Robust Localization System Using Vector Combination in Wireless Sensor Networks

• Published in: IEEE access Vol. 10; pp. 73437 - 73445
• Main Authors: Kang, Insung, Nam, Haewoon
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Angle of arrival (AOA); Clustering algorithms; communication range; Coordinates; Costs; distance; Global Positioning System; Localization; Location awareness; Measurement methods; Nodes; positioning; Power demand; Prediction algorithms; Robustness; Sensors; vector combination; Wireless networks; wireless sensor network; Wireless sensor networks
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2022.3190409

This paper proposes a vector-based localization system that uses both distance and angle information. In wireless sensor networks, the positions of nodes are commonly determined by a range-based localization system using distance information. If both distance and angle information are available, it is possible to improve the accuracy of estimating the positions of nodes compared to a positioning system with only distance information. Existing studies using distance and angle information assume that all the nodes are directly connected to one another and do not consider a method for measuring angle information between the nodes that are not directly connected. However, this assumption may not be valid for real-world wireless sensor networks especially with a large number of nodes having a limited communication range. The proposed localization algorithm solves this problem by a vector combination that transforms the vectors on the local coordinate system to the network-wide global coordinate system. The proposed algorithm is shown to be robust especially even in a network with 1-edge connectivity. Simulation results show that the proposed algorithm has up to 70% higher positioning accuracy compared to the existing iterative range-based algorithm such as MDS-MAP(C,R).