没有合适的资源?快使用搜索试试~ 我知道了~
容错多传感器组合导航系统算法研究及仿真实现1
需积分: 0 0 下载量 154 浏览量
2022-08-03
14:34:44
上传
评论
收藏 5.38MB PDF 举报
温馨提示
试读
77页
摘要随着电子信息技术的高速发展,现代战场环境日趋复杂化,包括 GPS、北斗、GLONASS以及伽利略导航系统在内的各种无线电导航系统容易受到敌方强电磁干扰,天文
资源详情
资源评论
资源推荐
南京航空航天大学
硕士学位论文
容错多传感器组合导航系统算法研究及仿真实现
姓名:陈海明
申请学位级别:硕士
专业:精密仪器及机械
指导教师:熊智
2011-01
南京航空航天大学硕士学位论文
I
摘 要
随着电子信息技术的高速发展,现代战场环境日趋复杂化,包括 GPS、北斗、GLONASS
以及伽利略导航系统在内的各种无线电导航系统容易受到敌方强电磁干扰,天文导航系统需要
观测到星光才能工作,地形辅助导航系统受到地域和计算机存储地图容量的限制,这些不利的
因素导致依靠单一的导航传感器无法确保完全满足导航系统的正常可靠工作,当导航信息输出
发生故障时,会影响整个导航系统的精度和可靠性;结合高空长航无人机的应用背景和工作特
点,其对导航系统长时间的高可靠性和高精度性要求较高,所以单一的组合导航模式不能满足
其工作的需求,为此,论文针对高空长航无人机的工作特点设计了相应的惯性/多传感器组合导
航系统容错方案,并对具体的惯性/多传感器组合导航融合算法和传感器故障检测算法进行了深
入研究,在此基础上设计了基于分布式网络结构的惯性/多传感器容错组合导航系统仿真实验平
台,从而为未来多信息融合导航算法在高空长航无人机的工程应用奠定了一定的理论基础。
论文首先结合高空长航无人机的应用背景和工作特性,以惯性导航系统、天文导航系统、
GPS 和 SAR 图像匹配导航系统为基础,对组合导航系统融合算法进行了详细深入的研究,首先
根据各导航传感器的误差特性建立相应的状态方程和量测方程,然后建立相应的卡尔曼滤波模
型,最后通过算法仿真验证了所提出的融合算法的可行性和有效性。
其次论文针对传感器工作过程中容易出现故障的问题,对传感器故障检测算法进行了深入
研究,针对残差
2
χ
检测算法对小值的故障信息检测灵敏度较低的缺点,提出了一种基于特征值
提取的改进故障检测算法,并通过仿真验证了该算法对小值的故障信息检测灵敏度明显好于残
差
2
χ
检测算法,该改进算法有利于进一步提高导航系统的精度和可靠性。
最后,论文在前面研究的惯性/多传感器组合导航系统容错方案、多信息融合算法以及传感
器故障检测算法的基础上,设计并实现了基于分布式网络结构的惯性/多传感器容错组合导航系
统仿真实验平台,该实验平台由惯性传感器仿真子系统、多传感器仿真子系统、融合与控制子
系统以及显示子系统 4 个部分组成,该仿真实验平台可以对多种导航传感器组合模式下的融合
算法进行仿真研究,仿真实验平台的灵活性和适应性较强,最后通过系统仿真验证了该实验平
台的可行性和有效性。
关键词
:组合导航,卡尔曼滤波,故障检测,联邦滤波,信息融合,仿真实验平台
容错多传感器组合导航系统算法研究及仿真实现
II
Abstract
With the rapid development of electronic information technology, the modern battlefield
environment of high altitude was growing more complex. A variety of radio navigation systems
including GPS, Compass, GLONASS and Galileo navigation system, were vulnerable to enemy
electromagnetic interference; Celestial navigation system was vulnerable to the impact of natural
environment; Terrain aided navigation was limited by the region and the capacity of computer storage;
These adverse factors lead that the navigation sensors didn’t work well, and the output of navigation
information was wrong, which affected the accuracy and reliability of navigation systems. According
to the application background and work characteristics of the high altitude and long endurance
UAV(unmanned aerial vehicle), its navigation system should have high reliability and high navigation
precision for long time, so a single navigation model could not meet the needs for its work.. To this
end, this paper designed the corresponding integration program of SINS/multi-sensor integrated
navigation system, and studied the integration algorithm and fault detection algorithm in depth. On
this basis, the simulation platform of SINS/multi-sensor integrated navigation system was designed,
so as to set some theoretical basis for project application.
