天基信息支援体系离散事件仿真与效能评估

doi:10.12305/j.issn.1001-506X.2024.03.16

Abstract

Abstract:

To solve the problem that accuracy and real-time performance cannot be balanced in the effectiveness evaluation of space-based information support system, based on the system simulation, a method of constructing the performance evaluation model based on discrete event simulation is proposed. Firstly, a discrete event simulation model is established based on simulation tools to simulate the structure and operation process of the system, and an evaluation index system is constructed based on the simulation model to generate performance evaluation data samples. Then, by using the powerful expressive ability of deep learning for complex mapping, the performance evaluation proxy model is constructed based on the deep belief network, and the training and parameter optimization of the network are realized by combining unsupervised pre-training and supervised tuning. Finally, the evaluation model verification experiment is carried out on the test set samples generated by simulation. The results show that the proposed method has a high degree of reduction to the original evaluation model while calculating quickly.

Key words: space-based information support system, discrete event simulation, effectiveness evaluation, proxy model

CLC Number:

Li MA, Peng SHI, Yu CHEN, Wenlong LI. Discrete event simulation and effectiveness evaluation of space-based information support system[J]. Systems Engineering and Electronics, 2024, 46(3): 906-913.

Figures/Tables 11

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References 30

1	于小岚, 熊伟, 韩驰, 等. 天基信息支援装备体系作战效能评估方法研究[J/OL]. 系统仿真学报[2023-09-01]. https://doi.org/10.16182/j.issn1004731x.joss.22-0683.
	YU X L, XIONG W, HAN C, et al. Research on operational effectiveness evaluation method of space-based information support equipment system[J/OL]. Journal of System Simulation[2023-09-01]. https://doi.org/10.16182/j.issn1004731x.joss.22-0683.
2	奚丹. 空间信息资源对空地进攻作战效能影响分析及评估方法[D]. 长沙: 国防科技大学, 2008.
	XI D. Analysis on impact of space information resources on ope-rational effectiveness in air-to-ground strike and evaluation methods[D]. Changsha: National University of Defense Technology, 2008.
3	姜剑雄, 赵毅, 师鹏, 等. 基于直觉模糊推理的天基海洋监视系统贡献度评估研究[J]. 上海航天, 2016, (6): 7- 18.
	JIANG J X , ZHAO Y , SHI P , et al. Evaluation study of contribution to system warfighting for space-based ocean surveillance based on intuitionistic fuzzy reasoning[J]. Aerospace Shanghai, 2016, (6): 7- 18.
4	刘翔宇, 张裕, 赵洪利, 等. 卫星装备体系贡献度评估[J]. 现代防御技术, 2019, 47 (3): 137- 144.
	LIU X Y , ZHANG Y , ZHAO H L , et al. Satellite equipment's contribution to system warfighting evaluation[J]. Modern Defence Technology, 2019, 47 (3): 137- 144.
5	HAN C, XIONG W, JIAN P. Data-driven operational effectiveness evaluation of space-based information system[C]//Proc. of the IEEE 5th Information Technology, Networking, Electronic and Automation Control Conference, 2021: 1687-1692.
6	陈秋琼, 饶世钧, 王山. 基于组合赋权法和Vague集的侦察卫星情报处理系统效能评估[J]. 中国电子科学研究院学报, 2022, 17 (9): 856- 861.
	CHEN Q Q , RAO S J , WANG S . Efficiency evaluation of reconnaissance satellite intelligence processing systems based on combination weight method and vague set[J]. Journal of China Academy of Electronics and Information Technology, 2022, 17 (9): 856- 861.
7	韩驰, 熊伟. 基于改进灰狼算法优化SVR的航天侦察装备效能评估[J]. 系统工程与电子技术, 2021, 43 (10): 2902- 2910. doi: 10.12305/j.issn.1001-506X.2021.10.25
	HAN C , XIONG W . Operational effectiveness evaluation of space reconnaissance equipment based on SVR optimized by improved grey wolf optimizer[J]. Systems Engineering and Electronics, 2021, 43 (10): 2902- 2910. doi: 10.12305/j.issn.1001-506X.2021.10.25
8	LI Z , DONG Y F , LI P Y , et al. A new method for remote sensing satellite observation effectiveness evaluation[J]. Aerospace, 2022, 9 (6): 317. doi: 10.3390/aerospace9060317
9	饶世钧, 陈涛, 洪俊. 基于改进KELM的电子侦察卫星效能评估方法[J]. 火力与指挥控制, 2022, 47 (11): 71- 75.
	RAO S J , CHEN T , HONG J . Effectiveness evaluation method of electronic reconnaissance satellite based on improved KELM algorithm[J]. Fire Control & Command Control, 2022, 47 (11): 71- 75.
10	张世坤, 操新文, 申宏芬. 作战体系评估方法综述[J]. 指挥控制与仿真, 2021, 43 (6): 1- 5.
	ZHANG S K , CAO X W , SHEN H F . Overview of operational system of systems evaluation method[J]. Command Control & Simulation, 2021, 43 (6): 1- 5.
