University of Calgary Geomatics Engineering graduate students Peiyuan Zhou, Paul Gratton, Kaixiang Tong, and Yuting Gao presented abridged versions of their recent papers from ION GNSS+.
Topic: U of C Student Papers at ION GNSS+
ION GNSS+ is the worlds largest technical meeting on GNSS positioning and technology. Each year the University of Calgary sends multiple students who present award winning research on their respective topics. This seminar will be an opportunity to meet some of those bright student-researchers, learn about the innovative research they are undertaking and ask questions on where the technology will be going next.
1. Performance Analysis of an Improved GPS LNAV to Support Development of Low-Cost Real-Time PPP Systems with High Scalability and Availability
Speaker: Peiyuan Zhou is a Ph.D. student at the University of Calgary, Canada. His research interests include GNSS precise positioning and integrated navigation.
Abstract: Highly scalable and available real-time precise satellite orbit and clock corrections are the prerequisite to the development of low-cost real-time Precise Point Positioning (PPP) system. At present, Radio Technical Commission for Maritime Services (RTCM) State Space Representation (SSR) messages are commonly used for representing and disseminating real-time precise satellite orbit and clock corrections. Since RTCM SSR requires a continuous connection between the server and the user ends to transmit the high-rate corrections, real-time PPP positioning accuracy may be affected by the increasing satellite orbit and clock errors during correction outages caused by communication link corruptions, server malfunction, and so on. To better support the development of low-cost real-time PPP systems demanding both high precision and low costs, the improved Legacy Navigation messages (LNAV) is generated by estimating the satellite orbit parameters with International GNSS Service (IGS) ultra-rapid orbits as well as by estimating the satellite clock parameters with real-time correction streams. The improved LNAV has fully-consistent representation and user-end algorithms as the conventional LNAV from GPS systems but with significantly improved accuracy. The update rates of the improved LNAV is fully scalable to accommodate different low-cost real-time PPP systems in terms of communication bandwidth (costs) and accuracy. Furthermore, real-time precise satellite orbit and clock corrections are available for up to 2 hours when correction outages occur, so real-time PPP positioning accuracy can be maintained. In this study, the accuracy of improved LNAV is compared with RTCM SSR corrections, and the quality degradation during correction outages is analyzed. The positioning performance of the improved GPS LNAV is explored using both static and kinematic datasets from the Android Nexus 9 tablet and U-Blox M8T receivers. The results indicated that the improved LNAV can provide corrections with sufficient accuracy to meet consumer application requirements and can provide high availability even during correction outages. It is concluded that the improved LNAV can be an effective alternative approach for delivering real-time precise corrections of high scalability and availability and can be applied to support the development of next-generation low-cost real-time PPP systems for mass-market applications.
2. Automated Processing of Low-Cost GNSS Receiver Data
Speaker: Paul Gratton graduated with a BSc in geomatics engineering from the University of Calgary in Spring 2019. He has been involved in PPP research on both low-cost and high-end GNSS receivers since 2018, resulting in co-authorship of several publications. He is still with the Department of Geomatics Engineering at the University of Calgary, pursuing a master’s degree.
Abstract: The availability of raw observations from smartphones and tablets brings new challenges to GNSS data processing. Low-cost GNSS chipsets, combined with omnidirectional antennas, can lead to measurements highly contaminated by noise and multipath. Therefore, data quality depends not only on the device but also on the environment. Such a diversity is complex to handle for automated GNSS data processing services such as the NRCan precise point positioning (PPP) service. Processing strategies developed for geodetic receivers now require adaptations to be suitable for low-cost devices: 1) carrier-to-noise weighting should replace elevation-dependent weighting; 2) precise ionospheric corrections with meaningful quality indicators should be available; 3) the residual tropospheric zenith delay parameter should not be estimated in the PPP filter, which calls for more accurate a priori tropospheric models; and 4) quality control algorithms should rely on geometry-based rather than geometry-free approaches. With such modifications, static PPP solutions using data collected with a Huawei Mate 20X smartphone can converge to cm-level accuracies under favorable signal tracking conditions
3. A software-defined gyroscope: concept, implementation and application
Speaker: Kaixiang Tong is a Ph.D. Candidate at The University of Calgary. His research interest covers several fields such as GNSS receiver design, INS, new GNSS/INS integrated navigation algorithm development.
Abstract: This paper describes a new concept of GNSS/INS integration that is conducted in the signal domain of GNSS and INS systems. Previous efforts have been made to the GNSS/INS integration in the signal domain of GNSS receivers including ultra-tight integration algorithms and the introduction of software-defined receivers (SDR) to allow flexibility in GNSS receiver design and performance improvement. In this paper, we focus on the introduction of a software-defined IMU (SDI) to support GNSS/INS integration in the signal domain of the INS system. To demonstrate the new concept and considering the fact that gyroscope has a greater impact on the performance of IMU, a prototype system of a software-defined MEMS Gyroscopes (SDG) has been designed and implemented which is also tested in a road test. The concept of SDI opens new ways to improve the low-cost IMU design and performance particularly in challenging environments.
4. A Kalman filter considering coloured noise and application to low-cost high-precision GNSS
Speaker: Yuting Gao is a Ph.D. student at the University of Calgary, Canada. Her current research focuses on integrity monitoring of GNSS precise positioning, low-cost GNSS receiver and non-Gaussian modelling.
Abstract: Generally, GNSS receiver’s measurement noise is assumed to be Gaussian distribution. However, be subject to various noise sources, the measurements from low-cost devices do not follow the Gaussian white noise assumption used in Kalman filter which often show strong characteristics of colored noise especially in a challenging environment. Many of the involved noises such satellite clock error and multipath are presented as time correlated. To deal with this problem, an approach based on colored Kalman filter (CKF) is presented in this paper, which considers measurement time correlation by a first order autoregressive model and rebuilds a new measurement model for the CKF. A short baseline RTK experiment is performed with a low-cost receiver in challenging environment. The experiment results show that the state variance matrix obtained by the CKF can perfectly reflect the realistic position error, while the estimate of the standard Kalman filter is found too optimistic to reveal the real value. In addition, the CKF can improve around 30% of the AR (Ambiguity Resolution) convergence time, and the reliability of AR has pretty high AR ratio in challenging environment.