首页    期刊浏览 2022年08月17日 星期三
登录注册

文章基本信息

  • 标题:An Improved Location Algorithm by Extend Square-root Cubature Kalman Filter
  • 本地全文:下载
  • 作者:Sheng, Rui Guo ; Zhang, Yang ; Miao, Jun
  • 期刊名称:Journal of Computers
  • 印刷版ISSN:1796-203X
  • 出版年度:2013
  • 卷号:8
  • 期号:2
  • 页码:471-477
  • DOI:10.4304/jcp.8.2.471-477
  • 语种:English
  • 出版社:Academy Publisher
  • 摘要:In this paper, the new nonlinear filter method Cubature Kalman Filter (CKF) is improved to solve the passive location problem. Firstly, the Empirical Mode Decomposition (EMD) algorithm is used to estimate the new measurement noise covariance in the filter process; And then the new covariance of the noise is brought into the circle; Meanwhile, the location process is improved by the way of square root to keep its stability and positivity,and the results of track with moving angle-measured sensors’ measurements by Extend SCKF are compared with the results by Unscented Kalman Filter (UKF) in the paper; By the tracking results to the velocity of the target, Extend SCKF algorithm can not only track the target with unknown measurement noise but also improve the passive position precision remarkably with the same complexity of UKF algorithm.
  • 关键词:Cubature Kalman Filter;Sensor;Empirical Mode Decomposition;Square-Root Cubature Kalman Filter;Unscented Kalman Filter
国家哲学社会科学文献中心版权所有