Attitude in Motion: Constraints Aided Accurate Vehicle Orientation Tracking in Harsh Environment

Accurate vehicle orientation tracking in three dimensions or 3-D attitude tracking is an essential requirement for various vehicle stability and safety applications. In this article, we consider the problem of vehicle attitude tracking along with its external acceleration estimation using low-cost inertial measurement units. The current state-of-the-art approaches are unable to estimate orientation when the body is in motion for a prolonged period as the accelerometer measurements are corrupted by external accelerations that are produced due to body movements. In this article, a novel filtering framework is proposed to eliminate the acceleration-induced uncertainty for the body observing severe and prolonged external acceleration, which is based on a linear Kalman filter. We show that the sensor constraints allow the removal of external acceleration from all all of its axes. This approach is unique and superior to the current state of the art as it estimates the acceleration without using any information from additional sensors, such as wheel encoder, GPS, and/or camera. A unique state formulation is proposed that incorporates magnetometer to complement the accelerometer in a rotation matrix framework. Simulations and real-world experimental tests are conducted to verify the performance of the proposed algorithm in various dynamic conditions.