Network RTK Computing in the Cloud and the Importance of Using GLONASS and QZSS

Z. Lukes, C. Rocken, L. Mervart, T. Iwabuchi, J. Barron, S. Cummins, M. Kanzaki, L. Mullen

Abstract:	Network RTK is a widely used method for GNSS signal augmentation. With respect to the pure RTK method based on processing of phase and code measurements from a real reference station, the network RTK brings many advantages -- lower demand on reference network density contributing to significantly reduced infrastructure costs, higher robustness, and reduction of some station-dependent errors. Several concepts for network RTK have been developed and are used widely nowadays: VRS, FKP, MAC, reverse RTK. GPS Solutions (GPSS) has developed and implemented a new complete system for the network RTK consisting of all necessary components: data gathering, processing center & corrections data generator, NTRIP front-end interface for RTK clients, and a web-based GUI for system administrators. We call this system RTRef. In the RTRef system we place the maximum emphasis on precise modeling of systematic errors; mainly the tropospheric and ionospheric delays. Receivers of various manufactures are supported. Since our RTK system supports GPS, QZSS and GLONASS satellite systems, inter-system and receiver specific inter-frequency biases for GLONASS observations are estimated among numerous other parameters. The system is currently tested and used in three locations. In Ireland we are generating network RTK corrections for a six-site network in the center of the country. In Japan we are operating the system for two networks – one in the Osaka area and the other one around Tokyo. In the Czech Republic the system is tested for a nationwide network. In all locations we are comparing our system to the performance of alternative commercial services. Initial tests show similar or slightly better performance for client RTK positioning (using geodetic receivers) with our RTRef corrections in comparison with other existing commercial services in terms of estimated position accuracy and time-to-fix statistic. In order to compare the performance of our corrections with those of other services we have configured tests client receivers to estimate RTK solutions. We are switching the corrections that this receiver receives every 30 seconds and force the receiver to estimate a new “cold start” position. We log the time to obtain a fixed solution and the position error (the test client is installed at a known location). Even though we are not comparing different services at exactly the same time no service has an advantage with this test setup because all differences should average out over multi-day tests periods with 30-second resets. The results of system evaluation and the results of long-term comparisons with other commercial services are presented in this paper. The keystone of the RTK method is the resolution of doubly-differenced ambiguities. While the methods for ambiguity resolution for GPS data are well-known, the ambiguity resolution for GLONASS is more complicated and it is not described as well in the literature. The difference between GPS and GLONASS with respect to ambiguity resolution is twofold and it stems from the FDMA nature of the GLONASS signal. While for GPS integer ambiguities are indeed resolved on the double difference level, for GLONASS it is also necessary to resolve integer ambiguities on the single difference level since satellites involved in the double differenced observation transmit signals with different wavelengths. Therefore GLONASS ambiguities cannot be resolved using phase observations only and code measurements need to be involved in the processing. The other issue is the inter-frequency biases induced during digital signal processing in the receiver. The biases are frequency and receiver type specific and can approach several decimeters – too large to be neglected. In this paper we describe the algorithm used for GLONASS ambiguity resolution and we demonstrate the necessity of modeling of GLONASS inter-channel biases when processing networks of mixed type receivers. We will also discuss the importance of GLONASS ambiguity resolution and its effect on the client position quality by comparing solutions with and without resolved GLONASS ambiguities. Clearly GLONASS is expected to contribute significant improvement in areas with limited sky visibility, but we want to investigate to what extend it helps with time-to-fix and position quality in good and unobstructed locations. Similarly it is important to investigate the value of including the QZSS satellite in Japan for RTK services. The topic of delivery of network RTK services will be discussed. In Ireland we are exploring a new model where the Irish company Compass Informatics is operating the GNSS network. Informatics is also providing leased computing resources on a cloud computer. GPSS has installed its RTRef system on that cloud computer. GPSS and Compass Informatics are both monitoring the reference network and client user access via web-based tools that have been developed by GPSS. In addition all network activity related to the reference stations or to client access is monitored and stored in a database, that can also be inspected by authorized users via the web. In this way GPSS can remotely provide support and trouble shooting for server processing, while Compass Informatics can focus on network maintenance and customer support. The key benefit of this kind of collaboration with cloud-based computers is that Compass Informatics is not required to gain in-house expertise to operate Linux servers, and purchase and learn how to run GNSS server software. GPSS on the other hand does not have to interact directly with end users, has full control over optimal installation and configuration of the server system and can remotely support many such installations in the future. This business model allows anybody who operates a real-time streaming GNSS network with dual frequency receivers to enter into the field of network RTK.
Published in:	Proceedings of the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2013) September 16 - 20, 2013 Nashville Convention Center, Nashville, Tennessee Nashville, TN
Pages:	3172 - 3179
Cite this article:	Lukes, Z., Rocken, C., Mervart, L., Iwabuchi, T., Barron, J., Cummins, S., Kanzaki, M., Mullen, L., "Network RTK Computing in the Cloud and the Importance of Using GLONASS and QZSS," Proceedings of the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2013), Nashville, TN, September 2013, pp. 3172-3179.
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