P311.35
国家重点研发计划项目（2017YFB1300704）。
为提高惯性导航室内定位算法的精度与连续性，提出一种融合MT2503与MEMS传感器的惯性导航定位算法，算法以MT2503芯片作为定位终端，并将加速度计传感器、陀螺仪，磁力计等传感器与其进行融合，通过加速度计传感器解算步长、步幅、步频，通过陀螺仪与磁力计来识别定位终端微动偏移量，最后在初始位置上累加定位终端位移得出定位终端实时位置。实验证实通过零速修正和卡尔曼滤波对误差进行校正，有效的解决了MEMS（micro-electro mechanical system）定位算法中存在的导航解算误差累积问题，提升了MEMS惯性导航室内定位算法的精度。
A fusion inertial navigation location algorithm for MT2503 and MEMS sensors is presented to improve accuracy and continuity. MT2503 chip is the locating terminal of location algorithm which blends accelerometer sensors, gyroscopes, magnetometers, and other sensors. Accelerometer sensors are used to resolve step size, stride and stride frequency. Gyroscopes and magnetometers are used to recognize the offset of a locating terminal. Finally, an offset of the location terminal is added on the original location to obtain the real time location of the locating terminal. Experiments confirmed that the problem of accumulative errors in navigation solution of the MEMS location algorithm is solved well through zero velocity update and Kalman filter. The method improves the accuracy of indoor inertial navigation positioning algorithm based on MEMS sensors.
王超.融合MT2503与MEMS传感器的惯性导航定位算法[J].重庆大学学报,2019,42(3):76-84.
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