{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T03:00:02Z","timestamp":1769050802987,"version":"3.49.0"},"reference-count":114,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T00:00:00Z","timestamp":1765929600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T00:00:00Z","timestamp":1768953600000},"content-version":"vor","delay-in-days":35,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/100019457","name":"Chips Joint Undertaking","doi-asserted-by":"publisher","award":["101140226"],"award-info":[{"award-number":["101140226"]}],"id":[{"id":"10.13039\/100019457","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100019457","name":"Chips Joint Undertaking","doi-asserted-by":"publisher","award":["101140226"],"award-info":[{"award-number":["101140226"]}],"id":[{"id":"10.13039\/100019457","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100019457","name":"Chips Joint Undertaking","doi-asserted-by":"publisher","award":["101140226"],"award-info":[{"award-number":["101140226"]}],"id":[{"id":"10.13039\/100019457","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100019457","name":"Chips Joint Undertaking","doi-asserted-by":"publisher","award":["101140226"],"award-info":[{"award-number":["101140226"]}],"id":[{"id":"10.13039\/100019457","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["EURASIP J. Adv. Signal Process."],"DOI":"10.1186\/s13634-025-01269-w","type":"journal-article","created":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T05:04:13Z","timestamp":1765947853000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A review of localization and sensing technologies for UAV swarms in SAR missions"],"prefix":"10.1186","volume":"2026","author":[{"given":"Dimitris","family":"Georgiadis","sequence":"first","affiliation":[]},{"given":"Elena","family":"Politi","sequence":"additional","affiliation":[]},{"given":"Selim","family":"Solmaz","sequence":"additional","affiliation":[]},{"given":"George","family":"Dimitrakopoulos","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,12,17]]},"reference":[{"key":"1269_CR1","doi-asserted-by":"publisher","DOI":"10.3390\/drones6060147","author":"SAH Mohsan","year":"2022","unstructured":"S.A.H. Mohsan, M.A. Khan, F. Noor, I. Ullah, M.H. Alsharif, Towards the unmanned aerial vehicles (uavs): a comprehensive review. Drones (2022). https:\/\/doi.org\/10.3390\/drones6060147","journal-title":"Drones"},{"key":"1269_CR2","doi-asserted-by":"crossref","unstructured":"A. Phadke, F.A. Medrano, T. Chu, C.N. Sekharan, M.J. Starek, Drone2drone (d2d): a search and rescue framework module for finding lost uav swarm agents. In: 2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE), pp. 903\u2013908 (2023). IEEE","DOI":"10.1109\/CSCE60160.2023.00153"},{"issue":"3","key":"1269_CR3","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-020-3188-4","volume":"66","author":"X Hou","year":"2023","unstructured":"X. Hou, Z. Li, Q. Pan, Autonomous navigation of a multirotor robot in gnss-denied environments for search and rescue. SCI. CHINA Inf. Sci. 66(3), 139203 (2023)","journal-title":"SCI. CHINA Inf. Sci."},{"issue":"2","key":"1269_CR4","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1007\/s42797-023-00071-x","volume":"5","author":"J Ash","year":"2023","unstructured":"J. Ash, Flying against the clock-risk management and resilience in arctic search and rescue and casualty evacuation flights. Safety in extreme environments 5(2), 79\u201389 (2023)","journal-title":"Safety in extreme environments"},{"issue":"19","key":"1269_CR5","doi-asserted-by":"publisher","first-page":"4953","DOI":"10.3390\/rs14194953","volume":"14","author":"V Lukas","year":"2022","unstructured":"V. Lukas, I. Hu\u0148ady, A. Kintl, J. Mezera, T. Hammerschmiedt, J. Sobotkov\u00e1, M. Brtnick\u1ef3, J. Elbl, Using uav to identify the optimal vegetation index for yield prediction of oil seed rape (brassica napus L.) at the flowering stage. Remote Sens. 14(19), 4953 (2022)","journal-title":"Remote Sens."