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Full-Text Articles in Engineering
Theory And Design Of A Highly Compressed Dropped-Channel Polarimetric Synthetic Aperture Radar, John T. Becker
Theory And Design Of A Highly Compressed Dropped-Channel Polarimetric Synthetic Aperture Radar, John T. Becker
Theses and Dissertations
Compressed sensing (CS) is a recent mathematical technique that leverages the sparsity in certain sets of data to solve an underdetermined system and recover a full set of data from a sub-Nyquist set of measurements of the data. Given the size and sparsity of the data, radar has been a natural choice to apply compressed sensing to, typically in the fast-time and slow-time domains. Polarimetric synthetic aperture radar (PolSAR) generates a particularly large amount of data for a given scene; however, the data tends to be sparse. Recently a technique was developed to recover a dropped PolSAR channel by leveraging …
Effects Of Motion Measurement Errors On Radar Target Detection, Darnell D. Parker
Effects Of Motion Measurement Errors On Radar Target Detection, Darnell D. Parker
Theses and Dissertations
This thesis investigates the relationships present between signal-to-clutter ratios, motion measurement errors, image quality metrics, and the task of target detection, in order to discover what factor merit greater focus in order to attain the highest probability of target detection success. This investigation is accomplished by running a high number of Monte Carlo trials through a coherent target detector and analyzing the results. The aforementioned relationships are demonstrated via sample synthetic aperture radar imagery, histograms, receiver operating characteristics curves, and error bar plots.
Polarization-Based Image Segmentation And Height Estimation For Interferometric Sar, Augusta J. Vande Hey
Polarization-Based Image Segmentation And Height Estimation For Interferometric Sar, Augusta J. Vande Hey
Theses and Dissertations
To find scatterers in a synthetic aperture radar (SAR) image, a modification is proposed to improve peak region segmentation (PRS) with region merging. The modification considers the polarization of each pixel before it is added to a segment to ensure the segment only contains pixels of the same polarization. Prior to region merging, the polarization of the segments is compared, so that only segments with the same polarization are merged into a single region. The segmented regions are used to find the height of each scatterer through interferometric SAR (IFSAR) processing. Multiple methods of IFSAR are examined to find the …
Synthetic Aperture Radar Image Recognition Of Armored Vehicles, Christopher Szul [*], Torrey J. Wagner, Brent T. Langhals
Synthetic Aperture Radar Image Recognition Of Armored Vehicles, Christopher Szul [*], Torrey J. Wagner, Brent T. Langhals
Faculty Publications
Synthetic Aperture Radar (SAR) imagery is not affected by weather and allows for day-and-night observations, however it can be difficult to interpret. This work applies classical and neural network machine learning techniques to perform image classification of SAR imagery. The Moving and Stationary Target Acquisition and Recognition dataset from the Air Force Research Laboratory was used, which contained 2,987 total observations of the BMP-2, BTR-70, and T-72 vehicles. Using a 75%/25% train/test split, the classical model achieved an average multi-class image recognition accuracy of 70%, while a convolutional neural network was able to achieve a 97% accuracy with lower model …
Sar Collection Planning And Data Quality Assessment, Jacob M. Brumfield
Sar Collection Planning And Data Quality Assessment, Jacob M. Brumfield
Theses and Dissertations
Radar resource management is an important research topic in the radar community. Identifying the performance of a synthetic aperture radar image early into a data processing chain can improve intelligence collection mission performance. To achieve that goal, separate flags can be presented to a radar technician along a data processing chain to identify various errors within a data collection. Toward the end, this thesis analyzes he radar image processing chain and identifies data quality checks that could be implemented. The first quality check is to identify canonical targets and the necessary Nyquist-Shannon sampling requirements. Then, observations can be made to …
Effects Of Long-Term Evolution Waveform On Synthetic Aperture Radar Image Quality Metrics, Blake M. Colson
Effects Of Long-Term Evolution Waveform On Synthetic Aperture Radar Image Quality Metrics, Blake M. Colson
