Mission-driven autonomous perception and fusion based on UAV swarm

Distributed autonomous situational awareness is one of the most important foundation for Unmanned Aerial Vehicle (UAV) swarm to implement various missions. Considering the application environment being usually characterized by strong confrontation, high dynamics, and deep uncertainty, the distributed situational awareness system based on UAV swarm needs to be driven by the mission requirements, while each node in the network can autonomously avoid collisions and perform detection mission through limited resource sharing as well as complementarity of respective advantages. By efficiently solving the problems of self-avoidance, autonomous flocking and splitting, joint estimation and control, etc., perception data from multi-platform multi-source should be extracted and fused reasonably, to generate refined, tailored target information and provide reliable support for decision-making.     

基于博弈论模型的多机协同对抗多目标任务决策方法

根据多机协同对抗多目标的空战特征,以敌我双方可能的相互攻击组合方式作为策略集,由敌我双方对抗态势分析定量结果确定支付函数,建立完全信息静态博弈模型.通过求解博弈模型的混合策略纳什均衡解,并结合一定作战经验,形成任务决策方法.以无人作战飞机编队对抗敌地对空防御系统为例,对本文所研究的任务决策方法进行了验算.     

Unmanned aerial vehicle swarm mission reliability modeling and evaluation method oriented to systematic and networked mission

With the development of Unmanned Aerial Vehicle (UAV) system autonomy, network communication technology and group intelligence theory, mission execution in the form of a UAV swarm will be an important realization of future applications. Traditional single-UAV mission reliability modeling methods have been unable to meet the requirements of UAV swarm mission reliability modeling. Therefore, the UAV swarm mission reliability modeling and evaluation method is proposed. First, aimed at the interdependence among the multiple layers, a multi-layer network model of a UAV swarm is established. At the same time, based on the system having the following characteristics—using a mission chain to complete the mission and applying the connectivity of the mission network—the mission network model of a UAV swarm is established. Second, vulnerability and connectivity are selected as two indicators to reflect the reliability of the mission, and aimed at random attack and deliberate attack, vulnerability and connectivity evaluation methods are proposed. Finally, the validity and accuracy of the constructed model are verified through simulations, and the model and selected indicators can meet the reliability requirements of the UAV swarm mission. In this way, this study provides quantitative reference for UAV-swarm-related decision-making work and supports the development of UAV-swarm-related work.     

A novel compilation method of comprehensive mission spectrum of aero-engine maneuvering load based on use-related mission segment

Comprehensive Mission Spectrum (CMS) of an aero-engine can reflect the usage characteristics of the engine. It can provide load input for engine life prediction and accelerated mission test. In this paper, a novel compilation method of CMS of aero-engine maneuvering load based on mission segment is proposed. Firstly, the use-related Typical Mission Segment (TMS) of maneuvering load is divided and identified according to spectral characteristics. Secondly, the mathematical model of different kinds of TMS are established based on stochastic process theory. Finally, the CMS of maneuvering load is compiled based on TMS. The proposed method can accurately quantify the compilation of CMS. The compiled CMS shows good agreement with the original load spectrum. According to damage consistency inspection, the compiled CMS is consistent with the damage caused by the original load spectrum in terms of low cycle fatigue.     

任意结构系统的备件可用度评估模型

备件可用度评估是维修保障能力评估的重要内容。给出了部件失效服从指数分布的任意结构系统的备件可用度评估模型,该模型可以在已知系统结构函数、系统初始状态以及工作时间的条件下,计算不同备件方案的备件可用度,为维修保障指挥提供决策依据。     

基于多目标优化的运输机任务设备配置研究

为得到合理的任务设备配置比例,对运输机任务设备配置进行优化。军用运输机可执行多种任务类型,需要配置不同的任务设备以实现货舱构型的转换。任务设备的配置比例应兼顾任务成功率、经济性和利用率等多目标要求。为此,以小规模运输机队为研究对象,给出了任务设备配置目标优化原则和边界条件,建立了配置模型,运用线性加权和法进行求解,并进行了模型灵敏度分析和偏差分析,得出了各任务设备的最佳配置比例,可解决小规模运输机队的任务设备配置问题。实例证明了配置结果的有效性。     

Reliable flight performance assessment of multirotor based on interacting multiple model particle filter and health degree

