This page is a copy of research/systems_and_control/signalproc/topics/fundspec (Wed, 31 Aug 2022 15:09:07)
Fundamental problems in temporal/spatial spectral estimation, including array processing
Following is an enumeration of the research problems under consideration, along with a short explanation.
- Parameter estimation of sinusoidal signals using decimation
- Decimation of the data, making use of some a priori information, can significantly improve the resolution and accuracy of the methods for estimating the parameters of damped or undamped sine waves.
- Matched-filterbank spectral estimation
- Introducing a matched-filterbank class of spectral estimators, casting some existing estimators into that framework, and establishing their statistical properties.
- Parameter estimation of exponential signals with time varying envelope
- New methods and new tools for the above task (such as nonlinear least squares, polar decomposition-based methods etc), and their statistical properties.
- Novel estimators of covariance sequences
- New procedures for estimating the covariance sequence of stationary signals, with better properties than the usual sample covariance estimators.
- Covariance matching techniques for array signal processing
- Studying the properties of such techniques and applying them to a variety of problems in communications, underwater acoustics, and radar.
- Non-parametric spectral estimation
- New optimally smoothed nonparametric spectral estimators; Lower bounds on the performance achievable in a nonparametric spectral analysis exercise; Spectral smoothing based on cepstrum thresholding.
Selected references:
X Tan, W Roberts, J Li and P Stoica, Sparse learning via iterative minimization with application to MIMO radar imaging. IEEE Trans Signal Process, vol 59, 1088-1101, 2011.
P Stoica, P Babu and J Li, SPICE: a sparse covariance-based estimation method for array processing. IEEE Trans Signal Process, vol 59, 629-638, 2011.
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Comments on "Iterative Estimation of Sinusoidal Signal Parameters"
. In IEEE Signal Processing Letters, volume 17, number 12, pp 1022-1023, 2010. (DOI
).
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MIMO Radar: Diversity means superiority
. In MIMO Radar Signal Processing, pp 1-64, John Wiley & Sons, Hoboken, NJ, 2009.
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MIMO Radar Signal Processing
. John Wiley & Sons, Hoboken, NJ, 2009.
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On nonparametric estimation of 2-D smooth spectra
. In IEEE Signal Processing Letters, volume 13, number 10, pp 632-635, 2006. (DOI
).
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The waterbed effect in spectral estimation
. In IEEE Signal Processing Mag., pp 88-90, 2004.