复杂任务场景无人机集群自组织侦察建模与仿真

基于agent的作战建模与仿真是无人机集群侦察效能评估的重要方法,但以往方法中agent行为机制 和模型结构难以描述复杂任务场景下的自组织侦察行为。以反海盗侦察任务为例,提出一种面向集群自组织 侦察的作战建模与仿真方法。设计多agent分层复合行为机制和可组合模块化agent模型结构,通过简单行为 的组合描述复杂行为;通过信息素图模块与航路管理模块的交互,实现自组织航路规划与飞行控制;并通过仿 真算例,来验证方法的可行性,对比分析不同航路规划方法的侦察效能。结果表明:自组织航路规划对中断航 路侦察的动态事件的适应性更强;对于大区域、长时间、低目标密度的区域覆盖侦察任务,仅通过改进航路规划 方法来降低访问间隔难以显著提高目标发现概率。     

基于多目标算法的空中作战任务规划框架研究

空中作战任务规划是一项复杂的任务，随着空中作战飞行器的种类、数量及其之间交互性的增加，任务规划也变得越来越复杂。任务规划人员必须在有限的时间内制定出最优的任务分配策略。决策支持工具可以辅助任务规划人员找到最优的规划方案。介绍了设计多目标进化算法以及在空中作战任务规划领域的框架和工作流程，具体的任务包括空中打击动态目标的定位问题和情报监视侦察（ISR）任务规划。总结了这些研究的经验教训，探讨了未来可能的发展方向。     

基于深度强化学习的多无人机协同进攻作战智能规划

无人机依靠作战效费比高、灵活自主等优势逐步替代了有生力量作战,多无人机协同作战任务规划成为热点研究问题。针对传统任务规划采用的智能优化算法存在的依赖静态、低维的简单场景、机上计算较慢等不足,提出一种基于深度强化学习（DRL）的端到端的多无人机协同进攻智能规划方法。将压制敌防空作战（SEAD）任务规划过程建模为马尔科夫决策过程,建立基于近端策略优化（PPO）算法的SEAD 智能规划模型,通过两组实验验证智能规划模型的有效性和鲁棒性。结果表明：基于DRL 的智能规划方法可以实现快速、精细规划,适应未知、连续高维的环境态势,智能规划模型具有战术协同规划能力。     

Formation flight of fixed-wing UAV swarms: A group-based hierarchical approach

This paper investigates a formation control problem of fixed-wing Unmanned Aerial Vehicle (UAV) swarms. A group-based hierarchical architecture is established among the UAVs, which decomposes all the UAVs into several distinct and non-overlapping groups. In each group, the UAVs form hierarchies with one UAV selected as the group leader. All group leaders execute coordinated path following to cooperatively handle the mission process among different groups, and the remaining followers track their direct leaders to achieve the inner-group coordination. More specifically, for a group leader, a virtual target moving along its desired path is assigned for the UAV, and an updating law is proposed to coordinate all the group leaders’ virtual targets; for a follower UAV, the distributed leader-following formation control law is proposed to make the follower’s heading angle coincide with its direct leader, while keeping the desired relative position with respect to its direct leader. The proposed control law guarantees the globally asymptotic stability of the whole closed-loop swarm system under the control input constraints of fixed-wing UAVs. Theoretical proofs and numerical simulations are provided, which corroborate the effectiveness of the proposed method.     

重访机制驱动的多无人机协同动目标搜索方法

为实现多无人机高效捕获灰色任务区域内的移动目标,考虑传感器探测概率与虚警概率,提出了重访机制驱动的协同搜索规划（RMD-CSP）方法,以降低目标遗漏与误判概率。考虑无人机飞行性能约束,以最大化任务执行效能为目标建立多无人机协同搜索模型。根据目标先验信息初始化环境搜索信息图（包括目标概率分布图、环境不确定度图与环境搜索状态图）,利用无人机实时探测信息,基于贝叶斯准则持续更新搜索信息图。定制基于环境不确定度更新的重访机制,通过增加长时间未被重访区域的环境不确定度,引导无人机搜索该区域,降低移动目标的遗漏概率;定制基于目标函数权重更新的重访机制,引导无人机快速重访发现新的疑似目标的区域,对疑似目标进行再次确认,减少由于传感器虚警概率造成的目标误判概率。采用滚动时域规划架构,将搜索规划问题分解为一系列短时域规划问题,提升了求解效率。在典型任务想定下,通过数值仿真试验验证了所提方法的有效性。仿真结果表明,RMD-CSP能够在秒级时间内生成每个时域的搜索航迹,相比于光栅式搜索方法与标准的概率启发式搜索方法,能够引导无人机捕获更多的移动目标,同时减少误判次数,有效提升了多无人机协同搜索的任务效能。     

