Velocity-Aided Navigation in GNSS-Denied Environments
TL;DR
Calculations showed that the errors of the new VAN method are significantly smaller than those of the autonomous SINS integrated with GNSS using a Kalman filter, and experimental testing demonstrated that the errors of the new method are comparable to those of the SINS integrated with GNSS using a Kalman filter.
Abstract
Highlights What are the main findings? An alternative method for aircraft/drone navigation is proposed when the usual SINS/GNSS methods do not work. Semi-natural experiments confirmed the accuracy of the alternative method at the level of accuracy of SINS/GNSS methods, especially at intervals of up to 10 min. What are the implications of the main findings? The proposed VAN method is quite simple, since it is implemented using MEMS technology. The proposed method can be used as a backup method for aircraft navigation. Abstract The Velocity-Aided Navigation (VAN) method for determining latitude, longitude, and altitude is proposed when global navigation satellite system (GNSS) signals are unavailable. Currently, GNSS receivers are the primary navigation systems that meet consumer demand for location accuracy. However, GNSS receivers are not autonomous. Strapdown inertial navigation systems (SINSs), unlike GNSSs, are autonomous. Their operating principle is based on double integration of accelerometer output signals. However, they have a significant drawback: SINS errors increase significantly over time. Two approaches are used to improve accuracy. The first involves using expensive, high-precision gyroscopes and accelerometers. The other involves correcting the SINS by integrating it with navigation systems built on physical principles different from those of the SINS. An alternative method, based on VAN and an inertial measurement unit (IMU), for determining navigation parameters is proposed and does not require double integration of accelerometer output signals. Analytical expressions for the errors of the new method are derived. Calculations showed that the errors of the new method are significantly smaller than those of the autonomous SINS. Experimental testing confirmed the calculation results and demonstrated that the errors of the new method are comparable to those of the SINS integrated with GNSS using a Kalman filter. The proposed alternative VAN method for determining latitude, longitude, and altitude can be used independently, as an alternative to GNSS for integration with the SINS, and can also serve as a backup navigation system.