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}
}
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