Real-Time Attitude Estimation for Spinning Projectiles by Magnetometer Based on an Adaptive Extended Kalman Filter

Abstract

The attitude measurement system based on geomagnetic information offers advantages such as small space requirements, fast response times, excellent resistance to high-overload conditions, and cost-effectiveness. However, during the flight process of a high-mobility guided spinning projectile, calculating attitude based on geomagnetic information often leads to non-unique solutions. To address this challenge, this paper proposes the Adaptive Extended Kalman Filter (AEKF) attitude estimation algorithm, based on geomagnetic vector information. Based on the analysis of the short-term attitude motion characteristics of the projectile, the Kalman state system equation and the nonlinear observation equation are established, along with real-time correction of the yaw angle and adaptive updates of parameters. The effectiveness of the algorithm is verified by simulations and experiments, demonstrating its ability to eliminate the dual solution problem inherent in traditional Single-Epoch algorithms. It notably improves the accuracy of pitch and roll angle estimation while providing precise estimates of attitude angular rates. Furthermore, the algorithm effectively mitigates the impact of magnetic disturbances on attitude determination. The proposed method has many potential applications in attitude measurement and navigation using geomagnetic data.