远程联合打击下防空火力单元机动路线预测研究

doi:10.12305/j.issn.1001-506X.2024.07.23

Abstract

Abstract:

In the offensive operations of the red and blue sides, in order to fully seize the battlefield air superiority, the blue side air defense fire units are usually taken as the first key targets. Therefore, it is of great significance to accurately predict the activity law of the blue side air defense fire units and scientifically design the joint reconnaissance and attack actions. Firstly, the maneuver support mode adopted by the air defense fire unit is systematically analyzed, the defense capability calculation formula is given based on the definition of defense capability, and the grid network model is introduced to complete the quantitative calculation. Based on the support scope constraint, position resource constraint and maneuver process constraint, the shortest maneuver route and the highest defense capability are taken as the optimization objectives for the actual support requirements. A prediction model for maneuvering route of ground air defense fire units is established. Secondly, aiming at the problem of solving the nonlinear model, the model linearization transformation and solving method are proposed. Then, on the basis of the optimal transfer route, an algorithm for constructing maneuver route library is designed to generate the probabilistic prediction scheme of blue side maneuver route and analyze the maneuver law of blue side air defense fire units. Finally, based on the case simulation, the feasibility and global efficiency of the designed model and method are verified, which can effectively predict the maneuvering route of blue side anti-aircraft fire units.

Key words: multi-objective programming, shortest path, linearization, anti-aircraft fire, maneuver route prediction

CLC Number:

Haonan WU, Lingsong DI, Shoukui SI, Bing WAN, Xichao SU. Research on prediction of maneuvering routes of anti-aircraft fire units under long-range joint strikes[J]. Systems Engineering and Electronics, 2024, 46(7): 2413-2423.

