Integrated Radar and Missile System with Poisson-Prioritized Threat Management and PPN Guidance for Countering Multiple UAV Threats

Giselle Hage; Ari Santoso; Mochammad Sahal

doi:10.18196/jrc.v6i1.24894

Authors

Giselle Hage Institut Teknologi Sepuluh Nopember
Ari Santoso Institut Teknologi Sepuluh Nopember
Mochammad Sahal Institut Teknologi Sepuluh Nopember https://orcid.org/0000-0002-7943-8261

DOI:

https://doi.org/10.18196/jrc.v6i1.24894

Keywords:

Integrated Radar and Missile System, Pure Proportional Navigation Guidance, UAV Defense System, UAV Swarm Neutralization

Abstract

In military defense, critical infrastructure protection, and border and maritime surveillance, radar detection plays a critical role in neutralizing threats, since slight delays in detection can enable hostile UAVs to breach defenses and target critical objectives. This research proposes an air defense systems, consists of integrated radar and missile system, to detect and neutralize aerial threats. The radar detects UAVs, tracks their trajectories, and prioritizes threats according to the distance of UAVs within its detection range, incorporating Poisson-distributed probability to dynamically allocate missile resources, allowing the systems to cover broader threat zones, which is crucial for the real-time interception of multiple UAVs. Each UAV is equipped with a state feedback controller for accurate navigation, while the missile system consistently enhancing its trajectory to accurately track and intercept threats under PPN guidance. Simulated experiments indicate that the proposed system intercepted the aerial threats within its operational range and time constraints in various battlefield scenarios. The system’s effect within its operational radius has also been evaluated in an experiment designed to counter a swarm of 6 UAVs flies in a predefined formation. In this scenario, the air defense system successfully launched a missile towards UAV swarms that neutralized 83.33% of total identified threats. The proposed system can be an alternative air defense systems to confront UAV threats in battlefield situations, with potential application in disaster management, search and rescue, and early warning system.

References

J. Li et al., “RTPN method for cooperative interception of maneuvering target by gun-launched UAV,” Mathematical Biosciences and Engineering: MBE, vol. 19, no. 5, pp. 5190-5206, 2022.

M. Moreira, E. Papp, and R. Ventura, “Interception of Non-Cooperative UAVs,” 2019 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), pp. 120-125, 2019, doi: 10.1109/SSRR.2019.8848952.

A. Yang, X. Liang, Y. Hou, and M. Lv, “An Autonomous Cooperative Interception Method With Angle Constraints Using a Swarm of UAVs,” IEEE Transactions on Vehicular Technology, vol. 72, pp. 15436-15449, 2023, doi: 10.1109/TVT.2023.3298635.

N. Jia, Z. Yang, and K. Yang, “Operational Effectiveness Evaluation of the Swarming UAVs Combat System Based on a System Dynamics Model,” IEEE Access, vol. 7, pp. 25209-25224, 2019, doi: 10.1109/ACCESS.2019.2898728.

Q. Yang, J. Zhang, G. Shi, J. Hu, and Y. Wu, “Maneuver Decision of UAV in Short-Range Air Combat Based on Deep Reinforcement Learning,” IEEE Access, vol. 8, pp. 363-378, 2020, doi: 10.1109/ACCESS.2019.2961426.

N. Gomez, N. Pena, S. Rincon, S. Amaya, and J. Calderon, “Leader-follower Behavior in Multi-agent Systems for Search and Rescue Based on PSO Approach,” Conference Proceedings - IEEE SOUTHEASTCON, vol. 2022-March, pp. 413–420, 2022, doi: 10.1109/SoutheastCon48659.2022.9764133.

J. Hu, H. Niu, J. Carrasco, B. Lennox, and F. Arvin, “Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning,” IEEE Trans. Veh. Technol., vol. 69, no. 12, pp. 14413–14423, 2020, doi: 10.1109/TVT.2020.3034800.

N. Patrinopoulou, I. Daramouskas, D. Meimetis, V. Lappas, and V. Kostopoulos, “A Multi-Agent System Using Decentralized Decision-Making Techniques for Area Surveillance and Intruder Monitoring,” Drones, vol. 6, no. 11, 2022, doi: 10.3390/drones6110357.

B. G. Elkilany, A. A. Abouelsoud, A. M. R. Fathelbab, and H. Ishii, “A proposed decentralized formation control algorithm for robot swarm based on an optimized potential field method,” Neural Comput. Appl., vol. 33, no. 1, pp. 487–499, 2021, doi: 10.1007/s00521-020-05032-0.

