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

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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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Uncertainty analysis method for RSSI-based distance estimation


Wireless sensor networks


Received signal strength indicator


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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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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).

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