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High-Resolution Estimation of Multidimensional Spectra from Unevenly Sampled Data

Butt, Naveed LU and Jakobsson, Andreas LU (2011) 17th International Conference on Digital Signal Processing In Digital Signal Processing (DSP), 2011 17th International Conference on
Abstract
Estimation of high-resolution multidimensional spectra from unevenly sampled limited sized data sets plays an important role in a large variety of signal processing applications. In this work, we develop a high-resolution non-parametric estimator for unevenly sampled N-dimensional data based on a recently introduced iterative method, the so-called iterative adaptive approach (IAA). The proposed estimator uses the definition of the multidimensional Fourier transform to obtain a frequency domain representation of the unevenly sampled signal. Using tensor algebra, the multidimensional frequency domain representation is then recast into matrix format and used in a weighted least squares (WLS) fitting criterion to iteratively obtain estimates... (More)
Estimation of high-resolution multidimensional spectra from unevenly sampled limited sized data sets plays an important role in a large variety of signal processing applications. In this work, we develop a high-resolution non-parametric estimator for unevenly sampled N-dimensional data based on a recently introduced iterative method, the so-called iterative adaptive approach (IAA). The proposed estimator uses the definition of the multidimensional Fourier transform to obtain a frequency domain representation of the unevenly sampled signal. Using tensor algebra, the multidimensional frequency domain representation is then recast into matrix format and used in a weighted least squares (WLS) fitting criterion to iteratively obtain estimates of the spectral amplitudes and the covariance matrix. The proposed estimator is numerically shown to provide superior performance as compared to the commonly used least squares Fourier transform (LSFT) estimator. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
weighted least squares, estimation, Multidimensional spectra
in
Digital Signal Processing (DSP), 2011 17th International Conference on
pages
4 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
17th International Conference on Digital Signal Processing
external identifiers
  • Scopus:80053147646
ISBN
978-1-4577-0273-0 (print)
DOI
10.1109/ICDSP.2011.6004971
language
English
LU publication?
yes
id
09555017-5ebb-4178-ad4d-6b8495dd25e5 (old id 1888236)
date added to LUP
2011-12-22 19:36:45
date last changed
2017-02-19 04:30:14
@inproceedings{09555017-5ebb-4178-ad4d-6b8495dd25e5,
  abstract     = {Estimation of high-resolution multidimensional spectra from unevenly sampled limited sized data sets plays an important role in a large variety of signal processing applications. In this work, we develop a high-resolution non-parametric estimator for unevenly sampled N-dimensional data based on a recently introduced iterative method, the so-called iterative adaptive approach (IAA). The proposed estimator uses the definition of the multidimensional Fourier transform to obtain a frequency domain representation of the unevenly sampled signal. Using tensor algebra, the multidimensional frequency domain representation is then recast into matrix format and used in a weighted least squares (WLS) fitting criterion to iteratively obtain estimates of the spectral amplitudes and the covariance matrix. The proposed estimator is numerically shown to provide superior performance as compared to the commonly used least squares Fourier transform (LSFT) estimator.},
  author       = {Butt, Naveed and Jakobsson, Andreas},
  booktitle    = {Digital Signal Processing (DSP), 2011 17th International Conference on},
  isbn         = {978-1-4577-0273-0 (print)},
  keyword      = {weighted least squares,estimation,Multidimensional spectra},
  language     = {eng},
  pages        = {4},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {High-Resolution Estimation of Multidimensional Spectra from Unevenly Sampled Data},
  url          = {http://dx.doi.org/10.1109/ICDSP.2011.6004971},
  year         = {2011},
}