航天器v_(∞)转移轨道的模型和解析法

假定A和B是围绕一个引力中心按照开普勒轨道运行的卫星,针对航天器从A出发转移至B的轨道确定问题,文章提出了一个新的模型,称为v∞转移轨道(v∞-transfer-orbit,VTO).VTO选取航天器飞离A的时刻t0和逃逸速度大小v∞作为设计参数,求解抵达B的开普勒轨道.根据A和B运行轨道的空间位置关系,VTO分为A/B异面、A/B共面和A/B重合3种情况,同时存在3类解:General-VTO、Backflip-VTO和Resonant-VTO.文章建立了统一的VTO解析方法,即将航天器抵达B的位置约束分解为轨道约束和时间约束,根据轨道约束推导航天器轨道关于单个变量的解析式,根据时间约束建立该变量的一元方程,从而将原问题转化为一元方程寻根问题.首先,依次针对A/B异面、A/B共面和A/B重合情况构建了General-VTO的一元寻根方程,详细介绍了一元方程的寻根区间,并给出了一种基于三次样条插值的快速寻根算法;然后,构建了Backflip-VTO的一元寻根方程,在分析一元方程函数单调性、极值点和拐点的基础上给出了一元方程寻根区间和寻根方法;之后,构建了Resonant-VTO的直接解析式.最后,给出算例并重点说明VTO多解性.

Distributed Multicircular Circumnavigation Control for UAVs with Desired Angular Spacing

This paper addresses a multicircular circumnavigation control for UAVs with desired angular spacing around a nonstationary target.By defining a coordinated error relative to neighboring angular spacing,under the premise that target information is perfectly accessible by all nodes,a centralized circular enclosing control strategy is derived for multiple UAVs connected by an undirected graph to allow for formation behaviors concerning the moving target.Besides,to avoid the requirement of target’s states being accessible for each UAV,fixed-time distributed observers are introduced to acquire the state estimates in a fixed-time sense,and the upper boundary of settling time can be determined offline irrespective of initial properties,greatly releasing the burdensome communication traffic.Then,with the aid of fixed-time distributed observers,a distributed circular circumnavigation controller is derived to force all UAVs to collaboratively evolve along the preset circles while keeping a desired angular spacing.It is inferred from Lyapunov stability that all errors are demonstrated to be convergent.Simulations are offered to verify the utility of proposed protocol.

Construction Method of Civil Aircraft Airborne⁃system Supplier Development Process System

Based on the analysis of the development process system status of domestic and foreign civil aircraft airborne system suppliers,this paper proposes the overall construction idea of"a set of civil aircraft process system"based on IPD(Integrated product development)in the organization.The development stage,process,activity and task are the logical framework elements of the system construction."Based on process decomposition,vertical stratification,horizontal segmentation,combination of special and common,process customized to tools,role and process integration,giving full consideration to the interface between supplier management and process modules"etc.are the concrete ideas.Moreover,formulate top⁃level system construction standards,implemented by process system management tool platform,so that the process system and development work can be effectively integrated to effectively guide the development work of airborne system suppliers,and meet the quality and airworthiness requirements of civil aircraft development.Through the development application of a certain type of flight control system,the process system and tool platform were verified and optimized in practice.

各向异性Kelvin泡沫胞元高径比对其流动传热特性的影响

飞行器热管理系统中所用的高孔隙率泡沫材料具有质量轻、比表面积大等优点,孔隙尺度几何参数的优化设计对有效提升综合传热性能、降低结构质量至关重要。以各向异性Kelvin泡沫胞元为研究对象,采用混合热格子Boltzmann方法以及多GPU加速技术,实现了同时考虑泡沫骨架导热和多胞元孔隙尺度强迫对流换热的共轭传热数值模拟。在上述基础上,分别选取了Re=10、100、1000计算条件,开展了不同胞元高径比(H/D=0.5、0.75、1.0、1.5、2.0)对其流动传热特性的影响规律研究。结果表明,在不同Re条件下,随着各向异性Kelvin泡沫H/D的减小,其泡沫内部的流动阻力及努塞尔数均增大,且随着Re的增大,对流换热的作用增强,H/D的影响也更为明显。此外,相比于流动阻力,结构传热性能受H/D的影响变化速率更大,由此造成综合传热因子(j/f^(1/3))与H/D成反比关系,即减小Kelvin胞元H/D可有效提高泡沫结构的综合传热性能。

Energy-efficient joint UAV secure communication and 3D trajectory optimization assisted by reconfigurable intelligent surfaces in the presence of eavesdroppers

We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.