Firstly, considering the application background and work characteristics of UAV, the paper
studied the fusion algorithm of SINS/GPS/CNS/SAR integrated navigation system in detail;
According to the error characteristics of navigation sensors, the paper established the corresponding
state equation, measurement equation, information distribution coefficient, and then created the
corresponding kalman filter model; The result of MATLAB simulation proved the fusion algorithm
was feasibility and effectiveness.
Secondly, the paper studied the sensor fault detection algorithm. Considering the disadvantage of
residual chi-square detection algorithm which had low sensitivity to small fault information, the paper
proposed a improved fault detection algorithm based on eigenvalue detection; The result of MATLAB
simulation showed that the algorithm was better than the residual chi-square detection algorithm, and
the improved method could further improve the accuracy and reliability of navigation systems.
Finally, the paper designed a simulation experiment platform of SINS/multi-sensor integrated
navigation system based on the distributed network. The experiment platform consisted of inertial
sensor simulation subsystem, multi-sensor simulation subsystem, fusion and control subsystem, and
display subsystem. The experiment platform could research a variety of integrated navigation
algorithm, and had strong flexibility and adaptability.
南京航空航天大学硕士学位论文
III
Keywords: Integrated Navigation, Kalman Filter, Fault Detection, Federated Filter, Information
Fusion, Simulation Experiment Platform
容错多传感器组合导航系统算法研究及仿真实现
IV
图清单
图 1.1 Block 40 高空长航时无人机 ......................................................................................................2
图 1.2 Global Observer 高空长航时无人机 ..........................................................................................2
图 1.3 论文结构框图.............................................................................................................................6
图 2.1 基于联邦滤波结构的组合导航系统方案.................................................................................8
图 2.2 三维运行轨迹...........................................................................................................................14
图 2.3 纯惯性姿态误差曲线...............................................................................................................15
图 2.4 纯惯性速度误差曲线...............................................................................................................15
图 2.5 纯惯性位置误差曲线...............................................................................................................15
图 2.6 惯性/GPS 组合姿态误差曲线 .................................................................................................16
图 2.7 惯性/GPS 组合速度误差曲线 .................................................................................................16
图 2.8 惯性/GPS 组合位置误差曲线 .................................................................................................16
图 2.9 惯性/天文组合姿态误差曲线..................................................................................................17
图 2.10 惯性/天文组合速度误差曲线................................................................................................17
图 2.11 惯性/天文组合位置误差曲线................................................................................................17
图 2.12 惯性/SAR 组合姿态误差曲线...............................................................................................18
图 2.13 惯性/SAR 组合速度误差曲线...............................................................................................18
图 2.14 惯性/SAR 组合位置误差曲线...............................................................................................18
图 2.15 惯性/天文/GPS/SAR 姿态误差曲线 .....................................................................................19
图 2.16 惯性/天文/GPS/SAR 速度误差曲线
.....................................................................................19
图 2.17 惯性/天文/GPS/SAR 位置误差曲线 .....................................................................................20
图 3.1 基于联邦滤波结构的组合导航系统故障检测方案 ...............................................................22
图 3.2 三维运行轨迹...........................................................................................................................24
图 3.3 残差
2
χ
故障检测值.................................................................................................................25
图 3.4 纬度误差曲线...........................................................................................................................26
图 3.5 经度误差曲线...........................................................................................................................26
图 3.6 纬度估计误差曲线...................................................................................................................26
图 3.7 经度估计误差曲线...................................................................................................................26
图 3.8 基于特征值提取改进算法故障检测值...................................................................................28
图 3.9 经度误差曲线...........................................................................................................................29
剩余76页未读,继续阅读
艾斯·歪
- 粉丝: 34
- 资源: 343
上传资源 快速赚钱
- 我的内容管理 展开
- 我的资源 快来上传第一个资源
- 我的收益 登录查看自己的收益
- 我的积分 登录查看自己的积分
- 我的C币 登录后查看C币余额
- 我的收藏
- 我的下载
- 下载帮助
安全验证
文档复制为VIP权益,开通VIP直接复制
信息提交成功
评论0