小型测绘无人机遥感系统关键技术的研究

发布时间：2018-01-23 03:12

  本文关键词： 无人机 摄影测量 自驾仪 MEMS陀螺 MEMS加速度计 捷联惯性导航 组合导航 Kalman滤波 Fuzzy-PID 飞行控制律 自稳定平台 数字相机检定 DLT 多片后交 六旋翼　出处：《解放军信息工程大学》2014年博士论文　论文类型：学位论文

【摘要】：随着现代遥感技术的发展,测绘、土地、电力、公安、城建等部门对局部区域高空间分辨率、高光谱分辨率和高时间分辨率遥感产品的要求越来越迫切,测绘型无人机平台作为新型的遥感平台以其使用灵活方便,基本不受场地和天气的限制,可携带各种有效载荷,成本低廉等优点,已渐渐成为民用无人机应用研究的热点。本文主要围绕无人机遥感系统关键技术展开研究,重点对自动驾驶仪、组合导航算法、三轴自稳技术、相机检定技术进行研究,通过综合成图实验与精度验证实验证明本文所述方法的正确性。主要工作和创新点如下:1)为满足测绘型无人机对基于多传感器捷联惯导的多源导航数据信息融合、基于模糊控制的区域任务飞行和三轴稳定平台三个关键技术对硬件系统的要求,完成了小型自动驾驶仪系统的整体架构设计、电路参数计算、元器件选型以及原型机的制作等工作。2)在充分分析捷联惯性导航(SINS,Strapdown Inertial Navigation System)、全球卫星导航(GNSS,Global Navigation Satellite System)、大气导航和磁导航的原理基础上,重点推导了符合自制自驾仪硬件方案的集中式卡尔曼滤波(Kalman)滤波的实用组合导航算法。仿真实验结果表明,组合导航较独立导航系统在改善系统稳定性和提高精度方面有明显的优势,滤波后输出的航向角精度为0.28°(动态范围10°),横滚角精度为0.39°(动态范围10°),俯仰角度精度为0.77°(动态范围40°),水平精度可为2.25m,高度精度可达0.7m。3)依据航空摄影测量规范对飞行平台和有效载荷的要求,系统地提出了无人机飞控和三轴自稳定云台的控制精度指标,设计并实现了无人机飞控和三轴自稳定云台的Fuzzy-PID控制算法。实验证明,Fuzzy-PID比传统PID在响应时间、失调量、稳定时间和稳态误差上均优于传统PID,尤其超调量特性非常有利于无人机的稳定控制。Fuzzy-PID的上升时间为0.13s比传统PID慢0.05s,但在可接受范围内。室内精度实验和实际飞行实验检测表明各项指标达到或优于设计要求,满足小区域大比例尺地形图立体测绘对飞控和稳定平台的要求。4)针对非量测型CCD数字相机特点和野外快速检定非量测型相机的现实需求,详细分析了误差来源,建立了相机检定的数学模型。详细讨论了多片分组迭代求解DLT系数、内方位和畸变参数和多片后方交会法求解内外方位和畸变参数的方法,自制了野外快速非量测型相机的检定架,通过检定片分别求出两种方法下的内方位和畸变参数,通过验证片进行了精度验证。从精度验证片前方交会的结果来看,多片DLT算法的X最大误差为0.2585mm,Y最大误差为0.6719mm,Z最大误差为0.1319mm,多片后交算法的X最大误差为0.1914mm,Y最大误差为0.9808mm,Z最大误差为0.1453mm。2种方法的前方交会精度相当,均小于1mm;多片DLT算法平面精度小于0.2585mm,高程精度小于0.6719mm,多片后交算法平面精度小于0.1914mm,高程精度小于0.9808mm,多片后交算法平面精度略高于多片DLT,而多片DLT算法的高程精度好于多片后交算法。本文采取的两种多片相机检定的方法,都能够基本满足非量测型相机用于摄影测量的要求,同时也注意到了内方位元素和畸变差参数解算精度不高的问题。但是对于非量测相机来说,内方位和物镜畸变差参数真值的未知并不影响摄影测量的精度。
[Abstract]:With the development of modern remote sensing technology, surveying and mapping, land, power, public security, urban construction and other departments of the local area of high spatial resolution, high spectral resolution and high temporal resolution remote sensing products is more and more urgent, mapping the UAV platform as a new remote sensing platform with its flexible and convenient use, no space and weather restrictions that can carry a variety of payloads, low cost and other advantages, has gradually become a hot topic of civilian UAV applications. This paper mainly focuses on the key technology of UAV remote sensing system is studied, focusing on autopilot, navigation algorithm, three axis stabilization technology, research on camera calibration technology, through the integrated into the correct map experiment and accuracy verification experiment proves that the method in this paper. The main work and innovation are as follows: 1) to meet the unpiloted mapping of multiple sensors based on agile strapdown navigation multi Guide Navigation information fusion, fuzzy control of the regional flight mission requirements and three axis stabilized platform three key technologies of hardware system based on the completion of the overall architecture of the autopilot system design, circuit parameter calculation, component selection and prototype manufacture,.2) in the full analysis of strapdown inertial navigation (SINS, Strapdown Inertial Navigation System (GNSS), global satellite navigation, Global Navigation Satellite System), the basic principle of air navigation and magnetic navigation, the key is derived with self centralized driving Calman filter instrument hardware scheme (Kalman) practical navigation algorithm