GNSS多天线基线网单历元模糊度同步解算法

提出多天线基线网单历元模糊度同步解算法，其具体实现步骤为：1）根据宽巷组合模糊度易于固定的优点，采用附加已知基线长度约束法同步解算各基线的宽巷模糊度，得到dm~cm级精度的近似基线分量；2）将解算得到的各近似基线分量作为约束，同步解算各基线的基频模糊度，以获取mm级精度的基线矢量。该方法的关键在于检验各历元宽巷模糊度解算的正确性，以获取可靠的近似基线分量，为解算各基线的基频模糊度提供准确的基线先验信息。由于动态情况下各历元观测信息比较少，单纯依赖ratio检验不可靠，提出结合基线误差、单位权中误差、基线网模糊度闭合环及ratio值等对多组宽巷模糊度进行检验，避免ratio值设置不当导致模糊度检验中发生纳伪和弃真问题。实测数据结果证明，该处理方法使得模糊度解算的成功率提高1%~2%，可以获取移动平台更丰富的导航信息，提高其服务能力。     

A-FPN算法及其在遥感图像船舶检测中的应用

光学遥感图像船舶检测主要面临两个挑战:光学遥感图像背景复杂,船舶检测易受海浪、云雾及陆地建筑等多方面干扰;遥感图像分辨率低,船舶目标小,对于其分类与定位带来很大困难;针对上述问题,在FPN的基础上,提出一种融入显著性特征的卷积神经网络模型A-FPN (Attention-Based Feature Pyramid Networks)。首先,利用卷积提取图像特征金字塔;然后,利用顶层金字塔逐级构建显著特征层,抑制背景信息,通过金字塔顶层的细粒度特征提高浅层特征的表达能力,构建自上而下的多级显著特征映射结构;最后利用Softmax分类器进行多层级船舶检测。A-FPN模型利用显著性机制引导不同感受下的特征进行融合,提高了模型的分辨能力,对遥感图像处理领域具有重要应用价值。实验阶段,利用公开的遥感目标检测数据集NWPU VHR-10中的船舶样本进行测试,准确率为92.8%,表明A-FPN模型适用于遥感图像船舶检测。     

PTP协议在广电时间同步网中的应用研究

随着广电行业的飞速发展,以串行数字接口(SDI)基带信号为基础技术架构的传统电视信号已经很难满足未来技术发展和业务扩展的需求．得益于现代通信技术的迅速发展以及即将到来的万物互联的5G时代,广电行业也将采用IP化技术来构建新的网络系统．处在向IP化发展的过渡期,广电IP化目前还存在一些亟待解决的问题．为了解决广电系统网络中需要更高精度的同步信号来完成时间同步的问题,本文利用精确时间协议（PTP）时间同步技术在专用以太网中完成时间同步组网,搭建了测试环境并对测试数据进行了分析．测试结果表明,相较于传统的网络时间协议（NTP）时间同步技术,输出PTP信号的准确度能够达到亚微秒量级,完全满足广电行业IP化数字电视系统时间同步信号的高精度需求．      

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.     

高精度直升机机载LiDAR在高速公路改扩建勘测中的应用可行性研究

机载LiDAR在公路勘测方面的用途日益广泛。该文对直升机机载LiDAR在高速公路改扩建中的应用技术路线可行性进行了研究论证,从地面控制测量、点云数据获取、点云数据处理、成果应用等多个方面进行了阐述,通过分析LiDAR点云数据在5种不同地面控制点布设方案校正下的点云数据精度,论证了利用地面控制点对直升机机载LiDAR点云数据进行平面和高程校正的可行性。     

Hydrological management strategies for the control of algal blooms in regulated lowland rivers

Reservoirs of lowland floodplain rivers with eutrophic backgrounds cause variations in the hydrological and hydraulic conditions of estuaries and low-dam reservoir areas, which can promote planktonic algae to proliferate and algal bloom outbreaks. Understanding the ecological effects of variations in hydrological and hydraulic processes in lowland rivers is important for algal bloom control. In this study, the middle and lower reaches of the Han River, China, a typical regulated lowland river with a eutrophic background, are selected. Based on the effect of hydrological and hydraulic variability on algal blooms, a hydrological management strategy for river algal bloom control is proposed. The results showed that (a) differences in river morphology and background nutrient levels cause significant differences in the critical threshold flow velocities for algal bloom outbreaks between natural river and low-dam reservoir sections; there is no uniform threshold flow velocity for algal bloom control. (b) There are significant differences in the river hydrological/hydraulic conditions between years with and without algal blooms. The average river flow, water level and velocity in years with algal blooms are significantly lower than those in years without algal blooms. (c) For different river sections where algal blooms occur and to meet the threshold flow velocities, the joint operation of cascade reservoirs and diversion projects is an effective method to prevent and control algal blooms in regulated lowland rivers. This study is expected to deepen our understanding of the ecological significance of special hydrological processes and guide algal bloom management in regulated lowland rivers.     

