磁场信息对于确定航向角和姿态信息有着至关重要的作用, 但其极易受到周围铁磁性物质的干扰, 而传统用于磁场校准的椭球拟合算法对磁力计数据的质量要求较高, 对于客户的使用并不友好。本文在实现了一种使用更便捷, 精度更高的实时磁场校准。首先, 根据角速度和磁场物理关系, 推导使用陀螺仪数据递推得到磁力计数据的状态转移方程, 并把磁力计的测量作为量测方程, 结合扩展卡尔曼滤波算法完成陀螺仪补偿的实时EKF磁场校准算法。然后, 在手机中实时调取磁力计和陀螺仪数据, 对二者进行实时EKF磁场校准运算并输出校准结果, 之后与未校准数据和椭球拟合算法校准数据进行比较。在对比实验中: 当外部磁场环境改变时, 陀螺仪补偿算法不仅能够实现实时校准, 并且在2 s以内就可以完成对磁力计数据的校准。在校准精度方面, 当手机静置时, EKF算法可以实时减少磁场干扰, 校准的质量参数Q为0.72; 手机绕“8”字运动时, 校准的质量参数Q为0.53, 优于椭球拟合算法的0.03。模拟手机日常活动的四个情境时, 质量参数Q分别为0.73,0.54,0.52和0.48, 而这些情况下椭球拟合算法已经失去了校准作用。实验表明, 基于扩展卡尔曼滤波的磁场校准方法可实时对磁场干扰进行动态校准, 校准速度快, 精度高, 抗干扰能力强, 在消费类电子、车载惯导系统和**上均具有广泛应用。

Magnetic field information plays an important role in determining the heading angle and attitude information, but it is highly susceptible to interference from surrounding ferromagnetic materials. The traditional ellipsoid fitting algorithm for magnetic field calibration requires high quality magnetometer data, which is not customer-friendly. This paper implemented a more convenient and accurate real-time magnetic field calibration using a smartphone-based platform. Firstly, according to the physical relationship between angular velocity and magnetic field, the state transition equation of magnetometer data was derived by using the gyro data recursively. The magnetometer measurements were used in the measurement equation, and the extended Kalman filter algorithm was used to complete the real-time EKF magnetic field compensated by the gyroscope. Then, the data from the magnetometer and the gyroscope were retrieved in real time on the mobile phone, and a real-time EKF magnetic field calibration operation was performed on the two, producing the calibration result as the output.It was then compared with the uncalibrated data and the calibration data obtained via the ellipsoid fitting algorithm.During the comparison experiment,the gyroscope compensation algorithm can not only achieve real-time calibration with any change to the external magnetic field environment, but can also complete the calibration of the magnetometer data within 2 s. In terms of calibration accuracy, when the mobile phone is stationary, the EKF algorithm can reduce the magnetic field interference in real time, with the value of the quality parameter Q of the calibration being 0.72.When the mobile phone is wound around "8", the quality parameter Q of the calibration is observed to be 0.53, which is better than 0.03 - its value for the ellipsoid fitting algorithm. When four scenarios of daily activities on the mobile phone are simulated, the quality parameters Q obtained are 0.73, 0.54, 0.52, and 0.48, respectively, and in these cases, the ellipsoid fitting algorithm is observed to be incapableof calibration. Thus, real-time, high-precision, easy-to-use magnetic field calibration is achieved. Experimental testsdemonstrate that the magnetic field calibration method based on extended Kalman filter can dynamically calibrate magnetic field interference in real time. Its calibration speed is fast, its precision is high, and its anti-interference ability is adequate. Therefore, it has a wide range of applications in consumer electronics, vehicle inertial navigation systems, and the military.