Multiharmonic tracking using sigma-point Kalman filter.
Several groups have proposed the state-space approach to track time-varying frequencies ofmulti-harmonic quasi-periodic signals contaminated with white Gaussian noise. We compared the extended Kalman filter (EKF) and sigma-point Kalman filter (SPKF) algorithms on this problem. On average, the SPKF outperformed the EKF and more accurately tracked the instantaneous frequency over a wide range of signal-to-noise (SNR) ratios.
Kim
Sunghan
S
Biomedical Signal Processing Laboratory, Portland State University, Portland, Oregon, USA. sunghan@pdx.edu
Paul
Anindya S
AS
Wan
Eric A
EA
McNames
James
J
D000465:Algorithms; D001330:Electronic Data Processing; D004594:Electrophysiology / Q000379:methods; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D008962:Models, Theoretical; D016011:Normal Distribution; D012815:Signal Processing, Computer-Assisted; D012984:Software