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基于冗余陀螺系统的高速旋转弹丸滚转角速率测量

Roll Angular Rate Measurement for High Spinning Projectiles Based on Redundant Gyroscope System.

作者信息

Mi Jing, Li Jie, Zhang Xi, Feng Kaiqiang, Hu Chenjun, Wei Xiaokai, Yuan Xiaoqiao

机构信息

National Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China.

School of Electrical Control Engineering, North University of China, Taiyuan 030051, China.

出版信息

Micromachines (Basel). 2020 Oct 16;11(10):940. doi: 10.3390/mi11100940.

DOI:10.3390/mi11100940
PMID:33081267
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7603017/
Abstract

Precision-guided projectiles, which can significantly improve the accuracy and efficiency of fire strikes, are on the rise in current military engagements. The accurate measurement of roll angular rate is critical to guide a gun-launched projectile. However, Micro-Electro-Mechanical System (MEMS) gyroscope with low cost and large range cannot meet the requirement of high precision roll angular rate measurement due to the limitation by the current technology level. Aiming at the problem, the optimization-based angular rate estimation (OBARS) method specific for projectiles is proposed in this study. First, the output angular rate model of redundant gyroscope system based on the autoregressive integrated moving average (ARIMA) model is established, and then the conventional random error model is improved with the ARIMA model. After that, a Sage-Husa Adaptive Kalman Filter (SHAKF) algorithm that can suppress the time-varying process and measurement noise under the flight condition of the high dynamic of the projectile is designed for the fusion of dynamic data. Finally, simulations and experiments have been carried out to validate the performance of the method. The results demonstrate the proposed method can effectively improve the angular rate accuracy more than the related traditional methods for high spinning projectiles.

摘要

精确制导弹药在当前军事行动中日益增多,它能显著提高火力打击的准确性和效率。滚动角速率的精确测量对于引导火炮发射的弹药至关重要。然而,由于当前技术水平的限制,低成本、大测量范围的微机电系统(MEMS)陀螺仪无法满足高精度滚动角速率测量的要求。针对这一问题,本研究提出了一种专门针对弹药的基于优化的角速率估计(OBARS)方法。首先,建立基于自回归积分滑动平均(ARIMA)模型的冗余陀螺仪系统输出角速率模型,然后用ARIMA模型改进传统随机误差模型。之后,设计了一种Sage-Husa自适应卡尔曼滤波器(SHAKF)算法,用于融合动态数据,该算法能在弹药高动态飞行条件下抑制时变过程和测量噪声。最后,进行了仿真和实验以验证该方法的性能。结果表明,对于高速旋转弹药,所提方法能比相关传统方法更有效地提高角速率精度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/e1b7efa07fde/micromachines-11-00940-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/2579f55ac19b/micromachines-11-00940-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/3e52a5d5d1d1/micromachines-11-00940-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/374662fe9a9c/micromachines-11-00940-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/e3cab9b2dc9c/micromachines-11-00940-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/1cf62ff19447/micromachines-11-00940-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/fe38cda80c86/micromachines-11-00940-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/7d989256891a/micromachines-11-00940-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/f2ab5b31695f/micromachines-11-00940-g008a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/a5c2cc333614/micromachines-11-00940-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/51a43eb68d18/micromachines-11-00940-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/8266eb362cba/micromachines-11-00940-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/a65526b5d5d9/micromachines-11-00940-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/f1cb23df94f5/micromachines-11-00940-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/e1b7efa07fde/micromachines-11-00940-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/2579f55ac19b/micromachines-11-00940-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/3e52a5d5d1d1/micromachines-11-00940-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/374662fe9a9c/micromachines-11-00940-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/e3cab9b2dc9c/micromachines-11-00940-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/1cf62ff19447/micromachines-11-00940-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/fe38cda80c86/micromachines-11-00940-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/7d989256891a/micromachines-11-00940-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/f2ab5b31695f/micromachines-11-00940-g008a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/a5c2cc333614/micromachines-11-00940-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/51a43eb68d18/micromachines-11-00940-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/8266eb362cba/micromachines-11-00940-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/a65526b5d5d9/micromachines-11-00940-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/f1cb23df94f5/micromachines-11-00940-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43ba/7603017/e1b7efa07fde/micromachines-11-00940-g014.jpg

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ISA Trans. 2020 May;100:422-435. doi: 10.1016/j.isatra.2019.11.029. Epub 2019 Nov 25.
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Sensors (Basel). 2019 Apr 15;19(8):1799. doi: 10.3390/s19081799.
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基于动态方差模型的自适应滤波方法在降低 MEMS 陀螺仪随机误差中的应用。
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