發(fā)布時(shí)間：2018-05-30 10:09

  本文選題：航姿測(cè)量系統(tǒng) + 微機(jī)電系統(tǒng)�。� 參考：《哈爾濱工程大學(xué)》2014年碩士論文

【摘要】：MEMS技術(shù)的出現(xiàn),引領(lǐng)了慣性導(dǎo)航技術(shù)的巨大變革,使慣性導(dǎo)航系統(tǒng)向著低成本、低功耗、微型化的方向發(fā)展。特別是MEMS-IMU的出現(xiàn),使得慣性導(dǎo)航系統(tǒng)向著集傳感器與處理器于一身的“微系統(tǒng)”方向發(fā)展。鑒于MEMS技術(shù)在航空航天及軍事領(lǐng)域的巨大應(yīng)用潛力,對(duì)MEMS-IMU的研究成為目前慣性導(dǎo)航領(lǐng)域的研究熱點(diǎn)。本文以基于MEMS-IMU的捷聯(lián)式航姿測(cè)量系統(tǒng)的硬件平臺(tái)為依托,著重研究MEMS-IMU的誤差建模及標(biāo)定技術(shù)、航姿測(cè)量系統(tǒng)的初始對(duì)準(zhǔn)及基于自適應(yīng)Kalman濾波的姿態(tài)更新算法。首先,本文簡(jiǎn)要介紹了課題研究背景及意義,闡述了 MEMS慣性器件的發(fā)展歷程及其在相關(guān)領(lǐng)域的巨大應(yīng)用優(yōu)勢(shì);簡(jiǎn)要介紹了航姿測(cè)量系統(tǒng)中測(cè)量單元的構(gòu)成方案,并確定使用加速度計(jì)和磁強(qiáng)計(jì)來(lái)輔助陀螺儀進(jìn)行測(cè)姿,這種測(cè)姿方案優(yōu)勢(shì)明顯,通過(guò)使用加速度計(jì)和磁強(qiáng)計(jì)分別敏感重力向量和地磁向量來(lái)輔助陀螺儀測(cè)姿,很好的彌補(bǔ)了陀螺儀測(cè)姿時(shí)誤差隨時(shí)間積累的缺陷。然后,給出了航姿測(cè)量系統(tǒng)所使用的坐標(biāo)系定義及姿態(tài)角定義,闡述了航姿測(cè)量系統(tǒng)的捷聯(lián)矩陣的建立及即時(shí)修正算法;介紹了本文所依托硬件平臺(tái)的基本結(jié)構(gòu),特別是對(duì)MEMS-IMU模塊做了詳細(xì)介紹,分析了其性能特點(diǎn)及數(shù)據(jù)采集過(guò)程;這為后續(xù)的課題研究奠定了基礎(chǔ)。接著,針對(duì)MEMS慣性器件的特性,分析了其誤差來(lái)源,并根據(jù)本系統(tǒng)要求選取零偏、刻度因子和非正交安裝誤差系數(shù)作為主要誤差源,建立了相應(yīng)的誤差模型;對(duì)于MEMS-IMU的標(biāo)定,也針對(duì)陀螺儀、加速度計(jì)和磁強(qiáng)計(jì)的不同特點(diǎn)分別給出了具體的方法步驟;通過(guò)對(duì)陀螺儀和加速度計(jì)進(jìn)行標(biāo)定實(shí)驗(yàn),給出了標(biāo)定結(jié)果,并根據(jù)標(biāo)定結(jié)果驗(yàn)證了 MEMS-IMU的建模及標(biāo)定方法是可行的。然后,介紹了 Kalman濾波基本理論并做了簡(jiǎn)要分析,針對(duì)本課題的濾波算法流程分析了系統(tǒng)的初始對(duì)準(zhǔn)過(guò)程,給出了初始捷聯(lián)矩陣的求解方法;在Kalman濾波基本原理的基礎(chǔ)上,本文使用四元數(shù)誤差和陀螺儀零偏誤差作為狀態(tài)變量,以加速度計(jì)誤差和磁強(qiáng)計(jì)誤差作為觀(guān)測(cè)變量,完成了航姿測(cè)量系統(tǒng)的自適應(yīng)Kalman濾波器設(shè)計(jì),實(shí)現(xiàn)了姿態(tài)角的最優(yōu)估計(jì),并給出了濾波器自適應(yīng)參數(shù)的調(diào)節(jié)規(guī)則。最后,通過(guò)仿真實(shí)驗(yàn)具體分析了陀螺儀零偏對(duì)系統(tǒng)性能的影響;對(duì)系統(tǒng)在受擾情況下的性能進(jìn)行了定性測(cè)試;并進(jìn)一步確定了濾波器的自適應(yīng)參數(shù)值;對(duì)系統(tǒng)的動(dòng)靜態(tài)性能測(cè)試表明系統(tǒng)可以在中低動(dòng)態(tài)環(huán)境下穩(wěn)定工作,驗(yàn)證了系統(tǒng)算法是切實(shí)可行的。
[Abstract]:The emergence of MEMS technology leads to a great change in inertial navigation technology and makes inertial navigation system develop in the direction of low cost, low power consumption and miniaturization. In particular, the emergence of MEMS-IMU makes inertial navigation system (ins) develop towards a "microsystem" which combines sensors and processors. In view of the great application potential of MEMS technology in aerospace and military fields, the research on MEMS-IMU has become a hotspot in inertial navigation field. Based on the hardware platform of strapdown attitude measurement system based on MEMS-IMU, this paper focuses on the error modeling and calibration technology of MEMS-IMU, the initial alignment of attitude measurement system and the attitude updating algorithm based on adaptive Kalman filter. First of all, this paper briefly introduces the research background and significance of the subject, describes the development of MEMS inertial