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Full-Text Articles in Signal Processing
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 …
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 …
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 …
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 …