A Robust Self-contained Solution for Inertial Attitude Determination Under External Acceleration

One of the main issues in inertial navigation systems is attitude determination, which means estimating the level angles (i.e., roll and pitch). This paper investigates the attitude estimation problem for an accelerated rigid body using three gyros and three accelerometers. The most critical challenges in attitude determination systems are external accelerations and gyroscope drift errors. Thus, a novel method based on the adaptive filter-Kalman algorithm is proposed to estimate and compensate for these errors. Linearization was performed around a general work point, and the covariance matrix's adaptive values were obtained so that leveling angles were accurately determined despite external accelerations. The simulation results, along with the car test, which was performed in different dynamic conditions with external accelerations, showed that the introduced algorithm has a high capability in accurately estimating leveling angles. This approach can be used for GPS-less navigation Algorithms.