基于多模型级联的VSV调节机构装配智能检错方法

在航空发动机可调静子叶片(Variable stator vane,VSV)调节机构的装配过程中,目前仍需要人工检测其连杆防松钢丝的装配正确性,效率低且易出错。为替代人工检错,提出了一种基于多模型级联的智能检错方法。该方法是多个卷积神经网络级联的模型集成,其中包含检测模块、分类模块以及后处理比对检错3个部分。首先在检测模块上提出混合不同尺寸卷积核的深度可分离卷积与轻量化解耦头来对YOLOv5s进行改进,改进的YOLOv5s在测试集上的平均精度达到97.9%,相较于YOLOv5s、YOLOv8s分别提升了3.4%、1.5%。其次在分类模块上使用7×7深度卷积替代全局平均池化以改进ConvNeXt分类头,改进后性能得到提升,在连杆数据集和螺纹数据集上的准确率分别达到97.5%和95.4%。最后在后处理模块对两个分类模型的结果进行匹配,得出装配检测结果。利用现场装配车间采集的图片数据集对该智能检错方法进行验证,结果显示该方法平均精度达到92.7%,进一步验证了智能装配检错方法的可靠性。

UAV-Assisted Dynamic Avatar Task Migration for Vehicular Metaverse Services: A Multi-Agent Deep Reinforcement Learning Approach

Avatars, as promising digital representations and service assistants of users in Metaverses, can enable drivers and passengers to immerse themselves in 3D virtual services and spaces of UAV-assisted vehicular Metaverses. However, avatar tasks include a multitude of human-to-avatar and avatar-to-avatar interactive applications, e.g., augmented reality navigation,which consumes intensive computing resources. It is inefficient and impractical for vehicles to process avatar tasks locally. Fortunately, migrating avatar tasks to the nearest roadside units(RSU)or unmanned aerial vehicles(UAV) for execution is a promising solution to decrease computation overhead and reduce task processing latency, while the high mobility of vehicles brings challenges for vehicles to independently perform avatar migration decisions depending on current and future vehicle status. To address these challenges, in this paper, we propose a novel avatar task migration system based on multi-agent deep reinforcement learning(MADRL) to execute immersive vehicular avatar tasks dynamically. Specifically, we first formulate the problem of avatar task migration from vehicles to RSUs/UAVs as a partially observable Markov decision process that can be solved by MADRL algorithms. We then design the multi-agent proximal policy optimization(MAPPO) approach as the MADRL algorithm for the avatar task migration problem. To overcome slow convergence resulting from the curse of dimensionality and non-stationary issues caused by shared parameters in MAPPO, we further propose a transformer-based MAPPO approach via sequential decision-making models for the efficient representation of relationships among agents. Finally, to motivate terrestrial or non-terrestrial edge servers(e.g., RSUs or UAVs) to share computation resources and ensure traceability of the sharing records, we apply smart contracts and blockchain technologies to achieve secure sharing management. Numerical results demonstrate that the proposed approach outperforms the MAPPO approach by around 2% and effectively reduces approximately 20% of the latency of avatar task execution in UAV-assisted vehicular Metaverses.

Introduction and Prospects of Gravity-1 Launch Vehicle’s Sea-Based Three Verticals Testing and Launch Mode

Gravity-1 was the world's first carrier rocket to adopt the sea-based “three vertical” testing launch mode. This article introduces the overall layout of the launch site and the workflow of rocket testing and launch for its maiden flight mission. The process of vertical assembly, vertical testing, vertical transportation, and sea-based hot launches are explained. Additionally, it provides an outlook on the improved “three vertical” testing and launch mode for future missions, such as land-based launches, rapid launches, and remote sea launches.

