NDLI: Unscented Kalman Filter for frequency and amplitude estimation

Content Provider	IEEE Xplore Digital Library
Author	Novanda, H. Regulski, P. Gonzalez-Longatt, F.M. Terzija, V.
Copyright Year	2011
Description	Author affiliation: Same University, UK (Gonzalez-Longatt, F.M.; Terzija, V.) \|\| School of Electrical and Electronic Engineering, The University of Manchester, UK (Novanda, H.; Regulski, P.)
Abstract	This paper introduces a new digital signal processing algorithm for frequency and amplitude estimation based on Unscented Kalman Filter (UKF). The results of computer simulated and realistic synthetic data tests are presented. The initial parameters used during the tests were chosen carefully using an established parameter estimation method, the Self Tuning Least Square (STLS). It is concluded that the proposed algorithm is simple, efficient and has low computational demands compare to STLS which makes the UKF a very promising method in next generation of power quality monitoring devices.
Starting Page	1
Ending Page	6
File Size	961935
Page Count	6
File Format	PDF
ISBN	9781424484195
e-ISBN	9781424484188
e-ISBN	9781424484171
DOI	10.1109/PTC.2011.6019414
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-19
Publisher Place	Norway
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kalman filters Frequency estimation Estimation Power system dynamics Signal processing algorithms Noise Power quality amplitude estimation unscented transformation power quality frequency estimation
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Parameters estimation for underwater Doppler signal using unscented Kalman filter

Improved unscented particle filter for nonlinear bayesian estimation

The unscented Kalman filter for the sandwich system with hysteresis

A simplified functional link net architecture for dynamic system identification with a UKF algorithm

Adaptive unscented filtering technique and particle swarm optimization for estimation of non-stationary signal parameters

Spacecraft attitude & rate estimation by an adaptive unscented Kalman filter

Dynamic state estimation in power systems using Kalman filters

Adaptive Unscented Kalman Filter at the presence of non-additive measurement noise

Estimation of power quality using an unscented Kalman filter

Unscented Kalman Filter for frequency and amplitude estimation

Similar Documents

Parameters estimation for underwater Doppler signal using unscented Kalman filter

Improved unscented particle filter for nonlinear bayesian estimation

The unscented Kalman filter for the sandwich system with hysteresis

A simplified functional link net architecture for dynamic system identification with a UKF algorithm

Adaptive unscented filtering technique and particle swarm optimization for estimation of non-stationary signal parameters

Spacecraft attitude & rate estimation by an adaptive unscented Kalman filter

Dynamic state estimation in power systems using Kalman filters

Adaptive Unscented Kalman Filter at the presence of non-additive measurement noise

Estimation of power quality using an unscented Kalman filter

Unscented Kalman Filter for frequency and amplitude estimation