Designing Low-Correlation GPS Spreading Codes with a Natural Evolution Strategy Machine-Learning Algorithm

Abstract

Operations Squadron (2 SOPS) issued a statement that the first GPS III satellite was marked healthy and available for use (Cozzens, 2020). This announcement officially marked the birth of the next-generation GPS constellation. In addition to broadcasting the new L1C signal, the modernized constellation was distinguished by its reprogrammable payload which allows it to evolve with new technologies and changing mission needs.Furthermore, with the upcoming launch of the Navigation Technology Satellite-3 (NTS-3) testing platform in 2023 (Cozzens, 2021), the United States Air Force (USAF) seeks to explore technologies which will help shape future GPS constellations (Chapman et al., 2020). The NTS-3 will demonstrate the agility of the next-generation satellite-based navigation architecture and the ability to rapidly deploy new technological advancements and capabilities via the reprogrammable

Spreading code optimization for low-earth orbit satellites via mixed-integer convex programming

“…To address those limitations, there has been growing interest in designing the spreading codes by directly optimizing the auto-and cross-correlation. Populationbased methods, such as genetic algorithms [21,22], natural evolution strategies [23], and the cross-entropy method [24], have been applied, and the European Union's Galileo constellation uses spreading codes designed by a genetic algorithm [12,25]. However, those methods do not consider the structure in the objective, and often require extensive tuning in order to work well.…”

“…However, those methods do not consider the structure in the objective, and often require extensive tuning in order to work well. In addition, they have focused on codes for medium-Earth orbit (MEO) constellations such as GPS [16,23] and Galileo constellations [12,25]. In those settings, the code length is orders of magnitude larger than the number of the codes; this is necessary for good system performance due to the relatively lower SNR in the MEO setting.…”

Research on Acquisition Performance of FFT Algorithm for Low-Frequency Spread-Spectrum Signals Using Acoustic Sensors

“…Since radio spread-spectrum carriers are radio frequency carriers with a high code rate, long spreading spectrum codes, such as the GPS C/A code as a 10-order sequence [3], are generally directly used to boost performance. In the field of GNSS, abundant research has been conducted on spreading spectrum code design, but much is concentrated on designing pseudo-code sequences with a better performance and new design methods, exemplified by the Kasami code and Weil code derived from the conventional sequences [18,19]. Sun et al [20] studied the influence of the change of the partial matched filter length on the acquisition performance indexes.…”