},{"issue":"10","key":"1269_CR6","doi-asserted-by":"publisher","DOI":"10.3390\/rs15102511","volume":"15","author":"MS Mia","year":"2023","unstructured":"M.S. Mia, R. Tanabe, L.N. Habibi, N. Hashimoto, K. Homma, M. Maki, T. Matsui, T.S. Tanaka, Multimodal deep learning for rice yield prediction using uav-based multispectral imagery and weather data. Remote Sens. 15(10), 2511 (2023)","journal-title":"Remote Sens."},{"key":"1269_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.srs.2021.100019","volume":"3","author":"E Alvarez-Vanhard","year":"2021","unstructured":"E. Alvarez-Vanhard, T. Corpetti, T. Houet, Uav & satellite synergies for optical remote sensing applications: a literature review. Sci. Remote Sens. 3, 100019 (2021)","journal-title":"Sci. Remote Sens."},{"issue":"1","key":"1269_CR8","volume":"2022","author":"M Khelifi","year":"2022","unstructured":"M. Khelifi, I. Butun, Swarm unmanned aerial vehicles (suavs): a comprehensive analysis of localization, recent aspects, and future trends. J. Sens. 2022(1), 8600674 (2022)","journal-title":"J. Sens."},{"issue":"1","key":"1269_CR9","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1109\/LRA.2023.3333742","volume":"9","author":"P-Y Lajoie","year":"2023","unstructured":"P.-Y. Lajoie, G. Beltrame, Swarm-slam: sparse decentralized collaborative simultaneous localization and mapping framework for multi-robot systems. IEEE Robot. Autom. Lett. 9(1), 475\u2013482 (2023)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"1269_CR10","doi-asserted-by":"publisher","DOI":"10.3390\/s21113820","author":"ZA Ali","year":"2021","unstructured":"Z.A. Ali, Z. Han, R.J. Masood, Collective motion and self-organization of a swarm of uavs: a cluster-based architecture. Sensors (2021). https:\/\/doi.org\/10.3390\/s21113820","journal-title":"Sensors"},{"key":"1269_CR11","doi-asserted-by":"crossref","unstructured":"M. Kowshika, M. Ooviya, B. Pavithradevi, K. Rashika, S. Sampath\u00a0Kumar, Unmanned aerial systems in search and rescue: a comprehensive review and future directions. In: 2024 5th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI), pp. 15\u201318 (2024). IEEE","DOI":"10.1109\/ICMCSI61536.2024.00008"},{"key":"1269_CR12","doi-asserted-by":"publisher","DOI":"10.3390\/s19194349","author":"A Viseras","year":"2019","unstructured":"A. Viseras, T. Wiedemann, C. Manss, V. Karolj, D. Shutin, J. Marchal, Beehive-inspired information gathering with a swarm of autonomous drones. Sensors (2019). https:\/\/doi.org\/10.3390\/s19194349","journal-title":"Sensors"},{"key":"1269_CR13","doi-asserted-by":"publisher","first-page":"53698","DOI":"10.1109\/ACCESS.2019.2913448","volume":"7","author":"L Amorosi","year":"2019","unstructured":"L. Amorosi, L. Chiaraviglio, J. Galan-Jimenez, Optimal energy management of uav-based cellular networks powered by solar panels and batteries: formulation and solutions. IEEE Access 7, 53698\u201353717 (2019)","journal-title":"IEEE Access"},{"issue":"12","key":"1269_CR14","doi-asserted-by":"publisher","first-page":"605","DOI":"10.2514\/1.12823","volume":"1","author":"JD Boskovic","year":"2004","unstructured":"J.D. Boskovic, R. Prasanth, R.K. Mehra, A multi-layer autonomous intelligent control architecture for unmanned aerial vehicles. J. Aerosp. Comput. Inf. Commun. 1(12), 605\u2013628 (2004)","journal-title":"J. Aerosp. Comput. Inf. Commun."