多涵道无人机设计及悬停性能数值仿真

针对无人机空中自主对接和组合飞行任务需求设计了6涵道螺旋桨无人机气动构型。运用数值模拟对该型无人机进行悬停工况气动特性研究，研究不同悬停转速下整机气动性能的变化，并在涵道环括工况下对螺旋桨进行气动优化。研究结果表明：螺旋桨是悬停升力的主要来源，随着转速变化，涵道升力始终占总升力的17%左右；阻力来自机体上表面和电机支架的迎风阻力，支架的阻力达到涵道螺旋桨总升力的10%；随着桨盘载荷提升，无人机功率载荷降低；涵道的存在影响了螺旋桨的滑流特性，造成桨盘平面轴向速度增加，截面翼型迎角变小，工作效率降低，经过合理调整其扭转角分布螺旋桨效率得到提升，拉力提高3.3%，效率提高2.9%。     

Target localization based on cross-view matching between UAV and satellite

Matching remote sensing images taken by an unmanned aerial vehicle (UAV) with satellite remote sensing images with geolocation information. Thus, the specific geographic location of the target object captured by the UAV is determined. Its main challenge is the considerable differences in the visual content of remote sensing images acquired by satellites and UAVs, such as dramatic changes in viewpoint, unknown orientations, etc. Much of the previous work has focused on image matching of homologous data. To overcome the difficulties caused by the difference between these two data modes and maintain robustness in visual positioning, a quality-aware template matching method based on scale-adaptive deep convolutional features is proposed by deeply mining their common features. The template size feature map and the reference image feature map are first obtained. The two feature maps obtained are used to measure the similarity. Finally, a heat map representing the probability of matching is generated to determine the best match in the reference image. The method is applied to the latest UAV-based geolocation dataset (University-1652 dataset) and the real-scene campus data we collected with UAVs. The experimental results demonstrate the effectiveness and superiority of the method.     

Green UAV communications for 6G: A survey

Unmanned Aerial Vehicles (UAVs) have received a wide range of attention for military and commercial applications. Enhanced with communication capability, UAVs are considered to play important roles in the Sixth Generation (6G) networks due to their low cost and flexible deployment. 6G is supposed to be an all-coverage network to provide ubiquitous connections for space, air, ground and underwater. UAVs are able to provide air-borne wireless coverage flexibly, serving as aerial base stations for ground users, as relays to connect isolated nodes, or as mobile users in cellular networks. However, the onboard energy of small UAVs is extremely limited. Thus, UAVs can be only deployed to establish wireless links temporarily. Prolonging the lifetime and developing green UAV communication with low power consumption becomes a critical challenge. In this article, a comprehensive survey on green UAV communications for 6G is carried out. Specifically, the typical UAVs and their energy consumption models are introduced. Then, the typical trends of green UAV communications are provided. In addition, the typical applications of UAVs and their green designs are discussed. Finally, several promising techniques and open research issues are also pointed out.     

无人机群体视角下的轨迹预测CSCD

利用无人机对观测目标的运动轨迹进行预测是当前无人系统领域的关键任务之一。目前的目标轨迹预测研究通常基于单一无人机所采集的轨迹数据,但由于场景中障碍物以及视角倾斜等因素的影响,单无人机不易稳定监测目标具体位置,容易导致目标丢失。而且,现有利用无人机的目标轨迹预测一般基于鸟瞰视角,没有发挥出无人机的灵活性。随着无人机集群协同技术的发展,无人机群体视角为目标全方位监测提供了新的思路,在解决目标丢失和目标遮挡问题中具有明显的优势。同时,基于多无人机的位姿估计可以估计出目标的准确三维坐标,为无人机的灵活视角观测提供基础。因此,从轨迹预测的相关工作出发,探讨无人机群体视角下轨迹预测中面临的挑战和解决思路,以期对未来的轨迹预测研究以及集群协同技术发展提供一定帮助。     

Design,modeling, and control of morphing aircraft:A review

A morphing aircraft can adapt its configuration to suit different types of tasks, which is also an important requirement of Unmanned Aerial Vehicles(UAV). The successful development of an unmanned morphing aircraft involves three steps that determine its ability and intelligent: configuration design, dynamic modeling and flight control. This study conducts a comprehensive survey of morphing aircraft. First, the methods to design the configuration of a morphing aircraft are presented and analyzed...     

