Title :
Adaptive time-varying spectral analysis for multiple narrowband signals
Author :
Fineberg, Adam ; Mammone, Richard
Author_Institution :
Dept. of Electr. & Comput. Eng., Rutgers Univ., Piscataway, NJ, USA
Abstract :
An adaptive technique to compute the Fourier coefficients of a time-varying spectrum is presented. The algorithm performs a least squares decomposition of the signal onto a nonharmonic Fourier basis. The algorithm updates the spectral estimate on a sample by sample basis in the time domain. This technique produces a signal decomposition with very good localization in both time and frequency domains. The detection of tones spaced closer than expected by the uncertainty principle (super-resolution) is shown by computer simulation. Computational complexity issues of the new method are also discussed.<>
Keywords :
Fourier analysis; computational complexity; least squares approximations; spectral analysis; Fourier coefficients; adaptive time-varying spectral analysis; computational complexity; least squares decomposition; multiple narrowband signals; multiple nonstationary tones; nonharmonic Fourier analysis; row action projection method; signal decomposition; superresolution; Equations; Frequency domain analysis; Frequency estimation; Least squares methods; Matrix decomposition; Narrowband; Signal resolution; Spectral analysis; Symmetric matrices; Target tracking;
Conference_Titel :
Spectrum Estimation and Modeling, 1990., Fifth ASSP Workshop on
Conference_Location :
Rochester, NY, USA
DOI :
10.1109/SPECT.1990.205591