GPU Computing of GNSS Chipshape
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.
Proceedings of the 2023 International Technical Meeting of The Institute of Navigation
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