基于ARM的航姿参考系统研究
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摘要
在民用领域的电子玩具、三维仿真、运动检测、机器人、VR游戏等方面,都急需一种低成本小型化航姿参考系统,而传统的航姿参考系统由于价格高、体积大的原因限制了在这些方面的应用。随着嵌入式系统的飞速发展和新型MEMS惯性元器件的出现,使得研究低成本小型化航姿参考系统成为可能。本文研究了一种基于ARM内核的高性能的嵌入式微处理器和嵌入式实时操作系统的航向姿态参考系统。
本文首先介绍了航姿系统的基本理论及其工作原理,包括惯性系统中常用坐标系的定义、姿态角的定义、四元数法、旋转矢量法,重点介绍了载体姿态测量的原理。通过对自适应加权因子和预报残差的研究,提出了一种基于指数渐消因子的自适应卡尔曼滤波算法。
其次,介绍了基于嵌入式系统的微惯性航姿系统的硬件和软件设计。提出了硬件设计方案,并对各个功能模块进行了详细说明;同时也提出了软件设计方案,重点介绍了基于ARM的航姿参考系统的软件实现方法。为了验证系统的可行性和可靠性,搭建了嵌入式实时测试平台,详细论述了Simulink/RTW生成可移植C代码的原理。
最后,搭建了基于ARM航姿解算的实验系统,详细介绍了航姿解算实验的实现过程,解决了代码移值和调试中出现的很多问题,成功实现了代码的跨平台移植和运行。
实验结果证明,由三轴微加速度计、三轴微陀螺仪和三轴磁阻传感器组成,以S3C2410X微处理器和裁剪的Linux2.6实时操作系统为核心的航向姿态参考系统,与通常的航姿测量系统相比,具有体积小、成本低、实时性强等特点,在民用领域具有很广阔的应用前景。
Although there is a huge demand of low-cost and miro Attitude and Heading Reference System(AHRS) in civil fields, such as the electronic toys, tridimensional emulation, sports detection, robots and VR games; the traditional AHRS limits in these fields because of high prices and large volume. With the rapid development of embedded system and the appearance of newly high-performed inertial components, it’s possible to design a low-cost and micro AHRS. This paper researches a kind of AHRS which consists of high-performance ARM embedded microprocessor and embedded real-time operating system.
Firstly, the basic theories and operational principles of AHRS are introduced, including the definition of usually coordinates in inertia system, carrier’s attitude denotation, the Quaternion and Rotation vector attitude matrix algorithms,the principle of carrier’s attitude measurement. An exponent fading factor adaptive algorithm which is based on the adaptive estimation is proposed.
Secondly, this paper introduces the hardware and software design of AHRS based on ARM. We present the overall plan of hardware designing and discuss every function in detail. We also present the overall plan of software desiging and focus on software implementation of AHRS based on ARM. In order to verify the feasibility and reliability of the AHRS, we built an embedded real-time test platform and discuss the tool of Simulink/RTW which can generate portable C code in detail.
Lastly, we build the experimental system based on the ARM HARS solution and describe the process of the experiment in detail, then in the experiment succeeded in solving the problems in debugging code, at last the successful implementation of the code and run cross-platform migration.
Research proves that the AHRS compared with general attitude and heading measurement system is small size,low cost,high real time and so on. AHRS based on S3C2410X microprocessor and Linux2.6 real-time operating system is composed of 3-axis micro accelerometers, 3-axis micro rate gyros and 3-axisMangetoresistive sensors. The system is of great practical value in civil fields.
本文首先介绍了航姿系统的基本理论及其工作原理,包括惯性系统中常用坐标系的定义、姿态角的定义、四元数法、旋转矢量法,重点介绍了载体姿态测量的原理。通过对自适应加权因子和预报残差的研究,提出了一种基于指数渐消因子的自适应卡尔曼滤波算法。
其次,介绍了基于嵌入式系统的微惯性航姿系统的硬件和软件设计。提出了硬件设计方案,并对各个功能模块进行了详细说明;同时也提出了软件设计方案,重点介绍了基于ARM的航姿参考系统的软件实现方法。为了验证系统的可行性和可靠性,搭建了嵌入式实时测试平台,详细论述了Simulink/RTW生成可移植C代码的原理。
最后,搭建了基于ARM航姿解算的实验系统,详细介绍了航姿解算实验的实现过程,解决了代码移值和调试中出现的很多问题,成功实现了代码的跨平台移植和运行。
实验结果证明,由三轴微加速度计、三轴微陀螺仪和三轴磁阻传感器组成,以S3C2410X微处理器和裁剪的Linux2.6实时操作系统为核心的航向姿态参考系统,与通常的航姿测量系统相比,具有体积小、成本低、实时性强等特点,在民用领域具有很广阔的应用前景。
Although there is a huge demand of low-cost and miro Attitude and Heading Reference System(AHRS) in civil fields, such as the electronic toys, tridimensional emulation, sports detection, robots and VR games; the traditional AHRS limits in these fields because of high prices and large volume. With the rapid development of embedded system and the appearance of newly high-performed inertial components, it’s possible to design a low-cost and micro AHRS. This paper researches a kind of AHRS which consists of high-performance ARM embedded microprocessor and embedded real-time operating system.