Theses and Dissertations
As a greater demand by the private sector for bandwidth drives spectrum allocations away from defense, new methods for coexistence in the spectrum are being explored. One of the prominent areas in defense for this coexistence is passive radar. This mode of radar system allows for data collection by referencing signals already established in the environment of interest. Some of the most prolific signals currently available are those used for mobile communication networks. In particular, Long- Term Evolution (LTE) is a common waveform that could be leveraged for discrete collection of image intelligence. Seeking to build a base of knowledge, …
Target Detection In Heterogeneous Clutter With Low Resolution Radar, Kyle G. Stankowski
Target Detection In Heterogeneous Clutter With Low Resolution Radar, Kyle G. Stankowski
Theses and Dissertations
This thesis develops a framework for SAR target detection and super-resolution in low-resolution environments. The primary focus in this research is the background clutter heterogeneity that often accompanies low range and cross-range resolutions. A corrective model which accounts for clutter replacement is developed to define the detection and false alarm rates of the detector more accurately than a traditional model in which the radar return from the target supplements the existing clutter. In a heterogeneous clutter cell, the clutter replacement model leverages the different scattering distributions among the individual clutter types to generate a probability distribution function for the areas …
Implementation And Performance Of Factorized Backprojection On Low-Cost Commercial-Off-The-Shelf Hardware, Alec C. Rasmussen
Implementation And Performance Of Factorized Backprojection On Low-Cost Commercial-Off-The-Shelf Hardware, Alec C. Rasmussen
Theses and Dissertations
Traditional Synthetic Aperture Radar (SAR) systems are large, complex, and expensive platforms that require significant resources to operate. The size and cost of the platforms limits the potential uses of SAR to strategic level intelligence gathering or large budget research efforts. The purpose of this thesis is to implement the factorized backprojection SAR image processing algorithm in the C++ programming language and test the code's performance on a low cost, low size, weight, and power (SWAP) computer: a Raspberry Pi Model B. For a comparison of performance, a baseline implementation of filtered backprojection is adapted to C++ from pre-existing MATLAB® …
Hardware Development And Error Characterisation For The Afit Rail Sar System, Dayne A. Schmidt
Hardware Development And Error Characterisation For The Afit Rail Sar System, Dayne A. Schmidt
Theses and Dissertations
This research is focussed on updating the Air Force Institute of Technology (AFIT) Radar Instrumentation Lab (RAIL) Synthetic Aperture Radar (SAR) experimental system. Firstly, this research assesses current hardware limitations and updates the system configuration and methodology to enable collections from a receiver in motion. Secondly, orthogonal frequency-division multiplexing (OFDM) signals are used to form (SAR) images in multiple experimental and simulation configurations. This research analyses, characterises and attempts compensation of relevant SAR image error sources, such as Doppler shift or motion measurement errors (MMEs). Error characterisation is conducted using theoretical, simulated and experimental methods. Final experimental results are presented …
Bayesian Methods And Confidence Intervals For Automatic Target Recognition Of Sar Canonical Shapes, Richard W. Rademacher
Bayesian Methods And Confidence Intervals For Automatic Target Recognition Of Sar Canonical Shapes, Richard W. Rademacher
Theses and Dissertations
This research develops a new Bayesian technique for the detection of scattering primitives in synthetic aperture radar (SAR) phase history data received from a sensor platform. The primary goal of this research is the estimation of size, position, and orientation parameters defined by the “canonical” shape primitives of Jackson. Previous Bayesian methods for this problem have focused on the traditional maximum a posteriori (MAP) estimate based on the posterior density. A new concept, the probability mass interval, is developed. In this technique the posterior density is partitioned into intervals, which are then integrated to form a probability mass over that …
Passive Synthetic Aperture Radar Imaging Using Commercial Ofdm Communication Networks, Jose R. Gutierrez Del Arroyo