基于调和线性化Navier-Stokes方程的局部感受性

高超声速边界层中Mack模态的感受性决定了触发转捩的扰动的初始幅值,因而考虑感受性是构建合理的转捩预测方法的前提。壁面粗糙元与来流声波作用从而激发Mack模态是典型的局部感受性过程,对该过程的描述方法大致包括大雷诺数渐近理论、有限雷诺数理论和直接数值模拟。由于需要做小粗糙元线性假设,所以前两种方法无法有效预测有限高度粗糙元工况,而第三种方法则由于计算量庞大而无法进行参数化研究。本文发展了一套基于调和线性化Navier-Stokes方程的局部感受性高效算法,并针对马赫数5.92的高超声速平板边界层系统地研究了小尺度及有限高度粗糙元与声波引起的Mack模态感受性。结果表明,快声波诱导Mack模态的局部感受性显著强于慢声波。对于有限高度粗糙元,快声波的局部感受性在较大声波参数范围内随粗糙元高度增加而超线性增强。

Robust fixed-time flight controller for a dual-system convertible UAV in the cruise mode

This paper investigates the attitude tracking control problem for the cruise mode of a dual-system convertible unmanned aerial vehicle(UAV)in the presence of parameter uncertainties,unmodeled uncertainties and wind disturbances.First,a fixed-time disturbance observer(FXDO)based on the bi-limit homogeneity theory is designed to estimate the lumped disturbance of the convertible UAV model.Then,a fixed-time integral sliding mode control(FXISMC)is combined with the FXDO to achieve strong robustness and chattering reduction.Bi-limit homogeneity theory and Lyapunov theory are applied to provide detailed proof of the fixed-time stability.Finally,numerical simulation experimental results verify the robustness of the proposed algorithm to model parameter uncertainties and wind disturbances.In addition,the proposed algorithm is deployed in a open-source UAV autopilot and its effectiveness is further demonstrated by hardware-in-the-loop experimental results.

Multi-UAVs Collaborative Path Planning in the Cramped Environment

Due to its flexibility and complementarity, the multiUAVs system is well adapted to complex and cramped workspaces, with great application potential in the search and rescue(SAR) and indoor goods delivery fields. However, safe and effective path planning of multiple unmanned aerial vehicles(UAVs)in the cramped environment is always challenging: conflicts with each other are frequent because of high-density flight paths, collision probability increases because of space constraints, and the search space increases significantly, including time scale, 3D scale and model scale. Thus, this paper proposes a hierarchical collaborative planning framework with a conflict avoidance module at the high level and a path generation module at the low level. The enhanced conflict-base search(ECBS) in our framework is improved to handle the conflicts in the global path planning and avoid the occurrence of local deadlock. And both the collision and kinematic models of UAVs are considered to improve path smoothness and flight safety. Moreover, we specifically designed and published the cramped environment test set containing various unique obstacles to evaluating our framework performance thoroughly. Experiments are carried out relying on Rviz, with multiple flight missions: random, opposite, and staggered, which showed that the proposed method can generate smooth cooperative paths without conflict for at least 60 UAVs in a few minutes.The benchmark and source code are released in https://github.com/inin-xingtian/multi-UAVs-path-planner.

RMPC-Based Visual Servoing for Trajectory Tracking of Quadrotor UAVs With Visibility Constraints

Dear Editor,This letter deals with the tracking problem of quadrotors subject to external disturbances and visibility constraints by designing a robust model predictive control(RMPC) scheme. According to the imagebased visual servoing(IBVS) method, a virtual camera is constructed to express image moments of the tracking target.

