Color Filtering Localization for Three-Dimensional Underwater Acoustic Sensor Networks

Sensors

Zhihua Liu²  Han Gao³  Wuling Wang²  Shuai Chang³  Jiaxing Chen³  Luciano Lavagno¹ 

[1] College of Information Technology, Hebei Normal University, Shijiazhuang 050024, China;;College of Information Technology, Hebei Normal University, Shijiazhuang 050024, China; E-Mails:;College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang 050024, China; E-Mails:

关键词: underwater acoustic sensor networks (UASNs);    self-localization;    color filtering;    Red Green Blue (RGB);    hierarchical structure;   

DOI  :  10.3390/s150306009

来源: mdpi

【 摘 要 】

Accurate localization of mobile nodes has been an important and fundamental problem in underwater acoustic sensor networks (UASNs). The detection information returned from a mobile node is meaningful only if its location is known. In this paper, we propose two localization algorithms based on color filtering technology called PCFL and ACFL. PCFL and ACFL aim at collaboratively accomplishing accurate localization of underwater mobile nodes with minimum energy expenditure. They both adopt the overlapping signal region of task anchors which can communicate with the mobile node directly as the current sampling area. PCFL employs the projected distances between each of the task projections and the mobile node, while ACFL adopts the direct distance between each of the task anchors and the mobile node. The proportion factor of distance is also proposed to weight the RGB values. By comparing the nearness degrees of the RGB sequences between the samples and the mobile node, samples can be filtered out. The normalized nearness degrees are considered as the weighted standards to calculate the coordinates of the mobile nodes. The simulation results show that the proposed methods have excellent localization performance and can localize the mobile node in a timely way. The average localization error of PCFL is decreased by about 30.4% compared to the AFLA method.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.