M. Sahal, T. Agustinah, A. Jazidie, and H. Du, “Strategic Control in Cooperative Multi-Agent Moving Source Seeking with Obstacles Avoidance,” Int. J. Intell. Eng. Syst., vol. 16, no. 5, 2023.

X. Cao, M. Li, Y. Tao, and P. Lu, "HMA-SAR: Multi-Agent Search and Rescue for Unknown Located Dynamic Targets in Completely Unknown Environments," in IEEE Robotics and Automation Letters, vol. 9, no. 6, pp. 5567-5574, June 2024, doi: 10.1109/LRA.2024.3396097.

V. C. Maynad, Y. E. Nugraha, A. Alkaff, and C. Author, “Three-Dimensional Coordination Control of Multi-UAV for Partially Observable Multi-Target Tracking,” J. Res. Comput., vol. 5, no. 5, pp. 1227–1240, 2024, doi: 10.18196/jrc.v5i5.22560.

M. Sahal, T. Agustinah, and A. Jazidie, “Distributed Velocity Control in Cooperative Multi-Agent Moving Source Seeking,” Przegląd Elektrotechniczny, vol. 2023, no. 8, 2023.

V. M. Nuzhdin, A. E. Ananenkov, and D. V. Marin, “Radar of complex UAV detection and neutralization,” in Proc. 2021 Syst. Signals Generating Process. Field On-Board Commun., pp. 1–4, 2021.

M. N. Alpdemir, “Tactical UAV path optimization under radar threat using deep reinforcement learning,” Neural Comput. Appl., vol. 34, no. 7, pp. 5649–5664, 2022, doi: 10.1007/s00521-021-06702-3.

S. Shao, W. Zhu, and Y. Li, “Radar Detection of Low-Slow-Small UAVs in Complex Environments,” in Proc. 2022 IEEE 10th Joint Int. Inf. Technol. Artif. Intell. Conf. (ITAIC), vol. 10, pp. 1153–1157, 2022, doi: 10.1109/ITAIC54216.2022.9836542.

S. Rudys et al., “Hostile UAV Detection and Neutralization Using a UAV System,” Drones, vol. 6, no. 9, 2022.

F. Svanström, F. Alonso-Fernandez, and C. Englund, “Drone detection and tracking in real-time by fusion of different sensing modalities,” Drones, vol. 6, no. 11, p. 317, 2022, doi: 10.3390/drones6110317.

F. L. Chiper et al., “Drone detection and defense systems: Survey and a software-defined radio-based solution,” Sensors, vol. 22, no. 4, p. 1453, 2022, doi: 10.3390/s22041453.

C. Huang, I. Petrunin, and A. Tsourdos, “Radar-Camera Fusion for Ground-based Perception of Small UAV in Urban Air Mobility,” in Proc. 2023 IEEE 10th Int. Workshop Metrology AeroSpace (MetroAeroSpace), pp. 395–400, 2023.

C. Steffes, B. Demissie, M. Mandt, and M. Böswetter, “Surveillance of Critical Infrastructure using the LTE450 Network as Passive Radar Illuminator: Feasibility Study and Range Assessment,” in Proc. 2022 Sensor Data Fusion: Trends, Solut. Appl. (SDF), pp. 1–6, 2022, doi: 10.1109/SDF55338.2022.9931958.

Y. Lei, H. Yao, B. Jiang, T. Tian, and P. Xing, “Anti-UAV High-Performance Computing Early Warning Neural Network Based on PSO Algorithm,” Sci. Program., vol. 2022, 2022, doi: 10.1155/2022/7150128.

M. Rosamilia, A. Balleri, A. Maio, A. Aubry, and V. Carotenuto, “Radar Detection Performance Prediction Using Measured UAVs RCS Data,” IEEE Trans. Aerosp. Electron. Syst., vol. 59, pp. 3550–3565, 2023, doi: 10.1109/TAES.2022.3227224.

J. Zheng et al., “An Efficient Strategy for Accurate Detection and Localization of UAV Swarms,” IEEE Internet Things J., vol. 8, pp. 15372–15381, 2021, doi: 10.1109/JIOT.2021.3064376.

P. Zhu et al., "Detection and Tracking Meet Drones Challenge," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 11, pp. 7380-7399, 1 Nov. 2022, doi: 10.1109/TPAMI.2021.3119563.

