空天智联网络指挥控制体系的韧性保障与评估方法

doi:10.7527/S1000-6893.2026.33298

Abstract

Abstract:

As a core information infrastructure for future all-domain coverage and intelligent collaboration， the space-air integrated intelligent network faces multiple challenges in complex environments. To address the resilience enhancement and evaluation issues of the space-air integrated intelligent network command and control system， a system model incorporating space-based and air-based networks is first constructed. On this basis， a phased resilience enhancement framework is proposed， which divides the resilience enhancement process into four stages： resistance， absorption， recovery， and reconstruction. Systematic reviews of corresponding resilience enhancement methods for each stage are conducted. Furthermore， a resilience evaluation index system for the space-air integrated intelligent network command and control system is established， and a combination method of analytic hierarchy process and adaptive weight particle swarm optimization is proposed， which can achieve scenario-based adaptive weighting. Starting from four resilience dimensions-resistance capability， absorption capability， recovery capability， and reconstruction capability-the overall resilience evaluation results of the system are derived. Simulation tests are also designed to assess the resilience of the space-air integrated intelligent network command and control system.

Key words: space-air integrated intelligent network, command and control system, resilience enhancement, resilience evaluation index system, resilience evaluation method

CLC Number:

V279

Zexin LI, Zipeng YANG, Junyi YANG, Guoyang ZHANG, Luyou ZHANG, Guangwei CHEN, Zhenyu XIAO. Resilience enhancement and evaluation methods for space-air integrated intelligent network command and control system[J]. Acta Aeronautica et Astronautica Sinica, 2026, 47(18): 533298.

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保障方法	适用性场景	实现的突破	可能的挑战与改进方向
基于拉格朗日二元理论的子信道与功率分配方法	空天跨域小单元节点通信资源分配	最大化节点信道增益，降低中央服务器故障影响	挑战：空天跨域资源调度协同难度大、分布式集群场景下分配策略全局最优性难以保障改进方向：后续可围绕跨域异构资源统一调度模型、分布式场景协同调度机制开展优化
基于Stackelberg博弈的分层带宽分配框架	天基-空基分层多播通信服务	实现带宽分层最优分配，提升系统带宽利用率
基于模糊逻辑的认知无线电信道优先级分配算法	空基网络冗余信道动态调度	按信道质量与任务优先级分配资源，提升冗余资源利用率
基于多智能体强化学习的动态信道分配技术	多无人机对地大容量数据传输	分布式执行信道分配，缩短冗余资源调度用时

保障方法	适用性场景	实现的突破	可能的挑战与改进方向
基于边缘计算与计算卸载的空天跨域协同重构方法	天基节点受损后的任务分流场景	降低对天基网络的依赖，提升系统分布式抗毁能力	挑战：天基节点在轨重构难度大、空基高动态场景下拓扑重构收敛速度不足改进方向：可围绕星上在轨轻量化重构技术、任务驱动的快速拓扑重构算法等开展研究
SDN 多控制器重配置部署策略	空天跨域网络控制平面重构	优化控制器负载均衡，降低网络平均延迟
天基时变拓扑动态路由算法	新增卫星节点后的天基路由重构	综合链路属性优化路由，提升数传稳定性
空基社团网络拓扑优化方法	新增无人机节点后的空基拓扑重构	实现社团内外高效连接，提升链路重构效率
深度强化学习驱动的无人机轨迹与拓扑联合重构技术	空基网络服务链动态重构	联合优化轨迹与拓扑，最大化通信服务净效益
抗毁性K连通拓扑构建算法	多节点故障后的空基网络重构	构建高抗毁拓扑，保障系统连通性

仿真参数	设定值
天基卫星子网数	1
卫星轨道面数量	5
每轨道面卫星数	4
空基无人机子网数	4
空基每子网节点数	20
仿真总时隙	100
外部威胁开始时隙	3
威胁持续总时长	20
链路可用频段数	5
单次最多干扰频段数	2
骨干节点故障率	0.5
普通节点故障率	0.7

指标名称	指标值
抵御威胁成功率	0.63
效能衰减比	0.57
全局效能衰减速率	182.04
效能恢复因子	0.90
效能恢复速率	124.99
重构成功率	0.37

Resilience enhancement and evaluation methods for space-air integrated intelligent network command and control system

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