Real-Time Doppler and Ionospheric Dispersion Correction Techniques for Arbitrary Waveforms Utilizing GPU Compute

TL;DR

This paper demonstrates real-time Doppler and ionospheric dispersion correction for arbitrary radar waveforms using GPU computing, enhancing system flexibility and performance in digital signal processing.

Contribution

It introduces GPU-based algorithms for ionospheric and Doppler dispersion correction that are waveform-agnostic and achieve real-time performance.

Findings

Algorithms perform in real-time on NVIDIA H100 GPU.

Dispersion correction accuracy matches waveform-specific methods.

Methods improve flexibility for software-defined radar systems.

Abstract

General requirements for radar digital signal processing are ionospheric distortion and Doppler dispersion correction, which has historically required radar-specific hardware to implement in real time. Although analog solutions are computationally efficient, they often come with system design drawbacks which limit waveform flexibility and can result in an overall increase of system complexity. With improvements in modern general compute systems, real-time digital signal processing is becoming more realizable using non-radar-specific high-performance compute. In this paper, we present an analysis of general Doppler and ionospheric correction algorithms for arbitrary waveforms for radar digital signal processing. We also include considerations for efficient implementation of these algorithms in software, specifically using GPU hardware. This analysis includes metrics of performance such as execution time and error correction accuracy. We also provide recommendations for application in radar signal processing. We identify two algorithms for dispersion correction: an FFT-based method for ionospheric dispersion and a numerical interpolation method via sinc interpolation for Doppler dispersion. Both of these algorithms are able to compensate for dispersion equivalent in accuracy to waveform-specific analytical methods and were able to be performed in real-time on a single NVIDIA H100 GPU. These methods are waveform agnostic and applied directly to the samples, improving system flexibility and making them easy to incorporate into existing software-defined radio systems.