Authors : Vaibhav M. Nayakoji; Dr. Hassanali G. Virani

Volume/Issue : Volume 9 - 2024, Issue 6 - June

Google Scholar : https://tinyurl.com/bddpn7c5

Scribd : https://tinyurl.com/2xe98e8x

DOI : https://doi.org/10.38124/ijisrt/IJISRT24JUN1535

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Acquisition in software-defined GPS receivers is computationally intensive and time-consuming, especially with the increasing demand for rapid and accurate positioning services driven by globalization and digitization. Software-defined receivers face challenges in satellite signal acquisition, which becomes more demanding with longer signals. This paper aims to enhance the efficiency of GPS signal acquisition, a critical step for determining the code phase of PRN codes and the doppler shift in carrier frequency. Real-time applications encounter issues under dynamic conditions and degraded signals, as conventional computers lack the computational power for the necessary correlation and FFT operations. To address these challenges, a method using GPU acceleration for L1 signal acquisition is proposed. This method combines signal acquisition with GPU parallel computing using the SIMT model. A CPU-GPU platform via CUDA programming allows the CPU to handle data reading and intermediate processing, while the GPU performs the core acquisition algorithm in parallel.

Keywords : Software-Defined Receiver, Signal Acquisition, GPS, Compute Unified Device Architecture(CUDA), GPU Acceleration, Parallel Computing.

References :

1. Ghangho Kim, Hyoungmin So, Sanghoon Jeon, Changdon Kee, Youngsu Cho and Wansik Choi, ”The Development of Modularized Post Processing GPS Software Receiving Platform”, International Conference on Control, Automa tion and Systems 2008 Oct. 14-17, 2008 in COEX, Seoul, Korea.
2. Antoine Grenier, Elena Simona Lohan, Aleksandr Ometov, Jari Nurmi, ”An Open-Source Software-Defined Receiver for GNSS Algorithms Benchmark ing”, Electrical Engineering Unit, Tampere University, Tampere, Finland, 2022 14th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT).
3. Global Navigation Satellite Systems (GNSS). Website: www.unoosa.org. Accessed: May, 2024.
4. Yeqing Zhang, Meiling Wang, Yafeng Li,” LowComputational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time”, School of Automation, Beijing Institute of Technology, Beijing 100081, China.
5. NVIDIA CUDA C/C++ Programming Guide 12.4, NVIDIA Press, 2024.
6. M. Venu Gopala Rao, D. Venkata Ratnam, “Faster Acquisition Technique for Software-defined GPS Receivers”. K.L. University, Guntur-522 502, In dia, Defence Science Journal, Vol. 65, No. 1, January 2015, pp. 5-11, DOI: 10.14429/dsj.65.5579 2015, DESIDOC.
7. K. Borre, D. M. Akos, N. Bertelsen, P. Rinder, and S. H. Jensen, “A software defined GPS and Galileo receiver: A single-frequency approach”, Springer Science & Business Media, 2007.
8. M. Ettus, ”GETTING STARTED GUIDE- NI USRP-29xx”, National Instruments, December, 2012.
9. M. Ettus, ”USRP users and developers guide”, Ettus research LLC, 2005.
10. Shaik Fayaz Ahamed, G Sasibhushana Rao, L Ganesh, “Fast Acquisition of GPSSignal using FFT Decomposition”, Department of Electronics and Com munications Engineering, V R Siddhartha Engineering College, Vijayawada, India, Department of Electronics and Communications Engineering, Andhra University, Visakhapatnam, India, Department of Electronics and Communi cations Engineering ANITS, Visakhapatnam, India.
11. NVIDIA cuFFT Library User’s guide 11.7, NVIDIA Press, 2022.
12. David B. Kirk and Wen-mei W. Hwu, “Programming Massively Parallel Processors-A Hands-on Approach”, Elsevier Inc., 2013.
13. Rob Farber, “CUDA application design and development”, Elsevier, Amsterdam, 2011.
14. GPS, Website: www. novatel.com. Accessed: May, 2024.