无人机地面控制站 应急电源逆变控制系统设计

为了给地面控制站提供安全可靠的应急电源,文章主要根据由DSP数字技术+脉宽调制SPWM驱动+IGBT+隔离滤波为一体化设计发展起来的一个新型UPS电源系统,并对逆变控制系统进行了硬件和软件设计。通过对控制系统的仿真验证,得出所需的稳定的三相交流电,说明该电源逆变控制系统可以为无人机地面控制站提供安全可靠的应急电源。     

基于注意力机制和特征匹配的空对地多目标检测与跟踪算法

多目标跟踪算法是实现无人机自主导航的关键技术，为解决现有方法存在的小目标检测能力弱、计算能耗大、鲁棒性差等问题，提出一种基于注意力机制和特征匹配的多目标空对地跟踪算法，以实现航拍视角下对目标的精准高效跟踪。首先，引入通道可分离卷积，实现目标检测模型的轻量化；其次，构造融合空间注意力机制的小目标检测分支，提高对小微目标的检测精度，最后，优化目标跟踪算法的外观重识别网络，提高多目标跟踪效率。使用Visdrone2019-MOT数据集对所提算法进行验证，实验结果表明，所提算法的MOTA值提高了0.６%，FPS值为21.31帧/s，在模型大小和跟踪精度上实现了较好的平衡。     

无人集群组网系统相对定位技术研究

针对大规模无人集群在卫星导航拒止环境下的相对定位需求，研究一种基于无人集群自组网数据链测距的相对定位技术，通过集群组网测距信息构建广义距离平方阵，经过双中心处理化和特征值分解后即得到相对定位结果，最后通过仿真评估了该方法在不同测距误差和不同集群规模下的定位精度。结果表明：测距误差是影响定位性能的最主要误差来源，当节点数大于30时定位误差受节点个数影响较小。     

Prediction of electric-powered fixed-wing UAV endurance

To overcome the problems encountered in predicting the endurance of electricpowered fixed-wing unmanned aerial vehicles (UAVs),which were stemmed from the dynamic changes in electric power system efficiency and battery discharge characteristics under different operating conditions,the required battery power model and battery discharge model were studied.The required battery power model was determined using an approximate model of electric power system efficiency based on wind tunnel testing and the self-adaptive penalty function.Furthermore,current correction and ambient temperature correction terms were proposed for the trained Kriging model representing the discharge characteristics under standard operation,and then the discharged capacity-terminal voltage model was established.Through numerical integration of this model with the required battery power model,the electric-powered fixed-wing UAV endurance prediction model was obtained.Laboratory tests indicated that the proposed endurance model could precisely calculate the battery discharge time and accurately describe the battery discharge process.The similarity of the theoretical and flight test results reflected the accuracy of the proposed endurance model as well as the importance of considering dynamic changes in power system efficiency in endurance calculations.The proposed endurance model meeting precision requirements can be used in practical engineering applications.     

基于自抗扰的无人机俯仰姿态控制

针对无人机俯仰姿态控制回路在模型参数和复杂外界环境等不确定性干扰影响下鲁棒性差、系统响应速度慢的问题,采用工程上易实现的自抗扰控制(ADRC)方法设计了俯仰姿态控制器,通过构造线性扩张状态观测器(LESO)估计不确定性干扰,并在控制回路中对干扰进行实时补偿.性能分析与仿真结果表明,基于ADRC的无人机俯仰姿态控制器具有良好的性能和干扰抑制能力,并且能够实现对控制指令的精确跟踪.