Vehicle track identification in synthetic aperture radar images
Abstract
Various technologies pertaining to identification of vehicle tracks in synthetic aperture radar coherent change detection image data are described herein. Coherent change detection images are analyzed in a parameter space using Radon transforms. Peaks of the Radon transforms correspond to features of interest, including vehicle tracks, which are identified and classified. New coherent change detection images in which the features of interest and their characteristics are signified are then generated using inverse Radon transforms.
- Inventors:
- Issue Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1464128
- Patent Number(s):
- 10032077
- Application Number:
- 14/927,102
- Assignee:
- National Technology & Engineering Solutions of Sandia, LLC (Albuquerque, NM)
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06T - IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
G - PHYSICS G06 - COMPUTING G06K - RECOGNITION OF DATA
- DOE Contract Number:
- AC04-94AL85000
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 2015 Oct 29
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 47 OTHER INSTRUMENTATION; 45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEFENSE
Citation Formats
Chow, James G. Vehicle track identification in synthetic aperture radar images. United States: N. p., 2018.
Web.
Chow, James G. Vehicle track identification in synthetic aperture radar images. United States.
Chow, James G. Tue .
"Vehicle track identification in synthetic aperture radar images". United States. https://www.osti.gov/servlets/purl/1464128.
@article{osti_1464128,
title = {Vehicle track identification in synthetic aperture radar images},
author = {Chow, James G.},
abstractNote = {Various technologies pertaining to identification of vehicle tracks in synthetic aperture radar coherent change detection image data are described herein. Coherent change detection images are analyzed in a parameter space using Radon transforms. Peaks of the Radon transforms correspond to features of interest, including vehicle tracks, which are identified and classified. New coherent change detection images in which the features of interest and their characteristics are signified are then generated using inverse Radon transforms.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {7}
}
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