Convergence Results for the Gaussian Mixture Implementation of the Extended‐Target PHD Filter and Its Extended Kalman Filtering Approximation

Feng Lian, Chongzhao Han, Jing Liu and Hui Chen

Journal of Applied Mathematics, 2012, vol. 2012, issue 1

Abstract: The convergence of the Gaussian mixture extended‐target probability hypothesis density (GM‐EPHD) filter and its extended Kalman (EK) filtering approximation in mildly nonlinear condition, namely, the EK‐GM‐EPHD filter, is studied here. This paper proves that both the GM‐EPHD filter and the EK‐GM‐EPHD filter converge uniformly to the true EPHD filter. The significance of this paper is in theory to present the convergence results of the GM‐EPHD and EK‐GM‐EPHD filters and the conditions under which the two filters satisfy uniform convergence.

Date: 2012
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1155/2012/141727

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2012:y:2012:i:1:n:141727

Access Statistics for this article

More articles in Journal of Applied Mathematics from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().