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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 …
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 …
Chaos-Based Coffee Can Radar System, Conor Willsie, Rong Chen
Chaos-Based Coffee Can Radar System, Conor Willsie, Rong Chen
Honors Theses
Linear frequency modulated (LFM) radar systems are simple and easy to implement, making them ideal for inexpensive undergraduate research projects. Unfortunately, LFM radar schemes have multiple limitations that make them unviable in many real-world applications. Given the limitations of LFM radar systems, we propose a chaos-based frequency modulated (CBFM) system. In this paper, we present the theory, design, and experimental verification of a CBFM radar system that has both ranging and synthetic aperture radar imaging capabilities. The performance of our CBFM system is compared to that of the LFM system designed by MIT. We document many challenges and unforeseen obstacles …