for RSSI-based distance estimation in wireless sensor networks. Neural Comput & Applic 32, 13701–13714 (2020). https://doi.org/10.1007/s00521-020-04777-y

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  • DOI: https://doi.org/10.1007/s00521-020-04777-y

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