Abstract: | Existing and projected open service (OS) signals up until 2020 create a challenge for Global Navigation Satellite System (GNSS) receiver manufacturers. For mass-market receivers decisions have to be made as to which signals to exploit for the best performance and user experience. Traditional methods for satellite search and acquisition have been dominated by methods best suited for GPS. For example, search strategies used for GLONASS acquisition were often adopted from GPS search techniques and did not exploit the properties of the GLONASS signal structure such as its short PRN code sequence and the fact that two antipodal satellites are transmitted on the same GLONASS frequency channel. Also, GLONASS is more robust to jamming compared to GPS. A single narrow band jammer cannot simultaneously interfere with every GLONASS signal in view, while for CDMA signals the same jammer can disrupt all signals simultaneously. In a previous paper [Anyaegbu et al, ION GNSS+ 2014], optimal search strategies for multi-constellation receivers were presented. Specifically for GPS L1 C/A signals, GLONASS L1 C/A signals, BeiDou B1-I signals or Galileo E1 OS signals since these are centred in the GNSS band near 1575.42 MHz. Search performance with various start conditions were investigated for each signal structure and expanded to a multi-constellation strategy with the aim to achieve a consistent optimal performance across different test scenarios. Results showed that for similar acquisition performance across constellations the size and capacity of the search hardware varied from 50% of the size of that required for a similar GPS search to more than 1200% of the size of that required for GPS. The proposed methods were suitable for use in a mobile platform which has tight constraints on power consumption and silicon area. This paper will expand the study on the optimal multi-constellation search strategies for various scenarios, particularly those that represent typical real-life environments such as urban or indoor reception which are far from ideal for satellite navigation systems. These environments include signal obscuration, attenuation and an increased number of multipath contaminated signals. Other GNSS signals such as the Japanese Quasi-Zenith Satellite System (QZSS), which has a similar signal structure to the GPS L1 C/A signal and the Space-based Augmentation System (SBAS) will also be considered in this analysis. We would also address the impact on optimal multi-constellation search strategies with or without environmental and behavioral context aiding information, such as speed and heading measurements from sensors. Test results using Intel’s multi-constellation GNSS receiver CG2000 chipset will be presented. The test results presented will include Time-to-First-Fix (TTFF) from cold start and hot restart (coarse time and fine time) scenarios using a multi-constellation GNSS receiver with the proposed optimal search strategies implemented. Those results will be compared with results from a traditional GPS+GLONASS receiver using same scenarios. The improvement on the acquisition performance will be highlighted. It will also show test results from scenarios with and without sensor aiding and context awareness. In conclusion, the proposed optimal multi-constellation search strategies have been further analyzed in different environments with various start conditions. Test results generated using a multi-constellation GNSS receiver have shown the improvement achieved on the acquisition performance. |
Published in: |
Proceedings of the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2015) September 14 - 18, 2015 Tampa Convention Center Tampa, Florida |
Pages: | 219 - 244 |
Cite this article: | Townsend, Bryan, Anyaegbu, Esther, Zuo, Rui, "Optimal Search Strategies in a Multi-constellation Environment: Analysis and Test Results From a GNSS Receiver," Proceedings of the 28th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2015), Tampa, Florida, September 2015, pp. 219-244. |
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