Abstract
This dissertation develops a low-cost integrated navigation system, which integrates multi-constellation global navigation satellite system (GNSS) precise point positioning (PPP) with a low-cost micro-electro-mechanical sensor (MEMS)-based inertial system for precise applications. Both undifferenced and between-satellite single-difference (BSSD) ionosphere-free linear combinations of pseudorange and carrier phase measurements from three GNSS constellations, namely GPS, GLONASS and Galileo, are processed. An improved version of the PF, the unscented particle filter (UPF), which combines the UKF and the PF, is developed to merge the corrected GNSS satellite difference observations and inertial measurements and estimate inertial measurements biases and errors. The performance of the proposed integrated system is analyzed using real test scenarios. A tightly coupled GPS PPP/MEMS-based inertial system is first developed using EKF, which shows that decimeter-level positioning accuracy is achievable with both undifferenced and BSSD modes. However, in general, better positioning precision is obtained when BSSD linear combination is used. During GPS outages, the integrated system shows submeter-level accuracy in most cases when a 60-second outage is introduced. However, the positioning accuracy is improved to a few decimeter- and decimeter-level accuracy when 30- and 10-second GPS outages are introduced, respectively. The use of UPF, on the other hand, reduces the number of samples significantly, in comparison with the traditional PF. Additionally, in comparison with EKF, the use of UPF improves the positioning accuracy during the 60-second GPS outages by 14%, 13% and 15% in latitude, longitude and altitude, respectively. The addition of GLONASS and Galileo observations to the developed integrated system shows that decimeter- to centimeter-level positioning accuracy is achievable when the GNSS measurement updates are available. In comparison with the GPS-based integrated system, the multi-constellation GNSS PPP/MEMS-based inertial system improves the latitude, longitude and altitude components precision by 24%, 41% and 41%, respectively. In addition, the use of BSSD mode improves the precision of the latitude, longitude and altitude components by 23%, 15% and 13%, respectively, in comparison with the undifferenced mode. During complete GNSS outages, the developed integrated system continues to achieve decimeter-level accuracy for up to 30 seconds, while it achieves submeter-level accuracy when a 60-second outage is introduced.
Highlights
This chapter introduces the work included in this dissertation
The positioning accuracy was improved to a few decimeter and decimeter-level accuracy when 30- and 10-second Global Positioning System (GPS) outages were introduced, respectively
This paper examined the performance of unscented particle filter (UPF) and compared its results with those of unscented Kalman filter (UKF), traditional nonlinear particle filter (PF), and the extended Kalman filter (EKF) for tightly-coupled precise point positioning (PPP) GPS/micro-electro-mechanical sensors (MEMS)-based Inertial Navigation System (INS) integration
Summary
This chapter introduces the work included in this dissertation. Section 1.1 summarizes the necessary background for this research with emphasis on the limitations of previous work. The requirement of a base station is usually problematic for some applications, as it controls the operational range of the system and increases the system cost and complexity These problems can potentially be overcome through the use of a precise point positioning (PPP) technique. Based on the quality of observations, satellite availability and geometry, as well as the correct resolution of the integer ambiguity parameters, centimeter- and decimeter-level positioning accuracy can be achieved in static and kinematic modes, respectively, using GPS PPP. A drawback of the PPP technique is the relatively long convergence time, which the PPP solution takes to reach a sub-decimeter level positioning accuracy This is mainly attributed to the poor satellite geometry and the existence of un-calibrated errors and biases, such as the satellite and receiver code biases
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