A. Aldowesh, T. Alnuaim, and A. Alzogaiby, “Slow-Moving Micro-UAV detection with a small scale Digital Array Radar,” in Proc. 2019 IEEE Radar Conf. (RadarConf), pp. 1–5, 2019, doi: 10.1109/RADAR.2019.8835567.

A. Coluccia, G. Parisi, and A. Fascista, “Detection and classification of multirotor drones in radar sensor networks: A review,” Sensors, vol. 20, no. 15, p. 4172, 2020.

G. E. M. Abro, S. A. B. Zulkifli, R. J. Masood, V. S. Asirvadam, and A. Laouiti, “Comprehensive review of UAV detection, security, and communication advancements to prevent threats,” Drones, vol. 6, no. 10, p. 284, 2022.

I. Iswanto and I. Ahmad, “Second order integral fuzzy logic control based rocket tracking control,” J. Robot. Control (JRC), vol. 2, no. 6, pp. 594–604, 2021.

A. Eldosouky, A. Ferdowsi, and W. Saad, “Drones in Distress: A Game-Theoretic Countermeasure for Protecting UAVs Against GPS Spoofing,” IEEE Internet Things J., vol. 7, pp. 2840–2854, 2019, doi: 10.1109/JIOT.2019.2963337.

K. Zhou, R. Wei, Q. Zhang, and Z. Wu, “Research on Decision-making Method for Territorial Defense Based on Fuzzy Reinforcement Learning,” in Proc. 2019 Chinese Autom. Congr. (CAC), pp. 3759–3763, 2019, doi: 10.1109/CAC48633.2019.8996813.

W. Khawaja, V. Semkin, N. I. Ratyal, Q. Yaqoob, J. Gul, and I. Guvenc, “Threats from and countermeasures for unmanned aerial and underwater vehicles,” Sensors, vol. 22, no. 10, p. 3896, 2022.

J. Xie, Q. Fu, R. Jia, and M. Li, “Multi-UAV Path Planning under Radar Threats,” in Proc. 2023 IEEE Int. Conf. Smart Internet Things (SmartIoT), pp. 30–37, Aug. 2023.

V. P. Riabukha, “Radar surveillance of unmanned aerial vehicles,” Radioelectronics and Communications Systems, vol. 63, no. 11, pp. 561–573, 2020.

D. Xing, Z. Zhen, and H. Gong, “Offense–defense confrontation decision making for dynamic UAV swarm versus UAV swarm,” Proc. Inst. Mech. Eng. G: J. Aerosp. Eng., vol. 233, pp. 5689–5702, 2019.

R. Aievola et al., “Conflict Detection Performance of Ground-based Radar Networks for Urban Air Mobility,” in Proc. 2023 IEEE/AIAA 42nd Digit. Avion. Syst. Conf. (DASC), pp. 1–9, 2023, doi: 10.1109/DASC58513.2023.10311284.

Q. Xu, J. Ge, T. Yang, and X. Sun, “A trajectory design method for coupling aircraft radar cross-section characteristics,” Aerosp. Sci. Technol., vol. 98, p. 105653, 2020, doi: 10.1016/j.ast.2019.105653.

S. Singhal, S. Biswas, and S. Ram, “LEO/MEO-Based Multi-static Passive Radar Detection Performance Analysis Using Stochastic Geometry,” in Proc. 2023 IEEE Radar Conf. (RadarConf23), pp. 1–6, 2023, doi: 10.1109/RadarConf2351548.2023.10149574.

M. Kim et al., “Toward Optimal Placement of Spatial Sensors to Detect Poisson-Distributed Targets,” IEEE Access, vol. 11, pp. 121991–121998, 2023, doi: 10.1109/ACCESS.2023.3326349.

T. George, K. Wagner, and P. Rademacher, “Deep Q-network for radar task-scheduling problem,” in Proc. 2022 IEEE Radar Conf. (RadarConf22), pp. 1–5, March 2022.

J. Yan et al., “Collaborative detection and power allocation framework for target tracking in multiple radar system,” Inf. Fusion, vol. 55, pp. 173–183, 2020, doi: 10.1016/J.INFFUS.2019.08.010.

Y. Huang, Y. Shi, and T. Song, “An Efficient Multi-Path Multitarget Tracking Algorithm for Over-The-Horizon Radar,” Sensors (Basel), vol. 19, 2019, doi: 10.3390/s19061384.

