UAM-RDE: an uncertainty analysis method for RSSI-based distance estimation in wireless sensor networks
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ORIGINAL ARTICLE
UAM-RDE: an uncertainty analysis method for RSSI-based distance estimation in wireless sensor networks Xiaozhen Yan1,2,3,4 • Pengtai Zhou1,2,3,4 • Qinghua Luo1,2,3,4,5 Cong Hu2
•
Chuntao Wang5 • Jinfeng Ding5
•
Received: 10 June 2019 / Accepted: 6 February 2020 Ó Springer-Verlag London Ltd., part of Springer Nature 2020
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. Keywords Uncertainty analysis Distance estimation Received signal strength indicator Wireless sensor network 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
1 Introduction
& Xiaozhen Yan [email protected]
1
School of Information Science and Engineering, Harbin Institute of Technology at Weihai, No. 2 Wenhua West Road, Weihai 264209, Shandong Province, China
2
The Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin University of Electronic Technology, Guilin 541004, Guangxi Province, China
3
State Key Laboratory of Satellite Navigation Engineering Technology, Shijiazhuang, China
4
The Auto Test and Control Institute, Shandong Institute of Shipping, No. 2 Wenhua West Road, Weihai 264209, Shandong Province, China
5
Shandong New Beiyang Information Technology Co., Ltd., Weihai 264203, Shandong Province, China
& Qinghua Luo [email protected] Pengtai Zhou [email protected] Chuntao Wang [email protected]
In wireless sensor networks (WSNs), wireless distance estimation techniques are widely applied to the fields of wireless localization, wireless navigation, and so on. With the advent of the internet of things era (IOTE), wireless distance estimation techniques have attracted increased attention from the research community and industry [1]. In general, there are four co
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