Figures/Tables 13

Fig.1

Fig.2

Table 1

Fig.3

Fig.4

Fig.5

Fig.6

Table 2

Table 3

Fig.7

Fig.8

Fig.9

Fig.10

References 25

1	董晨, 帅逸仙, 周金鹏, 等. 网络化多传感器-多武器协同防空任务规划[J]. 系统工程与电子技术, 2022, 44 (12): 3738- 3746. doi: 10.12305/j.issn.1001-506X.2022.12.18
	DONG C , SHUAI Y X , ZHOU J P , et al. Cooperative air defense task planning of networked multi-sensor-multi-weapon[J]. Systems Engineering and Electronics, 2022, 44 (12): 3738- 3746. doi: 10.12305/j.issn.1001-506X.2022.12.18
2	徐浩, 邢清华, 王伟. 基于模糊多目标规划的防空反导火力分配[J]. 系统工程与电子技术, 2018, 40 (3): 563- 570. doi: 10.3969/j.issn.1001-506X.2018.03.12
	XU H , XING Q H , WANG W . WTA for air and missile defense based on fuzzy multi-objective programming[J]. Systems Engineering and Electronics, 2018, 40 (3): 563- 570. doi: 10.3969/j.issn.1001-506X.2018.03.12
3	王龚, 赵文飞, 滕克难, 等. 不确定因素下海上要地防空动态火力分配模型[J]. 兵工学报, 2022, 43 (11): 2885- 2896.
	WANG G , ZHAO W F , TENG K N , et al. Research on the priority ranking of air defense and anti-missile positions in important place at sea[J]. Acta Armamentarii, 2022, 43 (11): 2885- 2896.
4	杜继永, 张凤鸣, 杨骥, 等. 基于模糊理论的防空系统威胁评估方法[J]. 火力与指挥控制, 2012, 37 (10): 89- 92.
	DU J Y , ZHANG F M , YANG J , et al. Assessment of air defense threat based on fuzzy theory[J]. Fire Control & Command Control, 2012, 37 (10): 89- 92.
5	WANG Y , LI J , HUANG W L , et al. Dynamic weapon target assignment based on intuitionistic fuzzy entropy of discrete particle swarm[J]. China Communications, 2017, 14 (1): 169- 179. doi: 10.1109/CC.2017.7839767
6	付涛, 王军. 防空系统中空中目标威胁评估方法研究[J]. 指挥控制与仿真, 2016, 38 (3): 63- 69.
	FU T , WANG J . Threat assessment of aerial targets in air-defense[J]. Command Control & Simulation, 2016, 38 (3): 63- 69.
7	颜培远, 刘曙, 王君. 基于动态规划-遗传算法的防空部署优化模型[J]. 系统工程与电子技术, 2018, 40 (10): 2249- 2255. doi: 10.3969/j.issn.1001-506X.2018.10.14
	YAN P Y , LIU S , WANG J . Optimization model of air defense disposition based on dynamic programming and genetic algorithm[J]. Systems Engineering and Electronics, 2018, 40 (10): 2249- 2255. doi: 10.3969/j.issn.1001-506X.2018.10.14
8	万佳庆, 王鹏飞, 郭强, 等. 基于烟花算法的要地防空多传感器部署规划方法[J]. 飞行力学, 2021, 39 (6): 62- 67.
	WAN J Q , WANG P F , GUO Q , et al. Multi-sensor deployment planning method for air defense in strategic point based on firework algorithm[J]. Flight Dynamics, 2021, 39 (6): 62- 67.
9	LI J , XIN B , PARDALOS P M , et al. Solving bi-objective uncertain stochastic resource allocation problems by the CVaR-based risk measure and decomposition-based multi-objective evolutionary algorithms[J]. Annals of Operations Research, 2021, 296 (1/2): 639- 666.
10	王龚, 赵文飞, 陈健, 等. 海上要地防空反导阵地优度排序研究[J]. 系统工程与电子技术, 2022, 44 (6): 1920- 1926. doi: 10.12305/j.issn.1001-506X.2022.06.18
	WANG G , ZHAO W F , CHEN J , et al. Research on priority ranking of air defense and anti-missile positions in important place at sea[J]. Systems Engineering and Electronics, 2022, 44 (6): 1920- 1926. doi: 10.12305/j.issn.1001-506X.2022.06.18
11	孙海文, 谢晓方, 孙涛, 等. 改进型布谷鸟搜索算法的防空火力优化分配模型求解[J]. 兵工学报, 2019, 40 (1): 189- 197.
	SUN H W , XIE X F , SUN T , et al. Improved cuckoo search algorithm for solving antiaircraft weapon-target optimal assignment model[J]. Acta Armamentarii, 2019, 40 (1): 189- 197.
12	蔺向阳, 邢清华, 刘付显. 针对要点防空模型的作战兵力优化研究[J]. 系统工程与电子技术, 2022, 44 (3): 921- 928. doi: 10.12305/j.issn.1001-506X.2022.03.24
	LIN X Y , XING Q H , LIU F X . Research on combat force optimization for point air defense model[J]. Systems Engineering and Electronics, 2022, 44 (3): 921- 928. doi: 10.12305/j.issn.1001-506X.2022.03.24
13	雷宇曜, 姜文志, 刘立佳, 等. 基于子目标进化算法的要地防空武器系统优化部署[J]. 系统工程与电子技术, 2016, 38 (2): 314- 322. doi: 10.3969/j.issn.1001-506X.2016.02.12
	LEI Y Y , JIANG W Z , LIU L J , et al. Weapon system deployment optimization based on a sub-objective evolutionary algorithm for key-point air defense[J]. Systems Engineering and Electronics, 2016, 38 (2): 314- 322. doi: 10.3969/j.issn.1001-506X.2016.02.12
14	孙海文, 谢晓方, 庞威, 等. 基于改进火力分配模型的综合防空火力智能优化分配[J]. 控制与决策, 2020, 35 (5): 1102- 1112.
	SUN H W , XIE X F , PANG W , et al. Integrated air defense firepower intelligence optimal assignment based on improved firepower assignment model[J]. Control and Decision, 2020, 35 (5): 1102- 1112.
15	魏彤, 龙琛. 基于改进遗传算法的移动机器人路径规划[J]. 北京航空航天大学学报, 2020, 46 (4): 703- 711.
	WEI T , LONG C . Path planning for mobile robot based on improved genetic algorithm[J]. Journal of Beijing University of Aeronautics and Astronautic, 2020, 46 (4): 703- 711.
16	唐俊林, 张栋, 王孟阳, 等. 改进链式多种群遗传算法的防空火力任务分配[J]. 哈尔滨工业大学学报, 2022, 54 (6): 19- 27.
	TANG J L , ZHANG D , WANG M Y , et al. Air defense firepower task assignment based on improved chainlike multi-population genetic algorithm[J]. Journal of Harbin Institute of Technology, 2022, 54 (6): 19- 27.
17	张松涛, 王公宝, 赵虎. 含禁忌算子的遗传算法在水面舰艇编队防空作战目标分配中的应用[J]. 军事运筹与系统工程, 2009, 23 (2): 43- 47.
	ZHANG S T , WANG G B , ZHAO H . Application of genetic algorithm with tabu operator in antiaircraft target assignment of surface warship formation[J]. Military Operations Research and Systems Engineering, 2009, 23 (2): 43- 47.
18	李梦杰, 常雪凝, 石建迈, 等. 武器目标分配问题研究进展: 模型、算法与应用[J]. 系统工程与电子技术, 2023, 45 (4): 1049- 1071. doi: 10.12305/j.issn.1001-506X.2023.04.14
	LI M J , CHANG X N , SHI J M , et al. Developments of weapon target assignment problem: models, algorithms, and applications[J]. Systems Engineering and Electronics, 2023, 45 (4): 1049- 1071. doi: 10.12305/j.issn.1001-506X.2023.04.14
19	张志伟, 蒋道刚, 袁坤刚. 低空突防航线规划研究[J]. 飞行力学, 2019, 37 (4): 62- 67.
	ZHANG Z W , JIANG D G , YUAN K G . Study on low altitude penetration route planning[J]. Flight Mechanics, 2019, 37 (4): 62- 67.
20	OLEKSANDR M , YEVHEN R , DMYTRO K , et al. Decision-making model for task execution by a military unit in terms of queuing theory[J]. Military Operations Research, 2021, 26 (1): 59- 70.
21	MOHTASHAMI Z , AGHSAMI A , JOLAI F . A green closed loop supply chain design using queuing system for reducing environmental impact and energy consumption[J]. Journal of Cleaner Production, 2020, 242, 118452.
22	智洪欣, 赵鹏, 李中, 等. 基于可射击概率约束的防空作战火力优化分配[J]. 兵工学报, 2022, 43 (4): 952- 959.
	ZHI H X , ZHAO P , LI Z , et al. A weapon-target assignment in air-defense operations based on shooting probability constraint[J]. Acta Armamentarii, 2022, 43 (4): 952- 959.
23	张杰, 王刚, 宋亚飞, 等. 基于自适应SGD-多智能体的防空资源部署优化[J]. 系统工程与电子技术, 2019, 41 (7): 1536- 1543. doi: 10.3969/j.issn.1001-506X.2019.07.14
	ZHANG J , WANG G , SONG Y F , et al. Optimization of air defense resource deployment based on adaptive SGD-multi-agent[J]. Systems Engineering and Electronics, 2019, 41 (7): 1536- 1543. doi: 10.3969/j.issn.1001-506X.2019.07.14
24	朱晓雯, 范成礼, 卢盈齐, 等. 基于改进BBO算法和模糊期望效果的反导武器目标分配建模与实现[J]. 系统工程与电子技术, 2023, 45 (11): 3544- 3554. doi: 10.12305/j.issn.1001-506X.2023.11.21
	ZHU X W , FAN C L , LU Y Q , et al. Anti-missile weapon target allocation modeling and implementation based on improved BBO algorithm and fuzzy expected effect[J]. Systems Engineering and Electronics, 2023, 45 (11): 3544- 3554. doi: 10.12305/j.issn.1001-506X.2023.11.21
25	季军亮, 汪民乐, 魏桥, 等. 多层反导协同作战有关问题及解决思路分析[J]. 飞航导弹, 2021, 4, 68-73, 79.
	JI J L , WANG M L , WEI Q , et al. Analysis of problems and solutions related to multi-layer anti-missile coordinated operation[J]. Aerodynamic Missile Journal, 2021, 4, 68-73, 79.