},{"key":"1269_CR15","doi-asserted-by":"publisher","unstructured":"Q. Zong, D. Wang, S. Shao, B. Zhang, Y. Han, Research status and development of multi uav coordinated formation flight control. Harbin Gongye Daxue Xuebao\/Journal of Harbin Institute of Technology 49, 1\u201314 (2017) https:\/\/doi.org\/10.11918\/j.issn.0367-6234.2017.03.001","DOI":"10.11918\/j.issn.0367-6234.2017.03.001"},{"key":"1269_CR16","doi-asserted-by":"publisher","DOI":"10.3390\/drones8070320","author":"Y Bu","year":"2024","unstructured":"Y. Bu, Y. Yan, Y. Yang, Advancement challenges in uav swarm formation control: a comprehensive review. Drones (2024). https:\/\/doi.org\/10.3390\/drones8070320","journal-title":"Drones"},{"key":"1269_CR17","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.jprocont.2017.09.002","volume":"59","author":"J Ebegbulem","year":"2017","unstructured":"J. Ebegbulem, M. Guay, Distributed control of multi-agent systems over unknown communication networks using extremum seeking. J. Process Control 59, 37\u201348 (2017). https:\/\/doi.org\/10.1016\/j.jprocont.2017.09.002","journal-title":"J. Process Control"},{"key":"1269_CR18","doi-asserted-by":"publisher","DOI":"10.3390\/drones7030185","author":"C Tao","year":"2023","unstructured":"C. Tao, R. Zhang, Z. Song, B. Wang, Y. Jin, Multi-uav formation control in complex conditions based on improved consistency algorithm. Drones (2023). https:\/\/doi.org\/10.3390\/drones7030185","journal-title":"Drones"},{"key":"1269_CR19","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1016\/j.comcom.2019.10.014","volume":"149","author":"S Aggarwal","year":"2020","unstructured":"S. Aggarwal, N. Kumar, Path planning techniques for unmanned aerial vehicles: a review, solutions, and challenges. Comput. Commun. 149, 270\u2013299 (2020)","journal-title":"Comput. Commun."},{"issue":"21","key":"1269_CR20","doi-asserted-by":"publisher","first-page":"4019","DOI":"10.3390\/rs16214019","volume":"16","author":"D Debnath","year":"2024","unstructured":"D. Debnath, F. Vanegas, J. Sandino, A.F. Hawary, F. Gonzalez, A review of UAV path-planning algorithms and obstacle avoidance methods for remote sensing applications. Remote Sens. 16(21), 4019 (2024)","journal-title":"Remote Sens."},{"issue":"1","key":"1269_CR21","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1177\/09544100211007381","volume":"236","author":"Z Zhang","year":"2022","unstructured":"Z. Zhang, J. Wu, J. Dai, C. He, Optimal path planning with modified A-star algorithm for stealth unmanned aerial vehicles in 3D network radar environment. Proc. Inst. Mech. Eng. G, J. Aerosp. Eng. 236(1), 72\u201381 (2022)","journal-title":"Proc. Inst. Mech. Eng. G, J. Aerosp. Eng."},{"issue":"10","key":"1269_CR22","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1007\/s10462-024-10913-0","volume":"57","author":"Y Jiang","year":"2024","unstructured":"Y. Jiang, X.-X. Xu, M.-Y. Zheng, Z.-H. Zhan, Evolutionary computation for unmanned aerial vehicle path planning: a survey. Artif. Intell. Rev. 57(10), 267 (2024)","journal-title":"Artif. Intell. Rev."},{"key":"1269_CR23","doi-asserted-by":"publisher","first-page":"70353","DOI":"10.1109\/ACCESS.2023.3293203","volume":"11","author":"A Sonny","year":"2023","unstructured":"A. Sonny, S.R. Yeduri, L.R. Cenkeramaddi, Autonomous UAV path planning using modified PSO for UAV-assisted wireless networks. IEEE Access 11, 70353\u201370367 (2023)","journal-title":"IEEE Access"},{"key":"1269_CR24","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3326435","author":"C Chronis","year":"2023","unstructured":"C. Chronis, G. Anagnostopoulos, E. Politi, G. Dimitrakopoulos, I. Varlamis, Dynamic navigation in unconstrained environments using reinforcement learning algorithms. IEEE Access (2023). https:\/\/doi.org\/10.1109\/ACCESS.2023.3326435","journal-title":"IEEE Access"},{"key":"1269_CR25","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2024.3369485","author":"Z Wang","year":"2024","unstructured":"Z. Wang, W. Gao, G. Li, Z. Wang, M. Gong, Path planning for unmanned aerial vehicle via off-policy reinforcement learning with enhanced exploration. IEEE Trans. Emerg. Top. Comput. Intell. (2024). https:\/\/doi.org\/10.1109\/TETCI.2024.3369485","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"issue":"12","key":"1269_CR26","doi-asserted-by":"publisher","first-page":"14101","DOI":"10.1007\/s10489-022-03254-4","volume":"52","author":"A Puente-Castro","year":"2022","unstructured":"A. Puente-Castro, D. Rivero, A. Pazos, E. Fernandez-Blanco, UAV swarm path planning with reinforcement learning for field prospecting. Appl. Intell. 