Adaptive setting of scaling parameter of UKF based on step prediction information of measurement

作者：Huang, Ping; Zhan, Yang Yan; Cheng, Guang Zhou

来源：Systems Engineering and Electronics, 2016, 38(6): 1395-1398.

DOI：10.3969/j.issn.1001-506X.2016.06.27

• Adaptive setting
• Adjustable parameters
• Filtering parameters
• Nonlinear
• On-line adjustment
• Prediction informations
• Scaling parameter
• Unscented Kalman Filter

For the adjustable parameter selection problem of κin the unscented Kalman filter(UKF), through the study of the impact of the different κfor filtering, the method based on the step prediction information of the measurement, which is an online adjustment of the UKF, is presented. Based on the prediction information of measurement in every filtering time, the filtering parameter is selected, which is optimal and can realize the on-line adjustment. Numerical simulations show that the adjustment UKF based on the step prediction information of the measurement tracks the real state better than the traditional UKF.

• 出版日期2016
• 单位哈尔滨工程大学