摘要
针对车载桅杆式光电探测平台静动态情况下的姿态测量问题,提出了一种基于模糊加权的姿态估计算法。首先采用欧拉角法描述姿态运动学方程,并在详细分析陀螺和倾角仪数学模型的基础上,推导出系统的非线性连续状态空间模型;然后采用EKF对系统进行线性化和离散化,并在卡尔曼滤波框架下,提出姿态角和陀螺漂移的加权量测更新方程;最后通过分析加权值与载体运动状态的关系,提出了基于模糊推理系统的加权值确定方法。实验结果表明:该算法能够精确估计桅杆的姿态角运动,精度为0.041°。同时克服了倾角仪容易受振动和加速度干扰,以及陀螺的长期测量误差问题,并能在线实时估计补偿陀螺漂移。
A fuzzy weighted attitude estimation algorithm was proposed to resolve the problem of attitude determination for optronics mast systems （OMS）. Firstly, Euler representation was employed to descript attitude kinematics and nonlinear continuum state space model was derived based on analysis of mathematic model of gyros and inclinometer. Secondly, EKF was used to linearize and discretize the models and weighted measurement update equation of attitude and gyro drifts was developed under Kalman filter framework. Finally, according to the relations between the weighted value and body motion, a weighted value determination method was proposed based on fuzzy reasoning system. Experiental results show that the algorithin can estimate the attitude of mast exactly, and the accuracy of attitude estimation algorithm is 0.014°. The algorithm settles the problem of vibration disturber of inclinometer and measure error of gyros in long term. And the gyro drift is compansated on line real-time.
出处
《红外与激光工程》
EI
CSCD
北大核心
2011年第8期1569-1575,共7页
Infrared and Laser Engineering
基金
国家自然科学基金(50875257)
湖南省自然科学基金(09JJ4029)
关键词
模糊逻辑
光电桅杆
姿态估计
陀螺
倾角仪
卡尔曼滤波
fuzzy logic
optronics mast systems
attitude estimation
gyro
inclinometer
Kalman filter
