Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Hamed Danandeh Hesar; Maryam Mohebbi
Volume 11, Issue 4 , February 2018, , Pages 275-289
Abstract
Marginalized particle extended Kalman filter (MP-EKF) takes advantage of both extended Kalman filter and particle filter frameworks to estimate nonlinear ECG dynamic models (EDMs) with reduced number of calculations in comparison to typical particle filters. However, due to existence of Kalman filter ...
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Marginalized particle extended Kalman filter (MP-EKF) takes advantage of both extended Kalman filter and particle filter frameworks to estimate nonlinear ECG dynamic models (EDMs) with reduced number of calculations in comparison to typical particle filters. However, due to existence of Kalman filter framework inside MP-EKF, some limitations are introduced in implementation of MP-EKF especially in embedded systems with finite numerical accuracies. In this paper, for the first time, we propose a square root filtering strategy for MP-EKF which alleviates these restrictions using factorization. Typical or other square-root Kalman filters cannot be employed inside MP-EKF due to presence of minus operations in some equations of MP-EKF. However, our method can be implemented in MP-EKF structure. The proposed method can be used in any EDM previously used by EKF based frameworks in the field of ECG processing.