devices and its great application advantages in related fields, and briefly introduces the configuration of the measurement unit in the attitude measurement system. It is determined to use accelerometers and magnetometers to assist gyroscopes in attitude determination. This kind of attitude determination scheme has obvious advantages. By using accelerometers and magnetometers to sensitive gravity vectors and geomagnetic vectors respectively to assist gyroscopes in attitude determination, A good remedy for the gyroscope attitude measurement error with time accumulation of defects. Then, the definition of coordinate system and attitude angle used in attitude measurement system is given, the establishment of strapdown matrix of attitude measurement system and the algorithm of instant correction are expounded, and the basic structure of hardware platform based on this paper is introduced. In particular, the MEMS-IMU module is introduced in detail, and its performance characteristics and data acquisition process are analyzed, which lays a foundation for further research. Then, according to the characteristics of MEMS inertial devices, the error sources are analyzed, and the zero offset, calibration factor and non-orthogonal installation error coefficient are selected as the main error sources according to the requirements of the system, and the corresponding error model is established for the calibration of MEMS-IMU. According to the different characteristics of gyroscopes, accelerometers and magnetometers, the specific methods and steps are given, and the calibration results are given through the calibration experiments of gyroscopes and accelerometers. According to the calibration results, the modeling and calibration method of MEMS-IMU is proved to be feasible. Then, the basic theory of Kalman filter is introduced and briefly analyzed. The initial alignment process of the system is analyzed according to the filtering algorithm flow of this subject, and the solution method of initial strapdown matrix is given, which is based on the basic principle of Kalman filtering. In this paper, quaternion error and gyroscope zero bias error are used as state variables, accelerometer error and magnetometer error are used as observation variables, adaptive Kalman filter design of attitude measurement system is completed, and the optimal attitude angle estimation is realized. The regulation of adaptive parameters of filter is also given. Finally, the effect of gyroscope bias on the system performance is analyzed by simulation experiments, the system performance under disturbance is tested qualitatively, and the adaptive parameters of the filter are further determined. The dynamic and static performance test of the system shows that the system can work stably in low and low dynamic environment, and the algorithm is feasible.
【學(xué)位授予單位】：哈爾濱工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN96

