A review of unmanned aerial vehicle path planning technology for low-altitude economic application scenarios

WANG Ershen; ZHANG Shenglong; GUO Jing; XU Song; XU Yubin; QU Pingping; LI Wei

doi:10.11959/j.issn.1000-0801.2025215

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A review of unmanned aerial vehicle path planning technology for low-altitude economic application scenarios

Review | 更新时间：2026-01-08

- A review of unmanned aerial vehicle path planning technology for low-altitude economic application scenarios
- Telecommunications Science Vol. 41, Issue 12, Pages: 27-43(2025)
- 作者机构：
  
  1.沈阳航空航天大学电子信息工程学院，辽宁沈阳 110136
  2.沈阳航空航天大学民用航空学院，辽宁沈阳 110136
  3.沈阳航空航天大学人工智能学院，辽宁沈阳 110136
  4.中国民航科学技术研究院，北京 100028
  5.蜂巢航宇科技（北京）有限公司，北京 100160
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62173237);The Aeronautical Science Foundation(20240055054001);The General Project of the Education Department of Liaoning Province(310125011);The Applied Basic Research Program of Liaoning Province(2025JH2/101300011)
- DOI：10.11959/j.issn.1000-0801.2025215
  CLC： TP393;TN929.5
- Received：27 May 2025，
  
  Revised：2025-07-26，
  
  Accepted：12 August 2025，
  
  Published：20 December 2025
- 稿件说明：
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王尔申,张圣隆,郭婧等.面向低空经济应用场景的无人机路径规划技术研究综述[J].电信科学,2025,41(12):27-43.

WANG Ershen,ZHANG Shenglong,GUO Jing,et al.A review of unmanned aerial vehicle path planning technology for low-altitude economic application scenarios[J].Telecommunications Science,2025,41(12):27-43.
王尔申,张圣隆,郭婧等.面向低空经济应用场景的无人机路径规划技术研究综述[J].电信科学,2025,41(12):27-43. DOI： 10.11959/j.issn.1000-0801.2025215.

WANG Ershen,ZHANG Shenglong,GUO Jing,et al.A review of unmanned aerial vehicle path planning technology for low-altitude economic application scenarios[J].Telecommunications Science,2025,41(12):27-43. DOI： 10.11959/j.issn.1000-0801.2025215.

摘要

随着低空经济的快速发展，无人机（unmanned aerial vehicle，UAV）作为重要运载体，其路径规划技术在飞行安全保障与任务效率提升中发挥关键作用。基于低空空域划分、典型应用场景与任务需求，将无人机路径规划策略分为全局、局部与混合3类，系统梳理分析其技术特征与任务适应性，并从计算复杂度和环境动态性角度进行对比评估。进一步，综述路径规划技术的演进过程与关键机制（如协同避障与在线优化），结合多源感知与通信协同的发展需求，总结该领域的未来发展方向与面临的挑战，旨在为低空经济应用场景下无人机飞行安全提供理论支撑与方法参考。

Abstract

With the rapid development of the low-altitude economy

unmanned aerial vehicle (UAV)

as important carriers

have seen their path planning technology play a key role in ensuring flight safety and improving mission efficiency. Based on low-altitude airspace structure

typical application scenarios

and mission requirements

UAV path planning strategies were divided into three categories: global

local

and hybrid. Their technical characteristics and mission adaptability were systematically reviewed and analyzed

while a comparative evaluation was conducted from the perspectives of computational complexity and environmental dynamics. Furthermore

the evolutionary process and key mechanisms (such as collaborative obstacle avoidance and online optimization) of path planning technologies were summarized. In light of the development needs of multi-source perception and communication coordination

future research directions and challenges in this field were identified

aiming to provide theoretical support and methodological references for enhancing UAVs flight safety in low-altitude economic applications.

关键词

Keywords

references

张洪海 , 夷珈 , 李姗 , 等 . 低空空域容量评估研究综述 [J ] . 交通运输工程学报 , 2023 , 23 ( 6 ): 78 - 93 .

ZHANG H H , YI J , LI S , et al . Review on research of low-altitude airspace capacity evaluation [J ] . Journal of Traffic and Transportation Engineering , 2023 , 23 ( 6 ): 78 - 93 .

廖小罕 , 黄耀欢 , 徐晨晨 . 面向无人机应用的低空空域资源研究探讨 [J ] . 地理学报 , 2021 , 76 ( 11 ): 2607 - 2620 .