52(12), 14101\u201314118 (2022)","journal-title":"Appl. Intell."},{"issue":"3","key":"1269_CR27","doi-asserted-by":"publisher","first-page":"675","DOI":"10.1080\/02564602.2021.1894250","volume":"39","author":"A Sharma","year":"2022","unstructured":"A. Sharma, S. Shoval, A. Sharma, J.K. Pandey, Path planning for multiple targets interception by the swarm of UAVs based on swarm intelligence algorithms: a review. IETE Tech. Rev. 39(3), 675\u2013697 (2022)","journal-title":"IETE Tech. Rev."},{"key":"1269_CR28","doi-asserted-by":"publisher","first-page":"105086","DOI":"10.1109\/ACCESS.2019.2932008","volume":"7","author":"Y Wang","year":"2019","unstructured":"Y. Wang, P. Bai, X. Liang, W. Wang, J. Zhang, Q. Fu, Reconnaissance mission conducted by UAV swarms based on distributed PSO path planning algorithms. IEEE Access 7, 105086\u2013105099 (2019)","journal-title":"IEEE Access"},{"issue":"1","key":"1269_CR29","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.cja.2021.01.014","volume":"35","author":"Z Jiang","year":"2022","unstructured":"Z. Jiang, S. Jiaming, C. Zhihao, W. Yingxun, W. Kun, Distributed coordinated control scheme of UAV swarm based on heterogeneous roles. Chin. J. Aeronaut. 35(1), 81\u201397 (2022)","journal-title":"Chin. J. Aeronaut."},{"key":"1269_CR30","doi-asserted-by":"crossref","unstructured":"X. Fu, J. Pan, H. Wang, X. Gao, A formation maintenance and reconstruction method of uav swarm based on distributed control with obstacle avoidance. In: 2019 Australian & New Zealand Control Conference (ANZCC), pp. 205\u2013209 (2019). IEEE","DOI":"10.1109\/ANZCC47194.2019.8945601"},{"key":"1269_CR31","doi-asserted-by":"publisher","first-page":"61786","DOI":"10.1109\/ACCESS.2019.2916004","volume":"7","author":"F Dai","year":"2019","unstructured":"F. Dai, M. Chen, X. Wei, H. Wang, Swarm intelligence-inspired autonomous flocking control in UAV networks. IEEE Access 7, 61786\u201361796 (2019)","journal-title":"IEEE Access"},{"issue":"2","key":"1269_CR32","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1016\/j.cja.2020.03.006","volume":"34","author":"C Hao","year":"2021","unstructured":"C. Hao, W. Xiangke, S. Lincheng, C. Yirui, Formation flight of fixed-wing UAV swarms: a group-based hierarchical approach. Chin. J. Aeronaut. 34(2), 504\u2013515 (2021)","journal-title":"Chin. J. Aeronaut."},{"issue":"2","key":"1269_CR33","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1016\/j.cja.2019.08.009","volume":"33","author":"S Guibin","year":"2020","unstructured":"S. Guibin, Z. Rui, X. Kun, W. Zhi, Y. Zhang, D. Zhuoning, W. Yingxun, Cooperative formation control of multiple aerial vehicles based on guidance route in a complex task environment. Chin. J. Aeronaut. 33(2), 701\u2013720 (2020)","journal-title":"Chin. J. Aeronaut."},{"key":"1269_CR34","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3364230","author":"S Javed","year":"2024","unstructured":"S. Javed, A. Hassan, R. Ahmad, W. Ahmed, R. Ahmed, A. Saadat, M. Guizani, State-of-the-art and future research challenges in UAV swarms. IEEE Internet Things J. (2024). https:\/\/doi.org\/10.1109\/JIOT.2024.3364230","journal-title":"IEEE Internet Things J."},{"key":"1269_CR35","doi-asserted-by":"crossref","unstructured":"B. Sliwa, M. Patchou, K. Heimann, C. Wietfeld, Simulating hybrid aerial-and ground-based vehicular networks with ns-3 and limosim. In: Proceedings of the 2020 Workshop on Ns-3, pp. 1\u20138 (2020)","DOI":"10.1145\/3389400.3389407"},{"issue":"4","key":"1269_CR36","doi-asserted-by":"publisher","first-page":"3792","DOI":"10.1109\/TVT.2019.2902177","volume":"68","author":"J Chen","year":"2019","unstructured":"J. Chen, Y. Xu, Q. Wu, Y. Zhang, X. Chen, N. Qi, Interference-aware online distributed channel selection for multicluster FANET: a potential game approach. IEEE Trans. Veh. Technol. 