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Discrete Dynamics in Nature and Society
Volume 2016 (2016), Article ID 7670609, 8 pages
Research Article

The Nonsequential Fusion Method for Localization from Unscented Kalman Filter by Multistation Array Buoys

College of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China

Received 23 December 2015; Accepted 2 March 2016

Academic Editor: Filippo Cacace

Copyright © 2016 Gou Yanni and Wang Qi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Based on special features of array buoy and the research field of location and tracking of underwater target, the research combines the highly adaptive nonlinear filtering algorithm unscented Kalman filter with the nonlinear programming of multistation array buoy positioning system. In accordance with the model of nonsequential target location, the research utilizes Unscented Transformation to update the measuring error and covariance matrix of state error, aiming at estimating the filtering of state variable and acquiring the object’s current state of motion. The research analyzes the positioning performance of algorithm, pursuit path, astringency, and other performance indexes of target-relevant parameter through numerical simulation experiment. From the result, the conclusion that multistation array buoy can complete the task of tracing target track very well can be reached, which provides theoretical foundation for putting the algorithm into engineering practice.