无人机空地安全通信与航迹规划的多目标联合优化方法

doi:10.13229/j.cnki.jdxbgxb20220557

吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (3): 913-922.doi: 10.13229/j.cnki.jdxbgxb20220557

• 通信与控制工程 • 上一篇

无人机空地安全通信与航迹规划的多目标联合优化方法

何颖¹(),樊俊松²,王巍¹,孙庚²(),刘衍珩^1,²

^1.长春财经学院信息工程学院，长春 130122
^2.吉林大学软件学院，长春 130012

收稿日期:2022-05-12 出版日期:2023-03-01 发布日期:2023-03-29
通讯作者: 孙庚 E-mail:yinghe@ccufe.edu.cn;sungeng@jlu.edu.cn
作者简介:何颖（1982-），女，副教授，博士. 研究方向：移动网络应用. E-mail：yinghe@ccufe.edu.cn
基金资助:
国家自然科学基金面上项目(62172186);吉林省科技发展计划项目(20210201072GX)

Joint optimization of secure communication and trajectory planning in unmanned aerial vehicle air⁃to⁃ground

Ying HE¹(),Jun-song FAN²,Wei WANG¹,Geng SUN²(),Yan-heng LIU^1,²

^1.College of Information and Engineering，Changchun University of Finance and Economics，Changchun 130122，China
^2.College of Software，Jilin University，Changchun 130012，China

Received:2022-05-12 Online:2023-03-01 Published:2023-03-29
Contact: Geng SUN E-mail:yinghe@ccufe.edu.cn;sungeng@jlu.edu.cn

摘要/Abstract

摘要：

针对无人机在无线通信网络场景中的保密通信和飞行过程中保证安全节能问题，提出了一种多目标优化设计方案。基于无人机通信模型、无人机能耗模型和环境限制模型构建了无人机调度和航迹规划问题（USPOP）的多目标优化模型，以无人机无线通信的平均保密率、无人机悬停能耗和无人机飞行能耗3个目标为优化目标进行优化，并通过改进的第三代非支配排序遗传算法对问题进行求解。仿真结果表明，本文改进算法能有效解决构建的优化问题，并且相对于其他对比算法有更好的收敛效果。

关键词: 计算机应用, 无人机通信网络, 航迹规划, 通信保密率, 能量损耗, 多目标优化

Abstract:

Aiming at the problem of UAV secrecy communication and ensuring safety as well energy saving during flight in the wireless network scenario， a multi-objective optimization scheme was proposed. The scheme mainly includes UAV transmission model， UAV energy consumption model and environmental constraints model， and further constructs the multi-objective optimization model of UAV scheduling and path optimization problem （USPOP）， which optimizes average communication secrecy rate of UAV wireless communication， UAV hovering energy consumption and UAV flight energy consumption. Then， a non-dominated sorting genetic algorithm III （NSGA-III） with discrete normal distribution initialization， differential mechanism， genetic mechanism and avoiding obstacles operator （NDGA-NSGA-III） is proposed to solve USPOP. Simulation results show that the proposed algorithm can effectively solve the constructed optimization problem， and the convergence effect is better than other comparison algorithms.

Key words: computer application, unmanned aerial vehicle（UAV） communication network, trajectory planning, secrecy rate, energy consumption, multi-objective optimization

中图分类号:

TP393

何颖,樊俊松,王巍,孙庚,刘衍珩. 无人机空地安全通信与航迹规划的多目标联合优化方法[J]. 吉林大学学报(工学版), 2023, 53(3): 913-922.

Ying HE,Jun-song FAN,Wei WANG,Geng SUN,Yan-heng LIU. Joint optimization of secure communication and trajectory planning in unmanned aerial vehicle air⁃to⁃ground[J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(3): 913-922.

图/表 10

图1

图2

图3

图4

图5

表1

在平均保密率最大化时不同算法得到的数值结果"

算法	$f 1$ /［bit·（s·Hz）^-1］	$f 2$ /kJ	$f 3$ /kJ
NDGA-NSGA-III	9.17	96.79	9 996.43
NSGA-III	0.75	1352.32	9 660.04
MOMVO	1.19	781.57	13 503.28
PESA2	0.76	1297.87	12 088.44
SPEA2	0.70	1477.13	10 071.86

表1

表2

在悬停能耗最小化时不同算法得到的数值结果"

算法	$f 1$ ［bit·（s·Hz）^-1］	$f 2$ /kJ	$f 3$ /kJ
NDGA-NSGA-III	8.24	89.59	8 926.63
NSGA-III	0.19	883.39	10 320.59
MOMVO	0.16	453.58	13 944.13
PESA2	0.76	1 296.87	12 078.51
SPEA2	0.39	1 270.88	10 716.25

表2

表3

在飞行能耗最小化时不同算法得到的数值结果"

算法	$f 1$ /［bit·（s·Hz）^-1］	$f 2$ /kJ	$f 3$ /kJ
NDGA-NSGA-III	8.24	98.02	8 414.29
NSGA-III	0.0001	2 825.53	8 829.82
MOMVO	0.28	599.11	13 121.44
PESA2	0.76	1 314.87	12 059.52
SPEA2	0.58	1 542.76	9 911.77

表3

图6

图7

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无人机空地安全通信与航迹规划的多目标联合优化方法

Joint optimization of secure communication and trajectory planning in unmanned aerial vehicle air⁃to⁃ground

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