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Levenberg-Marquardt Method Based Iterative Square Root Cubature Kalman Filter and its Applications to Maneuvering Re-entry Target Tracking

Authors
  • Jing, Mu1
  • Changyuan, Wang1
  • 1 School of Computer Science and Engineering Xi’an Technological University, Xi’an, 710032 , (China)
Type
Published Article
Journal
International Journal of Advanced Network, Monitoring and Controls
Publisher
Exeley Inc.
Publication Date
Jan 01, 2018
Volume
3
Issue
2
Pages
10–13
Identifiers
DOI: 10.21307/ijanmc-2018-027
Source
Exeley
Keywords
License
Green

Abstract

Levenberg-Marquardt (abbr.L-M) method based iterative square root cubature Kalman filter (abbr. ISRCKFLM) inherits the numerical stability of square root Cubature Kalman filter and effectively suppresses the influence of the larger initial estimation error and the nonlinearity of the measurement equation on the state estimation in the nonlinear state estimation due to obtaining the optimal state and variance estimates using the latest measurement through L-M method. We apply the ISRCKFLM algorithm to the state estimation of maneuvering re-entry target tracking, the simulation results demonstrate that the ISRCKFLM algorithm has better accuracy of state estimation, comparable to Unscented Kalman filter and square root Cubature Kalman filter, according to estimation error analysis of the position, velocity, drag coefficient, turn coefficient and climbing force coefficient, and has fast convergence rate.

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