CAJ | 학술논문

针对无人机低成本姿态解算这一基本问题，考虑到传统姿态算法运算量大、不易调试，采用微惯性单元（MEMS）测量无人机原始姿态数据，采用基于四元数的互补滤波算法，有效降低姿态解算的运算量，实现MEMS各传感器的信息融合。从理论上证明了基于四元数的互补滤波器的稳定性，分析了滤波器的性能。采用无人机真实数据验证了算法的有效性，解算得到的俯仰角、滚转角精度小于1°，航向角精度小于2°。与传统姿态算法比较，本算法简单有效、运算量小、易于调试。
침대무인궤저성본자태해산저일기본문제，고필도전통자태산법운산량대、불역조시，채용미관성단원（MEMS）측량무인궤원시자태수거，채용기우사원수적호보려파산법，유효강저자태해산적운산량，실현MEMS각전감기적신식융합。종이론상증명료기우사원수적호보려파기적은정성，분석료려파기적성능。채용무인궤진실수거험증료산법적유효성，해산득도적부앙각、곤전각정도소우1°，항향각정도소우2°。여전통자태산법비교，본산법간단유효、운산량소、역우조시。
Aiming at the basic problem of attitude estimation of unmanned aerial vehicles, in consideration of the quality of the traditional algorithm which is complex and hard to debug, MEMS is used to measure the data of UAV primitive attitude. Quaternion complementary filtering algorithm is applied to reduce the operation quantity of attitude estimation and make the fuse of information collected by every sensor. The complementary filter stability based on quaternion is theoretically proved. And the quality of filter was analysed here. The effectiveness of the algorithm used here is testified by real data from UAV. The precision of pitch and yaw are less than 1° and 2° respectively. Compared with traditional attitude algorithm, this algorithm is simple and effective, small computational complexity, and easy to debug.