Dr. Guillermo C. Gaunaurd Profile

Dr. Guillermo C. Gaunaurd

Retired from ARL at

SPIE Involvement:

Fellow status | Conference Program Committee | Author

Publications (36)

SPIE Journal Paper | April 1, 2009

Time-frequency analysis of synthetic aperture radar images of selected ordnance pieces

Wong, David , Nguyen, Lam , Gaunaurd, Guillermo , Sullivan, Anders

JEI Vol. 18 Issue 02

KEYWORDS: Synthetic aperture radar, Time-frequency analysis, Radar, Data modeling, Land mines, Metals, Target detection, Roads, Signal detection, Antennas

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SPIE Journal Paper | February 1, 2008

Impact of rain on radar transmittance through building walls

Gaunaurd, Guillermo , Nguyen, Lam

OE Vol. 47 Issue 02

KEYWORDS: Transmittance, Radar, Water, Reflectivity, Optical engineering, Unattended ground sensors, Dielectrics, Microwave radiation, Homogenization, Refractive index

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SPIE Journal Paper | July 1, 2007

Computerized tomographic radar target imaging behind opaque walls

Nguyen, Lam , Le, Calvin , Gaunaurd, Guillermo

OE Vol. 46 Issue 07

KEYWORDS: Radar, Tomography, Fourier transforms, Synthetic aperture radar, Radar imaging, Scattering, Signal attenuation, Dielectrics, Computed tomography, Target detection

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SPIE Journal Paper | July 1, 2007

Time-frequency analysis for radar classification of land-mine images

Wong, David , Nguyen, Lam , Gaunaurd, Guillermo

JEI Vol. 16 Issue 03

KEYWORDS: Mining, Synthetic aperture radar, Time-frequency analysis, Radar, Image classification, Soil science, Inspection, Metals, Algorithm development, Spatial resolution

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PROCEEDINGS ARTICLE | May 7, 2007

Radar classification of landmines by time-frequency analysis

Proc. SPIE. 6566, Automatic Target Recognition XVII

KEYWORDS: Radar, Soil science, Synthetic aperture radar, Silicon, Polarimetry, Mining, Algorithm development, Time-frequency analysis, Land mines

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PROCEEDINGS ARTICLE | May 18, 2006

Comparison of optimization-algorithm based feature extraction from time data or time-frequency data for target recognition purposes

Proc. SPIE. 6234, Automatic Target Recognition XVI

KEYWORDS: Roads, Soil science, Metals, Dielectrics, Mining, Target recognition, Time-frequency analysis, Ground penetrating radar, Land mines, General packet radio service

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SPIE Journal Paper | December 1, 2005

Buried object characterization via ground-penetrating radar and Huynen polarimetric parameters

Sadjadi, Firooz , Chun, Cornell , Sullivan, Anders , Gaunaurd, Guillermo

OE Vol. 44 Issue 12

KEYWORDS: Scattering, Radar, Dielectrics, Optical engineering, Magnetism, Polarimetry, Mining, Land mines, Matrices, Ground penetrating radar

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PROCEEDINGS ARTICLE | May 19, 2005

A method for classifying underground targets and simultaneously estimating their burial conditions

Proc. SPIE. 5807, Automatic Target Recognition XV

KEYWORDS: Radar, Roads, Soil science, Metals, Mining, Antennas, Target recognition, Time-frequency analysis, Land mines, General packet radio service

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Ultra-wideband ground penetrating radar (GPR) systems are useful for extracting and displaying information for target recognition purposes. The frequency content of projected signals is designed to match the size and type of prospective targets and environments. Target signatures whether in the time, frequency, or joint time-frequency domains, will substantially depend on the target's burial conditions such as the type of soil, burial depth, and the soil’s moisture content. Such returned echoes from two targets for several moisture contents and burial depths in a soil with known electrical properties were simulated earlier by using a Method-of-Moments (MoM) code. The signature template of each target was computed using a time-frequency distribution of the returned echo when the target was buried at standard conditions, namely, a selected depth in the soil with a selected moisture content. For any returned echo the relative difference between the likewise computed target signature and a template signature was computed. That signature difference, chosen as objective function, or cost function, could then be minimized by adjusting the depth and moisture content, now taken to be unknown parameters. This can be done using the differential evolution method (DEM) together with our target translation method (TTM). The template that gave the smallest value of the minimized objective function for the returned echo signified the classification, and the corresponding values of the depth and moisture parameters turned out to be good predictions of the actual target depth and soil moisture content. Here, we implement a more efficient and faster running version of this classification method on a stepped-frequency continuous-wave (SFCW) GPR system. We demonstrate the ability to classify mines or mine-like targets buried underground from measured GPR signals. The targets are buried either in an indoor sandbox or in a test field at the Swedish Explosive Ordnance Disposal and Demining Center (SWEDEC) at Eksjo, Sweden.

