SIA OpenIR  > 水下机器人研究室
AUV组合导航定位方法的研究
Alternative TitleResearch on the Integrated Navigation System of AUV
冯子龙1,2
Department水下机器人技术研究室
Thesis Advisor刘键
ClassificationTP242.3
KeywordAuv 组合导航 航位推算
Call NumberTP242.3/F66/2005
Pages61页
Degree Discipline模式识别与智能系统
Degree Name硕士
2005-05-31
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Abstract自治水下机器人(AUV)主要用于海洋环境监测、海洋地球科学数据采集、海底资源调查、海洋救助与打捞、军事和国防建设等领域。对于内部空间有限,携带能源有限,需要在未知水域远距离、长时间、低速航行的AUV来说,导航系统性能的优劣将在很大程度上决定AUV能否完成使命或高质量完成使命。当前,各种单一的导航系统和设备的发展已趋于成熟稳定,它们各自的优缺点也早已被明显地表现出来。随着技术的发展,近10年来,涌现出了多种组合导航系统。但实际中,针对上述这种特殊AUV运动载体的组合导航研究相对较少。本文根据实际工程项目需要,介绍了两种组合导航方案以实现AUV远距离、低速、长时间任务的导航需要:全球定位系统(GPS)/航位推算系统(DR)构成的组合导航系统、超短基线水声通讯系统(USBLCS)/多普勒计程仪(DVL)/光纤陀螺(FOG)组合导航系统。前者适用于大多数情况下的AUV导航,后者对于特殊环境下的AUV导航有着独到的优势(如极地冰层下的作业环境、深海作业等场合)。文章还结合实际,对应用最广泛的导航算法之一的航位推算算法进行了改进,考虑了AUV远程导航过程中地球不规则形状的影响,考虑了实际工程中航向传感器存在一定安装偏角、航速传感器输出的航速存在误差的影响,通过最小二乘辨识方法进行了校正。对组合导航系统中的滤波算法、融合算法,尤其是对应用最广泛的卡尔曼滤波理论进行了讨论,最终选用自适应卡尔曼滤波器来实现上述方案中AUV实时在线导航信息的滤波融合。而对于航行导航过程中,精度要求不是非常严格的高度信息和深度信息,本文采用相对简单、有效且实时性好的渐消记忆递推最小二乘法进行滤波。最后,利用实际AUV载体航行实验所获得的传感器数据进行了仿真实验,结果表明,利用经过滤波、融合后的航向数据、航速数据以及改进后的航位推算公式进行航位推算导航,推算精度提高了将近一倍,与经过滤波后的GPS数据一起构成的组合导航精度得到了进一步提高。实验表明,以上组合导航方案能够满足实际工程需要。
Other AbstractAt present, autonomous underwater vehicle is widely used for those areas such as sea environments detection, sea-earth scientific data sampling and sea floor resources investigation and so on. However, for AUV which inter-place is limited and taking resources is finite and sails long distances for a long time, so whether good or not its navigation system performance decides whether AUV can accomplish tasks or not. Now the development of various solo-navigation systems and devices tends to be in the autumn period. Therefore, their respective shortcomings have already been obviously demonstrated. For recent decade years, with development of technology multifarious integrated navigation systems have been rushing. So especially in terms of those sailing indices such as long distance in unknown areas, low velocity for a long time and so on, research on integrated navigation systems is becoming more important. However, in fact those investigations are relatively less. On the basis of the requirements of practical projects two types of navigation system schemes, which are integrated navigation system that one is made up of GPS and Dead Reckoning system, the other one that consists of Ultra Short Baseline Communication System, Doppler Velocity Log and Fiber Optic Gyro, are introduced in this paper. The former adapts to most of AUV navigation. However, the later has special predominance in those environments such as Polar Regions, deep-sea areas etc. Moreover, in order to better satisfy the practical needs, dead reckoning that is one of the most widely used ways in AUV navigation is developed in this paper. Besides, the navigation filtering and fusion algorithms are discussed and ultimately adaptive Kalman filter is chosen to implement real-time fusing navigation information of AUV. And for the case that demands not high precisions for altitude and depth information when AUV is marching, a relatively simple, available way that also has a good real-time performance, Recursive least square filtering with fading factor, is adopted to filter navigation information. Finally, applying sensors data that have been acquired through AUV navigation experiments to simulate in this way, the outcomes indicate that dead-reckoning precisions have been doubled. Moreover, the precisions of the integrated navigation system incorporating with filtering GPS data have been further improved. So those experiments make clear that the integrated navigation scheme can satisfy the projection requirements and have a certain application values.
Language中文
Contribution Rank1
Document Type学位论文
Identifierhttp://ir.sia.cn/handle/173321/9481
Collection水下机器人研究室
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院研究生院
Recommended Citation
GB/T 7714
冯子龙. AUV组合导航定位方法的研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2005.
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