Experimental Study of a Command Governor Adaptive Depth Controller for an Unmanned Underwater Vehicle

Unmanned Underwater Vehicles (UUVs) are increasingly being used in advanced applications that require them to operate in tandem with human divers and around underwater infrastructure and other vehicles. These applications require precise control of the UUVs which is challenging due to the non-linear and time varying nature of the hydrodynamic forces, presence of external disturbances, uncertainties and unexpected changes that can occur within the UUV’s operating environment. Adaptive control has been identified as a promising solution to achieve desired control within such dynamic environments. Nevertheless, adaptive control in its basic form, such as Model Reference Adaptive Control (MRAC) has a trade-off between the adaptation rate and transient performance. Even though, higher adaptation rates produce better performance they can lead to instabilities and actuator fatigue due to high frequency oscillations in the control signal. Command Governor Adaptive Control (CGAC) is a possible solution to achieve better transient performance at low adaptation rates. In this study CGAC has been experimentally validated for depth control of a UUV, which is a unique challenge due to the unavailability of full state measurement and a greater thrust requirement. These in turn leads to additional noise from state estimation, time-delays from input noise filters, higher energy expenditure and susceptibility to saturation. Experimental results show that CGAC is more robust against noise and time-delays and has lower energy expenditure and thruster saturation. In addition, CGAC offers better tracking, disturbance rejection and tolerance to partial thruster failure compared to the MRAC.     

基于GNSS方位辅助惯性导航系统的水下地形精密测量技术

多波束测深技术是目前水下地形测量的主要技术手段,测量平台的瞬时姿态及方位是影响多波束测深系统最终成果准确度的重要因素。GNSS方位辅助惯性导航系统,作为目前应用较为广泛的方位、姿态、及位置综合测量系统,不仅能够提供高精度位置信息,同时也能提供测量平台的瞬时姿态及方位数据,而且因为具有GNSS方位辅助测量,使得最终方位测量结果比传统方位测量精度大大提高,这对于多波束最终测量成果精度提高具有重要意义。文中从GNSS方位辅助惯性导航系统原理及技术优势出发,结合Trimble RTX后处理技术,从姿态测量、方位测量及辅助高程测量方面分析了在多波束水下地形测量中的应用,并以实际测量成果来展现其在水下地形精密测量技术方面的优势,结果显示,定位精度可以达到优于2 cm级别,方位精度可以优于0.01°(依赖于双GNSS天线之间的基线长度),该技术对水下地形测量准确度提升作用显著。     

天文定位中几何精度衰减因子最小值分析

天文定位是一种重要的导航定位方法,被广泛应用于大地天文测量、天文航海等领域。该方法中观测恒星的选择会影响最终的定位精度,目前缺少针对同时测定经纬度天文定位算法中最优选星问题的研究。随着观测仪器自动化水平的提高,观测数据的获取变得更加高效,这就要求研究最优的选星方案以达到最高的定位精度。本文借鉴卫星导航中几何精度衰减因子GDOP的概念,研究了天顶距法中恒星的数量以及分布对定位精度的影响,最后通过仿真试验和实测数据验证得到结论:在天顶距观测误差的统计特性一定时,GDOP能够用来描述恒星的分布对定位结果影响的优劣,且观测的恒星方位角均匀分布时定位误差最小。考虑到不同高度的恒星天顶距大气折射改正残差不同,在实际测量中应尽量采用等天顶距且方位角均匀分布的恒星。     

浅析房产面积测绘中存在的问题

随着房地产经济的迅猛发展,业主对房产面积测绘精度的要求越来越高。房产面积测绘的精确度与业主的合法利益有很大的关联,这就要求更加严格控制测绘过程质量,减少房产面积测绘误差。本文讨论了目前房产测绘中存在的几大问题,并对如何提高房产测绘质量提出相关的建议和对策。     

旋翼无人机测算风速风向技术研究

目前大部分民用无人机没有准确测量风速、风向和预警风场的功能,然而森林火灾扑救等多种场景需要无人机可以提供准确的风速。本文提出了一种基于旋翼无人机坐标数据测算风速风向的技术,通过无人机主机RTK坐标信息及方位角、倾角数据精准获取螺旋桨点相对坐标信息,选择不同负载条件下无人机以1~16 m/s的不同速度分别飞行30 s以上,根据螺旋桨坐标信息变化数值,结合风洞测试数据及风场动力学原理,研究风速与旋翼无人机倾角关系,并通过风洞试验检验该方法精度;并可根据无人机RTK推算出的螺旋桨坐标变化信息判断风向。结果表明,无人机风速与旋翼无人机倾角呈正相关关系;无人机负载加重时,对应受风速干扰的倾角会相对减小;无人机飞行受阵风干扰出现噪点的概率,高海拔区域大于低海拔区域;并建立六旋翼无人机飞行倾角的风速估算模型y=－1.043 5+1.150 1x,该模型测算风速的中误差值为0.966,绝对值小于1,满足应急指挥现场对无人机测量风速精度要求。该方法得到风速测算精度高,可以为旋翼无人机实时获取风速风向提供一种可行方法,具有一定的实用价值。     

