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

Abstract

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.

A Distributed Formation Joint Network Navigation and Positioning Algorithm

“…where ϕ = [ ϕ N ϕ E ϕ D ] is the misalignment angle of the platform between the platform coordinate system and the navigation coordinate system in the N, E, and D directions; δV = [δV N δV E δV D ] T is the three-dimensional velocity error; δP = δλ δL δh is the three-dimensional position error, and ξ g = ξ gx ξ gy ξ gz is the first-order Markov drift of the gyroscope; ξ a = ξ ax ξ ay ξ az is the first-order Markov drift of the accelerometer. Γ is a 15 × 15-dimensional matrix, X JP is an 15 × 1-dimensional matrix, Φ is a 15 × 6-dimensional matrix, and W JP is a 6 × 1-dimensional matrix [31,32].…”

A novel integrity monitoring method for slowly growing errors in inertial navigation system/global navigation satellite system integrated navigation system

“…[18], based on the scheme without requiring the EKF to be fully re‐initialised, the PL maintains lower. In addition, some advanced algorithms are integrated into the KF to improve the performance of integrity, such as a novel KF based on multi‐constellation [19]; independent detectors that are intended for GNSS and filter faults [20]; unscented Kalman filter for sensor fusion [21]. However, multi‐layers SS endure a heavy calculation burden and complicated construction because of the ‘three‐layer’ filters, which the number of ‘third‐layer filters’ almost increases with quadratic growth.…”

A Channel Compensation Technique Based on Frequency-Hopping Binary Offset Carrier Modulated Signal

“…In the construction of SAGIN, UAVs are indispensable and behave as a mainstay in the integration of satellite-terrestrial communication. Satellites themselves are not capable of handily satisfying tremendous requests from the ground, but numerous applications can be realized, likely with the assistance of UAVs [6]. In fact, several advanced projects have been developed based on SAGIN, such as the OneWeb constellation [7], the Global Information Grid (GIG) [8], SpaceX [9], etc.…”