PROCEEDINGS ARTICLE | September 21, 2004

Simultaneous classification of underground targets and determination of burial depth and soil moisture content

Proc. SPIE. 5426, Automatic Target Recognition XIV

KEYWORDS: Soil science, Scattering, Metals, Dielectrics, Mining, Target recognition, Time-frequency analysis, Ground penetrating radar, General packet radio service, Bandpass filters

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PROCEEDINGS ARTICLE | September 16, 2003

Reception and processing of electromagnetic pulses after propagation through dispersive and dissipative media

Proc. SPIE. 5094, Automatic Target Recognition XIII

KEYWORDS: Soil science, Reflection, Scattering, Metals, Dielectrics, Mining, Target recognition, Time-frequency analysis, Radio propagation, General packet radio service

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SPIE Journal Paper | February 1, 2003

Use of Mueller matrices in the photoelastic determination of the stress distribution in a model for a solid propellant rocket grain

Gaunaurd, Guillermo

OE Vol. 42 Issue 02

KEYWORDS: Mueller matrices, Photoelasticity, Rockets, Solids, Optical engineering, Calibration, Combustion, Wave plates, Radar, Photography

PROCEEDINGS ARTICLE | July 25, 2002

Influence of soil properties on time-frequency signatures of conducting and dielectric targets buried underground

Proc. SPIE. 4726, Automatic Target Recognition XII

KEYWORDS: Radar, Soil science, Metals, Dielectrics, Signal generators, Target recognition, Automatic target recognition, Environmental sensing, Time-frequency analysis, Land mines

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PROCEEDINGS ARTICLE | October 22, 2001

Automatic classification of minelike targets buried underground using time-frequency signatures extracted by a stepped-frequency radar

Proc. SPIE. 4379, Automatic Target Recognition XI

KEYWORDS: Target detection, Radar, Detection and tracking algorithms, Metals, Fourier transforms, Antennas, Target recognition, Nonmetals, Signal detection, Time-frequency analysis

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PROCEEDINGS ARTICLE | August 17, 2000

Comparison of the relative merits for target recognition by ultrawideband radar based on emitted impulse or step-frequency wave

Proc. SPIE. 4050, Automatic Target Recognition X

KEYWORDS: Radar, Optical spheres, Metals, Fourier transforms, Antennas, Target recognition, Signal detection, Time-frequency analysis, Ground penetrating radar, General packet radio service

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PROCEEDINGS ARTICLE | August 24, 1999

Comparison of fuzzy-cluster-based time-frequency signatures for automatic classification of underground minelike targets

Proc. SPIE. 3718, Automatic Target Recognition IX

KEYWORDS: Radar, Radon, Detection and tracking algorithms, Metals, Mining, Antennas, Fuzzy logic, Time-frequency analysis, Ground penetrating radar, General packet radio service

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PROCEEDINGS ARTICLE | March 22, 1999

Applications of time-frequency signature analysis to target identification

Proc. SPIE. 3723, Wavelet Applications VI

KEYWORDS: Radar, Optical spheres, Coating, Fourier transforms, Feature extraction, Target recognition, Signal analyzers, Spherical lenses, Time-frequency analysis, Ground penetrating radar

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PROCEEDINGS ARTICLE | September 18, 1998

Bistatic radar cross-sections and time-frequency signatures of dielectrically coated targets illuminated by an electromagnetic pulse

Proc. SPIE. 3371, Automatic Target Recognition VIII

KEYWORDS: Radar, Optical spheres, Scattering, Dielectrics, Coating, Target recognition, Spherical lenses, Electromagnetism, Electromagnetic scattering, Time-frequency analysis

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PROCEEDINGS ARTICLE | September 18, 1998

Time-frequency signatures based on a fuzzy-cluster representation as a means for automatic classification of targets buried underground

Proc. SPIE. 3371, Automatic Target Recognition VIII

KEYWORDS: Radar, Detection and tracking algorithms, Metals, Antennas, Target recognition, Nonmetals, Fuzzy logic, Time-frequency analysis, Ground penetrating radar, General packet radio service

