Welcome to Acta Armamentarii ! Today is Share:

Acta Armamentarii ›› 2024, Vol. 45 ›› Issue (4): 1237-1251.doi: 10.12382/bgxb.2022.1038

Previous Articles     Next Articles

Mission Support Capability Assessment of Early-warning Combat System-of-systems Based on Temporal Network Simulation and Contribution Rate

YU Jintao1,*(), XIAO Bing2, CUI Yuzhu3, QI Dong4, YAN Tao5   

  1. 1 Department of Information Countermeasures, Air Force Early Warning Academy, Wuhan 430019, Hubei, China
    2 Department of Early Warning Intelligence, Air Force Early Warning Academy, Wuhan 430019, Hubei, China
    3 Zhejiang Laboratory, Hangzhou 311121, Zhejiang, China
    4 Non-Commissioned Officer Academy of PAP, Hangzhou 310030, Zhejiang, China
    5 Department of Air-Space Early Warning, Air Force Early Warning Academy, Wuhan 430019, Hubei, China
  • Received:2022-11-07 Online:2024-04-30
  • Contact: YU Jintao

Abstract:

In response to the problems of capability errors in networked modelling, lack of dynamic characteristics of mission capabilities, and certain errors between assessment results and realistic effectiveness in the assessment of mission support capabilities of early-warning combat system-of-systems (EWCSOS), a method of assessing the mission support capability of EWCSOS based on temporal network simulation and contribution rate is presented. Firstly, based on the static network model of EWCSOS, it is extended to the temporal combat network, and the time-series path and temporal effectiveness loop are defined. Secondly, the mission requirements and capabilities are matched according to the mission hierarchical decomposition, and then the mapping relation between the temporal network and multi-Agent simulation is established to build a simulation framework which is close to actual operations. Finally, the mission support capability of different combat units in EWCSOS is calculated by using the idea of contribution ratio to analyze the mission support capability of early-warning combat system-of-systems based on simulation data and integrating the uncertain indicators represented by asymmetric Gaussian affiliation functions and precise indicators represented by statistical results with similarity weights. The experimental results indicate that the proposed method is efficient and close to the actual capability of the equipment, and can reduce the evaluation error with realistic results, which provides technical support for the system capability assessment and equipment requirement justification.

Key words: temporal network, temporal effectiveness loop, early-warning combat system-of-systems, Monte Carlo simulation, mission support capability

CLC Number: