DocumentCode
775389
Title
Two algorithms for adaptive retrieval of slowly time-varying multiple cisoids in noise
Author
Tichavsky, Petr ; Handel, Peter
Author_Institution
Inst. of Inf. Theory & Autom., Prague, Czech Republic
Volume
43
Issue
5
fYear
1995
fDate
5/1/1995 12:00:00 AM
Firstpage
1116
Lastpage
1127
Abstract
Two algorithms for tracking parameters of slowly varying multiple complex sine waves (cisoids) in noise (the multiple frequency tracker and the adaptive notch filter) are described. For high signal-to-noise ratio (SNR), the properties of the algorithms (i.e., stability, noise rejection, and tracking speed) are studied analytically using a linear filter approximation technique. The tradeoff between noise rejection and tracking error for both algorithms is shown to be similar. Different choices of the design variables are discussed, namely (i) minimal mean-square estimation error for random walk modeled frequency variations and (ii) minimal stationary estimation variance subject to a given tracking delay
Keywords
adaptive signal processing; approximation theory; delay circuits; delays; error analysis; noise; notch filters; parameter estimation; prediction theory; tracking filters; SNR; adaptive notch filter; adaptive retrieval; design variables; high signal-to-noise ratio; linear filter approximation; minimal mean-square estimation error; minimal stationary estimation variance; multiple complex sine waves; multiple frequency tracker; noise rejection; parameters tracking; random walk modeled frequency variations; recursive prediction error algorithm; slowly time-varying multiple cisoids; stability; tracking delay; tracking error; tracking speed; Adaptive filters; Algorithm design and analysis; Approximation algorithms; Delay estimation; Frequency estimation; Linear approximation; Nonlinear filters; Signal analysis; Signal to noise ratio; Stability analysis;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.382397
Filename
382397
Link To Document