GPU Computing of GNSS Chipshape

Tyler Bransfield, Sanjeev Gunawardena

Peer Reviewed

Abstract: By storing correlation results in individual bins according to fractional chip phase and transition state, the average shape of a satnav signal’s spreading code chip transient response can be estimated. Current methods for software-based processing of chip shape results are computationally inefficient and make processing time prohibitive. This paper presents a GPU based method of generating chip shape results that achieves real time performance. Several GPU based methods are compared in addition to a multi-threaded CPU based method.
Published in: Proceedings of the 2023 International Technical Meeting of The Institute of Navigation
January 24 - 26, 2023
Hyatt Regency Long Beach
Long Beach, California
Pages: 350 - 361
Cite this article: Bransfield, Tyler, Gunawardena, Sanjeev, "GPU Computing of GNSS Chipshape," Proceedings of the 2023 International Technical Meeting of The Institute of Navigation, Long Beach, California, January 2023, pp. 350-361. https://doi.org/10.33012/2023.18629
Full Paper: ION Members/Non-Members: 1 Download Credit
Sign In