CN112797967B - 一种基于图优化的mems陀螺仪随机漂移误差补偿方法 - Google Patents
一种基于图优化的mems陀螺仪随机漂移误差补偿方法 Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C19/00—Gyroscopes; Turn-sensitive devices using vibrating masses; Turn-sensitive devices without moving masses; Measuring angular rate using gyroscopic effects
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
- G01C25/005—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass initial alignment, calibration or starting-up of inertial devices
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US11808780B1 (en) | 2022-05-20 | 2023-11-07 | Honeywell International Inc. | Inertial sensor error modeling and compensation, and system for lifetime inertial sensor calibration and navigation enhancement |
CN117664117B (zh) * | 2024-01-31 | 2024-04-23 | 西安晟昕科技股份有限公司 | 一种光纤陀螺的漂移数据分析及优化补偿方法 |
Citations (3)
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CN105043384A (zh) * | 2015-04-30 | 2015-11-11 | 南京林业大学 | 一种基于鲁棒Kalman滤波的陀螺随机噪声ARMA模型建模方法 |
CN105787265A (zh) * | 2016-02-23 | 2016-07-20 | 东南大学 | 基于综合集成赋权法的原子自旋陀螺随机误差建模方法 |
CN109993113A (zh) * | 2019-03-29 | 2019-07-09 | 东北大学 | 一种基于rgb-d和imu信息融合的位姿估计方法 |
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US9269012B2 (en) * | 2013-08-22 | 2016-02-23 | Amazon Technologies, Inc. | Multi-tracker object tracking |
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CN105043384A (zh) * | 2015-04-30 | 2015-11-11 | 南京林业大学 | 一种基于鲁棒Kalman滤波的陀螺随机噪声ARMA模型建模方法 |
CN105787265A (zh) * | 2016-02-23 | 2016-07-20 | 东南大学 | 基于综合集成赋权法的原子自旋陀螺随机误差建模方法 |
CN109993113A (zh) * | 2019-03-29 | 2019-07-09 | 东北大学 | 一种基于rgb-d和imu信息融合的位姿估计方法 |
Non-Patent Citations (2)
Title |
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ARMA模型的MEMS陀螺随机误差卡尔曼补偿方法;孙伟;测绘科学;第42卷(第12期);正文第52-56页 * |
基于因子图的组合导航方法及其可行性研究;朱晓晗;电光与控制;第26卷(第4期);正文第66-69页 * |
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