近景摄影测量支持下的地铁盾构管片姿态测量方法及其应用

传统的地铁盾构管片姿态测量的方法存在作业时间长,与施工流水线交叉作业劳动量大,且无法实时测量等不足。本文提出了利用近景摄影测量的方法对盾构管片姿态进行测量,通过在盾构管片环上铺设人工标志点,使用数码相机进行拍摄,利用光束法平常对摄影图片进行数据解算,得到解算标志点坐标后,再根据空间三点定圆心原理确定盾构环圆心点的坐标。试验结果表明,对比传统测量方法,新方法误差不超过3 cm,能够完全满足盾构管片姿态的测量精度要求,具有很好的推广价值。     

River centerline extraction using the multiple direction integration algorithm for mixed and pure water pixels

The river centerline is a basic hydrological characteristic. Most prior studies have used remote sensing data to extract the river centerline from the open water region in a pure water pixel region. Extracting this type of river is relatively easy. However, extracting the centerline of a micro-river, which is mainly composed of mixed water pixels, is challenging. This paper presents a novel method, called the Multiple Direction Integration Algorithm (MDIA), to extract the river centerline using an image-enhancing method combined with river morphology. MDIA can be applied to regions mainly composed of pure water pixels, as well as to regions consisting of mixed water pixels in the index image. The method first calculates the normalized difference vegetation index (NDVI) and enhances the river linear structure using a Hessian matrix. Second, a small window is constructed as a circular structural element. In the window region, the local threshold is automatically obtained using water-oriented clustering segmentation and prior river knowledge to judge the pixel type. After completing the river centerline extraction in the current window, the next detecting window is generated to continue judgment. The structural element automatically executes river centerline judgment until the entire river centerline is extracted. The Landsat 8 images of six regions with different geomorphologies were chosen to analyze the method’s performance. The test sites include high mountain region, low mountain region, plains region with farmland and a residential region. The experimental results show that the optimal threshold of the processing results ranged from 0.2 to 0.3. In this range, the user’s accuracy is 0.813 to 0.997, and the producer’s accuracy is 0.981 to 1. The MDIA effectively and correctly extracts the river network in mixed-pixel regions. The presented method provides an effective algorithm for river centerline extraction that can be used to expand and update river datasets and provide reliable river centerline data for relevant hydrology studies.     

GNSS全自动解算软件研发及精度评估

根据载波相位差分定位技术,利用待定点周边稳定的CORS站网形成的区域误差改正模型,对待定控制点观测数据的噪声进行自动剔除,对电离层、对流层和多路径进行差分改正,研发GNSS全自动解算软件,并利用广西卫星定位基准站与待定控制点的GNSS观测数据对软件进行测试。结果表明,GNSS全自动解算软件具有较好的内外符合精度,其解算的三维坐标精度满足D级以下等级控制点的要求,可为工程测量应用提供新的自动化解算方案。     

基于DEM数据的月表撞击坑自动提取研究

提出一种基于地形与形态学的撞击坑自动提取算法,该算法主要利用撞击坑的形态特征进行提取,利用形态学方法提高提取结果的连续性并去除提取结果中的噪声,使提取的撞击坑边界线更为简单,定位更加准确,易于存储与计算。该算法使用月球勘测轨道器照相机(LROC)提供的100 m分辨率DEM数据进行测试,测试结果显示该算法对于形态较为完整的简单撞击坑提取效果较好,提取的边界线较为准确且能够反映撞击坑的真实形态。     

Trimble MX7移动测量系统精度影响因素分析

车载移动测量系统的测图精度受测量环境影响较大,而城市测量的环境一般较复杂,且环境对测量精度的影响程度并未明确,因此本文主要针对车辆在建筑物遮挡和拐弯两种情况下做了实验,同时对同一目标点的二维坐标和三维坐标进行了平面精度的对比,综合分析评价了Trimble MX7移动测量系统在实际应用中行驶轨迹精度和目标点位精度的变化情况。实验证明,轨迹拐弯处的点位精度比车辆直行时的点位精度差,但满足1∶1 000数字测图精度要求,在建筑遮挡最密集时点位精度最差但仍可应用于1∶1 000野外数字测图,直接对目标点的三维坐标进行提取的精度优于二维坐标提取方式,该测量系统可应用于1∶2 000野外数字测图的高程测量。