X. Wang, B. Tang, and M. Zhang, “A Probabilistic Model-Based Robust Waveform Design for MIMO Radar Detection,” in Proc. 2021 CIE Int. Conf. Radar (Radar), pp. 1686–1690, 2021, doi: 10.1109/Radar53847.2021.10028035.

A. D. Brown, “Radar challenges, current solutions, and future advancements for the counter unmanned aerial systems mission,” IEEE Aerosp. Electron. Syst. Mag., vol. 38, no. 9, pp. 34–50, 2023.

H. Lan et al., “Joint Target Detection and Tracking in Multipath Environment: A Variational Bayesian Approach,” IEEE Trans. Aerosp. Electron. Syst., vol. 56, pp. 2136–2156, 2019, doi: 10.1109/TAES.2019.2942706.

L. Gao, G. Battistelli, L. Chisci, and A. Farina, “Fusion-Based Multidetection Multitarget Tracking With Random Finite Sets,” IEEE Trans. Aerosp. Electron. Syst., vol. 57, pp. 2438–2458, 2021, doi: 10.1109/TAES.2021.3059093.

H. Zhang et al., “Sensor Scheduling and Resource Allocation in Distributed MIMO Radar for Joint Target Tracking and Detection,” IEEE Access, vol. 7, pp. 62387–62400, 2019, doi: 10.1109/ACCESS.2019.2916334.

J. Yan et al., “Optimal Resource Allocation for Asynchronous Multiple Targets Tracking in Heterogeneous Radar Networks,” IEEE Trans. Signal Process., vol. 68, pp. 4055–4068, 2020, doi: 10.1109/TSP.2020.3007313.

J. Lee and J. Park, “Threat-Based Resource Allocation Strategy for Target Tracking in a Cognitive Radar Network,” arXiv preprint arXiv:2311.13906, 2023, doi: 10.48550/arXiv.2311.13906.

G. Frazer and C. Williams, “Decametric Radar for Missile Defense,” in Proc. 2019 IEEE Radar Conf. (RadarConf), pp. 1–6, 2019, doi: 10.1109/RADAR.2019.8835810.

M. S. Ismail, A. Ahmad, S. Ismail, and N. M. M. Yusop, “A review on Unmanned Aerial Vehicle (UAV) threats assessments,” in AIP Conf. Proc., vol. 2617, no. 1, Nov. 2022.

L. Szarka and I. Harmati, “Swarm based drone umbrellas to counter missiles,” in Proc. 2020 23rd Int. Symp. Meas. Control Robot. (ISMCR), pp. 1–6, 2020, doi: 10.1109/ISMCR51255.2020.9263747.

G. Frazer and C. Williams, “Decametric Radar for Missile Defense,” in Proc. 2019 IEEE Radar Conf. (RadarConf), pp. 1–6, 2019, doi: 10.1109/RADAR.2019.8835810.

Y. Liu et al., “Effective Capacity Based Power Allocation for the Coexistence of an Integrated Radar and Communication System and a Commercial Communication System,” IEEE Access, vol. 8, pp. 58629–58644, 2020, doi: 10.1109/ACCESS.2020.2983328.

Z. Liu, Y. Lv, J. Zhou, and L. Hu, “On 3D simultaneous attack against manoeuvring target with communication delays,” Int. J. Adv. Robot. Syst., vol. 17, 2020, doi: 10.1177/1729881419894808.

D. Guo et al., “Weapon-Target Assignment for Multi-to-Multi Interception With Grouping Constraint,” IEEE Access, vol. 7, pp. 34838–34849, 2019, doi: 10.1109/ACCESS.2019.2898874.

V. Kurtz and H. Lin, “Toward Verifiable Real-Time Obstacle Motion Prediction for Dynamic Collision Avoidance,” in Proc. 2019 Am. Control Conf. (ACC), pp. 2633–2638, 2019, doi: 10.23919/ACC.2019.8815387.

I. S. Asti, T. Agustinah, and A. Santoso, “Obstacle avoidance with energy efficiency and distance deviation using KNN algorithm for quadcopter,” in Proc. 2020 Int. Seminar Intell. Technol. Its Appl. (ISITIA), pp. 285–291, July 2020.

D. Huo et al., “Collision-Free Model Predictive Trajectory Tracking Control for UAVs in Obstacle Environment,” IEEE Trans. Aerosp. Electron. Syst., vol. 59, pp. 2920–2932, 2023, doi: 10.1109/TAES.2022.3221702.

Z. Niu, X. Jia, and W. Yao, “Communication-Free MPC-Based Neighbors Trajectory Prediction for Distributed Multi-UAV Motion Planning,” IEEE Access, vol. 10, pp. 13481–13489, 2022, doi: 10.1109/ACCESS.2022.3148145.

