Signal fusion method of MHD-MEMS based on Allan variance decoupling adaptive filter

被引：0
作者：
Li X. [1 ]
Han J. [1 ]
Liu F. [1 ]
机构：
[1] State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin university, Tianjin
来源：
Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | 2020年 / 28卷 / 02期
关键词：
Adaptive Kalman; Allan variance; MHD angular rate sensor; Sensor fusion;
D O I：
10.13695/j.cnki.12-1222/o3.2020.02.016
中图分类号：
学科分类号：
摘要：
To meet the width bandwidth angular rate measurement requirement of satellite platforms and compensate the error of MHD angular rate sensor in low frequency, a decoupling adaptive Kalman filtering method based on Allan variance is proposed, achieving the combination measurement of MHD angular rate sensor and MEMS gyro. Allan variance is used to calculate the variance of measurement noise, avoiding the filtering divergence caused by coupling effect, which doesn't need to have a precise knowledge of system parameters like standard Kalman either. Finally, test results show that decoupling Kalman filtering achieves good fusion result under both single and mixing frequencies. Compared with original signal, the mean square error of the output signal after fusion reduces to 30%, and the SNR of which increases by more than 10 dB. The output signal after fusion meets the 1 kHz bandwidth requirement of satellites, which can be used in inertial measurement unit. © 2020, Editorial Department of Journal of Chinese Inertial Technology. All right reserved.
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页码：237 / 241
页数：4
相关论文
共 10 条
  • [1] Luzhansky E, Edwards B, Israel D, Et al., The overview and status of laser communications relay demonstration, Proceedings of SPIE, (2016)
  • [2] Xu M, Li X, Wu T, Et al., Error Analysis of theoretical model of angular velocity sensor based on magnetohydrodynamics at low frequency, Sensors and Actuators A: Physical, 226, pp. 116-125, (2015)
  • [3] Ji Y, Li X, Wu T, Et al., Quantitative analysis method of error sources in magnetohydrodynamic angular rate sensor for structure optimization, IEEE Sensors Journal, 16, 11, pp. 4345-4353, (2016)
  • [4] Xi Z, Li X, Wu T, Et al., Compensation algorithm of MHD angular rate sensor at low frequency based on low-pass filter, Nanotechnology and Precision Engineering, 1, 1, pp. 79-85, (2018)
  • [5] Iwata T., High-bandwidth attitude determination using jitter measurements and optimal filtering, Proceedings of AIAA GNC Conference, (2009)
  • [6] Mao Y, Ren W, Luo Y, Et al., Optimal design based on closed-loop fusion for velocity bandwidth expansion of optical target tracking system, Sensors, 19, 1, pp. 1-15, (2019)
  • [7] Jin Z, Gao J, Yang H, Et al., Kalman filtering-based attitude information fusion method, Journal of Beijing Information Science&Technology University, 30, 1, pp. 85-89, (2015)
  • [8] Hu J, Cheng X, Zhu Y., Refined alignment in rotary SINS based on Allan variance decoupling adaptive filter, Journal of Chinese Inertial Technology, 25, 2, pp. 156-160, (2017)
  • [9] Yan G, Deng Y., Review on practical Kalman filtering techniques in traditional integrated navigation system, Navigation Positioning& Timing, 7, 2, pp. 50-64, (2020)
  • [10] Li Y, Hu B, Qin F, Et al., De-nosing method of decoupling adaptive Kalman filter for FOG signal, Journal of Chinese Inertial Technology, 22, 2, pp. 260-264, (2014)
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