航电系统体系贡献率权重演化动态综合评估

doi:10.3969/j.issn.1001-506X.2020.08.14

系统工程与电子技术 ›› 2020, Vol. 42 ›› Issue (8): 1740-1750.doi: 10.3969/j.issn.1001-506X.2020.08.14

航电系统体系贡献率权重演化动态综合评估

周璇¹(), 何锋^1,*(), 谷晓燕²(), 贾子睿²(), 熊华钢¹()

1. 北京航空航天大学电子信息工程学院, 北京 100191
2. 北京信息科技大学信息管理学院, 北京 100192

收稿日期:2019-12-23 出版日期:2020-07-25 发布日期:2020-07-27
通讯作者: 何锋 E-mail:lomoo@buaa.edu.cn;fenghe@buaa.edu.cn;xiaoyangu@bistu.edu.cn;jzr@mail.bistu.edu.cn;hgxiong@buaa.edu.cn
作者简介:周璇(1994-),女,博士研究生,主要研究方向为航空电子综合、实时通信网络。E-mail:lomoo@buaa.edu.cn|谷晓燕 (1980-),女,副教授,硕士研究生导师，博士,主要研究方向为复杂网络与风险、智能决策与大数据分析。E-mail:xiaoyangu@bistu.edu.cn|贾子睿 (1996-),女,硕士研究生,主要研究方向为复杂网络与风险、物流优化。E-mail:jzr@mail.bistu.edu.cn|熊华钢 (1961-),男,教授,博士研究生导师，博士,主要研究方向为通信网络理论与技术、航空电子综合等。E-mail:hgxiong@buaa.edu.cn
基金资助:
国家自然科学基金(71701020);国家级--装备领域基金(61403120404)

Dynamic comprehensive evaluation with weight evolution forsystem contribution rate of avionics systems

Xuan ZHOU¹(), Feng HE^1,*(), Xiaoyan GU²(), Zirui JIA²(), Huagang XIONG¹()

1. School of Electronics and Information Engineering, Beihang University, Beijing 100191, China
2. School of Information Management, Beijing Information Science & Technology University, Beijing 100192, China

Received:2019-12-23 Online:2020-07-25 Published:2020-07-27
Contact: Feng HE E-mail:lomoo@buaa.edu.cn;fenghe@buaa.edu.cn;xiaoyangu@bistu.edu.cn;jzr@mail.bistu.edu.cn;hgxiong@buaa.edu.cn
Supported by:
国家自然科学基金(71701020);国家级--装备领域基金(61403120404)

摘要/Abstract

摘要：

随着应用需求的发展,航电系统建设的体系特征日益明显,开展航电系统体系贡献率评估成为引导其迭代更新与优化设计的关键。针对专家知识随时间积累以及蜂群、协同等作战场景变化带来的指标体系权重演化问题,提出了一种适用于航电系统体系贡献率多阶段评估的动态综合方法。基于航电系统任务能力要素,构建了体系贡献率评估指标体系,并应用粒子群优化算法实现了有效评估阶段的时间加权。与传统静态单次评估、基于熵权法(entropy weight method, EWM)的动态评估以及逼近理想解排序法(technique for order preference by similarity to an ideal solution, TOPSIS)的动态评比等对比,所提方法充分体现权重分配信息并统筹兼顾阶段时序差异,能够更准确地反映指标贡献权重和能力贡献分布等评估结果,从而为航电系统发展论证提供更可靠和更灵活的决策方法支持。

关键词: 航电系统, 体系贡献率, 动态综合评估, 权重演化, 粒子群优化

Abstract:

