DocumentCode :
3604047
Title :
Frequency Guided Generalized Adaptive Notch Filtering—Tracking Analysis and Optimization
Author :
Meller, Michal
Author_Institution :
Dept. of Autom. Control, Gdansk Univ. of Technol., Gdańsk, Poland
Volume :
63
Issue :
22
fYear :
2015
Firstpage :
6003
Lastpage :
6012
Abstract :
Generalized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems, encountered e.g., in RF applications when Doppler effect takes place. Current state of the art GANFs can deliver highly accurate estimates of system variations´ frequency, but underperform in terms of accuracy of system coefficient estimates. The paper proposes a novel multistage GANF with improved coefficient tracking properties and smaller sensitivity to choice of estimation gains. The processing pipeline consists of three stages. First, a pilot filter computes preliminary frequency estimates. Second, a special linear filter reshapes the pilot frequency estimates. Third, a frequency guided GANF works out final estimates of system coefficients. A nontrivial design of the second stage filter assures that the proposed solution has a considerably better performance than current stage of the art solutions or a simpler two-stage approach consisting of the pilot and the frequency guided filter only.
Keywords :
Doppler effect; adaptive filters; adaptive signal processing; frequency estimation; notch filters; optimisation; tracking; Doppler effect; adaptive signal processing; coefficient tracking properties; estimation gains; frequency guided GANF; frequency guided generalized adaptive notch filtering; linear filter; multistage GANF; nontrivial second stage filter design; preliminary frequency estimate computation; quasi-periodically time-varying systems; system coefficient estimates; tracking analysis; tracking optimization; Accuracy; Adaptive systems; Estimation; Frequency estimation; Mathematical model; Noise; Signal processing algorithms; Generalized adaptive notch filters; adaptive signal processing; estimation algorithms;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2015.2461522
Filename :
7169605
Link To Document :
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