David W Paglieroni from 3706 Angus Way, Pleasanton, CA 94588, age 63, Phone: 9254854832

Us Patents

Normalized Crosscorrelation Of Complex Gradients For Image Autoregistration
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US Patent:

6519372, Feb 11, 2003
Filed:

Aug 31, 1999
Appl. No.:

09/386246
Inventors:

Walter G. Eppler - Saratoga CA
David W. Paglieroni - Pleasanton CA
Sidney M. Petersen - Tracy CA
Marcus J. Louie - Sunnyvale CA
Assignee:

Lockheed Martin Corporation - Bethesda MD
International Classification:

G06K 932
US Classification:

382294, 382278, 382280
Abstract:

A system and method that computes the degree of translational offset between corresponding blocks extracted from images acquired by two sensors, such as electro-optic, infrared sensors, and radar for example, so that the images can be spatially registered. The present invention uses fast Fourier transform (FFT) correlation to provide for speed, and also uses gradient magnitude and phase (direction) information to provide for reliability and robustness.

Method And System For Detecting Polygon Boundaries Of Structures In Images As Particle Tracks Through Fields Of Corners And Pixel Gradients
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US Patent:

8081798, Dec 20, 2011
Filed:

Nov 20, 2008
Appl. No.:

12/275177
Inventors:

David W. Paglieroni - Pleasanton CA, US
Siddharth Manay - Livermore CA, US
Assignee:

Lawrence Livermore National Security, LLC - Livermore CA
International Classification:

G06K 9/00
US Classification:

382103
Abstract:

A stochastic method and system for detecting polygon structures in images, by detecting a set of best matching corners of predetermined acuteness α of a polygon model from a set of similarity scores based on GDM features of corners, and tracking polygon boundaries as particle tracks using a sequential Monte Carlo approach. The tracking involves initializing polygon boundary tracking by selecting pairs of corners from the set of best matching corners to define a first side of a corresponding polygon boundary; tracking all intermediate sides of the polygon boundaries using a particle filter, and terminating polygon boundary tracking by determining the last side of the tracked polygon boundaries to close the polygon boundaries. The particle tracks are then blended to determine polygon matches, which may be made available, such as to a user, for ranking and inspection.

Synthetic Aperture Integration (Sai) Algorithm For Sar Imaging
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US Patent:

8482452, Jul 9, 2013
Filed:

Aug 26, 2011
Appl. No.:

13/219475
Inventors:

David H. Chambers - Livermore CA, US
Jeffrey E. Mast - Loveland CO, US
David W. Paglieroni - Pleasanton CA, US
N. Reginald Beer - Pleasanton CA, US
Assignee:

Lawrence Livermore National Security, LLC - Livermore CA
International Classification:

G01S 13/90
US Classification:

342 22, 342 25 R, 342 25 F
Abstract:

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Spatially Adaptive Migration Tomography For Multistatic Gpr Imaging
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US Patent:

8508403, Aug 13, 2013
Filed:

Aug 26, 2011
Appl. No.:

13/219449
Inventors:

David W. Paglieroni - Pleasanton CA, US
N. Reginald Beer - Pleasanton CA, US
Assignee:

Lawrence Livermore National Security, LLC - Livermore CA
International Classification:

G01S 13/89
US Classification:

342 22, 342179, 342195
Abstract:

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Radar Signal Pre-Processing To Suppress Surface Bounce And Multipath
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US Patent:

8618976, Dec 31, 2013
Filed:

Aug 26, 2011
Appl. No.:

13/219482
Inventors:

David W. Paglieroni - Pleasanton CA, US
Jeffrey E. Mast - Loveland CO, US
N. Reginald Beer - Pleasanton CA, US
Assignee:

Lawrence Livermore National Security, LLC - Livermore CA
International Classification:

G01S 13/00
US Classification:

342 22, 342 27, 342191
Abstract:

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Real-Time System For Imaging And Object Detection With A Multistatic Gpr Array
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US Patent:

20130082856, Apr 4, 2013
Filed:

Aug 26, 2011
Appl. No.:

13/219410
Inventors:

David W. Paglieroni - Pleasanton CA, US
N. Reginald Beer - Pleasanton CA, US
Steven W. Bond - Livermore CA, US
Philip L. Top - West Sacramento CA, US
David H. Chambers - Livermore CA, US
Jeffrey E. Mast - Loveland CO, US
John G. Donetti - Livermore CA, US
Blake C. Mason - Livermore CA, US
Steven M. Jones - Danville CA, US
International Classification:

G01S 13/89
G01S 13/90
US Classification:

342 22, 342 25 A
Abstract:

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Distributed Road Assessment System
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US Patent:

20130082857, Apr 4, 2013
Filed:

Aug 26, 2011
Appl. No.:

13/219430
Inventors:

N. Reginald Beer - Pleasanton CA, US
David W. Paglieroni - Pleasanton CA, US
International Classification:

G01N 29/04
G01N 33/42
US Classification:

342 22
Abstract:

A system that detects damage on or below the surface of a paved structure or pavement is provided. A distributed road assessment system includes road assessment pods and a road assessment server. Each road assessment pod includes a ground-penetrating radar antenna array and a detection system that detects road damage from the return signals as the vehicle on which the pod is mounted travels down a road. Each road assessment pod transmits to the road assessment server occurrence information describing each occurrence of road damage that is newly detected on a current scan of a road. The road assessment server maintains a road damage database of occurrence information describing the previously detected occurrences of road damage. After the road assessment server receives occurrence information for newly detected occurrences of road damage for a portion of a road, the road assessment server determines which newly detected occurrences correspond to which previously detected occurrences of road damage.

Classification Of Subsurface Objects Using Singular Values Derived From Signal Frames
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US Patent:

20130082858, Apr 4, 2013
Filed:

Aug 26, 2011
Appl. No.:

13/219435
Inventors:

David H. Chambers - Livermore CA, US
David W. Paglieroni - Pleasanton CA, US
International Classification:

G01S 13/89
US Classification:

342 22
Abstract:

The classification system represents a detected object with a feature vector derived from the return signals acquired by an array of N transceivers operating in multistatic mode. The classification system generates the feature vector by transforming the real-valued return signals into complex-valued spectra, using, for example, a Fast Fourier Transform. The classification system then generates a feature vector of singular values for each user-designated spectral sub-band by applying a singular value decomposition (SVD) to the N×N square complex-valued matrix formed from sub-band samples associated with all possible transmitter-receiver pairs. The resulting feature vector of singular values may be transformed into a feature vector of singular value likelihoods and then subjected to a multi-category linear or neural network classifier for object classification.