Passive Synthetic Aperture Radar Imaging Using Commercial Ofdm Communication Networks, Jose R. Gutierrez Del Arroyo
Theses and Dissertations
Modern communication systems provide myriad opportunities for passive radar applications. OFDM is a popular waveform used widely in wireless communication networks today. Understanding the structure of these networks becomes critical in future passive radar systems design and concept development. This research develops collection and signal processing models to produce passive SAR ground images using OFDM communication networks. The OFDM-based WiMAX network is selected as a relevant example and is evaluated as a viable source for radar ground imaging. The monostatic and bistatic phase history models for OFDM are derived and validated with experimental single dimensional data. An airborne passive collection …
Target Classification Of Canonical Scatterers Using Classical Estimation And Dictionary Based Techniques, G. Barry Hammond Ii
Target Classification Of Canonical Scatterers Using Classical Estimation And Dictionary Based Techniques, G. Barry Hammond Ii
Theses and Dissertations
This research effort will utilize a hierarchical dictionary-based approach for canonical shape classification within measured synthetic aperture radar (SAR) phase history data. This primary goal of this research is to develop an efficient framework for dictionary based SAR feature extraction using modi ed 3-D radar scattering models. Previous work in this area relies on maximum likelihood (ML) estimation and similar approaches to extract shapes using 2-D signal models. We include characterizations of shape model redundancies caused by similar shape scattering responses. Simulated SAR collection methods, including frequency, elevation aspect, and polarization diversities, are modeled to show reductions in inter-atom correlation. …
The Effect Of Synthetic Aperture Radar Image Resolution On Target Discrimination, John E. Mcgowan
The Effect Of Synthetic Aperture Radar Image Resolution On Target Discrimination, John E. Mcgowan
Theses and Dissertations
This research details the effect of spatial resolution on target discrimination in Synthetic Aperture Radar (SAR) images. Multiple SAR image chips containing targets and non-targets are used to test a baseline Automatic Target Recognition (ATR) system with reduced spatial resolution. Spatial resolution is reduced by lowering the pixel count or synthesizing a degraded image by filtering and reducing the pixel count. A two-parameter Constant False Alarm Rate (CFAR) detector is tested, and three feature sets, size, contrast, and texture, are used to train a linear classifier and to estimate probability density functions for the two classes. The results are scored …
Frequency Diversity For Improving Synthetic Aperture Radar Imaging, Jawad L. Farooq
Frequency Diversity For Improving Synthetic Aperture Radar Imaging, Jawad L. Farooq
Theses and Dissertations
In this work, a novel theoretical framework is presented for using recent advances in frequency diversity arrays (FDAs). Unlike a conventional array, the FDA simultaneously transmits a unique frequency from each element in the array. As a result, special time and space properties of the radiation pattern are exploited to improve cross-range resolution. The idealized FDA radiation pattern is compared with and validated against a full-wave electromagnetic solver, and it is shown that the conventional array is a special case of the FDA. A new signal model, based on the FDA, is used to simulate SAR imagery of ideal point …
Using Shadows To Detect Targets In Synthetic Aperture Radar Imagery, Brian P. Donnell
Using Shadows To Detect Targets In Synthetic Aperture Radar Imagery, Brian P. Donnell
Theses and Dissertations
Synthetic Aperture Radar (SAR) can generate high resolution imagery of re- mote scenes by combining the phase information of multiple radar pulses along a given path. SAR based Intelligence, Surveillance, and Reconnaissance (ISR) has the advantage over optical ISR that it can provide usable imagery in adverse weather or nighttime conditions. Certain radar frequencies can even result in foliage or limited soil penetration, enabling imagery to be created of objects of interest that would otherwise be hidden from optical surveillance systems. This thesis demonstrates the capability of locating stationary targets of interest based on the locations of their shadows and …
Joint Image And Pupil Plane Reconstruction Algorithm Based On Bayesian Techniques, James D. Phillips
Joint Image And Pupil Plane Reconstruction Algorithm Based On Bayesian Techniques, James D. Phillips
