MANCL: a multi‐anchor nodes collaborative localization algorithm for underwater acoustic sensor networks. Issue 6 (26th November 2014)

• Record Type: Journal Article
• Authors: Han, Guangjie; Zhang, Chenyu; Liu, Tongqing; Shu, Lei
• Is Part Of: Wireless communications and mobile computing. Volume 16:Issue 6(2016)
• Page Start: 682
• Page End: 702
• Publication Date: 2014-11-26
• Subjects: underwater acoustic sensor networks -- three‐dimensional environment -- collaborative localization -- multi‐anchor nodes -- upgrade anchor node; Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1002/wcm.2561
• Languages: English
• ISSNs: 1530-8669

Abstract

Abstract: Localization is an essential and major issue for underwater acoustic sensor networks (UASNs). Almost all the applications in UASNs are closely related to the locations of sensors. In this paper, we propose a multi‐anchor nodes collaborative localization (MANCL) algorithm, a three‐dimensional (3D) localization scheme using anchor nodes and upgrade anchor nodes within two hops for UASNs. The MANCL algorithm divides the whole localization process into four sub‐processes: unknown node localization process, iterative location estimation process, improved 3D Euclidean distance estimation process, and 3D DV‐hop distance estimation process based on two‐hop anchor nodes. In the third sub‐process, we propose a communication mechanism and a vote mechanism to determine the temporary coordinates of unknown nodes. In the fourth sub‐process, we use two‐hop anchor nodes to help localize unknown nodes. We also evaluate and compare the proposed algorithm with a large‐scale localization algorithm through simulations. Results show that the proposed MANCL algorithm can perform better with regard to localization ratio, average localization error, and energy consumption in UASNs. Copyright © 2014 John Wiley & Sons, Ltd. Abstract : The multi‐anchor nodes collaborative localization algorithm divides the whole localization process into four sub‐processes: unknown node localization process, iterative location estimation process, improved three‐dimensional (3D) Euclidean distance estimation process, and 3D DV‐hop distance estimation process based on two‐hop anchor nodes. In the third sub‐process, we propose a communication mechanism and a vote mechanism to determine the temporary coordinates of unknown nodes. In the fourth sub‐process, we use two‐hop anchor nodes to help localize unknown nodes.