Target tracking in glint noise environment using nonlinear non-Gaussian Kalman filter

  title={Target tracking in glint noise environment using nonlinear non-Gaussian Kalman filter},
  author={Igal Bilik and Joseph Tabrikian},
  journal={2006 IEEE Conference on Radar},
  pages={6 pp.-}
The problem of nonlinear non-Gaussian target tracking with glint measurement noise is addressed in this work. The heavy-tailed glint noise distribution is modeled by mixture of two Gaussians. A new nonlinear Gaussian mixture Kalman filter (NL-GMKF), is applied to this problem. The tracking performance of the NL-GMKF is evaluated and compared to the particle filter (PF) and the extended Kalman filter (EKF) via simulations. It is shown that the NL-GMKF outperforms both the PF and the EKF. 
Highly Cited
This paper has 23 citations. REVIEW CITATIONS
10 Citations
17 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 10 extracted citations


Publications referenced by this paper.
Showing 1-10 of 17 references


  • S. Arulampalam, S. Maskell
  • Gordon and T. Clapp, “A tutorial on particle…
  • 2002
Highly Influential
13 Excerpts

and J

  • G. Hewer, R. Martin
  • Zeh, “Robust preprocessing for Kalman filtering…
  • 1987
Highly Influential
15 Excerpts

Optimal filtering

  • B. Anderson, J. Moore
  • Prentice-Hall
  • 1979
Highly Influential
9 Excerpts

and H

  • H. Hu, Z. Jing, A. Li, S. Hu
  • Tian, “An MCMC-based particle filter for tracking…
  • 2005
2 Excerpts

A tutorial on particle filters for on - line non - linear / non - Gaussian Bayesian tracking

  • S. Maskell Arulampalam, N. Gordon, T. Clapp
  • IEEE Trans . AES
  • 2003

Estimation with applications to tracking and navigation

  • Y. Bar-Shalom, X. Li
  • Artech House, NY
  • 2001
3 Excerpts

Adaptive filtering and change detection

  • F. Gustafsson
  • John Wiley & Sons, NY
  • 2000
1 Excerpt

Similar Papers

Loading similar papers…