68(4), 3792\u20133804 (2019)","journal-title":"IEEE Trans. Veh. Technol."},{"key":"1269_CR37","doi-asserted-by":"publisher","first-page":"498","DOI":"10.1109\/ACCESS.2018.2885539","volume":"7","author":"MY Arafat","year":"2018","unstructured":"M.Y. Arafat, S. Moh, A survey on cluster-based routing protocols for unmanned aerial vehicle networks. IEEE Access 7, 498\u2013516 (2018)","journal-title":"IEEE Access"},{"key":"1269_CR38","doi-asserted-by":"publisher","first-page":"94593","DOI":"10.1109\/ACCESS.2019.2926741","volume":"7","author":"Y Li","year":"2019","unstructured":"Y. Li, R. Zhang, J. Zhang, S. Gao, L. Yang, Cooperative jamming for secure UAV communications with partial eavesdropper information. IEEE Access 7, 94593\u201394603 (2019)","journal-title":"IEEE Access"},{"key":"1269_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2021.108264","volume":"196","author":"H Touati","year":"2021","unstructured":"H. Touati, A. Chriki, H. Snoussi, F. Kamoun, Cognitive radio and dynamic TDMA for efficient UAVs swarm communications. Comput. Netw. 196, 108264 (2021)","journal-title":"Comput. Netw."},{"key":"1269_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.phycom.2020.101159","volume":"42","author":"S Khan","year":"2020","unstructured":"S. Khan, M. Zeeshan, Y. Ayaz, Implementation and analysis of multicode multicarrier code division multiple access (mc\u2013mc cdma) in IEEE 802.11 ah for UAV swarm communication. Phys. Commun. 42, 101159 (2020)","journal-title":"Phys. Commun."},{"issue":"3","key":"1269_CR41","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1109\/TRA.2004.825275","volume":"20","author":"HG Tanner","year":"2004","unstructured":"H.G. Tanner, G.J. Pappas, V. Kumar, Leader-to-formation stability. IEEE Trans. Robot. Autom. 20(3), 443\u2013455 (2004)","journal-title":"IEEE Trans. Robot. Autom."},{"issue":"10","key":"1269_CR42","doi-asserted-by":"publisher","first-page":"1597","DOI":"10.1016\/j.robot.2014.05.002","volume":"62","author":"V Rold\u00e3o","year":"2014","unstructured":"V. Rold\u00e3o, R. Cunha, D. Cabecinhas, C. Silvestre, P. Oliveira, A leader-following trajectory generator with application to quadrotor formation flight. Robot. Auton. Syst. 62(10), 1597\u20131609 (2014). https:\/\/doi.org\/10.1016\/j.robot.2014.05.002","journal-title":"Robot. Auton. Syst."},{"key":"1269_CR43","doi-asserted-by":"publisher","DOI":"10.3390\/s20154324","author":"SR Bassolillo","year":"2020","unstructured":"S.R. Bassolillo, E. D\u2019Amato, I. Notaro, L. Blasi, M. Mattei, Decentralized mesh-based model predictive control for swarms of UAVs. Sensors (2020). https:\/\/doi.org\/10.3390\/s20154324","journal-title":"Sensors"},{"key":"1269_CR44","doi-asserted-by":"crossref","unstructured":"B. Vik, T.I. Fossen, A nonlinear observer for gps and ins integration. In: Proceedings of the 40th IEEE Conference on Decision and Control (cat. No. 01CH37228), vol. 3, pp. 2956\u20132961 (2001). IEEE","DOI":"10.1109\/CDC.2001.980726"},{"issue":"6","key":"1269_CR45","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1016\/j.ast.2010.08.011","volume":"15","author":"TS No","year":"2011","unstructured":"T.S. No, Y. Kim, M.-J. Tahk, G.-E. Jeon, Cascade-type guidance law design for multiple-UAV formation keeping. Aerosp. Sci. Technol. 15(6), 431\u2013439 (2011). https:\/\/doi.org\/10.1016\/j.ast.2010.08.011","journal-title":"Aerosp. Sci. Technol."