filter. Simulation results show that the integrated navigation and navigation system is significantly more independent the advantage in improving the stability of the system and improve the accuracy of the filtered output precision of yaw angle is 0.28 degrees (dynamic range 10 degrees), roll angle precision 0.39 degrees (dynamic range of 10 DEG), pitch angle accuracy is 0.77 degrees (dynamic range of 40 DEG), the level of accuracy is 2.25m, the height accuracy of 0.7m.3) on the basis of aerial photogrammetric specification of flight platform and payload requirements, systematically put forward the index control precision of UAV flight control and three axis stabilized platform the design and implementation of Fuzzy-PID control algorithm for UAV flight control and three axis self stabilizing PTZ. The experimental results show that the misalignment Fuzzy-PID than the traditional PID in the response time, stable time and steady error is superior to the traditional PID, especially the overshoot characteristics of UAV is very conducive to the stability control of.Fuzzy-PID rise time 0.13s compared with the traditional PID slow 0.05s, but in the acceptable range. The accuracy of indoor experiment and practical flight test shows that all indexes reached or exceeded the design requirements, meet the area of large scale topographic map of stereo mapping on the fly Control and stable platform for.4) for non metric digital camera CCD characteristics and field verification non realistic demand measurement camera, a detailed analysis of the error sources, establishes the mathematical model of camera calibration. Multi block iterative DLT coefficients is discussed in detail, and in the range of distortion parameters and multi piece rear the intersection method of solving inside and outside orientation and distortion parameters, made the verification frame rapid field non metric camera, through the verification sheet were obtained by the two methods within the range and distortion parameters, through the verification sheet were verified. Verification sheet intersection results from the precision, the maximum error of more than X DLT algorithm for 0.2585mm Y, the maximum error is 0.6719mm, the maximum error is Z 0.1319mm X, the maximum error algorithm to multi chip after 0.1914mm Y, the maximum error is 0.9808mm, the maximum error is Z 0.1453mm.2 method of intersection The accuracy is less than 1mm; multi DLT algorithm of plane precision is less than 0.2585mm, the elevation accuracy is less than 0.6719mm, multi piece after the plane algorithm precision is less than 0.1914mm, the elevation accuracy is less than 0.9808mm, multi piece after the algorithm is slightly higher than the plane precision of multi DLT and multi DLT algorithm, high precision in multi process after algorithm. This article adopts the method of two kinds of multi camera calibration, can basically meet the non metric camera is used in photography measurement, but also pays attention to the inner orientation elements and the distortion parameters calculation accuracy is not high. But for non metric camera, and lens distortion parameters within the range the true value of the unknown does not affect the photographic measurement accuracy.

【学位授予单位】：解放军信息工程大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：P237
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本文编号：1456535