Theses and Dissertations
The focus of this research was to develop an joint pupil and focal plane image recovery algorithm for use with coherent LADAR systems. The benefits of such a system would include increased resolution with little or no increase in system weight and volume as well as allowing for operation in the absence of natural light since the target of interest would be actively illuminated. Since a pupil plane collection aperture can be conformal, such a system would also potentially allow for the formation of large synthetic apertures. The system is demonstrated to be robust and in all but extreme cases …
The Effects Of Signal And Image Compression Of Sar Data On Change Detection Algorithms, Kiran Shenoy
The Effects Of Signal And Image Compression Of Sar Data On Change Detection Algorithms, Kiran Shenoy
Theses and Dissertations
With massive amounts of SAR imagery and data being collected, the need for effective compression techniques is growing. One of the most popular applications for remote sensing is change detection, which compares two geo-registered images for changes in the scene. While lossless compression is needed for signal compression, the same is not often required for image compression. In almost every case the compression ratios are much higher in lossy compression making them more appealing when bandwidth and storage becomes an issue. This research analyzes different types of compression techniques that are adapted for SAR imagery, and tests these techniques with …
Point Spread Function Characterization Of A Radially Displaced Scatterer Using Circular Synthetic Aperture Radar, Uttam K. Majumder
Point Spread Function Characterization Of A Radially Displaced Scatterer Using Circular Synthetic Aperture Radar, Uttam K. Majumder
Theses and Dissertations
This research effort investigated characterizing the point spread function (PSF) behavior of radially displaced point scatterers using circular synthetic aperture radar (CSAR). Thus far, research has been conducted to understand PSF of a scatterer located at the imaging scene center. An analytic closed-form solution has been derived assuming the scatterer is located at the origin of the CSAR imaging geometry. However, it is difficult to derive an analytic PSF solution for a scatterer that is radially displaced from the imaging scene center. Using the back projection image formation algorithm, PSF responses are generated at various point target locations. Consistent with …
Verification Of A Decision Level Fusion Algorithm Using A Proven Atr System And Measured Sar Data, James Douglas Thompson
Verification Of A Decision Level Fusion Algorithm Using A Proven Atr System And Measured Sar Data, James Douglas Thompson
Theses and Dissertations
Decision level fusion (DLF) algorithms combine outputs of multiple single sensors to make one confident declaration of a target. This research compares performance results of a DLF algorithm using measured data and a proven ATR system with results from simulated data and a modeled ATR system. This comparison indicates that DLF offers significant performance improvements over single sensor looks. However, results based on simulated data and a modeled ATR are slightly optimistic and overestimate results from measured data and a proven ATR system by nearly 10% over all targets tested.
Doppler Aliasing Reduction In Wide-Angle Synthetic Aperture Radar Using Phase Modulated Random Stepped-Frequency Waveforms, Andrew W. Hyatt
Doppler Aliasing Reduction In Wide-Angle Synthetic Aperture Radar Using Phase Modulated Random Stepped-Frequency Waveforms, Andrew W. Hyatt
Theses and Dissertations
This research effort examines the theory, application and results of side-looking airborne radar operation in hot clutter. Hot clutter is an electronic counter-measure used to degrade the performance of airborne radar. Hot clutter occurs by illuminating the ground with an airborne jammer at some velocity, azimuth, elevation, and range from the airborne radar. When the received RCS scattered hot clutter waveform is perfectly coherent with the radar waveform, the radar believes the returns created by the hot clutter jammer resulted from the transmitting radar. Hot clutter degrades radar performance at locations in azimuth and Doppler. The effect of hot clutter …
Wide-Angle Multistatic Synthetic Aperture Radar: Focused Image Formation And Aliasing Artifact Mitigation, Jonathan E. Luminati
Wide-Angle Multistatic Synthetic Aperture Radar: Focused Image Formation And Aliasing Artifact Mitigation, Jonathan E. Luminati
