7101 Chase Oaks Blvd, Plano, TX 75025 • 9725277227
Work
Company:
Arizona sensors
Jul 2010 to Dec 2014
Position:
Founder
Education
Degree:
Doctorates, Doctor of Philosophy
School / High School:
The University of Kansas
1998 to 2002
Specialities:
Electrical Engineering
Skills
Radar Systems and Signal Processing • Statistical Signal Processing • Array Processing • Signal Processing • Matlab • Algorithms • Radar • Electrical Engineering
Arizona Sensors Jul 2010 - Dec 2014
Founder
University of Oklahoma Jul 2010 - Dec 2014
Professor
The University of Arizona Aug 2002 - Dec 2011
Associate Professor
The University of Kansas 1998 - 2002
Graduate Research Assistant
Raytheon 1996 - 1998
Rf Systems Engineer
Education:
The University of Kansas 1998 - 2002
Doctorates, Doctor of Philosophy, Electrical Engineering
The University of Kansas 1995 - 1997
Master of Science, Masters, Electrical Engineering
The University of Kansas 1991 - 1995
Bachelors, Bachelor of Science, Electrical Engineering
Skills:
Radar Systems and Signal Processing Statistical Signal Processing Array Processing Signal Processing Matlab Algorithms Radar Electrical Engineering
Alphonso A. Samuel - Tucson AZ, US Robert M. Pawloski - Tucson AZ, US Nathan A. Goodman - Oro Valley AZ, US
Assignee:
Raytheon Company - Waltham MA The Arizona Board of Regents on behalf of the University of Arizona - Tucson AZ
International Classification:
F41G 7/28 G01S 13/90
US Classification:
342 62, 342 25 A
Abstract:
Virtual Aperture Radar (VAR) imaging provides terminal phase radar imaging for an airborne weapon that can resolve multiple closely-spaced or highly correlated scatterers on a given target with a single pulse to provide an aimpoint update at a useful range to target without training data and without requiring a large aperture antenna. VAR imaging exploits the sparse, dominant-scatterer nature of man-made targets. The array manifold is constructed with a large number of basis functions that are parameterized by range or angle (or both) to target. The number of basis functions extends the capability to resolve scatterers beyond the Rayleigh resolution. However, this also makes the manifold underdetermined. A sparse reconstruction technique that places a sparsity constraint on the number of scatterers is used to solve the manifold to uniquely identify the ranges or angles to the scatterers on the target. These updates are passed to the weapon's guidance system, which in turn generates command signals to actuate aerodynamic surfaces such as fins or canards to steer the weapon to the target.