Multiple model adaptive Kalman filter for the system without the knowledge of process noise

LI Xiaoli; QIAN Xiaolong

doi:10.13374/j.issn1001-053x.2008.01.019

Volume 30 Issue 1

Aug. 2021

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Article Navigation > Chinese Journal of Engineering > 2008 > 30(1): 101-104

LI Xiaoli, QIAN Xiaolong. Multiple model adaptive Kalman filter for the system without the knowledge of process noise[J]. Chinese Journal of Engineering, 2008, 30(1): 101-104. doi: 10.13374/j.issn1001-053x.2008.01.019

Citation:

LI Xiaoli, QIAN Xiaolong. Multiple model adaptive Kalman filter for the system without the knowledge of process noise[J]. Chinese Journal of Engineering, 2008, 30(1): 101-104. doi: 10.13374/j.issn1001-053x.2008.01.019

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Multiple model adaptive Kalman filter for the system without the knowledge of process noise

doi: 10.13374/j.issn1001-053x.2008.01.019

LI Xiaoli¹,
QIAN Xiaolong²

1. School of Information Engineering, University of Science and Technology Beijing, Beijing 100083, China;
2. College of Information Science and Engineering, Northeastern University, Shenyang 110004, China

Received Date: 2006-12-05
Rev Recd Date: 2007-04-01

Available Online: 2021-08-06

Abstract

Abstract

To solve the bad transient response of a conventional adaptive Kalman filter, multiple Kalman filters based on different noise covariances and a conventional adaptive Kalman filter (AKF) were used to form a multiple model adaptive Kalman filter (MMAKF) by using a switching index function. Compared with a conventional AKF, the MMAKF could improve the transient response greatly without losing the characteristic of the conventional AKF.
- noise characteristic,
- unknown system,
- adaptive Kalman filtering,
- switching,
- multiple model