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Title: The phase gradient autofocus algorithm: An optimal estimator of the phase derivative

Abstract

The phase gradient algorithm represents a powerful new signal processing technique with applications to aperture synthesis imaging. These include, for example, synthetic aperture radar phase correction and stellar image reconstruction. The algorithm combines redundant information present in the data to arrive at an estimate of the phase derivative. In this report, we show that the estimator is in fact a linear, minimum variance estimator of the phase derivative. 7 refs.

Authors:
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
DOE/DP
OSTI Identifier:
5609345
Report Number(s):
SAND-89-0761
ON: DE90000895
DOE Contract Number:  
AC04-76DP00789
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; SYNTHETIC-APERTURE RADAR; FOCUSING; ALGORITHMS; AUTOMATION; IMAGE PROCESSING; IMAGES; MATHEMATICAL MODELS; PHASE SHIFT; MATHEMATICAL LOGIC; MEASURING INSTRUMENTS; PROCESSING; RADAR; RANGE FINDERS; 440300* - Miscellaneous Instruments- (-1989); 990220 - Computers, Computerized Models, & Computer Programs- (1987-1989)

Citation Formats

Eichel, P. H. The phase gradient autofocus algorithm: An optimal estimator of the phase derivative. United States: N. p., 1989. Web. doi:10.2172/5609345.
Eichel, P. H. The phase gradient autofocus algorithm: An optimal estimator of the phase derivative. United States. https://doi.org/10.2172/5609345
Eichel, P. H. 1989. "The phase gradient autofocus algorithm: An optimal estimator of the phase derivative". United States. https://doi.org/10.2172/5609345. https://www.osti.gov/servlets/purl/5609345.
@article{osti_5609345,
title = {The phase gradient autofocus algorithm: An optimal estimator of the phase derivative},
author = {Eichel, P. H.},
abstractNote = {The phase gradient algorithm represents a powerful new signal processing technique with applications to aperture synthesis imaging. These include, for example, synthetic aperture radar phase correction and stellar image reconstruction. The algorithm combines redundant information present in the data to arrive at an estimate of the phase derivative. In this report, we show that the estimator is in fact a linear, minimum variance estimator of the phase derivative. 7 refs.},
doi = {10.2172/5609345},
url = {https://www.osti.gov/biblio/5609345}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Sep 01 00:00:00 EDT 1989},
month = {Fri Sep 01 00:00:00 EDT 1989}
}