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基于机动性补偿的GPS/MEMS微惯性器件组合方法

         

摘要

This paper presents a new method for the combination of GPS and MEMS inertial sensors, and according to the combination, gives a GPS information filtering algorithm based on the carrier maneuverability model and the Kalman filter to obtain the acceleration caused by the carrier trajectory maneuvering. This acceleration can be removed from the accelerometer measurements, thus it can compensate the attitude determination algorithm based on MEMS inertial devices for the carrier maneuverability. The obtained attitude information is not sensitive to the unlock of GPS signals, thereby it can avoid the rapid and unlimited growth of the attitude error due to the low precision MEMS sensor in the case of traditional GPS/INS combinations without GPS assistance. The algorithm has very little computation , and is suitable for micro systems. The car tests showed that the attitude accuracy of the new algorithm decreased slightly compared to the traditional GPS/INS combinations, but it was much better than the attitude determination algorithm for MEMS inertial devices without maneuverability compensation.%提出了一种新的GPS/MEMS微惯性器件组合方法,并根据组合结构的需求.设计了基于载体机动模型和卡尔曼滤波器的GPS信息滤波算法来获取由于载体轨迹机动引起的加速度,从而对基于MEMS微惯性器件的姿态测量算法进行载体机动性补偿,得到的姿态信息对GPS信号失锁不敏感,避免了传统GPS/INS组合方式在无GPS辅助时由于MEMS器件精度低而导致的姿态误差快速、无限增长的问题,而且运算量小,适合在微小型系统上实现.跑车试验表明,该新组合算法与传统GPS/INS组合相比,姿态精度略有下降,但远好于未作机动性补偿的MEMS微惯性器件的姿态测量算法.

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