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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。
In order to solve the problem of attitude measurement under static and dynamic conditions of vehicle mast photoelectric detection platform, an attitude estimation algorithm based on fuzzy weighting is proposed. Firstly, the Euler angle method is used to describe the kinematic equation of attitude, and the mathematical model of the gyroscope and inclinometer is analyzed in detail. Then the nonlinear continuous state space model of the system is derived. Then the system is linearized and discretized by EKF In the framework of Kalman filter, a weighted update equation of attitude angle and gyro drift is proposed. Finally, a weighted method based on fuzzy reasoning system is proposed by analyzing the relationship between weighted values and carrier motion. The experimental results show that the proposed algorithm can precisely estimate the mast attitude angle with the accuracy of 0.041 °. At the same time, it overcomes that the inclinometer is easily disturbed by vibration and acceleration, as well as long-term measurement error of the gyroscope, and can compensate the gyroscope drift on-line in real time.