迭代扩展卡尔曼滤波在相对姿态估计中的应用  

Application of Iterated Extended Kalman Filtering in the Relative Attitude Estimation

作　　者：李建锋[1] 张慧星[2] 闫美辰[3] 

机构地区：[1]北京工商大学,北京100048 [2]装备指挥技术学院,北京101416 [3]北京化工大学,北京100029

出　　处：《导弹与航天运载技术》2012年第6期48-52,共5页Missiles and Space Vehicles

摘　　要：在航天器相对姿态测量过程中,由于基于单帧图像的相对姿态测量方法受噪声影响比较大,相对距离较远时,测量的稳定性较差,因此提出采用迭代扩展卡尔曼滤波进行相对姿态估计的方法。首先对卡尔曼滤波进行概述,然后建立基于迭代扩展卡尔曼滤波的航天器间的3D位置和姿态估计系统模型及观测模型,确定系统及测量噪声模型,给出运用卡尔曼滤波方法解决姿态估计问题的具体方法及详细过程,最后通过仿真数据和实测数据对该方法的正确性、可行性进行了验证。In the process of measuring the relative attitude of a spacecraft, the iterative extended Kalman filter is used to estimate the spacecraft relative attitude, because the measurement of a single frame image is more easily affected by noise and is less stable in longer relative distance. Firstly, an overview of the Kalman filter is provided in the paper. Secondly, the system model and observation model of 3D position and relative attitude between spacecrafts are built based on iterated extended Kalman filtering（IEKF）; the system and noise measurement models are determined; and methods to solve the attitude estimation with IEKF is given out. Finally, the correctness and feasibility of the method are verified by the simulation results and experimental measurements.

关 键 词：分布式微型航天器 相对姿态估计 迭代扩展卡尔曼滤波 

分 类 号：V448.25[航空宇航科学与技术—飞行器设计]