Multirotor has been applied to many military and civilian mission scenarios. From the perspective of reliability, it is difficult to ensure that multirotors do not generate hardware and software failures or performance anomalies during the flight process. These failures and anomalies may result in mission interruptions, crashes, and even threats to the lives and property of human beings. Thus, the study of flight reliability problems of multirotors is conductive to the development of the drone industry and has theoretical significance and engineering value. This paper proposes a reliable flight performance assessment method of multirotors based on an Interacting Multiple Model Particle Filter (IMMPF) algorithm and health degree as the performance indicator. First, the multirotor is modeled by the Stochastic Hybrid System (SHS) model, and the problem of reliable flight performance assessment is formulated. In order to solve the problem, the IMMPF algorithm is presented to estimate the real-time probability distribution of hybrid state of the established SHS-based multirotor model, since it can decrease estimation errors compared with the standard interacting multiple model algorithm based on extended Kalman filter. Then, the reliable flight performance is assessed with health degree based on the estimation result. Finally, a case study of a multirotor suffering from sensor anomalies is presented to validate the effectiveness of the proposed method.     

Optimal planning for a multi-debris active removal mission with a partial debris capture strategy

In this paper, a new mission model, called a multi-debris active removal mission with partial debris capture strategy, is proposed. The model assumes that a platform only captures part of the scheduled debris at a time and then releases these debris pieces to a disposal orbit. This process is then repeated until all of the scheduled debris is removed. A genetic algorithm with a multiparameter concatenated coding method is designed to optimize the plan of a multi-debris active removal mission wit...     

Decision-making of Aircraft Optimum Configuration Utilizing Multidimensional Game Theory

As multi-discipline coupling and components interference often affect the aircraft configuration decision-making and analysis during conceptual design process, this article presents an approach of multidimensional game theory based on aircraft components to deal with this problem. The idea is that the configuration decision-making process is regarded as the game for different disciplines and technologies, and the aircraft components are players. The payoff function with highest total gain means that according to the game protocols and multidimensional theory, the optimal aircraft configuration within the strategy set will be chosen. The decision-making model is applied to conceptual design process of the high altitude long endurance (HALE) unmanned aerial vehicle (UAV) based on the assessment of technological risk. The obtained optimum configuration is quite consistent with the current HALE UAV development trends. Thus, taking into account the coupling and interference factors, the multidimensional gaming model based on aircraft components will be an effective analysis method in the decision-making process of aircraft optimum configuration.     

日凌的计算及其对神六任务的影响分析

从信道链路上分析了日凌对卫星通信的影响,给出了日凌计算的几何模型与计算方法,并用该方法计算了神舟六号发射前后的日凌情况,分析了日凌对神舟六号发射的影响。该计算方法比较准确,并在实际观测中得到了验证。     

Optimization of fixed aviation support resource station configuration for aircraft carrier based on aircraft dispatch mission scheduling

Before the dispatch of the carrier-based aircraft, a series of pre-flight preparation operations need to be completed on the flight deck. Flight deck fixed aviation support resource station configuration has an important impact on operation efficiency and sortie rate. However, the resource station configuration is determined during the aircraft carrier design phase and is rarely modified as required, which may not be suitable for some pre-flight preparation missions. In order to solve the above defects, the joint optimization of flight deck resource station configuration and aircraft carrier pre-flight preparation scheduling is studied in this paper, which is formulated as a two-tier optimization decision-making framework. An improved variable neighborhood search algorithm with four original neighborhood structures is presented. Dispatch mission experiment and algorithm performance comparison experiment are carried out in the computational experiment section. The correlation between the pre-flight preparation time (makespan) and flight deck cabin occupancy percentage is given, and advantages of the proposed algorithm in solving the mathematical model are verified.     

航空发动机健康评估变精度粗糙集决策方法

针对航空发动机健康评估过程中存在的多工况、非线性和小子样问题,提出了一种基于相似性度量的发动机健康评估的变精度粗集决策方法.首先给出了变精度粗糙集中正确分类率的确定原则和方法,提取了决策规则;其次,提出了基于交叉信息熵的属性相对重要度计算方法,并给出了属性的客观权重,结合专家经验和运行工况形成了属性的综合权重;最后,提出了基于属性综合权重的加权相似性度量方法,通过比较当前对象与约简后的决策系统中所有对象的相似程度,给出决策结果,完成对发动机的健康评估.实例表明,在结合专家经验和运行环境对评估结果进行修正后,该方法对发动机的健康评估更贴近实际,方法具有一定的普适性.      

基于OBDD的可修航天测控系统任务可靠性分析

基于顺序二元决策图(OBDD)理论,针对航天测控系统(TT&C系统)特点定义了新的OBDD数据结构,提出了一种考虑设备可修的TT&C系统任务可靠性分析方法.通过将各测控站的时间窗口划分为不同阶段,分析各阶段内设备逻辑关系并构建阶段OBDD模型,然后将所有阶段OBDD模型合并为最终的任务OBDD模型.采用连续时间Markov链(CTMC)分析可修设备的状态转移行为,基于新的OBDD数据结构给出了任务可靠性计算算法.与Markov方法和仿真方法的对比分析结果表明:所提出的方法能够精确计算设备可修的TT&C系统任务可靠性,设备数量多于30个时算法效率高于Markov方法.      