LIAO X H , HUANG Y H , XU C C . Views on the study of low-altitude airspace resources for UAV applications [J ] . Acta Geographica Sinica , 2021 , 76 ( 11 ): 2607 - 2620 .

JIANG T , GELLER J , NI D H , et al . Unmanned aircraft system traffic management: concept of operation and system architecture [J ] . International Journal of Transportation Science and Technology , 2016 , 5 ( 3 ): 123 - 135 .

陈谋 , 马浩翔 , 雍可南 , 等 . 无人机安全飞行控制综述 [J ] . 机器人 , 2023 , 45 ( 3 ): 345 - 366 .

CHEN M , MA H X , YONG K N , et al . Safety flight control of UAV: a survey [J ] . Robot , 2023 , 45 ( 3 ): 345 - 366 .

潘泉 , 郭亚宁 , 吕洋 , 等 . 无人机系统自主安全: 定义、建模与分级 [J ] . 中国科学: 信息科学 , 2023 , 53 ( 8 ): 1608 - 1628 .

PAN Q , GUO Y N , LYU Y , et al . Autonomous safety and security of UAV systems: definition, modeling, and gradation [J ] . Scientia Sinica (Informationis) , 2023 , 53 ( 8 ): 1608 - 1628 .

中国民用航空局 . 国家空域基础分类方法 [EB ] . 2023 .

Civil Aviation Administration of China . National airspace basic classification method [EB ] . 2023 .

吴盘龙 , 黄樊晶 , 何山 , 等 . 无人机系统控制研究综述 [J ] . 电光与控制 , 2024 , 31 ( 10 ): 1 - 9 .

WU P L , HUANG F J , HE S , et al . A review on unmanned aircraft system control [J ] . Electronics Optics & Control , 2024 , 31 ( 10 ): 1 - 9 .

董超 , 崔灿 , 贾子晔 , 等 . 面向低空智联网的多维信息统一表征技术综述 [J ] . 电子与信息学报 , 2025 , 47 ( 5 ): 1215 - 1229 .

DONG C , CUI C , JIA Z Y , et al . Survey of unified representation technology of multi-dimensional information for low altitude intelligent network [J ] . Journal of Electronics & Information Technology , 2025 , 47 ( 5 ): 1215 - 1229 .

薛震 , 盛汉霖 , 陈欣 , 等 . 基于剪枝可视性地图的无人机全局规划方法 [J ] . 航空学报 , 2025 , 46 ( 10 ): 336 - 348 .

XUE Z , SHENG H L , CHEN X , et al . Global planning method for UAVs based on pruned visibility map [J ] . Acta Aeronautica et Astronautica Sinica , 2025 , 46 ( 10 ): 336 - 348 .

MENG W L , ZHANG X G , ZHOU L Z Y , et al . Advances in UAV path planning: a comprehensive review of methods, challenges, and future directions [J ] . Drones , 2025 , 9 ( 5 ): 376 .

GHAMBARI S , GOLABI M , JOURDAN L , et al . UAV path planning techniques: a survey [J ] . RAIRO - Operations Research , 2024 , 58 ( 4 ): 2951 - 2989 .

HAYAJNEH M R , GARIBEH M H , YOUNES A B , et al . Unmanned aerial vehicle path planning using acceleration-based potential field methods [J ] . Electronics , 2025 , 14 ( 1 ): 176 .

ZHANG S T , LI Y B , YE F , et al . A hybrid human-in-the-loop deep reinforcement learning method for UAV motion planning for long trajectories with unpredictable obstacles [J ] . Drones , 2023 , 7 ( 5 ): 311 .

DIJKSTRA E W . A note on two problems in connexion with graphs [J ] . Numerische Mathematik , 1959 , 1 ( 1 ): 269 - 271 .

WANG J Y , LI Y H , LI R X , et al . Trajectory planning for UAV navigation in dynamic environments with matrix alignment Dijkstra [J ] . Soft Computing , 2022 , 26 ( 22 ): 12599 - 12610 .

HUSAIN Z , AL ZAABI A , HILDMANN H , et al . Search and rescue in a maze-like environment with ant and dijkstra algorithms [J ] . Drones , 2022 , 6 ( 10 ): 273 .

