基于MARG的无人机抗干扰系统的研究

由IMU或电子罗盘组成的无人机航姿测量系统易受载体有害加速度或周围局部磁场干扰导致姿态角解算不准确。针对该问题提出将自适应扩展卡尔曼滤波算法应用于该系统。在卡尔曼滤波算法中提出引入分段函数构造自适应测量噪声方差阵。相比于传统噪声方差阵的阈值判断方法，该方法提高了传感器信息的利用率，进一步减小了外界干扰对系统姿态估计的影响，最终提高了姿态角的解算精度。最后针对该方法进行了仿真分析和无磁转台实验验证，仿真和实验结果表明，该方法能有效提高无人机航姿测量系统的抗干扰能力，具有一定的应用价值。

An anti-interference system of UAV based on MARG

The pose measurement system navigation of unmanned aerial vehicle (UAV) is usually composed of Inertial Measurement Unit or electronic compass measurement system, which is vulnerable to harmful acceleration vector and the surrounding Local magnetic field around, causing attitude angle calculating is not accurate. According to the problem, an adaptive extended kalman filtering algorithm based on the MARG sensor is put forward. The adaptive measurement noise covariance matrix is adjusted in Real-time by piecewise linear function. The utilization rate of the sensor information is improved. The influence of interference on the system attitude estimation is reduced. Eventually, the calculating precision of the attitude Angle is improved. Simulation and experimental results show that the proposed algorithm can effectively improve the anti-interference ability of the pose measurement system navigation.