基于地面任务-空间姿态映射的敏捷卫星任务规划

面向观测时间窗口相互重叠的多点目标观测任务需求,对敏捷卫星单星单轨任务规划问题进行研究。针对传统方法在卫星机动能力受限和成像任务冗余两种情况下求解效率低的缺陷,引入任务-姿态协同规划思想。首先,建立地面任务和空间姿态映射关系,并考虑相邻任务间姿态机动时间的最优性使得卫星在观测相邻任务时无多余等待时间,以此来设计任务-姿态协同规划数学模型。其次,根据任务-姿态协同规划数学模型,设计自适应伪谱遗传算法（APGA）,用以求解满足调整时间最优性的敏捷卫星任务规划问题。最后,通过仿真实验,验证了模型和算法能够有效地解决传统算法求解敏捷卫星任务规划问题时存在的求解效率低的缺陷。     

Inverse design of mission success space for combat aircraft contribution evaluation

This paper presents a novel design method of the Mission Success Space (MSS) for the evaluation on aircraft contribution effectiveness. MSS concept was proposed for giving success criterion of a mission and judging the success by conventional mission effectiveness with regards to the aircraft capabilities. This space is created by the Mission Success Function (MSF) and the original Effectiveness Index Space (EIS) where empirical equations are usually assumed to be MSFs. Based on this MSS concept, this paper firstly defines the MSS-based evaluation, then further summarizes the evaluation process of the Contribution to System-of-Systems (CSS). More importantly, based on the thought of Inverse Design (ID), a new design method of MSF is presented comprehensively analyzing aircraft’s CSS in a combat mission without using any empirical MSF. The definition of MSS based ID is given and the design procedure is sequentially introduced. Two different confrontation cases are depicted with many details as the simulation validation: Air-to-ground and Penetration. There are two design variables considered for designing MSS in the latter case while only one for the former. However, in both cases, the best design is given by evaluating the Gaussian fitting performance of CSS.     

Exploring mission planning method for a team of carrier aircraft launching

High-level efficiency and safety are of great significance for improving the fighting capability of an aircraft carrier. One way to enhance efficiency and safety level is to organize the carrier aircraft into combat effectively. This paper studies the mission planning problem for a team of carrier aircraft launching, and a novel distributed mission planning architecture is proposed. The architecture is hierarchical and is comprised of four levels, namely, the input level, the coordination level,the path planning level and the execution level. Realistic constraints in each level of the distributed architecture, such as the vortex flow effect, the crowd effect and the motion of aircraft, are considered in the model. To solve this problem, a distributed path planning algorithm based on the asynchronous planning strategy is developed. The proposed Mission Planning Approach for Carrier Aircraft Launching(MPACAL) is validated using the setups of the Nimitz-class aircraft carrier.Compared to the isolated planning architecture and the centralized planning architecture, the proposed distributed planning architecture has advantages in coordinating the launch tasks not only belonging to the same catapult but also when all different catapults are considered. The proposed MPACAL provides a modeling method for the flight deck operation on aircraft carrier.     

Distributed intelligent self-organized mission planning of multi-UAV for dynamic targets cooperative search-attack

This article studies the cooperative search-attack mission problem with dynamic targets and threats, and presents a Distributed Intelligent Self-Organized Mission Planning (DISOMP) algorithm for multiple Unmanned Aerial Vehicles (multi-UAV). The DISOMP algorithm can be divided into four modules: a search module designed based on the distributed Ant Colony Optimization (ACO) algorithm, an attack module designed based on the Parallel Approach (PA) scheme, a threat avoidance module designed based on the Dubins Curve (DC) and a communication module designed for information exchange among the multi-UAV system and the dynamic environment. A series of simulations of multi-UAV searching and attacking the moving targets are carried out, in which the search-attack mission completeness, execution efficiency and system suitability of the DISOMP algorithm are analyzed. The simulation results exhibit that the DISOMP algorithm based on online distributed down-top strategy is characterized by good flexibility, scalability and adaptability, in the dynamic targets searching and attacking problem.     