Firstly, the basic theories and operational principles of AHRS are introduced, including the definition of usually coordinates in inertia system, carrier’s attitude denotation, the Quaternion and Rotation vector attitude matrix algorithms,the principle of carrier’s attitude measurement. An exponent fading factor adaptive algorithm which is based on the adaptive estimation is proposed.
Secondly, this paper introduces the hardware and software design of AHRS based on ARM. We present the overall plan of hardware designing and discuss every function in detail. We also present the overall plan of software desiging and focus on software implementation of AHRS based on ARM. In order to verify the feasibility and reliability of the AHRS, we built an embedded real-time test platform and discuss the tool of Simulink/RTW which can generate portable C code in detail.
Lastly, we build the experimental system based on the ARM HARS solution and describe the process of the experiment in detail, then in the experiment succeeded in solving the problems in debugging code, at last the successful implementation of the code and run cross-platform migration.
Research proves that the AHRS compared with general attitude and heading measurement system is small size,low cost,high real time and so on. AHRS based on S3C2410X microprocessor and Linux2.6 real-time operating system is composed of 3-axis micro accelerometers, 3-axis micro rate gyros and 3-axisMangetoresistive sensors. The system is of great practical value in civil fields.
引文
[1]潘敏.DSP及其在捷联航姿系统中的应用[硕士论文].西安:西北工业大学,2003.
[2]傅建国,王孝通,金良安等.基于MARG传感器的自主姿态测量新算法[J].中国惯性技术学报,2004,12(4):51-56.
[3]魏萍.基于ARM的嵌入式航向姿态参考系统的研究[硕士论文].杭州:浙江大学,2006.
[4]陈哲.捷联惯导系统原理[M].北京:宇航出版社,1996.
[5]于波,陈云相,郭秀中.惯性技术[M].北京:北京航空航天大学出版社,1994.
[6]陈永冰,钟斌.惯性导航原理[M].北京:国防工业出版社,1990.
[7]蒋庆仙.关于MEMS惯性传感器的发展及在组合导航中的应用前景[J].测绘通报,2006,9:5-8.
[8] Braghin Francesco,Leo Elisabetta,Resta Ferruccio.The danping in MEMS inertial sensors both at high and low pressure levels.Nonlinear Dynamics,2008,10:79-92.
[9]陈义华,王凌云,孙道恒.基于MEMS技术的微型惯性测量组合[J].自动化博览,2005(S2):135-139.
[10]袁信,郑谬.捷联式惯性导航原理[M].航空专业教材编审组,1985.
[11]吕志清,吴旭峰.微机械惯性器件[J].压电与声光.1997,19(6):375~380.
[12]闻新,张伟,黄勤珍.微惯性测量装置的技术分析与发展建议[J].中国航天,2003,6.
[13]李荣冰,刘建业,曾庆化等.基于MEMS技术的微惯性导航系统的发展现状[J].中国惯性技术学报,2006,12(6):88-94.
[14]刘瑞华.微机电惯性测量元件在导航系统的应用研究[J].中国民航学院学报,2003,6.
[15]高健.基于ARM处理器的捷联系统研究[硕士论文].哈尔滨:哈尔滨工业大学,2007.
[16]田泽.嵌入式系统开发与应用[M].北京:北京航空航天大学出版社,2004.
[17]鄢化彪,朱建武,韩树人等.构建RTW下的嵌入式系统开发环境[J].单片机与嵌入式系统应用,2007,1.
[18]陈宇捷.基于MEMS的微小型嵌入式航姿参考系统研究[硕士论文].上海:上海交通大学,2009.