With the development of application requirements, the system characteristics of avionics system construction are becoming increasingly obvious, and the system contribution rate evaluation for the avionics system becomes the key to guide its iterative updatation and optimization design. Aiming at the weight evolution problem of the indicator system, which is caused by the accumulation of expert knowledge over time and the change in combat scenarios including swarm and collaboration, a dynamic comprehensive method for multi-stage evaluation of the system contribution rate of the avionics system is proposed. Based on the mission capability elements of the avionics system, an evaluation indication system for the system contribution rate is constructed, and the particle swarm optimization algorithm is applied to achieve the time weighting of the effective evaluation stages. Compared with the traditional static single evaluation and dynamic evaluation based on entropy weight method (EWM) or technique for order preference by similarity to an ideal solution (TOPSIS), the proposed method fully reflects the weight allocation information and takes into account the phase sequence differences, and can also reflect the evaluation results more accurately, such as the indicator contribution weight and the capacity contribution distribution, which provides more reliable and flexible dicision method support for the development demonstration of the avionics system.

Key words: avionics system, system contribution rate, dynamic comprehensive evaluation, weight evolution, particle swarm optimization

中图分类号:

TP393

周璇, 何锋, 谷晓燕, 贾子睿, 熊华钢. 航电系统体系贡献率权重演化动态综合评估[J]. 系统工程与电子技术, 2020, 42(8): 1740-1750.

Xuan ZHOU, Feng HE, Xiaoyan GU, Zirui JIA, Huagang XIONG. Dynamic comprehensive evaluation with weight evolution forsystem contribution rate of avionics systems[J]. Systems Engineering and Electronics, 2020, 42(8): 1740-1750.