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We study the backscattered echoes from selected targets that are extracted by an impulse radar system playing the role of a ground penetrating radar (GPR). The targets are metal and nonmetal objects buried to a selected depth in dry sand in an indoor sandbox. The recorded time-series data are analyzed in the joint time-frequency domain using a pseudo-Wigner distribution (PWD). These distributions with their extracted features in the two-dimensional time-frequency domain are viewed as the target signatures. To be useful for target identification purposes, a signature representation should display a 'sufficient' amount of distinguishing features, yet be robust enough to suppress the interference of noise contained in the received signals. Multiple scattering between a target and the surface of the ground is another obstacle for successful target recognition that time-frequency distributions could counteract by unveiling the time progression of the returned target information. We have previously demonstrated the merits of the PWD relative to various competing time-frequency distributions, in particular its capability of extracting a target's time-frequency signature when the target is buried at different depths. We have also used a classification method developed from the fuzzy C-means clustering technique to reduce the number and kind of features in the PWD signature templates. This is accomplished by converting the PWD signature into a point cluster representation and then reducing the cluster to a (smaller) number of cluster centers. This classification method has been further developed by associating a weight with each point in the cluster representation. We put the classification algorithm to a test against validation data taken from an additional set of returned echoes. The same targets are used but they are buried at a different location in the sand. Class membership of a target is then decided using a simple metric. The results of our investigation serve to assess the possibility of identifying subsurface targets using a GPR.

PROCEEDINGS ARTICLE | June 23, 1997

Analysis in the joint time-frequency domain of the identifying signatures of submerged targets insonified by dolphin clicks

Proc. SPIE. 3069, Automatic Target Recognition VII

KEYWORDS: Radar, Scattering, Fourier transforms, Interference (communication), Smoothing, Target recognition, Signal analyzers, Acoustics, Active sonar, Time-frequency analysis

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We study the scattering interaction of dolphin-emitted acoustic pulses ('clicks') with various elastic shells located, underwater, in front of the animal in a large test site in Kaneohe Bay, Hawaii. A carefully instrumented analog- to-digital system continuously captured the emitted clicks and also the returned, backscattered echoes. Using standard conditioning techniques and food reinforcers, the dolphin is taught to push an underwater paddle when the 'correct' target -- the one he has been trained to identify -- is presented to him. He communicates to us his consistently correct identifying choices in this manner. By means of several time- frequency distributions (TFD) of the Wigner-type, or Cohen class, we examine echoes returned by three types of cylindrical shells. The time-frequency distributions we compare in this survey are the pseudo-Wigner distribution (PWD), the Choi-Williams distribution (CWD), the adaptive spectrogram (AS), the cone-shaped distribution (CSD), the Gabor spectrogram (GS), and the spectrogram (SPEC). To be satisfactory for target identification purposes, a time- frequency representation of the echoes should display a sufficient amount of distinguishing features, and still be robust enough to suppress the interference of noise contained in the received signals. Both these properties in a time- frequency distribution depend on the distribution's capability of concentrating the featuers in time and frequency and of handling cross-term interference. With some time-frequency distributions there is a trade-off between the concentration of features and the suppression of cross-term interference. The results of our investigation serve the twofold purposes of (1) advancing the understanding of the amazing target identification capability of dolphins, and (2) to assist in assessing the possibility of identifying submerged targets using active sonar and a classifier based on target signatures in the combined time-frequency domain.

PROCEEDINGS ARTICLE | June 23, 1997

Fuzzy-cluster representation of time-frequency signatures as a means for classification of targets buried underground

Proc. SPIE. 3069, Automatic Target Recognition VII

KEYWORDS: Radar, Detection and tracking algorithms, Metals, Antennas, Target recognition, Nonmetals, Fuzzy logic, Time-frequency analysis, Ground penetrating radar, General packet radio service

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PROCEEDINGS ARTICLE | May 24, 1996

Understanding the echo clues used by dolphins to remotely identify the target characteristics of submerged elastic shells

Proc. SPIE. 2756, Automatic Object Recognition VI

KEYWORDS: Cadmium, Databases, Metals, Water, Wave plates, Control systems, Aluminum, Biological research, Target recognition, Acoustics

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PROCEEDINGS ARTICLE | May 24, 1996

Analysis in the joint time-frequency domain of signatures extracted from targets buried underground

Proc. SPIE. 2756, Automatic Object Recognition VI

KEYWORDS: Radar, Optical spheres, Scattering, Metals, Multiple scattering, Antennas, Target recognition, Time-frequency analysis, Ground penetrating radar, General packet radio service

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PROCEEDINGS ARTICLE | July 5, 1995

Signature features in time-frequency of simple targets extracted by ground penetrating radar

Proc. SPIE. 2485, Automatic Object Recognition V

KEYWORDS: Radar, Optical spheres, Metals, Feature extraction, Multiple scattering, Antennas, Target recognition, Time-frequency analysis, Ground penetrating radar, General packet radio service

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PROCEEDINGS ARTICLE | July 5, 1995

Electromagnetic scattering from finite-length cylinders and rods

Proc. SPIE. 2485, Automatic Object Recognition V

KEYWORDS: Radar, Diffraction, Polarization, Backscatter, Scattering, Electromagnetic radiation, Rayleigh scattering, Antennas, Geometrical optics, Electromagnetic scattering

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PROCEEDINGS ARTICLE | July 29, 1994

Identification of cylindrical shells with sets of reinforcing ribs by their acoustic Bragg diffraction (grating) patterns

Proc. SPIE. 2234, Automatic Object Recognition IV

KEYWORDS: Diffraction, Scattering, Distortion, Acoustics, Diffraction gratings

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PROCEEDINGS ARTICLE | July 29, 1994

Aspect dependence of impulse radar extracted signature features in the combined time-frequency domain

Proc. SPIE. 2234, Automatic Object Recognition IV

KEYWORDS: Radar, Scattering, 3D modeling, Feature extraction, Electronic filtering, 3D displays, Signal analyzers, Electromagnetism, Electromagnetic scattering, Time-frequency analysis

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PROCEEDINGS ARTICLE | October 15, 1993

Bistatic scattering by a spherical dielectric target illuminated by an electromagnetic pulse

Proc. SPIE. 1960, Automatic Object Recognition III

KEYWORDS: Radar, Optical spheres, Scattering, Dielectrics, Object recognition, Antennas, Spherical lenses, Electromagnetism, Electromagnetic scattering, Time-frequency analysis

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PROCEEDINGS ARTICLE | October 15, 1993

Resonance sonar identification of submerged shells that have oscillating internal masses attached by springs

Proc. SPIE. 1960, Automatic Object Recognition III

KEYWORDS: Oscillators, Warfare, Modulation, Scattering, Distortion, Object recognition, Motion models, Acoustics, Spherical lenses, Commercial off the shelf technology

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SPIE Journal Paper | December 1, 1992

Strong resonance features present in the acoustic signatures of submerged elastic structures

Werby, Michael , Gaunaurd, Guillermo

OE Vol. 31 Issue 12

KEYWORDS: Acoustics, Solids, Phase velocity, Scattering, Spherical lenses, Wave plates, Optical spheres, Signal detection, Laser scattering

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SPIE Journal Paper | December 1, 1992

Active acoustic classification via transient resonance scattering

Gaunaurd, Guillermo

OE Vol. 31 Issue 12

KEYWORDS: Scattering, Acoustics, Optical spheres, Digital signal processing, Spherical lenses, Information operations, Inverse scattering problem, Chlorine, Solids

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PROCEEDINGS ARTICLE | September 16, 1992

Importance of the S1 symmetric Lamb wave in high frequency-scattering from spherical shells

Proc. SPIE. 1700, Automatic Object Recognition II

KEYWORDS: Scattering, Interfaces, Wave plates, Wave propagation, Solids, Object recognition, Spherical lenses, Bromine, Phase velocity, Liquids

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PROCEEDINGS ARTICLE | September 16, 1992

Classification of elastic objects by active sonar in the vicinity of shallow sea boundaries

Proc. SPIE. 1700, Automatic Object Recognition II

KEYWORDS: Optical spheres, Backscatter, Scattering, Interfaces, Solids, Object recognition, Aluminum, Chemical elements, Spherical lenses, Active sonar

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PROCEEDINGS ARTICLE | September 16, 1992

Extraction of target signature features in the combined time-frequency domain by means of impulse radar

Proc. SPIE. 1700, Automatic Object Recognition II

KEYWORDS: Radar, Optical spheres, Scattering, Metals, Fourier transforms, Data processing, Object recognition, Antennas, Target recognition, Time-frequency analysis

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PROCEEDINGS ARTICLE | August 1, 1991

Target identification by means of impulse radar

Proc. SPIE. 1471, Automatic Object Recognition

KEYWORDS: Radar, Optical spheres, Digital filtering, Dielectrics, Fourier transforms, Solids, Object recognition, Target recognition, Spherical lenses, Bandpass filters

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PROCEEDINGS ARTICLE | August 1, 1991

Inverse scattering problems in the acoustic resonance region of an underwater target

Proc. SPIE. 1471, Automatic Object Recognition

KEYWORDS: Digital signal processing, Optical spheres, Scattering, Sensors, Object recognition, Target recognition, Automatic target recognition, Acoustics, Spherical lenses, Inverse scattering problem

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