变量	解释说明
S	蓝方防空火力单元最大拦截面积
φ	红方火箭弹来袭方向的最大夹角
θ	蓝方防空火力单元有效拦截角度
θ_max	栅格网络节点与目标城市的方位角最大值
θ_min	栅格网络节点与目标城市的方位角最小值
A	蓝方防空火力单元有效拦截面积
S_N	防空火力单元最大拦截面积内的节点数目
A_N	红方火箭弹可能来袭方向夹角之内的最大拦截面积内的节点数目
O_k	蓝方重点城市
F_i	防空火力单元
B_i	基本阵地
C_i	预备阵地
D_k	普通城市
d	蓝方防空火力单元l h机动的距离
γ	蓝方防空火力单元的防御能力
γ_总	蓝方5个城市目标的总防御能力
d_ij	火力单元从普通阵地B_i转移到备用阵地C_j的最短距离
γ_ik	位于基本阵地B_i的火力单元对城市O_k的防御能力
γ_jk	位于备用阵地B_j的火力单元对城市O_k的防御能力

单元	状态	机动目的阵地	保护目标	防御能力值	到达阵地时间	是否能接替值班
F1	机动	C16	O1	0.74	58.46	1
F2	机动	C21	O2	0.49	101.63	1
F3	机动	C17	O1	0.68	80.85	1
F4	机动	C18	O1	0.85	100.48	1
F5	值班	-	O5	0.61	-	0
F6	值班	-	O1	0.76	-	0
F7	值班	-	O2	0.40	-	0
F8	机动	C20	O2	0.50	54.05	1
F9	值班	-	O4	0.67	-	0
F10	值班	-	O2	0.20	-	0
F11	机动	C28	O3	0.31	52.00	1
F12	机动	C26	O3	0.39	112.30	1
F13	机动	C36	O4	0.55	55.01	1
F14	机动	C12	O5	0.56	94.29	1
F15	机动	C6	O1	0.34	113.25	1
15个防空火力单元对目标的防御能力之和				8.07