图/表 10

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参考文献 37

1	张先超, 马亚辉. 体系能力模型与装备体系贡献率测度方法[J]. 系统工程与电子技术, 2019, 41 (4): 843- 849.
	ZHANG X C , MA Y H . Capability model of combat system of systems and measurement method of armament contribution to combat system of systems[J]. Systems Engineering and Electronics, 2019, 41 (4): 843- 849.
2	刘鹏, 赵丹玲, 谭跃进, 等. 面向多任务的武器装备体系贡献度评估方法[J]. 系统工程与电子技术, 2019, 41 (8): 1763- 1770.
	LIU P , ZHAO D L , TAN Y J , et al. Multi-task oriented contribution evaluation method of weapon equipment system of systems[J]. Systems Engineering and Electronics, 2019, 41 (8): 1763- 1770.
3	林木, 李小波, 王彦锋, 等. 基于QFD和组合赋权TOPSIS的体系贡献率能效评估[J]. 系统工程与电子技术, 2019, 41 (8): 1802- 1809.
	LIN M , LI X B , WANG Y F , et al. Capability effectiveness evaluation of contribution ratio to system-of-systems based on QFD and combination weights TOPSIS[J]. Systems Engineering and Electronics, 2019, 41 (8): 1802- 1809.
4	游雅倩, 姜江, 孙建彬, 等. 基于证据网络的装备体系贡献率评估方法研究[J]. 系统工程与电子技术, 2019, 41 (8): 1780- 1788.
	YOU Y Q , JIANG J , SUN J B , et al. Evidential network-based evaluation method of contribution to weapon system-of-systems[J]. Systems Engineering and Electronics, 2019, 41 (8): 1780- 1788.
5	PEI D, QIN D G. Evaluation of contribution rate of weapon equipment system of systems capability based on conditional evi dential network[C]//Proc.of the 8th IEEE International Conference on Software Engineering and Ser vice Science, 2017: 459-463.
6	YANG H D, LIU F, YAN Y D. A new perspective on evaluation software of contribution rate for weapon equipment system[C]//Proc.of the International Conference on Geo-Spatial Knowledge and Intellig ence, 2017: 305-312.
7	SONG J H, LI L, GUO Q S, et al. System contribution rate assessment methods[C]//Proc.of the 2nd international conference on Computer, mechatronics and Engineering, 2017: 806-811
8	姚天乐, 胡起伟, 齐子元, 等. 基于软计算的轻武器装备体系贡献率评估方法[J]. 兵工学报, 2019, 40 (5): 938- 945.
	YAO T L , HU Q W , QI Z Y , et al. Soft computing-based assessment method of contribution rate of small arms and equipment system[J]. Acta Armamentarii, 2019, 40 (5): 938- 945.
9	陈文英, 张兵志, 史力晨, 等. 新型智能装甲作战系统体系贡献率评估研究[J]. 兵工学报, 2018, 39 (9): 1841- 1849.
	CHEN W Y , ZHANG B Z , SHI L C , et al. Research on evaluation of contribution rate of a new intelligent armoured combat system to army weapon system-of-systems[J]. Acta Armamentarii, 2018, 39 (9): 1841- 1849.
10	LYU H W, ZHANG W. System contribution rate evaluation of the equipment system based on rough set and neural network[C]//Proc.of the International Conference on Computer Science and Artificial Intelligence, 2017: 234.
11	管东林, 吴鑫辉, 常歌. 基于模糊层次分析的舰艇编队信息系统体系贡献率评估[J]. 指挥控制与仿真, 2019, 41 (3): 122- 127.
	GUAN D L , WU X H , CHANG G . Contribution ratio evaluation for naval battle group information system base d on Fuzzy-AHP method[J]. Command Control & Simulation, 2019, 41 (3): 122- 127.
12	李崑, 彭洁, 宋爽. 通信装备作战试验评估指标体系研究[J]. 通信技术, 2018, 51 (7): 1649- 1655.
	LI K , PENG J , SONG S . Evaluation index system of communication equipment operation test[J]. Communications Technology, 2018, 51 (7): 1649- 1655.
13	周浩, 戴国忠. 指挥信息系统体系贡献度指标体系[J]. 指挥信息系统与技术, 2018, 9 (5): 68- 73.
	ZHOU H , DAI G Z . System-of-systems contribution indicators system of command information system[J]. Command Information System and Technology, 2018, 9 (5): 68- 73.
14	王涛, 汪刘应, 常雷雷, 等. 基于作战环的导弹作战体系效能动态评估[J]. 现代防御技术, 2019, 47 (3): 42- 49.
	WANG T , WANG L Y , CHANG L L , et al. Dynamic evaluation of missile combat system effectiveness based on operation loop[J]. Modern Defense Technology, 2019, 47 (3): 42- 49.
15	昝翔, 陈春良, 张仕新, 等. 考虑权重演化的装备重要度动态评估方法[J]. 系统工程与电子技术, 2017, 39 (9): 2022- 2030.
	ZAN X , CHEN C L , ZHANG S X , et al. Dynamic evaluation method for equipment important degree consi dering weight-evolving[J]. Systems Engineering and Electronics, 2017, 39 (9): 2022- 2030.
16	LIU W W , SHI C S , LI J . Evaluation matrix with the speed feature based on double inspiriting control lines[J]. Journal of Systems Engineering and Electronics, 2013, 24 (6): 962- 970.
17	王翯华, 朱建军, 方志耕. 基于灰色关联度的多阶段语言评价信息集结方法[J]. 控制与决策, 2013, 28 (1): 109- 114.
	WANG H H , ZHU J J , FANG Z G . Aggregation of multi-stage linguistic evaluation information based on grey incidence degree[J]. Control and Decision, 2013, 28 (1): 109- 114.