},{"key":"1269_CR46","doi-asserted-by":"publisher","DOI":"10.3390\/s19204584","author":"P Garcia-Aunon","year":"2019","unstructured":"P. Garcia-Aunon, J. Cerro, A. Barrientos, Behavior-based control for an aerial robotic swarm in surveillance missions. Sensors (2019). https:\/\/doi.org\/10.3390\/s19204584","journal-title":"Sensors"},{"issue":"11","key":"1269_CR47","doi-asserted-by":"publisher","DOI":"10.1016\/j.cja.2025.103445","volume":"38","author":"S Yue","year":"2025","unstructured":"S. Yue, D. Zheng, M. Wei, Z. Chu, D. Lin, Behavior-based cooperative control method for fixed-wing UAV swarm through a virtual tube considering safety constraints. Chin. J. Aeronaut. , 103445 (2025). https:\/\/doi.org\/10.1016\/j.cja.2025.103445","journal-title":"Chin. J. Aeronaut."},{"key":"1269_CR48","unstructured":"P. Garc\u00eda\u00a0Au\u00f1\u00f3n, Behavior-based search and surveillance algorithm for aerial robtic swarms. PhD thesis, Industriales (2020)"},{"issue":"1","key":"1269_CR49","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/205759","volume":"2014","author":"D Xu","year":"2014","unstructured":"D. Xu, X. Zhang, Z. Zhu, C. Chen, P. Yang, Behavior-based formation control of swarm robots. Math. Probl. Eng. 2014(1), 205759 (2014)","journal-title":"Math. Probl. Eng."},{"key":"1269_CR50","unstructured":"N.H. Li, H.H. Liu, Formation uav flight control using virtual structure and motion synchronization. In: 2008 American Control Conference, pp. 1782\u20131787 (2008). IEEE"},{"key":"1269_CR51","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1007\/978-3-319-17518-8_24","volume-title":"Advances in Aerospace Guidance, Navigation and Control: Selected Papers of the Third CEAS Specialist Conference on Guidance, Navigation and Control Held in Toulouse","author":"C Kownacki","year":"2015","unstructured":"C. Kownacki, D. O\u0142dziej, Flocking algorithm for fixed-wing unmanned aerial vehicles, in Advances in Aerospace Guidance, Navigation and Control: Selected Papers of the Third CEAS Specialist Conference on Guidance, Navigation and Control Held in Toulouse. (Springer, 2015), pp.415\u2013431"},{"key":"1269_CR52","doi-asserted-by":"publisher","DOI":"10.1515\/ama-2016-0015","author":"C Kownacki","year":"2016","unstructured":"C. Kownacki, Multi-uav flight using virtual structure combined with behavioral approach. Acta Mech. Autom. (2016). https:\/\/doi.org\/10.1515\/ama-2016-0015","journal-title":"Acta Mech. Autom."},{"key":"1269_CR53","doi-asserted-by":"crossref","unstructured":"C.W. Reynolds, Flocks, herds and schools: a distributed behavioral model. In: Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques, pp. 25\u201334 (1987)","DOI":"10.1145\/37401.37406"},{"issue":"7","key":"1269_CR54","doi-asserted-by":"publisher","first-page":"1147","DOI":"10.1016\/j.mechatronics.2011.06.006","volume":"21","author":"H Mehrjerdi","year":"2011","unstructured":"H. Mehrjerdi, J. Ghommam, M. Saad, Nonlinear coordination control for a group of mobile robots using a virtual structure. Mechatronics 21(7), 1147\u20131155 (2011). https:\/\/doi.org\/10.1016\/j.mechatronics.2011.06.006","journal-title":"Mechatronics"},{"issue":"1","key":"1269_CR55","doi-asserted-by":"publisher","first-page":"73","DOI":"10.2514\/1.9287","volume":"27","author":"W Ren","year":"2004","unstructured":"W. Ren, R.W. Beard, Decentralized scheme for spacecraft formation flying via the virtual structure approach. J. Guid. Control. Dyn. 27(1), 73\u201382 (2004)","journal-title":"J. Guid. Control. Dyn."},{"key":"1269_CR56","doi-asserted-by":"crossref","unstructured":"J. Seo, C. Ahn, Y. Ahn, Controller design for uav formation flight using consensus based decentralized approach. In: AIAA Infotech@ Aerospace Conference and AIAA Unmanned... Unlimited Conference, p. 1826 (2009)","DOI":"10.2514\/6.2009-1826"},{"issue":"4","key":"1269_CR57","doi-asserted-by":"publisher","first-page":"912","DOI":"10.1109\/TRO.2009.2022423","volume":"25","author":"H-L Choi","year":"2009","unstructured":"H.