Extended Kalman filter method for micro-inertial strapdown attitude determination system
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摘要: 采用低精度的微惯性陀螺和加速度计作为微惯性捷联姿态确定系统元件,首先分析了捷联惯性姿态解算的非线性问题和误差累积的原因;根据姿态三角函数关系引入横滚、俯仰角的3个替换变量作为状态变量,并根据状态变量之间的约束方程和运动体前向速度测量,建立了捷联惯性姿态的一种扩展卡尔曼滤波模型;采用MTi微惯性捷联测量组合进行实验,将该扩展卡尔曼滤波方法解算载体姿态结果与捷联姿态解算结果相比较,验证了该方法抑制惯性姿态解算累积误差的能力.
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关键词:
- 微惯性捷联姿态确定系统 /
- 约束方程 /
- 扩展卡尔曼滤波 /
- 累积误差
Abstract: Low precision micro-inertial gyros and accelerometers were used as elements of an inertial strapdown attitude system. Firstly, the nonlinear problem and the cause of accumulated error for inertial strapdown attitude solution were analyzed. Then according to the trigonometric function relationship between attitude angles, three variants replaced the roll and the pitch as state variants. Furthermore, with the restrained equation among state variants and the forward motion speed, one extended Kalman filter(EKF) model was built to solve the attitude angles. Using micro-inertial strapdown measurement unit MTi in the experiment to verify whether the EKF can restrain the accumulated error of the inertial attitude solution. The two results which come from EKF and from inertial attitude solution without compensation were compared, and show that the EKF algorithm can restrain the accumulated error. -
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