[19]索夫HT.控制系统的最优滤波和辨识方法[M].燕申译.北京:国防工业出版社,1984,166-202.
[20]宋文尧,张牙.卡尔曼滤波[M].北京:科学出版社,1991,100.
[21] Kwang Hoon KimJang Gyu Lee,Chan Gook Park,and Gyu In Jee.The Stability Analysis of the Adaptive Fading Extended Kalman Filter.16th IEEE International Conference on Control Applications Part of IEEE Multi-conference on Systems and Control Singapore,1-3 October2007.
[22]蔡毅,张怡,杨舸,仝浩.基于联邦滤波的自适应算法研究[J].计算机工程与控制,2009,45(1).
[23]徐景硕,秦永元,彭蓉.自适应卡尔曼滤波器渐消因子选取方法研究[J].系统工程与电子技术,2004,26(11).
[24] ADI.ADIS16350 Tri-Axis sensor.Analog devices Inc.2007.
[25]朱俊华,周兆英,叶雄鹰等.微型隧道效应磁强计的设计和加工工艺研究[J].微细加工技术,2001,(1):53-55.
[26] HMC1001/1002 HMC1021/1022 1-axis and 2-axis magnetic sensors.Rev.B. Honeywell.2004.
[27]陈桂明,张明照,戚红雨等.应用MATLAB建模与仿真[M].北京:科学出版社,2001.
[28] GAO Zhong yu, Niu Xiao-ji, Guo Mei-feng.Quaternion-based Kalman Filter for Micro-machined strapdown attitude heading reference system[J].Chinese Journal of Aeronautics,2002,13(3):171-175.
[29] Gebre-Rgziabher D, Gabriel H, etal. A gyro-free quaternion-based attitude determination system suitable for implementation using low cost sensors[J]. IEEE Position Location and Navigation Symposium,2000,185:192.
[30] Gul Farid,Fang Jiancheng, Gaho Anwar Ali.GPS/SINS navigation data fusion using quaternion model and unscented Kalman filter. 2006 IEEE International Conference on Mechatronics and Automation,ICMA 2006, 2006:1854-1859.
[31] Florian Knorn Douglas J. Leith. Adaptive Kalman Filtering for Anomaly Detection in Software Appliances. Computer Communications Workshops, 2008. INFOCOM. IEEE Conference on 13-18 April 2008 Page(s):1-6.
[32] Kwang Hoon KimJang Gyu Lee,Chan Gook Park,and Gyu In Jee.The Stability Analysis of the Adaptive Fading Extended Kalman Filter.16th IEEE International Conference on Control Applications Part of IEEE Multi-conference on Systems and Control Singapore,1-3 October 2007.
[33]乔海泉,王奇霞,梁加红.基于RLLinux的MATLAB实时仿真[J].计算机仿真,2002,19(6).
[34]连冬.基于RTW/Linux的实时仿真技术研究[硕士论文].长沙:国防科学技术大学,2004.
[35]王奇霞.通用实时数据采集系统仿真研究[硕士论文].长沙:国防科学技术大学,2002.
[36]乔海泉.通用仿真测试系统研究[硕士论文].长沙:国防科学技术大学,2002.
[37]王健.飞机刹车半实物仿真系统研究[硕士论文].西安:西北工业大学,2007.
[2]傅建国,王孝通,金良安等.基于MARG传感器的自主姿态测量新算法[J].中国惯性技术学报,2004,12(4):51-56.
[3]魏萍.基于ARM的嵌入式航向姿态参考系统的研究[硕士论文].杭州:浙江大学,2006.
[4]陈哲.捷联惯导系统原理[M].北京:宇航出版社,1996.
[5]于波,陈云相,郭秀中.惯性技术[M].北京:北京航空航天大学出版社,1994.
[6]陈永冰,钟斌.惯性导航原理[M].北京:国防工业出版社,1990.
[7]蒋庆仙.关于MEMS惯性传感器的发展及在组合导航中的应用前景[J].测绘通报,2006,9:5-8.
[8] Braghin Francesco,Leo Elisabetta,Resta Ferruccio.The danping in MEMS inertial sensors both at high and low pressure levels.Nonlinear Dynamics,2008,10:79-92.
[9]陈义华,王凌云,孙道恒.基于MEMS技术的微型惯性测量组合[J].自动化博览,2005(S2):135-139.