HART P E , NILSSON N J , RAPHAEL B . A formal basis for the heuristic determination of minimum cost paths [J ] . IEEE Transactions on Systems Science and Cybernetics , 1968 , 4 ( 2 ): 100 - 107 .

张洪海 , 李翰 , 刘皞 , 等 . 城市区域物流无人机路径规划 [J ] . 交通运输系统工程与信息 , 2020 , 20 ( 6 ): 22 - 29 .

ZHANG H H , LI H , LIU H , et al . Path planning for logistics unmanned aerial vehicle in urban area [J ] . Journal of Transportation Systems Engineering and Information Technology , 2020 , 20 ( 6 ): 22 - 29 .

谢华 , 韩斯特 , 尹嘉男 , 等 . 城市低空无人机飞行计划协同推演与优化调配方法 [J ] . 航空学报 , 2024 , 45 ( 19 ): 330018 .

XIE H , HAN S T , YIN J N , et al . Cooperative deduction and optimal allocation method for urban low-altitude UAV flight plan [J ] . Acta Aeronautica et Astronautica Sinica , 2024 , 45 ( 19 ): 330018 .

LAVALLE S . Rapidly-exploring random trees: a new tool for path planning [J ] . Research Report 9811 , 1998 .

张海阔 , 孟秀云 . 基于改进RRT*算法的无人机在线航迹规划 [J ] . 系统工程与电子技术 , 2024 , 46 ( 12 ): 4157 - 4164 .

ZHANG H K , MENG X Y . UAV online trajectory planning based on improved RRT* algorithm [J ] . Systems Engineering and Electronics , 2024 , 46 ( 12 ): 4157 - 4164 .

YANG F , FANG X , GAO F , et al . Obstacle avoidance path planning for UAV based on improved RRT algorithm [J ] . Discrete Dynamics in Nature and Society , 2022 , 2022 ( 1 ): 4544499 .

HOLLAND J H . Adaptation in natural and artificial systems: an introductory analysis with applications to biology [M ] . Ann Arbor : University of Michigan Press , 1975 .

杨小鹏 , 马忠杰 , 钟世超 , 等 . 基于遗传算法的无人机载穿墙三维SAR航迹规划方法 [J ] . 雷达学报 , 2024 , 13 ( 4 ): 731 - 746 .

YANG X P , MA Z J , ZHONG S C , et al . Trajectory planning method for UAV-through-the-wall 3D SAR based on a genetic algorithm [J ] . Journal of Radars , 2024 , 13 ( 4 ): 731 - 746 .

PEHLIVANOGLU Y V , PEHLIVANOGLU P . An enhanced genetic algorithm for path planning of autonomous UAV in target coverage problems [J ] . Applied Soft Computing , 2021 , 112 : 107796 .

KENNEDY J , EBERHART R . Particle swarm optimization [C ] // Proceedings of ICNN'95 - International Conference on Neural Networks . Piscataway : IEEE Press , 2002 : 1942 - 1948 .

王飞 , 杨清平 . 基于改进粒子群算法的城市物流无人机路径规划 [J ] . 科学技术与工程 , 2023 , 23 ( 30 ): 13187 - 13194 .

WANG F , YANG Q P . Route planning of urban logistics unmanned aerial vehicle based on improved particle swarm optimization algorithm [J ] . Science Technology and Engineering , 2023 , 23 ( 30 ): 13187 - 13194 .

王飞 , 杨清平 . 面向多无人机物流配送的双层任务规划方法 [J ] . 北京航空航天大学学报 , 2024 : 1 - 14 .

WANG F , YANG Q P . Two-layer task planning method for multi-UAV logistics distribution [J ] . Journal of Beijing University of Aeronautics and Astronautics , 2024 : 1 - 14 .

DORIGO M , MANIEZZO V , COLORNI A . Ant system: optimization by a colony of cooperating agents [J ] . IEEE Transactions on Systems, Man, and Cybernetics Part B , Cybernetics, 1996 , 26 ( 1 ): 29 - 41 .

唐立 , 郝鹏 , 张学军 . 基于改进蚁群算法的山区无人机路径规划方法 [J ] . 交通运输系统工程与信息 , 2019 , 19 ( 1 ): 158 - 164 .

TANG L , HAO P , ZHANG X J . An UAV path planning method in mountainous area based on an improved ant colony algorithm [J ] . Journal of Transportation Systems Engineering and Information Technology , 2019 , 19 ( 1 ): 158 - 164 .

