Abstract and Applied Analysis
- Abstr. Appl. Anal.
- Volume 2014 (2014), Article ID 127643, 6 pages.
A Filtering Algorithm for Maneuvering Target Tracking Based on Smoothing Spline Fitting
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.
Abstr. Appl. Anal., Volume 2014 (2014), Article ID 127643, 6 pages.
First available in Project Euclid: 2 October 2014
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Liu, Yunfeng; Suo, Jidong; Karimi, Hamid Reza; Liu, Xiaoming. A Filtering Algorithm for Maneuvering Target Tracking Based on Smoothing Spline Fitting. Abstr. Appl. Anal. 2014 (2014), Article ID 127643, 6 pages. doi:10.1155/2014/127643. https://projecteuclid.org/euclid.aaa/1412273154