起始点	终点	标号	使用次数	使用频率/%
B1	B3	1	0	0.00
B10	B11	2	511	3.41
B10	B8	3	105	0.70
B10	B7	4	1 074	7.19
B10	B9	5	0	0.00
B10	B12	6	981	6.55
B13	B12	7	497	3.31
B14	B13	8	3	0.00
B14	B15	9	0	0.00
B15	B13	10	2	0.00
B3	B4	11	137	0.90
B3	D2	12	954	6.38
B5	O1	13	522	3.48
B5	B4	14	144	0.97
B6	B1	15	578	3.88
B6	D1	16	1 042	6.95
B7	B6	17	1 093	7.29
B7	O2	18	210	1.40
B8	B11	19	406	2.71
B8	B5	20	570	3.81
D1	B2	21	369	2.47
D1	O1	22	1 563	10.46
D1	B5	23	142	0.97
D2	B15	24	503	3.38
D2	B14	25	449	3.01
O1	B1	26	269	1.80
O1	B3	27	1 328	8.86
O1	B2	28	138	0.90
O1	B4	29	493	3.31
O2	B8	30	101	0.67
O2	D1	31	608	4.04
O2	B9	32	177	1.20

[1]	Zhengyang LIU, Li ZHOU, Rui ZHANG. Attitude control of hypersonic vehicle with random parameter perturbations [J]. Systems Engineering and Electronics, 2024, 46(2): 703-714.
[2]	Yuang ZHU, Yali ZHAO, Jialuan HE, Chenguang ZHANG, Chaojun WU, Xiaoxiao JIA. Topology discovery method for mobile communication systems based on distributed SDN [J]. Systems Engineering and Electronics, 2024, 46(1): 357-365.
[3]	Lei WU, Ju LIU, Zhichao GAO, Zheng DONG, Hongji XU. Time delay optimization scheme of industrial internet based on time sensitive software defined network [J]. Systems Engineering and Electronics, 2023, 45(6): 1836-1846.
[4]	Bin ZENG, Quanxian ZHANG, Houpu LI. Optimal scheduling for cooperative support chain of logistics and equipment under uncertainty [J]. Systems Engineering and Electronics, 2021, 43(5): 1277-1286.
[5]	Liben YANG, Wenjun WEI, Jianfeng YANG, Taiguo LI, Dong WANG. Improved ADRC attitude control algorithm for tilting dual-fan vector aircraft [J]. Systems Engineering and Electronics, 2021, 43(10): 2976-2983.
[6]	Cheng WANG, Xugang WANG. Terminal sliding mode control for hypersonic guided projectile [J]. Systems Engineering and Electronics, 2020, 42(12): 2859-2866.
[7]	XU Hao, XING Qinghua, WANG Wei. WTA for air and missile defense based on fuzzy multi-objective programming [J]. Systems Engineering and Electronics, 2018, 40(3): 563-570.
[8]	MENG Xiangfei, WANG Ying, QI Yao, LV Maolong, LI Chao. New method for I-UMOP problem based on P_EV principle [J]. Systems Engineering and Electronics, 2018, 40(2): 338-345.
[9]	LIU Jianghui, LI Haiyang. Augmented proportional navigation control for approach to uncontrolled tumbling satellite#br# [J]. Systems Engineering and Electronics, 2018, 40(10): 2311-2316.
[10]	LI Jiguang, CHEN Xin, WANG Xin, ZHANG Rong. Nonlinear robust adaptive control of flying wing UAV maneuvering flight [J]. Systems Engineering and Electronics, 2017, 39(9): 2058-2067.
[11]	SUN Huadong, YU Jianqiao, MEI Yuesong. Control of wrap-around fin rolling missiles based on#br# Lipschitz adaptive trajectory linearization [J]. Systems Engineering and Electronics, 2017, 39(1): 162-167.
[12]	GAI Jun-feng, ZHAO Guo-rong, SONG Chao. Model predictive control based on linearization and neural network approach [J]. Systems Engineering and Electronics, 2015, 37(2): 394-399.
[13]	WANG Qing， WANG Tong， HOU De-long， DONG Chao-yang. Robust LPV control for morphing vehicles via velocity based linearization [J]. Systems Engineering and Electronics, 2014, 36(6): 1130-1136.
[14]	ZHENG Hao-tian, GU Xiao-dong . PCNN shortest path algorithm based on bandwidth remaining rate [J]. Journal of Systems Engineering and Electronics, 2013, 35(4): 859-863.
[15]	LIU Xiao, LIU Zhong, HOU Wen-shu， XU Jiang-hu. Improved MOPSO algorithm for multi-objective programming model of weapon target assignment [J]. Journal of Systems Engineering and Electronics, 2013, 35(2): 326-330.

Research on prediction of maneuvering routes of anti-aircraft fire units under long-range joint strikes

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 13

References 25

Related Articles 15

Recommended Articles

Metrics

Comments