蒋丽 , 王洪艳 , 梁昌勇 . 新零售背景下卡车与无人机协同的电商物流末端配送优化 [J ] . 系统管理学报 , 2024 , 33 ( 6 ): 1461 - 1470 .

JIANG L , WANG H Y , LIANG C Y . Optimization of E-commerce logistics last mile distribution based on truck and drone collaboration in the new retail context [J ] . Journal of Systems & Management , 2024 , 33 ( 6 ): 1461 - 1470 .

JONES M , DJAHEL S , WELSH K . Path-planning for unmanned aerial vehicles with environment complexity considerations: a survey [J ] . ACM Computing Surveys , 2023 , 55 ( 11 ): 1 - 39 .

丁兵兵 , 匡珍春 , 卢来 . 基于Q学习算术优化算法的无人机三维航迹规划 [J ] . 电光与控制 , 2024 , 31 ( 3 ): 61 - 69 .

DING B B , KUANG Z C , LU L . Three-dimensional UAV path planning based on Q-learning arithmetic optimization algorithm [J ] . Electronics Optics & Control , 2024 , 31 ( 3 ): 61 - 69 .

赵慧敏 , 罗贺 , 阴酉龙 , 等 . 面向集合任务的多无人机电力巡检任务分配方法研究 [J ] . 系统工程理论与实践 , 2025 , 45 ( 2 ): 666 - 684 .

ZHAO H M , LUO H , YIN Y L , et al . Research on task allocation method for multiple drones power inspection for collective tasks [J ] . Systems Engineering-Theory & Practice , 2025 , 45 ( 2 ): 666 - 684 .

TU G T , JUANG J G . UAV path planning and obstacle avoidance based on reinforcement learning in 3D environments [J ] . Actuators , 2023 , 12 ( 2 ): 57 .

XU Z C , WANG Q , KONG F C , et al . Ga-DQN: a gravity-aware DQN based UAV path planning algorithm [C ] // Proceedings of the 2022 IEEE International Conference on Unmanned Systems (ICUS) . Piscataway : IEEE Press , 2022 : 1215 - 1220 .

BALESTRIERI E , DAPONTE P , DE VITO L , et al . Sensors and measurements for UAV safety: an overview [J ] . Sensors , 2021 , 21 ( 24 ): 8253 .

张香竹 , 张立家 , 宋逸凡 , 等 . 基于深度学习的无人机单目视觉避障算法 [J ] . 华南理工大学学报(自然科学版) , 2022 , 50 ( 1 ): 101 - 108, 131 .

ZHANG X Z , ZHANG L J , SONG Y F , et al . Obstacle avoidance algorithm for unmanned aerial vehicle vision based on deep learning [J ] . Journal of South China University of Technology (Natural Science Edition) , 2022 , 50 ( 1 ): 101 - 108, 131 .

ALDAO E , GONZÁLEZ-DESANTOS L M , MICHINEL H , et al . UAV obstacle avoidance algorithm to navigate in dynamic building environments [J ] . Drones , 2022 , 6 ( 1 ): 16 .

FOX D , BURGARD W , THRUN S . The dynamic window approach to collision avoidance [J ] . IEEE Robotics & Automation Magazine , 1997 , 4 ( 1 ): 23 - 33 .

刘斌 , 兰莹 , 黄文焘 , 等 . 融合动态窗口法的无人机动态路径规划算法 [J ] . 系统仿真学报 , 2024 , 36 ( 8 ): 1843 - 1853 .

LIU B , LAN Y , HUANG W T , et al . UAV dynamic path planning algorithm combined with dynamic window approach [J ] . Journal of System Simulation , 2024 , 36 ( 8 ): 1843 - 1853 .

HE Y , HOU T C , WANG M R . A new method for unmanned aerial vehicle path planning in complex environments [J ] . Scientific Reports , 2024 , 14 ( 1 ): 9257 .

KHATIB O . Real-time obstacle avoidance for manipulators and mobile robots [C ] // Proceedings of 1985 IEEE International Conference on Robotics and Automation . Piscataway : IEEE Press , 1985 : 500 - 505 .

郭一聪 , 刘小雄 , 章卫国 , 等 . 基于改进势场法的无人机三维路径规划方法 [J ] . 西北工业大学学报 , 2020 , 38 ( 5 ): 977 - 986 .