人工智能在航天飞行任务规划中的应用研究

 在航天飞行任务中，如何设计航天器的飞行过程，如何确定地面对航天器的控制操作，如何制定飞行控制计划等，是地面飞行控制中心面临的重大问题，也是航天飞行任务规划所要解决的基本问题。在充分认识和把握人工智能基本原理、方法和技术的基础上，提出了一个基于规则演绎和状态演化的生长式推理模型，并对模型的特性进行了详细讨论，然后导出了该模型在航天飞行任务规划问题中的具体形式，从而成功地解决了航天任务自动规划的难题。通过在实际航天任务中的应用和验证，不仅证明该模型和方法是正确的、可行的和高效的，而且证明人工智能在航天飞行任务规划中有着广阔的应用前景。     

舰载战术导弹值班可靠性评估方法

舰载导弹海上值班是导弹使用的重要任务之一,其值班可靠性是影响导弹舰上使用能力的关键因素。针对舰载导弹值班任务下的故障数据特点,基于随机截尾数据分析方法,建立了舰载导弹值班可靠性评估模型,给出了其值班可靠性计算方法,最后通过示例数据,验证了所给方法的有效性。     

基于改进Event模型的航路飞行过程垂直碰撞风险研究

随着民航空域运行的日益繁忙,如何从量化分析的角度构建有效合理的数学模型对航路飞行碰撞风险进行量化评估,提高航路规划与管理的科学性是业界面临的重要问题。提出基于改进Event 模型的航路飞行过程垂直碰撞风险评估方法,用符合航空器在空间上速度矢量分布的几何体即两个拼接的椭圆锥体碰撞盒代替原Event 模型中的长方体碰撞盒计...     

基于蚁群算法的无人机协同多任务分配

采用蚁群算法对无人机协同多任务分配问题(CMTAP)进行研究。在通用CMTAP模型的基础上,综合考虑包括动态任务时间约束和无人机任务能力的差别多类复杂约束条件,建立扩展的协同多任务分配模型。在多子群蚁群算法的基础上,提出了基于分工机制的蚁群算法对CMTAP进行求解。根据协同多任务分配的特点,设计了基于任务能力评估的问题解构造策略和基于任务代价的状态转移规则,提高了算法的性能。仿真实验结果表明该方法能有效地解决无人机协同多任务分配问题。     

基于执行时段滑动调整策略的中继卫星任务规划算法设计

针对中继卫星任务规划问题开展研究,提出一种基于执行时段滑动调整策略的任务规划算法。首先分析了中继卫星资源调度过程,并对任务申请的时间特征进行形式化描述,然后归纳出任务分配的主要约束,从而完成问题建模。在此基础上,对优化算法进行设计,给出了执行时段滑动调整步骤。通过调整已规划任务执行时段的方法,使部分原本无法执行任务具备执行可能,提升了任务执行率和资源利用率。在仿真实验中,通过大规模测试分析对比不同算法的优化效果,验证了文中所提方法的有效性。     

联翼布局传感器飞机多目标优化设计

针对联翼布局传感器飞机的任务需求特点,建立了专用于该类无人机的能够综合考虑气动、结构和雷达性能的多目标优化设计模型。利用改进的类函数/形函数参数化方法完成整机外形进行参数化,利用风洞试验进行了气动分析模型的验证,基于工程梁理论搭建了联翼布局结构重量估算模型。在雷达距离方程的基础上,建立了机翼内部雷达天线性能估算的数学模型。利用该模型,能够在优化过程中考虑到内置机载预警天线安装位置和性能评估对翼型选择、结构重量和气动特性的影响,最终得到全局最优设计。对某方案的优化结果表明,相较于优化前,多目标优化结果能够明显提升整机升阻比和前后视雷达探测范围,同时减轻结构重量。优化结果和敏感性分析表明了该多目标优化模型的可行性和必要性。     

军用教练机任务可靠性预计方法研究

 完成任务成功概率(MCSP)是军用飞机的一项重要的可靠性指标,在可靠性设计中必须反复进行预计。飞机整机的任务可靠性预计国内尚未有先例。本文从工程实践中总结了一套预计军用教练机MCSP及系统的任务可靠度的方法,比较全面地论述了任务可靠性框图的特点,并提出了一个计算军用教练机MCSP的实用数学模型。