基于北斗/惯导与多传感融合的无人机参数矫正方法研究

针对无人机飞行过程中姿态、定位以及高度参数不精确的问题,提出基于北斗/惯导与多传感器融合的无人机参数矫正方法,介绍了在北斗/惯导组合系统中融合气压传感器与速度传感器的采集参数,结合卡尔曼滤波器算法推算最优定位值。由速度传感器提供具体参数给惯导系统,并利用加速度与航偏角之间的关系预测无人机轨迹,结合北斗系统当前定位参数推算出最优值,将运算得到的无人机参数通过无线通讯的方式发送到终端进行存储显示。结果表明:采用多传感融合方式矫正的方法有效提高飞行轨迹与姿态的监测精度,定位精度达到3m,为操控无人机提供了有力的理论依据。

Parameter correction of unmanned aerial vehicle based on beidou/inertial navigation and multi-sensor fusion

Aiming at the problem of attitude, orientation and inaccuracy of UAV in the process of UAV flight, a method of parameter correction for UAV based on Beidou/Inertial navigation and multi-sensor is proposed. The parameters of pressure sensor and speed sensor are introduced in the Beidou/inertial navigation system, and combined with Kalman filter algorithm to calculate the optimal positioning value. The specific parameters are given to the inertial navigation system by the speed sensor, and the UAV trajectory is predicted by the relationship between the acceleration and declination. The optimal value is calculated by combining the current positioning parameters of the Beidou system, and the calculated UAV parameters are transmitted through wireless communication to the terminal for storage and display. The results show that the method of multi-sensor fusion is effective to improve the accuracy of flight trajectory and attitude, and the positioning accuracy is 3 m, which provides a powerful theoretical basis for handling UAV.