Spectral analysis of periodically gapped data

Author

Larsson, Erik G. ; Jian Li

Author_Institution

Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA

Volume

39

Issue

3

fYear

2003

fDate

7/1/2003 12:00:00 AM

Firstpage

1089

Lastpage

1097

Abstract

We devise novel, interpolation-free, and computationally tractable extensions of the spectral analysis methods Capon and APES (amplitude and phase estimation) to periodically gapped data. Our methods are based on the observation that periodically gapped data usually have a structure that supports estimation of a relatively large number of covariance lags. The large signal-to-noise-ratio (SNR) behavior of the new algorithms is discussed, and numerical examples are provided to illustrate their performance.

Keywords

amplitude estimation; phase estimation; radar signal processing; spectral analysis; synthetic aperture radar; APES; Capon; amplitude estimation; computationally tractable extensions; covariance lags; periodically gapped data; phase estimation; signal-to-noise-ratio; spectral analysis; synthetic aperture radar; Adaptive filters; Discrete Fourier transforms; Image analysis; Phase estimation; Robust stability; Signal to noise ratio; Spectral analysis; Synthetic aperture radar; Time series analysis; Yield estimation;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2003.1238761

Filename

1238761