-L. Choi, L. Brunet, J.P. How, Consensus-based decentralized auctions for robust task allocation. IEEE Trans. Rob. 25(4), 912\u2013926 (2009). https:\/\/doi.org\/10.1109\/TRO.2009.2022423","journal-title":"IEEE Trans. Rob."},{"key":"1269_CR58","doi-asserted-by":"crossref","unstructured":"D. Dionne, C.A. Rabbath, Multi-uav decentralized task allocation with intermittent communications: the dtc algorithm. In: 2007 American Control Conference, pp. 5406\u20135411 (2007). IEEE","DOI":"10.1109\/ACC.2007.4282637"},{"key":"1269_CR59","doi-asserted-by":"crossref","unstructured":"E. Falomir, S. Chaumette, G. Guerrini, A mobility model based on improved artificial potential fields for swarms of uavs. In: 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 8499\u20138504 (2018). IEEE","DOI":"10.1109\/IROS.2018.8593738"},{"key":"1269_CR60","doi-asserted-by":"publisher","first-page":"78342","DOI":"10.1109\/ACCESS.2018.2885003","volume":"6","author":"J Zhang","year":"2018","unstructured":"J. Zhang, J. Yan, P. Zhang, Fixed-wing uav formation control design with collision avoidance based on an improved artificial potential field. IEEE Access 6, 78342\u201378351 (2018)","journal-title":"IEEE Access"},{"issue":"3","key":"1269_CR61","first-page":"1129","volume":"69","author":"Z Pan","year":"2021","unstructured":"Z. Pan, C. Zhang, Y. Xia, H. Xiong, X. Shao, An improved artificial potential field method for path planning and formation control of the multi-uav systems. IEEE Trans. Circuits Syst. II Express Briefs 69(3), 1129\u20131133 (2021)","journal-title":"IEEE Trans. Circuits Syst. II Express Briefs"},{"issue":"4","key":"1269_CR62","doi-asserted-by":"publisher","first-page":"125","DOI":"10.3390\/drones8040125","volume":"8","author":"W Zhao","year":"2024","unstructured":"W. Zhao, L. Li, Y. Wang, H. Zhan, Y. Fu, Y. Song, Research on a global path-planning algorithm for unmanned arial vehicle swarm in three-dimensional space based on theta*-artificial potential field method. Drones 8(4), 125 (2024)","journal-title":"Drones"},{"issue":"6","key":"1269_CR63","doi-asserted-by":"publisher","first-page":"1407","DOI":"10.1080\/00207721.2014.929191","volume":"47","author":"Y-b Chen","year":"2016","unstructured":"Y.-b Chen, G.-c Luo, Y.-s Mei, J.-q Yu, X.-l Su, UAV path planning using artificial potential field method updated by optimal control theory. Int. J. Syst. Sci. 47(6), 1407\u20131420 (2016)","journal-title":"Int. J. Syst. Sci."},{"key":"1269_CR64","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2025.3528390","author":"M Eser","year":"2025","unstructured":"M. Eser, A.E. Yilmaz, A gossip-based auction algorithm for decentralized task rescheduling in heterogeneous drone swarms. IEEE Trans. Aerosp. Electron. Syst. (2025). https:\/\/doi.org\/10.1109\/TAES.2025.3528390","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"issue":"11","key":"1269_CR65","doi-asserted-by":"publisher","first-page":"6803","DOI":"10.1109\/TCYB.2022.3162907","volume":"53","author":"J Xiong","year":"2022","unstructured":"J. Xiong, J. Li, J. Li, S. Kang, C. Liu, C. Yang, Probability-tuned market-based allocations for uav swarms under unreliable observations. IEEE Trans. Cybern. 53(11), 6803\u20136814 (2022)","journal-title":"IEEE Trans. Cybern."},{"issue":"12","key":"1269_CR66","first-page":"7420","volume":"22","author":"N Qi","year":"2022","unstructured":"N. Qi, Z. Huang, W. Sun, S. Jin, X. Su, Coalitional formation-based group-buying for uav-enabled data collection: an auction game approach. IEEE Trans. Mob. Comput. 22(12), 7420\u20137437 (2022)","journal-title":"IEEE Trans. Mob. Comput."},{"issue":"1","key":"1269_CR67","first-page":"37","volume":"2","author":"E Can","year":"2025","unstructured":"E. Can, M. Namdar, A. Ba\u015fg\u00fcm\u00fc\u015f, Development of a greedy auction-based distributed task allocation algorithm for uav swarms with long range communication. ITU J. Wirel. Commun. Cyber Secur. 