Abstract
This article examines the positioning effect of integrated navigation after adding an LEO constellation signal source and a 5G ranging signal source in the context of China’s new infrastructure construction. The tightly coupled Kalman federal filters are used as the algorithm framework. Each signal source required for integrated navigation is simulated in this article. At the same time, by limiting the range of the azimuth angle and visible height angle, different experimental scenes are simulated to verify the contribution of the new signal source to the traditional satellite navigation, and the positioning results are analyzed. Finally, the article compares the distribution of different federal filtering information factors and reveals the method of assigning information factors when combining navigation with sensors with different precision. The experimental results show that the addition of LEO constellation and 5G ranging signals improves the positioning accuracy of the original INS/GNSS by an order of magnitude and ensures a high degree of positioning continuity. Moreover, the experiment shows that the federated filtering algorithm can adapt to the combined navigation mode in different scenarios by combining different precision sensors for navigation positioning.
Highlights
Affected by the poor accuracy of 5G/INS position, the overall federated filtering accuracy is in meter level, but it is higher than the accuracy of single 5G/INS position, and the positioning error is more stable than 5G/INS, the positioning convergence speed is faster, and the positioning continuity is more guaranteed
Constellations in Figure 10, it can be seen that the geometric distribution of the Low Earth Orbit Satellite Systems (LEO) constellation is significantly improved compared with that of the GNSS constellation
According to the DOP value analysis of GNSS and LEO constellations in Figure 10, it can be seen that the geometric distribution of the LEO constellation is significantly improved compared with that of the GNSS constellation
Summary
The integrated navigation system is called multi-sensor information fusion. According to different task scenarios, using multiple sensors for integrated navigation and optimally fusing multiple types of information according to a certain optimal fusion criterion can be expected to improve positioning accuracy. Used single-sensor navigation methods today include the Inertial Navigation System (Inertial Navigation System, INS), which has autonomous navigation capabilities, but INS positioning error drifts greatly over time [1]. The other one is the Satellite Navigation System (Global Navigation Satellite System, GNSS), which has all-weather, high-precision positioning ability. Integrated navigation is designed based on the complementary performance of a single navigation system; that is, the combination of GNSS/INS can achieve autonomous and high-precision navigation and positioning to a certain extent [3,4]
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