基于合同机制的多UCAV分布式协同任务控制

 针对集中式控制的不足，采用基于合同机制的分布式控制方法对多无人作战飞机（UCAV）协同任务控制问题开展研究。设计了有限中央控制下的分布式控制体系结构，以支持UCAV在任务控制站的监控下实现不同级别上的自治。在通过合同网协议实现动态任务分配的基础上，建立条件合同机制对任务执行过程进行协调，提高了多UCAV协同作战的效能。采用时间约束网络对UCAV的任务计划进行量化表达，保证了多UCAV战术行为配合的准确实现。仿真结果验证了方法的有效性。     

军用直升机任务效能综合评估技术及应用

论述了军用直升机任务效能综合评估的意义、方法,提出了以任务效能为优化目标的直升机综合设计技术,建立了直升机效能-费用模型。     

区域防空组网雷达对跟踪目标交接班模型研究

组网雷达对跟踪目标进行交接班是对目标进行稳定跟踪的基础.在综合考虑组网雷达的作战背景的基础上,分析了接班雷达选择模型和交班时机选择模型.在接班雷达选择模型中,将定位精度和目标在接班雷达探测区域的飞行时间作为接班雷达选择的两个指标,并利用基于理想点的多属性决策方法进行决策,可保证对目标跟踪的连续性并防止频繁交接班情况的发生.最后对提出的交接班模型进行了仿真验证.     

航空电子系统综合技术分析

系统综合是指将机载电子设备综合成以作战、飞行功能为核心的统一控制、管理和显示的系统,这样可以提高系统自动化和智能化的程度,最大限度的发挥载机的战斗效能。本文对系统综合模式、设计方法、作战效能、故障诊断等诸方面进行了论述,并介绍了航电系统的综合试验和试飞评定系统的软件功能。     

直升机任务能力评估

首先介绍了直升机任务能力的主要内容及其应用领域,然后建立了一种适用于直升机任务能力评估的对数法,并对其评估的具体项目进行了说明。最后给出了一些机型的评估算例,计算结果表明用该方法对直升机的任务能力进行评估是合理的。     

侦察-攻击作战航空综合体效能模型分析

对侦察-攻击作战航空综合体的基本概念、组成和功能进行全面系统地阐述;并根据侦察-攻击作战航空综合体作战过程的特点,阐述了评估侦察-攻击作战航空综合体效能的数学模型,为进一步研究该类型作战航空综合体作战效能提供了一些帮助。     

多无人机协同覆盖路径规划

多无人机协同覆盖路径规划(CPP)由于其并行性和容错能力,对于提高无人机完成侦察、监视、搜索等任务的效率具有重要意义。提出了一种基于无人机任务性能评价和任务区域划分的多无人机协同CPP算法。定量分析了无人机执行覆盖任务的能力,根据无人机及携带成像传感器的性能给出了计算无人机任务性能指数的数学公式;提出了一种基于任务性能和子区域宽度的任务区域划分算法,使无人机的总转弯次数达到最少。仿真结果表明,所提出的CPP算法能够规划出全局最优的多无人机协同覆盖路径。     

大跨时空任务背景下的太阳能无人机任务规划技术研究进展

通过任务规划技术合理的优化太阳能无人机的飞行轨迹和动力学参数，能够有效提高太阳能无人机的能量利用率，使其胜任许多大范围跨时间跨空间飞行任务。从能量建模、续航评估和能量管理策略3个方面对大跨时空任务背景下太阳能无人机任务规划技术的研究进展进行了综述。在能量建模方面，介绍了当前主流的太阳辐射模型和能量生产基本框架；在续航评估方面，分析了目前的指标设计和应用方法；在能量管理策略方面，从能量综合应用、风力滑翔机制、轨迹优化方法和面向特定任务的应用4个角度，梳理了当前的研究现状。最后，对该领域未来可能的研究方向进行了展望。     

有限姿控能力的低RCS微小卫星姿态实时规划

 为提高在轨微小卫星使用效能及生存能力,提出一种受姿控能源消耗及驱动能力约束的低雷达散射截面（RCS）微小卫星姿态实时规划算法。算法应用曲面像素法、时域有限差分法及假设检验,在三维空间内对微小卫星的RCS及雷达探测水平进行建模,并结合雷达分布模型构建了相应的威胁评估函数及规划代价评估函数。同时,为提高算法的实时性能,采用了粒子群优化(PSO)算法以降低计算复杂度。仿真结果表明,在有限计算量的基础上,算法能够以较小规划代价有效降低卫星威胁方向的RCS及雷达探测概率,满足对微小卫星飞行姿态实时规划的需要。     

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...     

Real-time evaluation method of flight mission load based on sensitivity analysis of physiological factors

As the complexity of flight missions continues to increase, sending a timely warning or providing assistance to pilots helps to reduce the probability of operational errors and flight accidents. Monitoring pilots’ physiological data, real-time evaluation of mission load is a feasible technical way to achieve this. In this paper, a set of flight tasks including aircraft control, humancomputer interaction and mental arithmetic tests are designed to simulate five mission loads at different flight d...