SCIRP Mobile Website
Paper Submission

Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.


Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
Paper Publishing WeChat
Book Publishing WeChat

Article citations


Xia, N., Qiu, T. and Li, J. (2013) A Nonlinear Kalman Filtering Algorithm Combining the Kalman Filter and the Particle Filter. Acta Electronica Sinica, 41, 148-152.

has been cited by the following article:

  • TITLE: Two Second-Order Nonlinear Extended Kalman Particle Filter Algorithms

    AUTHORS: Hongxiang Dai, Li Zou

    KEYWORDS: Kalman Particle Filter, Nonlinear System, Taylor Expansion, Linearization Approximation

    JOURNAL NAME: Open Journal of Statistics, Vol.5 No.4, June 2, 2015

    ABSTRACT: In algorithms of nonlinear Kalman filter, the so-called extended Kalman filter algorithm actually uses first-order Taylor expansion approach to transform a nonlinear system into a linear system. It is obvious that this algorithm will bring some systematic deviations because of ignoring nonlinearity of the system. This paper presents two extended Kalman filter algorithms for nonlinear systems, called second-order nonlinear Kalman particle filter algorithms, by means of second-order Taylor expansion and linearization approximation, and correspondingly two recursive formulas are derived. A simulation example is given to illustrate the effectiveness of two algorithms. It is shown that the extended Kalman particle filter algorithm based on second-order Taylor expansion has a more satisfactory performance in reducing systematic deviations and running time in comparison with the extended Kalman filter algorithm and the other second-order nonlinear Kalman particle filter algorithm.