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The emergence of low-cost micro-electro-mechanical system inertial measurement units, cameras and global navigation satellite system (GNSS) receivers has promoted the research of multisensor fusion positioning. With the rapid development of chip technology, it has become a trend for low-cost GNSS chips to provide multi-frequency carrier phase observations while supporting multiple constellations. To enhance the positioning performance of multi-frequency and multi-system precise point positioning (PPP) in the difficult urban environment, we propose a tightly coupled system of monocular visual-inertial odometry (MVIO) and uncombined PPP (UC-PPP) based on factor graph optimization. The initialization of MVIO and UC-PPP adopts a coarse-to-fine approach to correct the transformation of local and global frames online. Moreover, the sliding window and marginalization methods are adopted to retain the constraints between adjacent observations and eliminate useless observations in the window. The pedestrian and vehicle tests in urban environments verify the performance of the proposed method. Compared with open-source software GVINS, the positioning accuracy of the proposed method has been further improved by using carrier phase observations with higher measurement accuracy. Compared with PPP alone, the improvement of the proposed method for the low-speed and short-distance pedestrian test in the east, north, and up directions is 73.3, 54.8 and 62.7%, respectively, while the improvement for the high-speed and long-distance vehicle test is 63.0, 59.3 and 70.5%, respectively. Experiment results show that the proposed method has better positioning accuracy and continuity in difficult urban environments. [ABSTRACT FROM AUTHOR]

Integration of the global positioning system (GPS) with inertial navigation system (INS) has been very intensively studied and widely applied in recent years. Conventional GPS/INS integrated systems that receive pseudorange and Doppler observations can only attain meter-scale accuracy. An INS has also been integrated with double-differenced GPS measurements that remove GPS errors, although this increases system cost. Following the availability of real-time precise orbit and clock products, a precise point positioning PPP/INS tightly coupled navigation system is presented here. Because various types of measurements such as pseudorange, carrier phase and Doppler are available, an adaptive federated filter method is proposed and applied to the PPP/INS integrated system to improve filter efficiency and adaptivity. Provided that the federated local filter and the adaptive filter are equivalent in form, an information allocation factor in the federated filter is constructed based on the adaptive filter factor. Simulation analyses for different INS grades show that the tactical grade INS can provide higher initial value accuracy for PPP. An experiment was performed to validate the new algorithm, and the results indicate that the INS can improve PPP accuracy, especially under challenging positioning conditions. PPP solution accuracy in the east, north and down components can improve by 45, 47 and 24 %, respectively, during partial GPS satellite blockages. The resolution accuracy of the proposed adaptive federated filter is similar to that of a centralized Kalman filter. The proposed method can also realize parallel filter computing and remove the influence of dynamic model errors. [ABSTRACT FROM AUTHOR]