GUO Y C , LIU X X , ZHANG W G , et al . 3D path planning method for UAV based on improved artificial potential field [J ] . Journal of Northwestern Polytechnical University , 2020 , 38 ( 5 ): 977 - 986 .

刘光才 , 马寅松 , 齐福强 , 等 . 基于改进A * -人工势场法的城市物流无人机路径规划 [J ] . 飞行力学 , 2022 , 40 ( 6 ): 16 - 23 .

LIU G C , MA Y S , QI F Q , et al . Flight path planning for urban logistics UAV based on improved A * -APF algorithm [J ] . Flight Dynamics , 2022 , 40 ( 6 ): 16 - 23 .

FIORINI P , SHILLER Z . Motion planning in dynamic environments using velocity obstacles [J ] . The International Journal of Robotics Research , 1998 , 17 ( 7 ): 760 - 772 .

RIBEIRO M , ELLERBROEK J , HOEKSTRA J . Velocity obstacle based conflict avoidance in urban environment with variable speed limit [J ] . Aerospace , 2021 , 8 ( 4 ): 93 .

郭华 , 郭小和 . 改进速度障碍法的无人机局部路径规划算法 [J ] . 航空学报 , 2023 , 44 ( 11 ): 271 - 281 .

GUO H , GUO X H . Local path planning algorithm for UAV based on improved velocity obstacle method [J ] . Acta Aeronautica et Astronautica Sinica , 2023 , 44 ( 11 ): 271 - 281 .

OUAHOUAH S , BAGAA M , PRADOS-GARZON J , et al . Deep-reinforcement-learning-based collision avoidance in UAV environment [J ] . IEEE Internet of Things Journal , 2022 , 9 ( 6 ): 4015 - 4030 .

AIT SAADI A , SOUKANE A , MERAIHI Y , et al . UAV path planning using optimization approaches: a survey [J ] . Archives of Computational Methods in Engineering , 2022 , 29 ( 6 ): 4233 - 4284 .

ZHAO F Y , LI D Y , WANG Z X , et al . Autonomous localized path planning algorithm for UAVs based on TD3 strategy [J ] . Scientific Reports , 2024 , 14 ( 1 ): 763 .

吕超 , 李慕宸 , 欧家骏 . 基于分层深度强化学习的无人机混合路径规划 [J ] . 北京航空航天大学学报 , 2023 : 1 - 13 .

LYU C , LI M C , OU J J . UAV hybrid path planning based on hierarchical deep reinforcement learning [J ] . Journal of Beijing University of Aeronautics and Astronautics , 2023 : 1 - 13 .

HE J , JIA Z Y , DONG C , et al . UAV swarm deployment and trajectory for 3D area coverage via reinforcement learning [C ] // Proceedings of the 2023 International Conference on Wireless Communications and Signal Processing (WCSP) . Piscataway : IEEE Press , 2023 : 683 - 688 .

方祝平 , 李理 , 唐荣 , 等 . 融合改进A * 和速度障碍法的无人机局部避障规划 [J ] . 电光与控制 , 2025 , 32 ( 7 ): 7 - 12 .

FANG Z P , LI L , TANG R , et al . Local obstacle avoidance planning of UAV combining improved a with velocity obstacle method [J ] . Electronics Optics & Control , 2025 , 32 ( 7 ): 7 - 12 .

WU T , ZHANG Z , JING F , et al . A dynamic path planning method for UAVs based on improved informed-RRT* fused dynamic windows [J ] . Drones , 2024 , 8 ( 10 ): 539 .

LINDQVIST B , MANSOURI S S , AGHA-MOHAMMADI A A , et al . Nonlinear MPC for collision avoidance and control of UAVs with dynamic obstacles [J ] . IEEE Robotics and Automation Letters , 2020 , 5 ( 4 ): 6001 - 6008 .

OLCAY E , MEEß H , ELGER G . Dynamic obstacle avoidance for UAVs using MPC and GP-based motion forecast [C ] // Proceedings of the 2024 European Control Conference (ECC) . Piscataway : IEEE Press , 2024 : 1024 - 1031 .

XU Z F , JIN H Y , HAN X M , et al . Intent prediction-driven model predictive control for UAV planning and navigation in dynamic environments [J ] . IEEE Robotics and Automation Letters , 2025 , 10 ( 5 ): 4946 - 4953 .

陆音 , 刘金志 , 张珉 . 一种模型辅助的联邦强化学习多无人机路径规划方法 [J ] . 电子与信息学报 , 2025 , 47 ( 5 ): 1368 - 1380 .

