无人机磁惯导系统中航向校正的双内积算法

针对无人机磁惯导系统中广泛采用的三轴磁强计,建立航向角误差模型,分析出航向角的非对准误差等效为常值误差加半圆罗差,提出了一种基于双内积的航向误差校正方法,即利用地磁场矢量与自身内积得到的模值为定值以及地磁矢量与重力矢量二者的内积为常数原理进行航向角解算补偿。该方法能克服基于矢量模值不变校正方法无法补偿非对准误差的缺陷,可实现三轴磁强计的完全校正。数值仿真及实验结果显示,该方法校正效果优于标量校正法、点积不变法以及两步法,能有效降低磁场矢量的模值误差和无人机航向角误差,且对磁惯导系统中的传感器噪声有较好的鲁棒性。

Dual inner product algorithm for heading calibration in magneto inertial navigation system of UAV

By establishing the error model of heading angle for tri axial magnetometer that widely used in magneto inertial navigation system of unmanned aerial vehicle (UAV), the heading misalignment error that consists of constant error and half circle compass error is concluded. Therefore, a novel calibration algorithm is proposed, which is based on dual inner products. The principle of proposed method makes use of the invariance of geomagnetic vector and itself inner product, as well as the constant inner product of geomagnetic vector and gravity vector. This method can eliminate the mutual misalignment of tri axial magnetometer that cannot be identified using the invariance of vector norm only, and thus it can achieve complete calibration of tri axial magnetometer. Numerical simulations and experiment results show that the proposed method has better performance compared with scalar checking, dot product invariance and two step methods. It can effectively reduce the norm error of geomagnetic vector and heading angle error of UAV, and it has preferable robustness against sensor noise.