CAJ | 학술논문

针对MEMS陀螺、加速度计、磁强计组合的姿态确定系统,笔者设计了用于微小型飞行器姿态估计的四元数扩展卡尔曼滤波算法.取姿态误差四元数和陀螺随机漂移构建滤波状态向量,通过误差四元数微分方程和陀螺随机误差模型建立了卡尔曼滤波状态方程;采用改进的高斯-牛顿算法将传感器观测量转化为四元数,通过与利用陀螺信息估计的四元数相乘,得到姿态误差四元数作为卡尔曼滤波量测值,显著减小了机动加速度对姿态估计的影响.仿真实验显示:四元数静态估计误差小于0.22%,在动态情况下,四元数估计值能够较好地跟踪真实值的变化,表明该滤波算法能够有效提高姿态估计的精度.
침대MEMS타라、가속도계、자강계조합적자태학정계통,필자설계료용우미소형비행기자태고계적사원수확전잡이만려파산법.취자태오차사원수화타라수궤표이구건려파상태향량,통과오차사원수미분방정화타라수궤오차모형건립료잡이만려파상태방정;채용개진적고사-우돈산법장전감기관측량전화위사원수,통과여이용타라신식고계적사원수상승,득도자태오차사원수작위잡이만려파량측치,현저감소료궤동가속도대자태고계적영향.방진실험현시:사원수정태고계오차소우0.22%,재동태정황하,사원수고계치능구교호지근종진실치적변화,표명해려파산법능구유효제고자태고계적정도.
In this paper, a new quatemion-based extended Kalman filter algorithm was proposed to improve the accuracy of attitude estimation of micro aerial vehicles based on the MEMS sensors such as gyroscope, accelerometer and magnetometer. Attitude quaternion errors and drift bias of gyroscope were selected to construct a state vector,and the state equation was established based on attitude quatemion error differential equation and stochastic error model of gyroscope. The modified Gauss-Newton algorithm was used to convert the outputs of sensors to quatemion by which the measurements of Kalman filter were obtained through making combination of attitude quatemion from gyroscope signals, which significantly reduces the influences of maneuvering acceleration on attitude estimation. Experimental results show that the maximum estimated errors were less than 0.22% in static and the estimated quatemion could well track its true values dynamically. The algorithm is proved to be effective at improving the accuracy of attitude estimation.