几何扩展卡尔曼滤波算法在卫星姿态确定系统中的应用  

Application of geometric extended Kalman filtering algorithm in satellite attitude determination system

作　　者：江丹[1] 邓新蒲[1] 吴京[1] 莫邵文 杨媛媛[1] 

机构地区：[1]国防科学技术大学电子科学与工程学院,湖南长沙410073

出　　处：《传感器与微系统》2016年第9期156-160,共5页Transducer and Microsystem Technologies

基　　金：国家自然科学基金资助项目(61401474)

摘　　要：卡尔曼滤波因其良好的性能广泛应用于卫星姿态确定中。经典的扩展卡尔曼滤波(EKF)算法在估计姿态坐标系中表示估计误差矢量,由于没有考虑到估计姿态坐标系与真实姿态坐标系之间存在偏差,从而导致姿态估计精度下降。针对这个问题,Andrle M S通过几何变换引入误差一致性表示,在此基础上,提出了几何扩展卡尔曼滤波(GEKF)算法,将姿态误差四元数和陀螺漂移增量通过几何变换进行一致性表示,解决了估计误差矢量表示不一致的问题。本文介绍了误差一致性表示的原理,并将GEKF算法应用于含常值漂移与时间相关漂移的陀螺模型中,仿真实验表明:GEKF算法比MEKF对陀螺漂移的估计更加精确,在滤波精度上取得了明显改善。Kalman filtering is widely used in satellite attitude determination because of its good performance. The classical EKF algorithm represents the estimated error vector in the estimated attitude coordinate system, because there is no consideration to estimate the deviation between the attitude coordinate system and the true attitude coordinate system, which leads to decrease of attitude estimation precision. To solve this problem, Andrle M S introduces error consistent represent method through geometric transformation, and on this basis, he proposes GEKF algorithm attitude error quaternion and gyro drift increment through geometric transformation of consistency representation, solve the problem that estimate error vector representation is not consistent. The principle of error consistency representation is introduced, and apply GEKF algorithm to gym model with constant drift and time drift. Simulation experiments show that the GEKF algorithm is more accurate than MEKF on gyro drift estimation, and filtering precision is improved significantly.

关 键 词：姿态确定 卡尔曼滤波 误差一致性 陀螺漂移 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]