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Abstract and Applied Analysis
Volume 2014, Article ID 127643, 6 pages
Research Article

A Filtering Algorithm for Maneuvering Target Tracking Based on Smoothing Spline Fitting

1College of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
2Department of Engineering, Faculty of Technology and Science, University of Agder, 4898 Grimstad, Norway

Received 15 October 2013; Revised 14 December 2013; Accepted 20 December 2013; Published 6 February 2014

Academic Editor: Zexu Zhang

Copyright © 2014 Yunfeng Liu et al. 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.


Maneuvering target tracking is a challenge. Target’s sudden speed or direction changing would make the common filtering tracker divergence. To improve the accuracy of maneuvering target tracking, we propose a tracking algorithm based on spline fitting. Curve fitting, based on historical point trace, reflects the mobility information. The innovation of this paper is assuming that there is no dynamic motion model, and prediction is only based on the curve fitting over the measured data. Monte Carlo simulation results show that, when sea targets are maneuvering, the proposed algorithm has better accuracy than the conventional Kalman filter algorithm and the interactive multiple model filtering algorithm, maintaining simple structure and small amount of storage.