JOURNAL ARTICLE

Accurate range-free ANN-based localization in wireless sensor networks

Abstract

We propose a novel range-free localization algorithm for wireless sensor networks (WSN)s that is robust against the anisotropic signal attenuation induced by fading, shadowing, and interference, etc., present in any wireless channel, and hereby develop a new distance estimation (DE) approach able to efficiently derive distances' estimates in closed form. Exploiting artificial neural networks (ANN)s, we also develop a power-efficient DE correction mechanism that properly accounts for anisotropic signal attenuation. Simulation results show that the proposed algorithm significantly outperforms most representative range-free localization algorithms, not only in accuracy, but also in robustness against anisotropic attenuation.

Keywords:
Robustness (evolution) Attenuation Computer science Fading Wireless sensor network Shadow mapping Wireless Artificial neural network Range (aeronautics) Interference (communication) Wireless network SIGNAL (programming language) Algorithm Channel (broadcasting) Electronic engineering Artificial intelligence Telecommunications Engineering Computer network Physics

Metrics

4
Cited By
0.26
FWCI (Field Weighted Citation Impact)
14
Refs
0.62
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Underwater Vehicles and Communication Systems
Physical Sciences →  Engineering →  Ocean Engineering
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence

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