Theses and Dissertations
Traditional monostatic Synthetic Aperture Radar (SAR) platforms force the user to choose between two image types: larger, low resolution images or smaller, high resolution images. Switching to a Wide-Angle Multistatic Synthetic Aperture Radar (WAM-SAR) approach allows formation of large high-resolution images. Unfortunately, WAM-SAR suffers from two significant implementation problems. First, wavefront curvature effects, non-linear flight paths, and warped ground planes lead to image defocusing with traditional SAR processing methods. A new 3-D monostatic/bistatic image formation routine solves the defocusing problem, correcting for all relevant wide-angle effects. Inverse SAR (ISAR) imagery from a Radar Cross Section (RCS) chamber validates this approach. …
Doppler Aliasing Reduction In Wide-Angle Synthetic Aperture Radar Using A Linear Frequency Modulated Random Stepped-Frequency Waveform, Jason R. Mcmahon
Doppler Aliasing Reduction In Wide-Angle Synthetic Aperture Radar Using A Linear Frequency Modulated Random Stepped-Frequency Waveform, Jason R. Mcmahon
Theses and Dissertations
This research examines the theory, application, and results of using Random Stepped-Frequency (RSF) waveforms to mitigate Doppler aliasing in a wide-angle Synthetic Aperture Radar (SAR) imaging scenario. Severe Doppler aliasing typically occurs in this scenario since range extent requirements force the pulse repetition frequency to a value violating the lower bound for Doppler aliasing. Building on previous research, this work expands upon RSF waveform analysis using a Linear Frequency Modulated RSF (LFM-RSF) waveform. The RSF waveform suppresses Doppler aliasing by positioning nulls at the aliased scatterer location. Applying LFM with RSF processing theoretically provides greater frequency coverage and aliased scatterer …
Cross Range Smear Characterization In Xpatch Isar Images, Peter E. Muend
Cross Range Smear Characterization In Xpatch Isar Images, Peter E. Muend
Theses and Dissertations
This thesis investigates a cross range smear phenomenon seen in far field, frequency domain Xpatch calculations. The phenomenon is very subtle, manifesting itself in 2-D ISAR images as a low-level scatterer response smeared in the cross range direction. This cross range smear occurs only using complex target models with certain characteristics. It is also a mathematical construct, not occurring in physical SAR systems. Using a carefully constructed scattering target set, Xpatch-generated ISAR images are used to characterize cross range smear in terms of its input parameters. The characterization is done as a DOE-based polynomial approximation to the observed smear levels. …
Using Gps As A Reference System To Hit A Moving Target, Daryl J. Burnette
Using Gps As A Reference System To Hit A Moving Target, Daryl J. Burnette
Theses and Dissertations
The Affordable Moving Surface Target Engagement (AMSTE) project attempts to develop affordable solutions to the precise moving target surface target engagement problem. Up to this point, most of the error analysis performed for the AMSTE project has been at the error variance level, generating root-sum-square (RSS) total errors from error budgets consisting of constant error variances. In reality, the level of error for both Global Positioning System (GPS) positioning and radar targeting systems is highly dependent upon the given situation (such as the distance between sensor and target, the altitude differences, etc.) This research generates a more comprehensive model of …
An Objective Evaluation Of Four Sar Image Segmentation Algorithms, Jason B. Gregga
An Objective Evaluation Of Four Sar Image Segmentation Algorithms, Jason B. Gregga
Theses and Dissertations
Because of the large number of SAR images the Air Force generates and the dwindling number of available human analysts, automated methods must be developed. A key step towards automated SAR image analysis is image segmentation. There are many segmentation algorithms, but they have not been tested on a common set of images, and there are no standard test methods. This thesis evaluates four SAR image segmentation algorithms by running them on a common set of data and objectively comparing them to each other and to human segmentors. This objective comparison uses a multi-metric a approach with a set of …
Target Pose Estimation From Radar Data Using Adaptive Networks, Andrew W. Learn
Target Pose Estimation From Radar Data Using Adaptive Networks, Andrew W. Learn
Theses and Dissertations
