Abstract
This paper proposes a new nonlinear filtering algorithm called the self-recovering extended Kalman filter (SREKF). In the SREKF algorithm, the EKF's failure or abnormal operation is automatically diagnosed. When the failure is diagnosed, an assisting filter, a nonlinear finite impulse response (FIR) filter, is operated. Using the output of the nonlinear FIR filter, the EKF is reset and rebooted. In this way, the SREKF can self-recover from failures. The SREKF is applied to a frequency tracking problem for demonstration of its effectiveness.
| Original language | English |
|---|---|
| Title of host publication | ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 389-392 |
| Number of pages | 4 |
| ISBN (Print) | 9788993215090 |
| DOIs | |
| Publication status | Published - 2015 Dec 23 |
| Event | 15th International Conference on Control, Automation and Systems, ICCAS 2015 - Busan, Korea, Republic of Duration: 2015 Oct 13 → 2015 Oct 16 |
Other
| Other | 15th International Conference on Control, Automation and Systems, ICCAS 2015 |
|---|---|
| Country | Korea, Republic of |
| City | Busan |
| Period | 15/10/13 → 15/10/16 |
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Keywords
- extended Kalman filter (EKF)
- finite impulse response (FIR) filter
- frequency tracking
- Self-recovering extended Kalman filter (SREKF)
ASJC Scopus subject areas
- Control and Systems Engineering
Cite this
Self-recovering extended Kalman filter for frequency tracking. / Pak, Jung Min; Ahn, Choon Ki; Lim, Myo Taeg.
ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. p. 389-392 7364945.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Self-recovering extended Kalman filter for frequency tracking
AU - Pak, Jung Min
AU - Ahn, Choon Ki
AU - Lim, Myo Taeg
PY - 2015/12/23
Y1 - 2015/12/23
N2 - This paper proposes a new nonlinear filtering algorithm called the self-recovering extended Kalman filter (SREKF). In the SREKF algorithm, the EKF's failure or abnormal operation is automatically diagnosed. When the failure is diagnosed, an assisting filter, a nonlinear finite impulse response (FIR) filter, is operated. Using the output of the nonlinear FIR filter, the EKF is reset and rebooted. In this way, the SREKF can self-recover from failures. The SREKF is applied to a frequency tracking problem for demonstration of its effectiveness.
AB - This paper proposes a new nonlinear filtering algorithm called the self-recovering extended Kalman filter (SREKF). In the SREKF algorithm, the EKF's failure or abnormal operation is automatically diagnosed. When the failure is diagnosed, an assisting filter, a nonlinear finite impulse response (FIR) filter, is operated. Using the output of the nonlinear FIR filter, the EKF is reset and rebooted. In this way, the SREKF can self-recover from failures. The SREKF is applied to a frequency tracking problem for demonstration of its effectiveness.
KW - extended Kalman filter (EKF)
KW - finite impulse response (FIR) filter
KW - frequency tracking
KW - Self-recovering extended Kalman filter (SREKF)
UR - http://www.scopus.com/inward/record.url?scp=84966415558&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84966415558&partnerID=8YFLogxK
U2 - 10.1109/ICCAS.2015.7364945
DO - 10.1109/ICCAS.2015.7364945
M3 - Conference contribution
AN - SCOPUS:84966415558
SN - 9788993215090
SP - 389
EP - 392
BT - ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -