无人机协同测控中SC-FDMA技术设计

针对无人机协同任务测控传输的多机接入问题,提出基于分布式任务分配模型的高动态SC-FDMA技术.通过将贪婪原则、信道动态分配机制和多用户接入技术结合,利用集中映射方式设计子信道数目可调的映射规则,配置各无人机节点所占用子载波数目.仿真结果表明,与传统FDMA、CDMA、TDMA、OFDMA等相比,基于SC-FDMA设计...     

一种可重复出水两栖无人飞行器多循环推进系统方案

针对一种可重复出水的两栖无人飞行器（UAV）总体方案及任务需求，提出一种水下采用泵喷水推进、出水采用液体火箭发动机推进、空中巡航采用涡扇发动机推进的多循环推进系统方案。根据推进系统技术发展现状、趋势，不同发动机循环特点、各阶段推力需求及多循环任务需求，开展了多循环方案设计方法研究，并计算出典型推进系统方案尺寸、质量、任务剖面燃油消耗质量等参数，验证了推进系统多循环方案及其设计方法的可行性，结果表明：综合未来飞行器及推进系统技术发展水平，所设计的多循环推进系统方案，能够实现无人飞行器可重复出水需求，其中能源需求占全机总质量的比例为26%左右。     

Energy-efficient data collection for UAV-assisted IoT: Joint trajectory and resource optimization

Internet of Things (IoT) can be conveniently deployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. As energy-efficient operations are critical to prolong the lifetime of the energy-constrained IoT devices, the Unmanned Aerial Vehicle (UAV) can be dispatched to geographically approach the IoT clusters towards energy-efficient IoT transmissions. This paper intends to maximize the system energy efficiency by considering both the IoT transmission energy and UAV propulsion energy, where the UAV trajectory and IoT communication resources are jointly optimized. By applying large-system analysis and Dinkelbach method, the original fractional optimization is approximated and reformulated in the form of subtraction, and further a block coordinate descent framework is employed to update the UAV trajectory and IoT communication resources iteratively. Extensive simulation results are provided to corroborate the effectiveness of the proposed method.     

Contributions to data transmission at critical moments on unmanned aerial vehicles

As for unmanned aircraft, the knowledge of the aircraft performance is directly related with the navigation, guidance, and control system programming. Therefore, the measured data in each phase of the flight must be sufficiently precise to obtain a good characterization of aircraft. This article proposes new methods of sending information to ground, which make it possible to know the aircraft behavior accurately, and for this purpose, four contributions have been made for ALO (Avión Ligero de Observación, Spanish acronym for Light Observation Aircraft). Currently, the characterization is based on data obtained at ten samples per second, insufficient to acquire detailed knowledge of what happened during the whole flight of an aircraft. As a result of these contributions, many more samples per second of accelerations and angular velocities are obtained at the most critical moments of the flight, such as takeoff or landing. Among the improvements included are data compression techniques, providing references to locate the measured data in time and identifying labels of each parameter.     

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.     

非死锁合同网协议驱动的多机分布式时序任务分配

针对多无人机协同任务分配的时序约束问题，提出了基于非死锁合同网协议(DF CNP)的分布式时序任务分配方法，从理论上避免任务死锁，提升分配结果最优性。定义了局部信息条件下时序任务死锁判据，通过检测时序任务图环路状态与顶点可达性，判定分配方案的全局死锁状态，保证分配结果的可行性。定制了最近邻-深度优先混合搜索算法，在合同网排序过程中优先选择最近邻任务，并结合死锁判据递归回溯，在分布式架构下并行生成满足死锁约束的任务排序方案，提升分配结果的最优性。仿真对比结果表明：相比于非死锁遗传算法(TB GA)，DF CNP在求解效率方面具有显著优势；与耦合约束一致性束算法(CBBA TCC)相比，DF CNP结果最优性明显提升。     

一种超视距组网无人机载通信系统设计

针对超视距集群作业需求，提出将Ka频段高通量卫星技术与TD-LTE协议区域组网技术相结合，构建一种“1+N”架构的无人机载测控通信系统。通过方案介绍，阐述了卫星、组网、载荷等模块的设计思路、方案选型及实物设计结果，明确核心单元特点。详细论述了异构网络通信、平滑低延时传输、信源加密等关键技术，并完成链路余量计算、带宽时延测试及飞行试验。试验结果表明：系统任意终端间双向通信稳定可靠，方案设计合理可行。相比于卫星、组网单模通信方式，系统在长航距集群测控、任务协同、临场机动及应用资费等方面具有明显优势，为后续构建空天一体化多平台支撑通信系统，提供工程实践参考。