[10]袁信,郑谬.捷联式惯性导航原理[M].航空专业教材编审组,1985.
[11]吕志清,吴旭峰.微机械惯性器件[J].压电与声光.1997,19(6):375~380.
[12]闻新,张伟,黄勤珍.微惯性测量装置的技术分析与发展建议[J].中国航天,2003,6.
[13]李荣冰,刘建业,曾庆化等.基于MEMS技术的微惯性导航系统的发展现状[J].中国惯性技术学报,2006,12(6):88-94.
[14]刘瑞华.微机电惯性测量元件在导航系统的应用研究[J].中国民航学院学报,2003,6.
[15]高健.基于ARM处理器的捷联系统研究[硕士论文].哈尔滨:哈尔滨工业大学,2007.
[16]田泽.嵌入式系统开发与应用[M].北京:北京航空航天大学出版社,2004.
[17]鄢化彪,朱建武,韩树人等.构建RTW下的嵌入式系统开发环境[J].单片机与嵌入式系统应用,2007,1.
[18]陈宇捷.基于MEMS的微小型嵌入式航姿参考系统研究[硕士论文].上海:上海交通大学,2009.
[19]索夫HT.控制系统的最优滤波和辨识方法[M].燕申译.北京:国防工业出版社,1984,166-202.
[20]宋文尧,张牙.卡尔曼滤波[M].北京:科学出版社,1991,100.
[21] Kwang Hoon KimJang Gyu Lee,Chan Gook Park,and Gyu In Jee.The Stability Analysis of the Adaptive Fading Extended Kalman Filter.16th IEEE International Conference on Control Applications Part of IEEE Multi-conference on Systems and Control Singapore,1-3 October2007.
[22]蔡毅,张怡,杨舸,仝浩.基于联邦滤波的自适应算法研究[J].计算机工程与控制,2009,45(1).
[23]徐景硕,秦永元,彭蓉.自适应卡尔曼滤波器渐消因子选取方法研究[J].系统工程与电子技术,2004,26(11).
[24] ADI.ADIS16350 Tri-Axis sensor.Analog devices Inc.2007.
[25]朱俊华,周兆英,叶雄鹰等.微型隧道效应磁强计的设计和加工工艺研究[J].微细加工技术,2001,(1):53-55.
[26] HMC1001/1002 HMC1021/1022 1-axis and 2-axis magnetic sensors.Rev.B. Honeywell.2004.
[27]陈桂明,张明照,戚红雨等.应用MATLAB建模与仿真[M].北京:科学出版社,2001.
[28] GAO Zhong yu, Niu Xiao-ji, Guo Mei-feng.Quaternion-based Kalman Filter for Micro-machined strapdown attitude heading reference system[J].Chinese Journal of Aeronautics,2002,13(3):171-175.
[29] Gebre-Rgziabher D, Gabriel H, etal. A gyro-free quaternion-based attitude determination system suitable for implementation using low cost sensors[J]. IEEE Position Location and Navigation Symposium,2000,185:192.
[30] Gul Farid,Fang Jiancheng, Gaho Anwar Ali.GPS/SINS navigation data fusion using quaternion model and unscented Kalman filter. 2006 IEEE International Conference on Mechatronics and Automation,ICMA 2006, 2006:1854-1859.
[31] Florian Knorn Douglas J. Leith. Adaptive Kalman Filtering for Anomaly Detection in Software Appliances. Computer Communications Workshops, 2008. INFOCOM. IEEE Conference on 13-18 April 2008 Page(s):1-6.
[32] Kwang Hoon KimJang Gyu Lee,Chan Gook Park,and Gyu In Jee.The Stability Analysis of the Adaptive Fading Extended Kalman Filter.16th IEEE International Conference on Control Applications Part of IEEE Multi-conference on Systems and Control Singapore,1-3 October 2007.
[33]乔海泉,王奇霞,梁加红.基于RLLinux的MATLAB实时仿真[J].计算机仿真,2002,19(6).
[34]连冬.基于RTW/Linux的实时仿真技术研究[硕士论文].长沙:国防科学技术大学,2004.
[35]王奇霞.通用实时数据采集系统仿真研究[硕士论文].长沙:国防科学技术大学,2002.
[36]乔海泉.通用仿真测试系统研究[硕士论文].长沙:国防科学技术大学,2002.
[37]王健.飞机刹车半实物仿真系统研究[硕士论文].西安:西北工业大学,2007.