6533b874fe1ef96bd12d6297
RESEARCH PRODUCT
A filtering algorithm for maneuvering target tracking based on smoothing spline fitting
Jidong SuoXiaoming LiuHamid Reza KarimiYunfeng Liusubject
Article Subjectlcsh:MathematicsApplied MathematicsMonte Carlo methodSpline fittingAnalysis; Applied MathematicsTracking (particle physics)lcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Smoothing splineCurve fittingPoint (geometry)Divergence (statistics)AlgorithmAnalysisTRACE (psycholinguistics)Mathematicsdescription
Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/127643 Open Access 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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-01-01 |