18	ZHU Y N , LI L , ZHAO Y , et al. Regional comprehensive drought disaster risk dynamic evaluation based on projection pursuit clustering[J]. Water Policy, 2018, 20 (2): 410- 428.
19	TIAN Y J , LI Z . Panel data based dynamic evaluation of agricultural resource utilization efficiency: a case study of hebei province[J]. Asian Agricultural Research, 2013, 5 (4): 58- 59, 62.
20	HU W , GUO Q T , ZHOU Y F , et al. Dynamic comprehensive methodology for assessing power development level based on provincial data[J]. CSEE Journal of Power and Energy Systems, 2018. doi: 10.17775/CSEEJPES.2018.00910
21	ZHANG Z Y, XU W J, LIU Q, et al. Dynamic manufacturing capability assessment of industrial robots based on feedback information in cloud manufacturing[C]//Proc.of the 12th Inter national Manufacturing Science and Engineering Conference collocated with the JSME, 2017.
22	LI P , ZHANG J S , XU J , et al. A dynamic approach to mea-suring China's provincial energy supply security along "the Belt and Road"[J]. Mathematical Problems in Engineering, 2018, 2018, 3605024.
23	杨锴, 赵希男, 周岩. 考虑二次优势判别的动态竞优评价方法及应用[J]. 运筹与管理, 2019, 28 (3): 139- 147.
	YANG K , ZHAO X N , ZHOU Y . A dynamic evaluation method and application on better action conforming to natural rules considering twice identification of advantage[J]. Operations Research and Management Science, 2019, 28 (3): 139- 147.
24	KOU G , ERGU D , SHI Y . An integrated expert system for fast disaster assessment[J]. Computers & Operations Research, 2014, 42, 95- 107.
25	罗承昆, 陈云翔, 项华春, 等. 装备体系贡献率评估方法研究综述[J]. 系统工程与电子技术, 2019, 41 (8): 1789- 1794.
	LUO C K , CHEN Y X , XIANG H C , et al. Review of the evaluation methods of equipment's contribution rate to system-of-systems[J]. Systems Engin eering and Electronics, 2019, 41 (8): 1789- 1794.
26	杨克巍, 杨志伟, 谭跃进, 等. 面向体系贡献率的装备体系评估方法研究综述[J]. 系统工程与电子技术, 2019, 41 (2): 311- 321.
	YANG K W , YANG Z W , TAN Y J , et al. Review of the evaluation methods of equipment system of systems facing the contribution rate[J]. Systems Engineering and Electronics, 2019, 41 (2): 311- 321.
27	陈小卫, 张军奇, 杨永志. 新研装备体系贡献率度量方法分析[J]. 兵器装备工程学报, 2018, 39 (4): 19- 22.
	CHEN X W , ZHANG J Q , YANG Y Z . Analysis on measurement methods of new equipment system-of-systems contribution[J]. Journal of Sichuan Ordnance, 2018, 39 (4): 19- 22.
28	JIANG J , LI X , ZHOU Z , et al. Weapon system capability assessment under uncertainty based on the evidential reasoning approach[J]. Expert Systems with Applications, 2011, 38 (11): 13773- 13784.
29	LI J C, FU C X, CHEN Y W, et al. An operational efficiency evaluation method for weapon system-of-systems combat networks based on operation loop[C]//Proc.of the 9th International Conference on System of Systems Engineering, 2014: 219-223.
30	XIA W, LIU X X, MENG S F, et al. Efficiency evaluation research of missile weapon system based on the ADC-model[C]//Proc.of the 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer, 2016.
31	卜广志. 武器装备体系的体系结构与体系效能[J]. 系统工程与电子技术, 2006, 28 (10): 1544- 1548.
	PU G Z . Study on the architecture and effectiveness for armament systems[J]. Systems Engineering and Electronics, 2006, 28 (10): 1544- 1548.
32	张博孜, 张国忠, 常华耀. 武器装备体系贡献度评估问题研究[J]. 计算机仿真, 2018, 35 (2): 397- 401.
	ZHANG B Z , ZHANG G Z , CHANG H Y . Problem of contribution evaluation of weapon system of systems[J]. Computer Simulation, 2018, 35 (2): 397- 401.
33	彭耿, 周少平, 张绪明, 等. 武器装备体系贡献率计算方法[J]. 火力与指挥控制, 2019, 44 (4): 33- 36, 43.
	PENG G , ZHOU S P , ZHANG X M , et al. Contribution rate calculation of weapon system[J]. Fire Control & Command Control, 2019, 44 (4): 33- 36, 43.
34	李振, 李峭, 熊华钢. 基于使命任务分解的航空电子跨平台通信组织与仿真[J]. 航空电子技术, 2015, 46 (1): 10- 14.
	LI Z , LI Q , XIONG H G . Organization and simulation of cross-platform communication of avionics based on mission decomposition[J]. Avionics Technology, 2015, 46 (1): 10- 14.
35	熊华钢, 王中华. 先进航空电子综合技术[M]. 北京: 国防工业出版社, 2009.
	XIONG H G , WANG Z H . Advanced avionics integrtion techniques[M]. Beijing: National Defense Industry Press, 2019.
36	LIU T S, MENG Y L, WANG G Q. Effectiveness evaluation algorithm of integrated avionics system based on improved AHP method[C]//Proc.of the International Conference on Advanced Control, Automation and Robotics, 2014: 14.
37	PENG Y , CHU J G , XUE Z C . Basin flood control system risk evaluation based on variable sets[J]. Science China Technological Sciences, 2017, 60 (1): 153- 165.

