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

摘要/Abstract

摘要：

针对天基信息支援体系效能评估中存在的准确性与实时性无法兼顾的问题, 以体系仿真为基础, 提出一种基于离散事件仿真的效能评估模型构建方法。首先, 基于仿真工具建立离散事件仿真模型, 对体系的结构与运作流程进行模拟, 并基于仿真模型构建评估指标体系, 生成效能评估数据样本。之后, 利用深度学习对复杂映射的强大表现能力基于深度置信网络构建效能评估代理模型, 结合无监督预训练和有监督调优实现网络的训练和参数优化。最后, 对仿真生成的测试集样本进行评估模型验证实验。结果表明, 所提方法在计算快速的同时对原评估模型有很高的还原度。

关键词: 天基信息支援体系, 离散事件仿真, 效能评估, 代理模型

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

中图分类号:

马力, 师鹏, 陈宇, 李文龙. 天基信息支援体系离散事件仿真与效能评估[J]. 系统工程与电子技术, 2024, 46(3): 906-913.

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.

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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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