With the measurement of the Earth’s magnetic field, magnetic compass can provide high frequency heading information. However, it suffers from local magnetic interference. An intelligent ellipsoid calibration method based on the grey wolf is proposed to generate optimal parameters for magnetic compass to generate high performance heading information. With the analysis of the projection relationship among the navigation coordinate frame, the body frame and the local horizontal frame, the heading ellipsoid equation is constructed. Furthermore, an improved grey wolf algorithm is proposed to find optimization solution in a large solution space. With the improvement of the convergence factor and the evolutionary mechanism, the improved grey wolf algorithm can generate optimized solution for heading ellipsoid equation. The effectiveness of the proposed method has been verified by a series of vehicle and flight tests. The experimental results show that the proposed method can eliminate errors caused by sensor defects, hard-iron interference, and soft-iron interference effectively. The heading error generated by the magnetic compass is less than 0.2162 degree in real flight tests.

通过测量地球磁场，磁罗盘可以提供高频航向信息。但是，它遭受局部磁场干扰。提出了一种基于灰太狼的智能椭球标定方法，为磁罗盘生成最优参数，以产生高性能的航向信息。通过分析导航坐标系，车体架和局部水平架之间的投影关系，构造了航向椭球方程。此外，提出了一种改进的灰狼算法，以在较大的求解空间内找到最优解。随着收敛因子和进化机制的改进，改进的灰狼算法可以为航向椭球方程生成优化解。所提出的方法的有效性已经通过一系列的车辆和飞行测试得到了验证。实验结果表明，该方法可以有效消除传感器缺陷，硬铁干扰和软铁干扰引起的误差。在实际飞行测试中，电磁罗盘产生的航向误差小于0.2162度。