11	张庆军, 张明智, 张庆娟, 等. 基于复杂网络理论空间信息支援体系建模研究[J]. 系统仿真学报, 2017, 29 (9): 1907- 1913.
	ZHANG Q J , ZHANG M Z , ZHANG Q J , et al. Research of modeling of spatial information support SoS based on complex network theory[J]. Journal of System Simulation, 2017, 29 (9): 1907- 1913.
12	于小岚, 熊伟, 韩驰. 基于神经网络的效能评估方法综述[J]. 兵工自动化, 2023, 42 (3): 1-8, 43.
	YU X L , XIONG W , HAN C . A survey of effectiveness evaluation methods based on neural network[J]. Ordnance Industry Automation, 2023, 42 (3): 1-8, 43.
13	戚宗锋, 王华兵, 李建勋. 基于深度学习的雷达侦察系统作战能力评估方法[J]. 指挥控制与仿真, 2020, 42 (2): 59- 64.
	QI Z F , WANG H B , LI J X . Combat capability evaluation method based on deep learning for radar reconnaissance system[J]. Command Control & Simulation, 2020, 42 (2): 59- 64.
14	HU X W, LUO P C, ZHANG X N, et al. Research on the effectiveness evaluation of big data in combat simulation[C]//Proc. of the 2nd International Conference on Big Data Research, 2018: 70-75.
15	胡鑫武. 基于作战仿真数据的智能化效能评估分析技术研究[D]. 长沙: 国防科技大学, 2018.
	HU X W. Intelligent effectiveness evaluation based on combat simulation data[D]. Changsha: National University of Defense Technology, 2018.
16	HU X W , LUO P C , ZHANG X N , et al. Improved ant colony optimization for weapon-target assignment[J]. Mathematical Problems in Engineering, 2018, 6481635.
17	李妮, 李玉红, 龚光红, 等. 基于深度学习的体系作战效能智能评估及优化[J]. 系统仿真学报, 2020, 32 (8): 1425- 1435.
	LI N , LI Y H , GONG G H , et al. Intelligent effectiveness evaluation and optimization on weapon system of systems based on deep learning[J]. Journal of System Simulation, 2020, 32 (8): 1425- 1435.
18	殷小静, 胡晓峰, 郭圣明, 等. 基于SDAE+Softmax模型的体系贡献率评估方法[J]. 火力与指挥控制, 2021, 46 (6): 7- 11.
	YIN X J , HU X F , GUO S M , et al. Evaluation method of the contribution rate to SoS based on SDAE+Softmax model[J]. Fire Control & Command Control, 2021, 46 (6): 7- 11.
19	TAN X P , SU S J , ZUO Z , et al. Intrusion detection of UAVs based on the deep belief network optimized by PSO[J]. Sensors, 2019, 19 (24): 5529. doi: 10.3390/s19245529
20	曹延华, 杨海涛, 何宇, 等. 天基信息服务体系概论[M]. 北京: 国防工业出版社, 2018: 74- 104.
	CAO Y H , YANG H T , HE Y , et al. Introduction to space-based information service system[M]. Beijing: National Defense Industry Press, 2018: 74- 104.
21	燕雪峰, 张德平, 黄晓东, 等. 面向任务的体系效能评估[M]. 北京: 电子工业出版社, 2020: 13- 25.
	YAN X F , ZHANG D P , HUANG X D , et al. Mission oriented effectiveness evaluation and optimization of system of systems[M]. Beijing: Publishing House of Electronics Industry, 2020: 13- 25.
22	ZEILER M D, KRISHNAN D, TAYLOR G W, et al. Deconvolutional networks[C]//Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010: 2528-2535.
23	李波, 雒浩然, 田琳宇, 等. 基于DBN效能拟合的舰艇编队作战效能敏感性分析[J]. 航空学报, 2019, 40 (12): 156- 166.
	LI B , LUO H R , TIAN L Y , et al. Sensitivity analysis of ship formation operational effectiveness based on DBN effectiveness fitting[J]. Acta Aeronautica et Astronautica Sinica, 2019, 40 (12): 156- 166.
24	SABAR N R , TURKY A , SONG A , et al. An evolutionary hyper-heuristic to optimise deep belief networks for image reconstruction[J]. Applied Soft Computing, 2020, 97, 105510. doi: 10.1016/j.asoc.2019.105510
25	李建勋, 王军, 韩山, 等. 系统效能评估方法与应用[M]. 北京: 国防工业出版社, 2022: 155- 226.
	LI J X , WANG J , HAN S , et al. System effectiveness evaluation method and application[M]. Beijing: National Defense Industry Press, 2022: 155- 226.
26	FATLAWI A H , LING S H , JABARDI M H . Diagnosis system for Parkinson's disease using speech characteristics of patients and deep belief network[J]. CAAI Transaction on Intelligence Technology, 2017, 2 (9): 246- 253.
27	HINTON G E , OSINDERO S , TEH Y W . A fast learning algorithm for deep belief nets[J]. Neural Computation, 2006, 18 (7): 1527- 1554. doi: 10.1162/neco.2006.18.7.1527
28	FISCHER A , IGEL C . Training restricted Boltzmann machines: an introduction[J]. Pattern Recognition, 2014, 47 (1): 25- 39. doi: 10.1016/j.patcog.2013.05.025
29	胡天真. 基于主成分分析和深度信念网络的轴承智能故障诊断[D]. 南京: 南京航空航天大学, 2020.
	HU T Z. PCA-DBN based bearing intelligent fault diagnosis[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2020.
30	HINTON G E . Training products of experts by minimizing contrastive divergence[J]. Neural Computation, 2002, 14 (8): 1771- 1800. doi: 10.1162/089976602760128018

