Two-Pass Smoother Based on the SVSF Estimation Strategy

被引：24
作者：
Gadsden, S. A. [1 ]
Al-Shabi, M. [2 ]
Kirubarajan, T. [3 ]
机构：
[1] Univ Maryland Baltimore Cty, Baltimore, MD 21250 USA
[2] Philadelphia Univ, Amman, Jordan
[3] McMaster Univ, Hamilton, ON L8S 4L7, Canada
来源：
SIGNAL PROCESSING, SENSOR/INFORMATION FUSION, AND TARGET RECOGNITION XXIV | 2015年 / 9474卷
关键词：
Minimum-variance; smoother; Kalman filter; smooth variable structure filter; aerospace actuator;
D O I：
10.1117/12.2177256
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The smooth variable structure filter (SVSF) has seen significant development and research activity in recent years. It is based on sliding mode concepts, which utilizes a switching gain that brings an inherent amount of stability to the estimation process. In this paper, the SVSF is reformulated to present a two-pass smoother based on the SVSF gain. The proposed method is applied on an aerospace flight surface actuator, and the results are compared with the popular Kalman-based two-pass smoother.
引用
收藏
页数：11
相关论文
共 22 条
  • [1] Al-Shabi M. A., 2011, The general Toeplitz/observability smooth variable structure filter
  • [2] Anderson B.D.O., 1979, Optimal Filtering
  • [3] [Anonymous], IEEE C DEC CONTR ATL
  • [4] [Anonymous], 2004, Kalman filtering and neural networks
  • [5] [Anonymous], IEEE ASME T MECHATRO
  • [6] [Anonymous], 2007, ASME J DYNAMIC SYSTE
  • [7] Bar-Shalom Y., 2004, Estimation with applications to tracking and navigation: Theory algorithms and software
  • [8] Gadsden S. A., 2014, SIGNAL PROCESSING, V96
  • [9] Gadsden S. A., 2014, IEEE T AEROSPACE ELE, V50
  • [10] Gadsden S. A., 2011, ASME J DYNAMIC SYSTE, V135
123