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 陳劍;孫金海;李金海;閻躍鵬;;慣性系統(tǒng)中加速度計(jì)標(biāo)定方法研究[J];微電子學(xué)與計(jì)算機(jī);2012年08期

2 李仁;曾慶雙;陳希軍;;一種低成本MEMS慣性傳感器應(yīng)用技術(shù)研究[J];傳感技術(shù)學(xué)報(bào);2009年11期

3 祝燕華;蔡體菁;楊卓鵬;;MEMS-IMU/GPS組合導(dǎo)航系統(tǒng)的實(shí)現(xiàn)[J];中國(guó)慣性技術(shù)學(xué)報(bào);2009年05期

4 蒙濤;王昊;李輝;賀光紅;金仲和;;MEMS陀螺誤差建模與濾波方法[J];系統(tǒng)工程與電子技術(shù);2009年08期

5 王玲玲;富立;陳三;;基于低成本IMU的捷聯(lián)航姿系統(tǒng)軟件設(shè)計(jì)與實(shí)現(xiàn)[J];中國(guó)慣性技術(shù)學(xué)報(bào);2009年04期

6 李杰;洪惠惠;張文棟;;MEMS微慣性測(cè)量組合標(biāo)定技術(shù)研究[J];傳感技術(shù)學(xué)報(bào);2008年07期

7 邵婷婷;馬建倉(cāng);張永波;;具有傾斜補(bǔ)償功能的三軸磁阻電子羅盤(pán)研制[J];電子測(cè)量技術(shù);2008年06期

8 孫宏偉;房建成;盛蔚;;一種基于MEMS的微慣性測(cè)量單元標(biāo)定補(bǔ)償方法[J];北京航空航天大學(xué)學(xué)報(bào);2008年04期

9 程龍;王壽榮;葉甫;;硅微機(jī)械振動(dòng)陀螺零偏溫度補(bǔ)償研究[J];傳感技術(shù)學(xué)報(bào);2008年03期

10 李榮冰;劉建業(yè);孫永榮;;MEMS-IMU構(gòu)型設(shè)計(jì)及慣性器件安裝誤差標(biāo)定方法[J];中國(guó)慣性技術(shù)學(xué)報(bào);2007年05期

相關(guān)博士學(xué)位論文 前4條

1 何昆鵬;MEMS慣性器件參數(shù)辨識(shí)及系統(tǒng)誤差補(bǔ)償技術(shù)[D];哈爾濱工程大學(xué);2009年

2 劉付強(qiáng);船用衛(wèi)星天線(xiàn)微型姿態(tài)測(cè)量系統(tǒng)關(guān)鍵技術(shù)研究[D];哈爾濱工程大學(xué);2008年

3 武元新;對(duì)偶四元數(shù)導(dǎo)航算法與非線(xiàn)性高斯濾波研究[D];國(guó)防科學(xué)技術(shù)大學(xué);2005年

4 劉危;基于MEMS的低成本MIMU的應(yīng)用研究[D];國(guó)防科學(xué)技術(shù)大學(xué);2004年

相關(guān)碩士學(xué)位論文 前10條

1 梁勇;基于MEMS的航姿系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn)[D];哈爾濱工程大學(xué);2011年

2 鄭婕;GPS/INS組合導(dǎo)航及非線(xiàn)性濾波方法在導(dǎo)航系統(tǒng)中的應(yīng)用研究[D];大連理工大學(xué);2010年

3 金阿鑫;微小型車(chē)載慣性/GPS組合導(dǎo)航系統(tǒng)技術(shù)研究[D];哈爾濱工程大學(xué);2010年

4 孫柏虹;基于MEMS的捷聯(lián)航姿系統(tǒng)初始對(duì)準(zhǔn)技術(shù)研究[D];哈爾濱工程大學(xué);2010年

5 王磊;硅微航姿系統(tǒng)技術(shù)研究[D];哈爾濱工程大學(xué);2010年

6 崔璐璐;基于MEMS器件的姿態(tài)測(cè)量系統(tǒng)研究與實(shí)現(xiàn)[D];大連理工大學(xué);2009年

7 胡志偉;基于MTi的硅微系統(tǒng)初始對(duì)準(zhǔn)技術(shù)研究[D];哈爾濱工程大學(xué);2009年

8 劉s鷗;基于MTi微慣性航姿系統(tǒng)研究[D];哈爾濱工程大學(xué);2008年

9 宋麗君;基于MEMS器件的航向姿態(tài)測(cè)量系統(tǒng)的研究[D];西北工業(yè)大學(xué);2007年

10 劉付強(qiáng);基于MEMS器件的捷聯(lián)姿態(tài)測(cè)量系統(tǒng)技術(shù)研究[D];哈爾濱工程大學(xué);2007年

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本文編號(hào)：1954905