Abstract
Modern radar and signal processing systems require efficient computational architectures to handle increasing data rates while still being able to maintain dynamic configurability and complex tasks. This thesis presents and explores hardware and algorithmic approaches addressing these demands across several different applications. First, a low-cost tracking platform and architecture for unmanned aerial vehicles (UAVs) is developed, which provides detection and tracking capabilities, compliant with new FAA remote ID regulations. Second, a GPU-FPGA based digital true time delay beamformer is implemented to achieve real-time wideband radio frequency interference (RFI) mitigation. Specifically this beamformer explores weight calculation and calibration through particle swarm optimization, a genetic algorithm implemented to achieve dynamic suppression of desired signals. Finally, a heterogeneous digital signal processing (DSP) architecture combining FPGA and NVIDIA Jetson ORIN GPU platform is discussed, showing improvements and and implementations for bi-directional high data rate applications.
Degree
MS
College and Department
Ira A. Fulton College of Engineering; Electrical and Computer Engineering
Rights
https://lib.byu.edu/about/copyright/
BYU ScholarsArchive Citation
Burnett, Nathan Lynn, "Compact Heterogeneous Architectures and Algorithmic Methods for Enhanced Real-Time Digital True Time Delay Beamforming and Radar Applications" (2025). Theses and Dissertations. 10937.
https://scholarsarchive.byu.edu/etd/10937
Date Submitted
2025-08-11
Document Type
Thesis
Permanent Link
https://apps.lib.byu.edu/arks/ark:/34234/q2513ba4cc
Keywords
temporal filtering, beamforming, phased array, GPU, RFSoC, true time delay, Hadamard projection, arbitrary waveform generator
Language
english