X. Zhang et al., “Trajectory Generation by Chance-Constrained Nonlinear MPC With Probabilistic Prediction,” IEEE Trans. Cybern., vol. 51, pp. 3616–3629, 2020, doi: 10.1109/TCYB.2020.3032711.

P. Wu, J. Xie, and J. Chen, “Safe Path Planning for Unmanned Aerial Vehicle under Location Uncertainty,” in Proc. 2020 IEEE 16th Int. Conf. Control Autom. (ICCA), pp. 342–347, 2020, doi: 10.1109/ICCA51439.2020.9264542.

B. Lindqvist, P. Sopasakis, and G. Nikolakopoulos, “A Scalable Distributed Collision Avoidance Scheme for Multi-agent UAV systems,” in Proc. 2021 IEEE/RSJ Int. Conf. Intell. Robots Syst. (IROS), pp. 9212–9218, 2021, doi: 10.1109/IROS51168.2021.9636293.

H. Huang et al., “Cooperative Collision Avoidance Method for Multi-UAV Based on Kalman Filter and Model Predictive Control,” in Proc. 2019 IEEE Int. Conf. Unmanned Syst. Artif. Intell. (ICUSAI), pp. 1–7, 2019, doi: 10.1109/ICUSAI47366.2019.9124863.

J. Kim and Y. Kim, “Impact Time Control Guidance with Finite-Time Convergence Based on Pure Proportional Navigation,” in Proc. 2019 18th Eur. Control Conf. (ECC), pp. 143–148, 2019, doi: 10.23919/ECC.2019.8795943.

R. Wang and S. Tang, “Intercepting Higher-Speed Targets Using Generalized Relative Biased Proportional Navigation,” J. Northwest. Polytech. Univ., 2019, doi: 10.1051/jnwpu/20193740682.

N. Singh and S. Hota, “FOV constrained guidance law for nonstationary nonmaneuvering target interception with any impact angle,” Proc. Inst. Mech. Eng. G: J. Aerosp. Eng., vol. 236, pp. 1947–1960, 2021, doi: 10.1177/09544100211046867.

E. Kapeel et al., “Evaluation of Missile Terminal Guidance Using Software in Loop (SIL),” in Proc. 2020 12th Int. Conf. Electr. Eng. (ICEENG), pp. 389–395, 2020, doi: 10.1109/ICEENG45378.2020.9171703.

K. Song et al., “A New Guidance Algorithm Against High-Speed Maneuvering Target,” Int. J. Aeronaut. Space Sci., pp. 1–13, 2021.

R. Zhang et al., “IMMPDA Algorithm for Missile Tracking in Clutter,” in Proc. 2021 Int. Conf. Control Autom. Inf. Sci. (ICCAIS), pp. 178–182, 2021, doi: 10.1109/ICCAIS52680.2021.9624617.

Y. Wang, H. Wang, D. Lin, and W. Wang, “Nonlinear modified bias proportional navigation guidance law against maneuvering targets,” Journal of the Franklin Institute, vol. 359, no. 7, pp. 2949-2975, 2022.

H. Shin and K. Li, “An Improvement in Three-Dimensional Pure Proportional Navigation Guidance,” IEEE Trans. Aerosp. Electron. Syst., vol. 57, pp. 3004–3014, 2021, doi: 10.1109/TAES.2021.3067656.

N. K. Singh and S. Hota, “Time-optimal moving target interception with impact angle constraint,” Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, vol. 237, no. 7, pp. 1600-1613, 2023.

A. Ranjan, S. Hota, and N. Singh, “Three-Stage Proportional Navigation for Intercepting Stationary Targets with Impact Angle Constraints,” in Proc. 2019 Sixth Indian Control Conf. (ICC), pp. 379–384, 2019, doi: 10.1109/ICC47138.2019.9123163.

V. Markevich and V. Legkostup, “Modified method of proportional navigation to intercept aeroballistic targets with a limited sector guidance of missile,” Syst. Anal. Appl. Inf. Sci., vol. 4, pp. 28–50, 2019.

J. Wu, W. Yuan, and L. Bai, “On the Interplay Between Sensing and Communications for UAV Trajectory Design,” IEEE Internet Things J., vol. 10, pp. 20383–20395, 2023, doi: 10.1109/JIOT.2023.3287991.

