Real-time GPU Based Arbitrary Waveform Generation Utilizing a Software-Defined Radar Platform

Due to the ever-growing demand for access to the finite resources of the electromagnetic spectrum, significant effort has been directed toward improving spectrum utilization. This has become a particular challenge in radar transmission design, where waveform diversity techniques have emerged as a promising solution despite the accompanying implementation complexity. Diverse signals are inherently non-repeating and pose unique challenges in comparison to traditional radar waveforms. Software defined radios (SDRs) allow for traditional RF components and signal processing to be implemented and controlled in software rather than hardware, providing a platform for testing experimental radar algorithms. This thesis presents a real-time parallel implementation of five previously developed distinct waveform-diverse radar signals for use in a coherent SDR system. The implemented waveforms include stochastic waveform generation (StoWGe), multi-user radar communication (MURC), phase-attached radar communication (PARC), pseudo-random optimized frequency modulation (PRO-FM), and waveform recycling. To enable real-time generation at maximum SDR data rates, these waveforms are implemented using digital synthesis techniques via GPU parallel processing. This approach alleviates CPU resource limitations by offloading computationally intensive waveform generation tasks to the GPU, enabling continuous high-throughput operation. A custom asynchronous transmit and receive architecture is developed to integrate these GPU-accelerated waveforms with UHD-based SDR hardware. The system leverages a multithreaded framework approach that can sustain coherent and synchronized radar operation. To validate the system, a series of loopback testing across all waveforms and a variety of parameters is completed to confirm the execution of the generate-transmit-receive chain.