Evaluation of GPU Computing Capacity for All-in-view GNSS SDR Implementation
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In this study, we design an optimized Graphics Processing Unit (GPU)-based GNSS signal processing technique with the goal of designing and implementing a GNSS Software Defined Receiver (SDR) that can operate in real time all-in-view mode under multi-constellation and multi-frequency signal environment. In the proposed structure the correlators of the existing GNSS SDR are processed by the GPU. We designed a memory structure and processing method that can minimize memory access bottlenecks and optimize the GPU memory resource distribution. The designed GNSS SDR can select and operate only the desired GNSS or desired satellite signals by user input. Also, parameters such as the number of quantization bits, sampling rate, and number of signal tracking arms can be selected. The computing capability of the designed GPU-based GNSS SDR was evaluated and it was confirmed that up to 2400 channels can be processed in real time. As a result, the GPU-based GNSS SDR has sufficient performance to operate in real-time all-in-view mode. In future studies, it will be used for more diverse GNSS signal processing and will be applied to multipath effect analysis using more tracking arms.
Abstract
In this study, we design an optimized Graphics Processing Unit (GPU)-based GNSS signal processing technique with the goal of designing and implementing a GNSS Software Defined Receiver (SDR) that can operate in real time all-in-view mode under multi-constellation and multi-frequency signal environment. In the proposed structure the correlators of the existing GNSS SDR are processed by the GPU. We designed a memory structure and processing method that can minimize memory access bottlenecks and optimize the GPU memory resource distribution. The designed GNSS SDR can select and operate only the desired GNSS or desired satellite signals by user input. Also, parameters such as the number of quantization bits, sampling rate, and number of signal tracking arms can be selected. The computing capability of the designed GPU-based GNSS SDR was evaluated and it was confirmed that up to 2400 channels can be processed in real time. As a result, the GPU-based GNSS SDR has sufficient performance to operate in real-time all-in-view mode. In future studies, it will be used for more diverse GNSS signal processing and will be applied to multipath effect analysis using more tracking arms.
참고문헌 (8)
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- Fernández-Prades, C., "GNSS-SDR: An open source tool for researchers and developers", Proceedings of the 24th International Technical Meeting of The Satellite Division of The Institute of Navigation (ION GNSS 2011), pp.780~794 (2011)
- Gregory W. Heckler, "SIMD correlator library for GNSS software receivers", GPS Solutions, 10(4), pp.269~276 (2006), Springer Science and Business Media LLC[DOI]
- 박귀우, "A Design and Implementation of Software Defined Radio for Rapid Prototyping of GNSS Receiver", Journal of Positioning, Navigation, and Timing, 7(4), pp.189~203 (2018), 사단법인 항법시스템학회[DOI]
- Erick Schmidt, "Development of a Real-Time Software-Defined GPS Receiver in a LabVIEW-Based Instrumentation Environment", IEEE Transactions on Instrumentation and Measurement, 67(9), pp.2082~2096 (2018), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- "GNSS-SDRLIB" (2014)[URL]
- Liangchun Xu, "Correlation acceleration in GNSS software receivers using a CUDA-enabled GPU", GPS Solutions, 21(1), pp.225~236 (2016), Springer Science and Business Media LLC[DOI]
- Won Jae Yoo, "Design and Implementation of SDR-based Multi-Constellation Multi-Frequency Real-Time A-GNSS Receiver Utilizing GPGPU", Journal of Positioning, Navigation, and Timing, 10(4), pp.315~333 (2021), 사단법인 항법시스템학회[DOI]