Optimizing Signal Processing Kernels for GNSS Software Receivers

Cillian O’Driscoll

Abstract: The Software Defined Radio (SDR) paradigm as applied to GNSS has blossomed in the last twenty years. This approach involves performing all the high rate processing from Intermediate Frequency (IF) to baseband, including acquisition, tracking and observation generation, in software. In this time interval the capabilities of modern processors have evolved significantly, enabling more interesting processing, of more signals with wider bandwidths. Equally, low cost or embedded platforms today have processing capabilities surpassing those of the desktop computers used in the first experiments in GNSS SDR. In this work we investigate the possibilities for optimizing the software implementation of high rate GNSS signal processing tasks. In contrast to some earlier work in this field, rather than considering the optimization of a specific operation for a specific platform, we consider the general problem of maintaining a software code base that is capable of performing across a range of target machines, with a range of performance requirements, both in terms of processing efficiency (the number of channels that can be processed in real time, for example) and the processing accuracy (certain approximations can reduce the computational complexity at the cost of a loss in Signal-to-Noise Ratio (SNR) or ranging performance).
Published in: 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)
April 20 - 23, 2020
Hilton Portland Downtown
Portland, Oregon
Pages: 1168 - 1177
Cite this article: O’Driscoll, Cillian, "Optimizing Signal Processing Kernels for GNSS Software Receivers," 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS), Portland, Oregon, April 2020, pp. 1168-1177.
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