RSS-Based Byzantine Fault-Tolerant Localization Algorithm Under NLOS Environment

Localization is one of the most critical tasks in wireless sensor networks, but achieving a relatively accurate location estimation is challenging when there have Byzantine fault and non-line-of-sight (NLOS) bias simultaneously. In this context, a localization method, based on received signal streng...

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Vydáno v:IEEE communications letters Ročník 25; číslo 2; s. 474 - 478
Hlavní autoři: Mei, Xiaojun, Wu, Huafeng, Xian, Jiangfeng, Chen, Bowen
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.02.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Approximation algorithms
Bias
Byzantine fault
Electronic mail
Fault tolerance
Fault tolerant systems
generalized trust region sub-problem (GTRS)
Iterative methods
Localization
Localization method
Noise measurement
non-line-of-sight (NLOS)
Probability density function
received signal strength (RSS)
Regularization
sensor networks
Signal strength
Target localization
Wireless networks
Wireless sensor networks
ISSN:1089-7798, 1558-2558
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Shrnutí:Localization is one of the most critical tasks in wireless sensor networks, but achieving a relatively accurate location estimation is challenging when there have Byzantine fault and non-line-of-sight (NLOS) bias simultaneously. In this context, a localization method, based on received signal strength (RSS), is proposed in this letter to mitigate the impact of Byzantine fault and NLOS bias on the localization accuracy of wireless sensor networks. The proposed method relies on a Byzantine fault-tolerant localization algorithm (BFLA), which converts the localization problem into a generalized trust-region subproblem (GTRS) by applying certain approximations. In order to obtain a feasible solution to the GTRS, a block-coordinate update (BCU) function with a regularization term is used to divide the localization problem into two subproblems. An iterative method, whose start-point is obtained by an unconstrained squared-range (USR) algorithm, is then used to obtain a solution. Numerical simulations are carried out to show the effectiveness of the proposed method, compared with the state-of-the-art approaches in different scenarios.
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ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2020.3027904