符号标识	物理含义	示例
ξ(n_kⁱ)	n_kⁱ下层节点个数	ξ(n₂²)=2
Λ(n_kⁱ)	n_kⁱ下层节点有序集合	Λ(n₂²)={n₅³, n₆³}
Λ(n_kⁱ, j)	n_kⁱ第j个下层节点	Λ(n₂², 1)=n₃⁵
u(n_kⁱ)	n_kⁱ上层节点	u(n₁₀³)=n₄²
α(n_kⁱ)	n_kⁱ上层节点编号	α(n₁₀³)=4
β(n_kⁱ)	n_kⁱ在有序集合Λ(u(n_kⁱ))中的编号	β(n₁₀³)=1

参数指标	stage₁	stage₂	stage₃
γ	0.893 9	0.897 1	0.839 6
ζ_SS	0	0	1
ζ_EDC^0.2	0.087 6	0.224 8	0.687 6
ζ_EDC^0.3	0.141 8	0.316 4	0.541 8
ζ_EDC^0.4	0.231 6	0.336 8	0.431 6
ζ_DC	0.370 6	0.371 7	0.257 7
ζ_IDC	0.326 3	0.325 5	0.348 2

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航电系统体系贡献率权重演化动态综合评估

Dynamic comprehensive evaluation with weight evolution forsystem contribution rate of avionics systems

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指标名称	ID	P	R^ideal	R^worst
通信容量/Mbps	1	52	100	10
覆盖范围/km	2	27	35	10
传输延迟/ms	3	4	1	10
误码率	4	2e-7	e-8	e-9
节点发现时间/s	5	14	10	20
网络规划时间/s	6	9	5	15
抗干扰性/%	7	80	95	60
抗截获性/%	8	78	95	70
抗窃听性/%	9	74	95	65
位置精度/m	10	31	10	100
速度精度/(m/s)	11	0.18	0.1	0.25
航向精度/(°)	12	1.6	1	2.5
航线规划时间/s	13	11	5	15
横向航迹偏差/%	14	6	4	10
测距精度/m	15	2	0.15	5
测速精度/(m/s)	16	2.3	1	3
测角精度/(°)	17	0.8	0.5	1
轨迹预测一致性/%	18	85	95	70
位置预测精确度/%	19	82	98	70
敌我属性准确度/%	20	90	98	80
目标类型准确度/%	21	86	95	75
虚警概率/%	22	0.18	0.05	0.3
漏警概率/%	23	0.33	0.09	0.6
失锁捕获时间/frame	24	36	20	50
干扰成功率/%	25	45	70	20
决策指挥时间/s	26	8	5	10
数据融合程度/level	27	4	5	2
体系结构通用性/level	28	3	3	1
飞行操纵自主性/level	29	2	4	1
显示输出时延/ms	30	264	150	370
指令输入识别率/%	31	95	98	90
调度派发合理性/%	32	84	95	75
性能降级鲁棒性/%	33	78	90	65
设备配置冗余度/copy	34	2	3	1
故障预测及时性/%	35	77	85	70
寿命预测准确度/%	36	59	80	50