Altimeter + INS/Giant LEO Constellation Dual-Satellite Integrated Navigation and Positioning Algorithm Based on Similar Ellipsoid Model and UKF

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 20; p. 4099
• Main Authors: Ye, Lvyang, Yang, Yikang, Jing, Xiaolun, Li, Hengnian, Yang, Haifeng, Xia, Yunxia
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2021
• Subjects: Algorithms; altimeter; Altimeters; Communication; Deviation; Dilution; double star; Earth orbits; Errors; Global positioning systems; GPS; Harsh environments; Inertial navigation; integrated navigation; Kalman filters; LEO; Low earth orbit satellites; Low earth orbits; Mountains; Navigation systems; Occlusion; Remote sensing; Satellite communications; Satellite constellations; Satellites; similar ellipsoid; Simulation; switching; Switching theory
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs13204099

To solve the problem of location service interruption that is easily caused by incomplete visual satellite environments such as occlusion, urban blocks and mountains, we propose an altimeter + inertial navigation system (INS) + giant low earth orbit (LEO) dual-satellite (LEO2) switching integrated navigation algorithm based on a similar ellipsoid model and unscented Kalman filter (UKF). In addition to effectively improving the INS error, for the INS + LEO dual-satellite switching algorithm without altimeter assistance, our algorithm can also significantly suppress the problem of excessive navigation and positioning error caused by this algorithm in a long switching time, it does not require frequent switching of LEO satellites, and can ensure navigation and positioning functions without affecting LEO satellite communication services. In addition, the vertical dilution of precision (VDOP) value can be improved through the clock error elimination scheme, so, the vertical accuracy can be improved to a certain extent. For different altimeter deviations, we provide simulation experiments under different altimeter deviations; it can be found that after deducting the fixed height deviation, the algorithm can also achieve good accuracy. Compared with other typical algorithms, our proposed algorithm has higher accuracy, lower cost and stronger real-time performance, and is suitable for navigation and positioning scenarios in harsh environments.