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机构地区:[1]清华大学精密仪器系,北京100084 [2]陆军装甲兵学院兵器与控制系,北京100072
出 处:《清华大学学报(自然科学版)》2020年第1期82-88,共7页Journal of Tsinghua University(Science and Technology)
摘 要:基于微机电系统(MEMS)技术的微惯性测量单元(MIMU)在体积、重量、功耗都具有显著优势,但是其较大的惯性器件误差限制了其应用范围。通过引入旋转调制技术抑制其影响,使得MIMU能够实现寻北应用,目前这方面已经得到比较多的研究。但是不足之处在于缺乏对MIMU的可观测性分析,而状态是否可观测与Kalman滤波能否准确估计误差状态量是紧密联系的。该文针对MIMU在静止、多位置、连续旋转3种情况下,基于实测数据用Kalman滤波分析其可观测性。结果表明:静止情况下MIMU的航向姿态角误差很大,无法自对准;通过绕航向轴及俯仰轴旋转的多位置方案,可以使得MIMU的误差状态量完全可观测;连续旋转情况下,Kalman滤波可以在较短时间内估计出航向角及天向加速度计零偏,并在一段时间后估计出方位陀螺漂移,但是无法准确估计出水平方向的陀螺漂移及加速度计零偏,不过寻北算法可以估计出水平方向的惯性器件常值误差。该研究结果为提高MIMU自对准精度以及评估其性能提供了途径和理论依据。Micro inertial measurement units(MIMU)based on micro-electro-mechanical-system(MEMS)designs are very small and light with low power consumption,but they have large inertial errors that limit applications.The rotation modulation technique was used to reduce the influence of these errors so that the MIMU systems can more accurately identify the northern direction.However,there have been few observability analyses of MIMU devices with the observability closely related to whether the Kalman filtering can accurately estimate the error state.This study analyzes the MIMU observability using Kalman filtering based on measured data for stationary,multi-position and continuous rotation conditions.The results show that the heading angle error in the stationary condition is quite large and the device cannot be self-aligned.A multi-positioning scheme with rotation around the heading axis and the pitch axis makes the MIMU error state completely observable.With continuous rotation,the Kalman filtering can quickly estimate the heading angle and the azimuth accelerometer bias with the azimuth gyro drift estimated after a short period of time.The gyro drift and the accelerometer bias in the horizontal plane cannot be accurately estimated using Kalman filtering,but they can be measured by the north-seeking algorithm.The research provides a theoretical basis for improving the self-alignment accuracy of MIMU devices and evaluating their performance.
关 键 词:微惯性测量单元 可观测性 KALMAN滤波 旋转调制
分 类 号:TH761[机械工程—仪器科学与技术]
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