功能模块	模块主要功能
	(Entity Generator)基于时间或事件生成实体，实体可以具有一定的特征参数
	(Queue)将消息或实体按一定的顺序存储在队列中，直到后续模块可以立即处理
	(Entity Server)为实体在一段时间内提供服务，“N”代表可对N个实体独立同时服务
	(Output Switch)通过使能端信号控制实体的分流

模型参数/指标名称	均值	概率分布模型
任务总时长/h	24	-
目标生成频率/min	0.5	Uniform(0, 1)

模型参数/指标名称	样本值范围	概率分布模型
搜索发现通道	x₁∈[1, 5]	-
平均搜索发现时间/min	x₂∈[4, 12]	Normal(x₂, 0.5)
搜索发现概率	x₃∈[0.6, 1]	-
平均信息传输链路延迟/min	x₄∈[9, 12]	Normal(x₄, 0.3)
信息传输链路通道数	x₅∈[2, 6]	-
识别确认时间/min	x₆∈[1, 5]	Normal(x₆, 0.2)
识别确认通道数	x₇∈[1, 7]	-
识别确认概率	x₈∈[0.6, 1]	-
平均跟踪所需持续时间/min	x₉∈[6, 11]	Normal(x₉, 0.5)
目标跟踪通道数	x₁₀∈[1, 6]	-

隐藏层数	隐层节点数	RMSE	MAE(训练)	MAE(测试)
1	20	0.018 6	0.016 4	0.040 8
	30	0.017 5	0.015 0	0.035 2
	40	0.017 3	0.014 9	0.036 1
2	3, 3	0.081 2	0.074 9	0.079 3
	9, 3	0.020 6	0.018 1	0.029 4
	9, 9	0.020 4	0.018 2	0.040 1
3	3, 2, 2	0.066 1	0.056 8	0.072 4
	3, 6, 3	0.076 2	0.069 5	0.087 9
	5, 3, 4	0.054 6	0.046 6	0.073 8

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Discrete event simulation and effectiveness evaluation of space-based information support system

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