Exact kalman filtering of respiratory motion

Date

2018-10-01

Author

Çetinkaya, Mehmet
Erkmen, Aydan Müşerref

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

206
views

0
downloads

In this paper we propose a novel Exact Kalman Filter for state estimation of quasi-periodic signals such as respiratory motion. Nonlinear functions of interest are approximations as truncated Fourier series. Instead of relying on approximations provided by Extended Kalman Filter or Unscented Kalman Filter, our filter performs exact calculation of the mean and covariances of interest. We then compare, through simulations, the performance of our filter to the two. Our results show that the theoretically derived mean and covariance calculations result in either comparable or better estimation performance depending on the circumstances.

Subject Keywords

Approximate nonlinear kalman filtering, Monte Carlo KF, Exact kalman filtering

URI

https://hdl.handle.net/11511/43178

DOI

https://doi.org/10.1109/ceit.2018.8751860

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Robust Attitude Estimation Using IMU-Only Measurements Candan, Batu; Söken, Halil Ersin (2021-01-01) © 1963-2012 IEEE.This article proposes two novel covariance-tuning methods to form a robust Kalman filter (RKF) algorithm for attitude (i.e., roll and pitch) estimation using the measurements of only an inertial measurement unit (IMU). KF-based and complementary filtering (CF)-based approaches are the two common methods for solving the attitude estimation problem. Efficiency and optimality of the KF-based attitude filters are correlated with appropriate tuning of the covariance matrices. Manual tuning proce...
Online EM algorithm for joint state and mixture measurement noise estimation Zhao, Yuxin; Yin, Feng; Gunnarsson, Fredrik; Amirijoo, Mehdi; Özkan, Emre; Gustafsson, Fredrik (null; 2012-07-09) In this study, we aim to estimate the unknown multimodal measurement noise distribution of nonlinear state space models. The unknown noise distribution is modeled as a mixture of exponential family of distributions. We use the ExpectationMaximization (EM) method in order to jointly estimate the unknown parameters as well as the states. The online version of the EM algorithm is implemented by using particle filtering techniques. The resulting algorithm is a noise adaptive particle filter which is applicable ...
Robust Kalman filtering with single and multiple scale factors for small satellite attitude estimation Söken, Halil Ersin; Sakai, Shin-ichiro (Springer, 2015-11-01) In case of normal operational conditions for a satellite, a conventional Kalman Filter gives sufficiently good attitude estimation results. On the other hand, when there is a fault in the measurements then the Kalman filter fails about providing the required accuracy and may even collapse by time. In this paper, a Robust Kalman filtering method is proposed for the attitude estimation problem. By using the proposed method both the Extended Kalman Filter and Unscented Kalman Filter are modified ...
Real-Time Detection of Interharmonics and Harmonics of AC Electric Arc Furnaces on GPU Framework Uz-Logoglu, Eda; Salor, Ozgul; Ermiş, Muammer (2019-11-01) In this paper, a method based on the multiple synchronous reference frame analysis is recommended and implemented to detect time-varying harmonics and interharmonics of rapidly fluctuating asymmetrical industrial loads. The experimental work has been carried out on a typical three-phase alternating current arc furnace installation. In the recommended method, the reference frame is rotated in both directions at speeds corresponding to the positive and negative sequences of all harmonics and all interharmonic...
Real-Time Detection of Interharmonics and Harmonics of AC Electric Arc Furnaces on GPU Framework Uz-Logoglu, Eda; Salor, Ozgul; Ermiş, Muammer (2017-10-05) In this paper, a method based on the multiple synchronous reference frame (MSRF) analysis is recommended and implemented to detect time-varying harmonics and interharmonics of rapidly fluctuating asymmetrical industrial loads. The experimental work has been carried out on a typical three-phase alternating current arc furnace (AC EAF) installation. In the recommended method, the reference frame is rotated in both directions at speeds corresponding to the positive and negative sequences of all harmonics and a...

Citation Formats

M. Çetinkaya and A. M. Erkmen, “Exact kalman filtering of respiratory motion,” 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/43178.