Sivells方法在高马赫数低总压喷管设计中的适用性分析

目前高超声速轴对称型面喷管广泛采用Sivells方法进行无黏型面设计,通过求解轴对称的von Kármán动量方程进行边界层修正。该方法在常规高超声速风洞、激波风洞等的高马赫数、高总压条件下已成功应用,但鲜有在高马赫数、低总压条件下的应用研究。在低总压条件下,采用该方法设计了马赫数6、8、10、12的轴对称型面喷管,通过数值模拟分析流场结构,并进行试验验证;模拟了喷管射流流场,通过对射流流场进行结构分析,判断设计方法的适用性。研究结果表明:马赫数6、8喷管流场与设计基本一致,射流流场品质较好,适合开展风洞试验;马赫数10、12喷管流场局部过度膨胀,马赫数高于设计值,其中马赫数10喷管的射流流场品质较好,马赫数12喷管的射流流场品质下降显著且马赫数轴向梯度增大。因此,在高马赫数、低总压条件下,Sivells设计方法仍适用于马赫数6、8喷管,马赫数10喷管处于临界状态,而不适用于马赫数12喷管。

基于YOLOv7通道冗余改进的飞机蒙皮损伤检测

为提高蒙皮损伤检测的自动化程度,提出一种基于改进YOLOv7通道冗余的机器视觉检测方法。首先针对飞机蒙皮损伤数据集背景单一的特点,提出增强型颈部特征融合改进算法,提高了飞机蒙皮损伤的识别精度和检测速度;其次针对主干特征提取网络的卷积通道冗余的问题,引入部分卷积PConv(Partial convolution),提出主干特征提取网络轻量化,减少模型的参数量,同时提高损伤的识别效率。试验部分首先在飞机蒙皮损伤数据集上探索了不同增强型颈部特征融合改进算法,确定了最优的改进方案;接着在飞机蒙皮损伤数据集上做消融和对比试验,改进算法与原YOLOv7算法比较,mAP(Mean average precision)提升了2.3%,FPS(Frames per second)提升了22.1 f/s,模型参数量降低了34.13%;最后将改进的YOLOv7模型与主流目标检测模型对比,证明了改进算法的先进性。

Modeling and Performance Analysis of UAV-Aided Millimeter Wave Cellular Networks with Stochastic Geometry

UAV-aided cellular networks,millimeter wave(mm-wave) communications and multi-antenna techniques are viewed as promising components of the solution for beyond-5G(B5G) and even 6G communications.By leveraging the power of stochastic geometry,this paper aims at providing an effective framework for modeling and analyzing a UAV-aided heterogeneous cellular network,where the terrestrial base stations(TBSs) and the UAV base stations(UBSs) coexist,and the UBSs are provided with mm-wave and multi-antenna techniques.By modeling the TBSs as a PPP and the UBSs as a Matern hard-core point process of type Ⅱ(MPH-Ⅱ),approximated but accurate analytical results for the average rate of the typical user of both tiers are derived through an approximation method based on the mean interference-to-signal ratio(MISR) gain.The influence of some relevant parameters is discussed in detail,and some insights into the network deployment and optimization are revealed.Numerical results show that some trade-offs are worthy of being considered,such as the antenna array size,the altitude of the UAVs and the power control factor of the UBSs.

A Survey on Sensor-and Communication-Based Issues of Autonomous UAVs

The application field for Unmanned Aerial Vehicle (UAV) technology and its adoption rate have been increasingsteadily in the past years. Decreasing cost of commercial drones has enabled their use at a scale broader thanever before. However, increasing the complexity of UAVs and decreasing the cost, both contribute to a lack ofimplemented securitymeasures and raise new security and safety concerns. For instance, the issue of implausible ortampered UAV sensor measurements is barely addressed in the current research literature and thus, requires moreattention from the research community. The goal of this survey is to extensively review state-of-the-art literatureregarding common sensor- and communication-based vulnerabilities, existing threats, and active or passive cyberattacksagainst UAVs, as well as shed light on the research gaps in the literature. In this work, we describe theUnmanned Aerial System (UAS) architecture to point out the origination sources for security and safety issues.Weevaluate the coverage and completeness of each related research work in a comprehensive comparison table as wellas classify the threats, vulnerabilities and cyber-attacks into sensor-based and communication-based categories.Additionally, for each individual cyber-attack, we describe existing countermeasures or detectionmechanisms andprovide a list of requirements to ensureUAV’s security and safety.We also address the problem of implausible sensormeasurements and introduce the idea of a plausibility check for sensor data. By doing so, we discover additionalmeasures to improve security and safety and report on a research niche that is not well represented in the currentresearch literature.

