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Code Design Using Machine Learning for Future Satellite Navigation

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Research Question: Can We Rethink the Design of Satellite Navigation Codes with the Recent Advances in Machine Learning? 

On January 14, 2020, the first GPS III satellite was marked healthy and available for use, thereby marking the birth of the next-generation GPS constellation. In addition to broadcasting the new L1C signal, the modernized constellation is distinguished by its reprogrammable payload, which allows it to evolve with new technologies. Furthermore, the NTS-3 satellite signal testing platform is planned to be launched in 2024 and will explore new technologies for the future GPS constellations. We are indeed entering a new era of satellite navigation. However, the legacy GPS codes are based on linear shift feedback registers, which were designed decades ago before personal computers. It is time to revisit the design methods of the GPS spreading code families. Powered by recent advances in machine learning, optimization and computing, we explore new platforms for learning high-quality spreading signal families.

Current Research Team: 

  • Tara Mina
  • Alan Yang

Related Works: 

  • Alan Yang, Tara Mina, Stephen Boyd, and Grace Gao, Gradient-Guided Coordinate Descent for Large-Scale Binary Spreading Code Optimization, Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2024), Baltimore, MD. Abstract submitted.
  • Alan Yang, Tara Mina, and Grace Gao, Fast Spreading Code Optimization Under Doppler Effects, ION International Technical Meeting (ION ITM 2024), Long Beach, CA, Jan 2024. [paper]  [slides] [video]
  • Tara Mina, Alan Yang, and Grace Gao, Designing Long GPS Memory Codes Using the Cross Entropy Method, Navigation: Journal of the Institute of Navigation. Submitted. [paper]
  • Tara Mina, Alan Yang, and Grace Gao, Designing Long GPS Memory Codes Using the Cross Entropy Method, Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2023), Denver, CO, Sep 2023. [paper] [slides] [video]
  • Alan Yang, Tara Mina, and Grace Gao, Spreading Code Sequence Design is a Convex Optimization Problem with Binary Constraints, Proceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2023), Denver, CO, Sep 2023. [paper] [slides] [video]
  • Alan Yang, Tara Mina, and Grace Gao, Binary sequence set optimization for CDMA applications via mixed-integer quadratic programming, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2023. [paper]
  • Tara Mina and Grace Gao, Designing Low-Correlation GPS Spreading Codes with a Natural Evolution Strategy Machine Learning Algorithm, Navigation: Journal of the Institute of Navigation. vol. 69, no. 1, Mar. 2022. doi: 10.33012/navi.506. [paper][video]
  • Tara Mina and Grace Gao, Designing Low-Correlation GPS Spreading Codes via a Policy Gradient Reinforcement Learning AlgorithmProceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2020), St. Louis, MO, Sep 2020. Best Presentation of the Session Award[paper] [slides] [video]
  • Tara Mina and Grace Gao, Devising High-Performing GPS Pseudo-Random Noise Codes Using Evolutionary Learning AlgorithmsProceedings of the Institute of Navigation GNSS+ conference (ION GNSS+ 2019), Miami, FL, Sep 2019. Best Presentation of the Session Award[paper] [slides]