LU Y , LIU J Z , ZHANG M . A model-assisted federated reinforcement learning method for multi-UAV path planning [J ] . Journal of Electronics & Information Technology , 2025 , 47 ( 5 ): 1368 - 1380 .

THEILE M , BAYERLEIN H , NAI R , et al . UAV path planning using global and local map information with deep reinforcement learning [C ] // Proceedings of the 2021 20th International Conference on Advanced Robotics (ICAR) . Piscataway : IEEE Press , 2021 : 539 - 546 .

WESTHEIDER J , RÜCKIN J , POPOVIĆ M . Multi-UAV adaptive path planning using deep reinforcement learning [C ] // Proceedings of the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . Piscataway : IEEE Press , 2023 : 649 - 656 .

贾子晔 , 姜官旺 , 崔灿 , 等 . 面向低空智联网的分布式鲁棒任务卸载方法 [J ] . 电子与信息学报 , 2025 , 47 ( 5 ): 1450 - 1460 .

JIA Z Y , JIANG G W , CUI C , et al . Distributionally robust task offloading for low-altitude intelligent networks [J ] . Journal of Electronics & Information Technology , 2025 , 47 ( 5 ): 1450 - 1460 .

JAVAID S , SAEED N , QADIR Z , et al . Communication and control in collaborative UAVs: recent advances and future trends [J ] . IEEE Transactions on Intelligent Transportation Systems , 2023 , 24 ( 6 ): 5719 - 5739 .

朱奕安 , 何佳 , 贾子晔 , 等 . 基于ADS-B与Remote ID的低空智联网无人机监视性能分析 [J ] . 数据采集与处理 , 2025 , 40 ( 1 ): 27 - 44 .

ZHU Y A , HE J , JIA Z Y , et al . ADS-B and Remote ID based performance analysis for UAV surveillance in low-altitude intelligent networks [J ] . Journal of Data Acquisition and Processing , 2025 , 40 ( 1 ): 27 - 44 .

ZHANG Y F , JIA Z Y , DONG C , et al . Recurrent LSTM-based UAV trajectory prediction with ADS-B information [C ] // Proceedings of the GLOBECOM 2022-2022 IEEE Global Communications Conference . Piscataway : IEEE Press , 2022 : 1 - 6 .

JIA Z Y , SHENG M , LI J D , et al . LEO-satellite-assisted UAV: joint trajectory and data collection for Internet of remote things in 6G aerial access networks [J ] . IEEE Internet of Things Journal , 2021 , 8 ( 12 ): 9814 - 9826 .

TANG R , ZHANG R Z , XU Y J , et al . Deep reinforcement learning-based resource allocation for multi-UAV-assisted full-duplex wireless-powered IoT networks [J ] . IEEE Transactions on Cognitive Communications and Networking , 2024 , 10 ( 6 ): 2236 - 2251 .

XU Y J , LIU Z J , HUANG C W , et al . Robust resource allocation algorithm for energy-harvesting-based D2D communication underlaying UAV-assisted networks [J ] . IEEE Internet of Things Journal , 2021 , 8 ( 23 ): 17161 - 17171 .

李国权 , 林金朝 , 徐勇军 , 等 . 无人机辅助的NOMA网络用户分组与功率分配算法 [J ] . 通信学报 , 2020 , 41 ( 9 ): 21 - 28 .

LI G Q , LIN J Z , XU Y J , et al . User grouping and power allocation algorithm for UAV-aided NOMA network [J ] . Journal on Communications , 2020 , 41 ( 9 ): 21 - 28 .

ZHU Y A , JIA Z Y , WU Q H , et al . UAV trajectory tracking via RNN-enhanced IMM-KF with ADS-B data [C ] // Proceedings of the 2024 IEEE Wireless Communications and Networking Conference (WCNC) . Piscataway : IEEE Press , 2024 : 1 - 6 .

吴启晖 , 董超 , 贾子晔 , 等 . 低空智联网组网与控制理论方法 [J ] . 航空学报 , 2024 , 45 ( 3 ): 6 - 23 .

WU Q H , DONG C , JIA Z Y , et al . Networking and control mechanism for low-altitude intelligent networks [J ] . Acta Aeronautica et Astronautica Sinica , 2024 , 45 ( 3 ): 6 - 23 .

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