Multi-UAV cooperative maneuver decision-making for pursuitevasion using improved MADRL

Aiming at the problem of multi-UAV pursuit-evasion confrontation, a UAV cooperative maneuver method based on an improved multi-agent deep reinforcement learning(MADRL) is proposed. In this method, an improved Comm Net network based on a communication mechanism is introduced into a deep reinforcement learning algorithm to solve the multi-agent problem. A layer of gated recurrent unit(GRU) is added to the actor-network structure to remember historical environmental states. Subsequently,another GRU is designed as a communication channel in the Comm Net core network layer to refine communication information between UAVs. Finally, the simulation results of the algorithm in two sets of scenarios are given, and the results show that the method has good effectiveness and applicability.

UAV maneuvering decision-making algorithm based on deep reinforcement learning under the guidance of expert experience

Autonomous umanned aerial vehicle(UAV) manipulation is necessary for the defense department to execute tactical missions given by commanders in the future unmanned battlefield. A large amount of research has been devoted to improving the autonomous decision-making ability of UAV in an interactive environment, where finding the optimal maneuvering decisionmaking policy became one of the key issues for enabling the intelligence of UAV. In this paper, we propose a maneuvering decision-making algorithm for autonomous air-delivery based on deep reinforcement learning under the guidance of expert experience. Specifically, we refine the guidance towards area and guidance towards specific point tasks for the air-delivery process based on the traditional air-to-surface fire control methods.Moreover, we construct the UAV maneuvering decision-making model based on Markov decision processes(MDPs). Specifically, we present a reward shaping method for the guidance towards area and guidance towards specific point tasks using potential-based function and expert-guided advice. The proposed algorithm could accelerate the convergence of the maneuvering decision-making policy and increase the stability of the policy in terms of the output during the later stage of training process. The effectiveness of the proposed maneuvering decision-making policy is illustrated by the curves of training parameters and extensive experimental results for testing the trained policy.

Recent Progress of Earth Observation Satellites in China

Currently,China has 32 Earth observation satellites in orbit.The satellites can provide various data such as optical,multispectral,infrared,and radar.The spatial resolution of China Earth observation satellites ranges from low to medium to high.The satellites possess the capability to observe across multiple spectral bands,under all weather conditions,and at all times.The data of China Earth observation satellites has been widely used in fields such as natural resource detection,environmental monitoring and protection,disaster prevention and reduction,urban planning and mapping,agricultural and forestry surveys,land survey and geological prospecting,and ocean forecasting,achieving huge social benefits.This article introduces the recent progress of Earth observation satellites in China since 2022,especially the satellite operation,data archiving,data distribution and data coverage.

Covert LEO Satellite Communication Aided by Generative Adversarial Network Based Cooperative UAV Jamming

In this paper,we study the covert performance of the downlink low earth orbit(LEO)satellite communication,where the unmanned aerial vehicle(UAV)is employed as a cooperative jammer.To maximize the covert rate of the LEO satellite transmission,a multi-objective problem is formulated to jointly optimize the UAV’s jamming power and trajectory.For practical consideration,we assume that the UAV can only have partial environmental information,and can’t know the detection threshold and exact location of the eavesdropper on the ground.To solve the multiobjective problem,we propose the data-driven generative adversarial network(DD-GAN)based method to optimize the power and trajectory of the UAV,in which the sample data is collected by using genetic algorithm(GA).Simulation results show that the jamming solution of UAV generated by DD-GAN can achieve an effective trade-off between covert rate and probability of detection errors when only limited prior information is obtained.