H. Yang et al., “A Distributed Cooperative Tracking Algorithm for the Interception of Small Patrol UAVs,” in Proc. 2023 42nd Chinese Control Conf. (CCC), pp. 3859–3865, 2023.

L. Ding et al., “Research on Collaborative Detection and Location Method of Infrared and Radar Aircraft Based on Federated Filter,” in Proc. 2021 6th Int. Conf. Multimedia Syst. Signal Process., 2021, doi: 10.1145/3471261.3471271.

C. Yu et al., “Research on Strategy of Breaking Through Multi-UAV Defense,” in Proc. 2021 33rd Chinese Control Decis. Conf. (CCDC), pp. 7525–7531, 2021, doi: 10.1109/CCDC52312.2021.9601995.

Y. Luo et al., “UAV-Cooperative Penetration Dynamic-Tracking Interceptor Method Based on DDPG,” Appl. Sci., vol. 12, no. 3, p. 1618, 2022, doi: 10.3390/app12031618.

M. Kratky et al., “Electronic Warfare Methods Combatting UAVs,” Adv. Sci. Technol. Eng. Syst. J., vol. 5, pp. 447–454, 2020.

J. Goricanec et al., “Collision-Free Trajectory Following With Augmented Artificial Potential Field Using UAVs,” IEEE Access, vol. 11, pp. 83492–83506, 2023, doi: 10.1109/ACCESS.2023.3303109.

H. Xie et al., “Three-Dimensional Path Planning of UAV Based on Improved Artificial Potential Field,” in Proc. 2021 40th Chinese Control Conf. (CCC), pp. 7862–7867, 2021.

C. Kownacki, “Artificial Potential Field Based Trajectory Tracking for Quadcopter UAV Moving Targets,” Sensors, vol. 24, no. 4, p. 1343, 2024.

X. Lu, “Improved path planning method for unmanned aerial vehicles based on artificial potential field,” Appl. Comput. Eng., vol. 10, no. 1, pp. 64-71, 2023, doi: 10.54254/2755-2721/10/20230142.

X. Fang et al., “JTEA: A Joint Trajectory Tracking and Estimation Approach for Low-Observable Micro-UAV Monitoring With 4-D Radar,” IEEE Trans. Instrum. Meas., vol. 73, pp. 1–14, 2024, doi: 10.1109/TIM.2023.3338650.

Z. Xia et al., “Multi-Agent Reinforcement Learning Aided Intelligent UAV Swarm for Target Tracking,” IEEE Trans. Veh. Technol., vol. 71, pp. 931–945, 2022, doi: 10.1109/TVT.2021.3129504.

J. Zhang et al., “A Many-to-Many UAV Pursuit and Interception Strategy Based on PERMADDPG,” in Proc. 2023 5th Int. Conf. Robot. Comput. Vis. (ICRCV), pp. 234–240, 2023, doi: 10.1109/ICRCV59470.2023.10329206.

X. Wang et al., “An Optimal Guidance Strategy for Moving-Target Interception by a Multirotor Unmanned Aerial Vehicle Swarm,” IEEE Access, vol. 8, pp. 121650–121664, 2020, doi: 10.1109/ACCESS.2020.3006479.

M. Sahal, V. C. Maynad, and Y. Bilfaqih, “Cooperative Formation and Obstacle Avoidance Control for Multi-UAV Based on Guidance Route and Artificial Potential Field,” J. Robot. Control (JRC), vol. 5, no. 6, pp. 1772–1783, 2024.

S. Nurjanah, T. Agustinah, and M. Fuad, “Cooperative position-based formation-pursuit of moving targets by multi-UAVs with collision avoidance,” JAREE (J. Adv. Res. Electr. Eng.), vol. 6, no. 2, 2022.

M. Sahal, T. Agustinah, and A. Jazidie, “Switching formation and topology in cooperative multi-agent source seeking using gradient estimation,” in Proc. 2019 Int. Conf. Artif. Intell. Inf. Technol. (ICAIIT), pp. 151–156, 2019, doi: 10.1109/ICAIIT.2019.9123163.

C. Xu, M. Xu, and C. Yin, “Optimized multi-UAV cooperative path planning under the complex confrontation environment,” Comput. Commun., vol. 162, pp. 196–203, 2020.

Z. Tian et al., “Missile Threat Detection and Evasion Maneuvers With Countermeasures for a Low-Altitude Aircraft,” IEEE Trans. Aerosp. Electron. Syst., vol. 59, no. 6, pp. 7352–7362, 2023.