his research investigates and extends recent work by J.C. Principe at the University of Florida in target pose estimation using adaptive networks. First, Principe's technique is successfully extended to estimate both azimuth and elevation using SAR images. A network trained and tested using MSTAR data yields mean errors of less than six degrees in azimuth and five degrees in elevation. Second, the technique is applied to high-range resolution radar (HRR) signatures. Ground target (azimuth only) testing yields mean errors of less than 11 degrees for most classes. Air target testing for networks trained and tested on the same aircraft class …
Application Of The Finite Element Method To The Scattering Of A Two-Dimensional, Semi-Infinite Periodic Structure, Perry N. Villanueva
Application Of The Finite Element Method To The Scattering Of A Two-Dimensional, Semi-Infinite Periodic Structure, Perry N. Villanueva
Theses and Dissertations
Infinite periodic structures have been studied heavily because of their efficient filtering capabilities. They generally exhibit sharp frequency roll-offs at the frequency band of interest. In the RF region of the electromagnetic spectrum, periodic structures find applications such as radomes and photonic bandgap materials. Most studies have been done with infinitely periodic arrays because it is convenient to collapse an infinite array into one representative period using Floquet Analysis. Truncating an infinite array introduces an edge and invalidates Floquet analysis over the entire array. This thesis formulates a Finite Element Method (FEM) solution of a semi-infinite periodic array consisting of …
A Dispersive Scattering Center, Parametric Model For 1-D Atr, Dane F. Fuller
A Dispersive Scattering Center, Parametric Model For 1-D Atr, Dane F. Fuller
Theses and Dissertations
The dispersive scattering center (DSC) model characterizes high-frequency backscatter from radar targets as a finite sum of localized scattering geometries distributed in range, these geometries, along with their relative locations, can be conveniently used as features in a one-dimensional automatic target recognition (ATR) algorithm. The DSC model's type and range parameters correspond to geometry and distance features according to the geometric theory of diffraction (GTD). Since these parameters are estimated in the phase history domain of the radar signal, the range parameter does provide superresolution in the time domain. To demonstrate the viability of feature extraction based on the DSC …
Maximum Likelihood Estimation Of Exponentials In Unknown Colored Noise For Target In Identification Synthetic Aperture Radar Images, Matthew P. Pepin
Maximum Likelihood Estimation Of Exponentials In Unknown Colored Noise For Target In Identification Synthetic Aperture Radar Images, Matthew P. Pepin
Theses and Dissertations
This dissertation develops techniques for estimating exponential signals in unknown colored noise. The Maximum Likelihood ML estimators of the exponential parameters are developed. Techniques are developed for one and two dimensional exponentials, for both the deterministic and stochastic ML model. The techniques are applied to Synthetic Aperture Radar SAR data whose point scatterers are modeled as damped exponentials. These estimated scatterer locations exponentials frequencies are potential features for model-based target recognition. The estimators developed in this dissertation may be applied with any parametrically modeled noise having a zero mean and a consistent estimator of the noise covariance matrix. ML techniques …
Maximum Likelihood Estimation Of Exponentials In Unknown Colored Noise For Target Identification In Synthetic Aperture Radar Images, Matthew P. Pepin
Maximum Likelihood Estimation Of Exponentials In Unknown Colored Noise For Target Identification In Synthetic Aperture Radar Images, Matthew P. Pepin
Theses and Dissertations
This dissertation develops techniques for estimating exponential signals in unknown colored noise. The Maximum Likelihood (ML) estimators of the exponential parameters are developed. Techniques are developed for one and two dimensional exponentials, for both the deterministic and stochastic ML model. The techniques are applied to Synthetic Aperture Radar (SAR) data whose point scatterers are modeled as damped exponentials. These estimated scatterer locations (exponentials frequencies) are potential features for model-based target recognition. The estimators developed in this dissertation may be applied with any parametrically modeled noise having a zero mean and a consistent estimator of the noise covariance matrix. ML techniques …