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2014 A Filtering Algorithm for Maneuvering Target Tracking Based on Smoothing Spline Fitting
Yunfeng Liu, Jidong Suo, Hamid Reza Karimi, Xiaoming Liu
Abstr. Appl. Anal. 2014: 1-6 (2014). DOI: 10.1155/2014/127643

Abstract

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.

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Yunfeng Liu. Jidong Suo. Hamid Reza Karimi. Xiaoming Liu. "A Filtering Algorithm for Maneuvering Target Tracking Based on Smoothing Spline Fitting." Abstr. Appl. Anal. 2014 1 - 6, 2014. https://doi.org/10.1155/2014/127643

Information

Published: 2014
First available in Project Euclid: 2 October 2014

zbMATH: 07021763
MathSciNet: MR3166562
Digital Object Identifier: 10.1155/2014/127643

Rights: Copyright © 2014 Hindawi

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