Study of the flood control scheduling scheme for the Three Gorges Reservoir in a catastrophic flood

The Three Gorges Project is the world's largest water conservancy project. According to the design standards for the 1,000‐year flood, flood diversion areas in the Jingjiang reach of the Yangtze River must be utilized to ensure the safety of the Jingjiang area and the city of Wuhan. However, once these areas are used, the economic and life loss in these areas may be very great. Therefore, it is vital to reduce this loss by developing a scheme that reduces the use of the flood diversion areas through flood regulation by the Three Gorges Reservoir (TGR), under the premise of ensuring the safety of the Three Gorges Dam. For a 1,000‐year flood on the basis of a highly destructive flood in 1954, this paper evaluates scheduling schemes in which flood diversion areas are or are not used. The schemes are simulated based on 2.5‐m resolution reservoir topography and an optimized model of dynamic capacity flood regulation. The simulation results show the following. (a) In accord with the normal flood‐control regulation discharge, the maximum water level above the dam should be not more than 175 m, which ensures the safety of the dam and reservoir area. However, it is necessary to utilize the flood diversion areas within the Jingjiang area, and flood discharge can reach 2.81 billion m³. (b) In the case of relying on the TGR to impound floodwaters independently rather than using the flood diversion areas, the maximum water level above the dam reaches 177.35 m, which is less than the flood check level of 180.4 m to ensure the safety of the Three Gorges Dam. The average increase of the TGR water level in the Chongqing area is not more than 0.11 m, which indicates no significant effect on the upstream reservoir area. Comparing the various scheduling schemes, when the flood diversion areas are not used, it is believed that the TGR can execute safe flood control for a 1,000‐year flood, thereby greatly reducing flood damage.     

Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification,visual interpretation and machine learning approaches

We evaluate three approaches to mapping vegetation using images collected by an unmanned aerial vehicle (UAV) to monitor rehabilitation activities in the Five Islands Nature Reserve, Wollongong (Australia). Between April 2017 and July 2018, four aerial surveys of Big Island were undertaken to map changes to island vegetation following helicopter herbicide sprays to eradicate weeds, including the creeper Coastal Morning Glory (Ipomoea cairica) and Kikuyu Grass (Cenchrus clandestinus). The spraying was followed by a large scale planting campaign to introduce native plants, such as tussocks of Spiny-headed Mat-rush (Lomandra longifolia). Three approaches to mapping vegetation were evaluated, including: (i) a pixel-based image classification algorithm applied to the composite spectral wavebands of the images collected, (ii) manual digitisation of vegetation directly from images based on visual interpretation, and (iii) the application of a machine learning algorithm, LeNet, based on a deep learning convolutional neural network (CNN) for detecting planted Lomandra tussocks. The uncertainty of each approach was assessed via comparison against an independently collected field dataset. Each of the vegetation mapping approaches had a comparable accuracy; for a selected weed management and planting area, the overall accuracies were 82 %, 91 % and 85 % respectively for the pixel based image classification, the visual interpretation / digitisation and the CNN machine learning algorithm. At the scale of the whole island, statistically significant differences in the performance of the three approaches to mapping Lomandra plants were detected via ANOVA. The manual digitisation took a longer time to perform than others. The three approaches resulted in markedly different vegetation maps characterised by different digital data formats, which offered fundamentally different types of information on vegetation character. We draw attention to the need to consider how different digital map products will be used for vegetation management (e.g. monitoring the health individual species or a broader profile of the community). Where individual plants are to be monitored over time, a feature-based approach that represents plants as vector points is appropriate. The CNN approach emerged as a promising technique in this regard as it leveraged spatial information from the UAV images within the architecture of the learning framework by enforcing a local connectivity pattern between neurons of adjacent layers to incorporate the spatial relationships between features that comprised the shape of the Lomandra tussocks detected.     

基于分布式控制力矩陀螺的水下航行器轨迹跟踪控制

基于控制力矩陀螺群(CMGs)的水下航行器具有低速或零速机动的能力。采用基于分布式CMGs的水下航行器方案,并研究其水平面的轨迹跟踪控制问题。通过全局微分同胚变换将非完全对称的动力学模型解耦成标准欠驱动控制模型,并根据简化的模型构建其轨迹跟踪的误差动力学模型,将轨迹跟踪控制问题转化为误差模型镇定问题。基于一种分流神经元模型和反步法设计了系统的轨迹跟踪控制律,该控制器不需要对任何虚拟控制输入进行求导计算,且能确保跟踪误差的最终一致有界性。仿真结果表明该控制器能够实现在不依赖动力学参数先验知识的情况下对光滑轨迹的有效跟踪。     

国产高分辨率遥感影像农村公路核查方法及其应用

传统的农村公路核查需要人工实地抽查或通过GNSS设备进行信息采集验核，存在成本高、效率低等问题。遥感影像具有成像范围广、时效性高、成本低、能客观反映现实情况等优点。相比于传统方法，将遥感影像引入农村公路核查，能客观、准确、高效地对农村公路相关信息进行核查。本文基于国产高分辨率遥感影像，结合农村公路遥感核查业务，采用遥感影像道路提取算法，设计并实现了一种农村公路核查方法。将本方法应用于某中部省份农村公路遥感核查业务，实际应用表明该方法能有效提高现有农村公路遥感核查的工作效率。