2(1), 37\u201344 (2025)","journal-title":"ITU J. Wirel. Commun. Cyber Secur."},{"key":"1269_CR68","unstructured":"M. Monaco, et al. Coordination of swarms of robots in target search: from bio-inspired heuristics to hyper-heuristics (2022)"},{"issue":"21","key":"1269_CR69","doi-asserted-by":"publisher","DOI":"10.3390\/app10217696","volume":"10","author":"F Aznar","year":"2020","unstructured":"F. Aznar, Md.M. Pujol\u00a0L\u00f3pez, R. Rizo, UAV deployment using two levels of stigmergy for unstructured environments. Appl. Sci. 10(21), 7696 (2020)","journal-title":"Appl. Sci."},{"key":"1269_CR70","doi-asserted-by":"crossref","unstructured":"M.G. Cimino, A. Lazzeri, G. Vaglini, Combining stigmergic and flocking behaviors to coordinate swarms of drones performing target search. In: 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA), pp. 1\u20136 (2015). IEEE","DOI":"10.1109\/IISA.2015.7387990"},{"key":"1269_CR71","doi-asserted-by":"crossref","unstructured":"P. Grasso, M.S. Innocente, Stigmergy-based collision-avoidance algorithm for self-organising swarms. In: Computational Vision and Bio-Inspired Computing: Proceedings of ICCVBIC 2021, pp. 253\u2013261 (2022)","DOI":"10.1007\/978-981-16-9573-5_19"},{"key":"1269_CR72","doi-asserted-by":"crossref","unstructured":"R. Olfati-Saber, Distributed kalman filter with embedded consensus filters. In: Proceedings of the 44th IEEE Conference on Decision and Control, pp. 8179\u20138184 (2005). IEEE","DOI":"10.1109\/CDC.2005.1583486"},{"key":"1269_CR73","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2023.104497","volume":"168","author":"J Kinnari","year":"2023","unstructured":"J. Kinnari, R. Renzulli, F. Verdoja, V. Kyrki, Lsvl: large-scale season-invariant visual localization for uavs. Robot. Auton. Syst. 168, 104497 (2023). https:\/\/doi.org\/10.1016\/j.robot.2023.104497","journal-title":"Robot. Auton. Syst."},{"key":"1269_CR74","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2020.103666","volume":"135","author":"A Couturier","year":"2021","unstructured":"A. Couturier, M.A. Akhloufi, A review on absolute visual localization for uav. Robot. Auton. Syst. 135, 103666 (2021)","journal-title":"Robot. Auton. Syst."},{"key":"1269_CR75","doi-asserted-by":"publisher","unstructured":"L. Ding, J. Zhou, L. Meng, Z. Meng, A practical cross-view image matching method between uav and satellite for uav-based geo-localization. Remote Sensing 13(1) (2021) https:\/\/doi.org\/10.3390\/rs13010047","DOI":"10.3390\/rs13010047"},{"issue":"6","key":"1269_CR76","doi-asserted-by":"publisher","first-page":"1529","DOI":"10.1109\/TGRS.2006.888937","volume":"45","author":"S Leprince","year":"2007","unstructured":"S. Leprince, S. Barbot, F. Ayoub, J.-P. Avouac, Automatic and precise orthorectification, coregistration, and subpixel correlation of satellite images, application to ground deformation measurements. IEEE Trans. Geosci. Remote Sens. 45(6), 1529\u20131558 (2007)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"1269_CR77","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.rse.2011.11.026","volume":"120","author":"M Drusch","year":"2012","unstructured":"M. Drusch, U. Del Bello, S. Carlier, O. Colin, V. Fernandez, F. Gascon, B. Hoersch, C. Isola, P. Laberinti, P. Martimort et al., Sentinel-2: ESA\u2019s optical high-resolution mission for gmes operational services. Remote Sens. Environ. 120, 25\u201336 (2012)","journal-title":"Remote Sens. Environ."},{"key":"1269_CR78","doi-asserted-by":"publisher","DOI":"10.3390\/rs13040808","author":"B Neupane","year":"2021","unstructured":"B. Neupane, T. Horanont, J. Aryal, Deep learning-based semantic segmentation of urban features in satellite images: a review and meta-analysis. Remote Sens. (2021). https:\/\/doi.org\/10.3390\/rs13040808","journal-title":"Remote Sens."},{"issue":"5","key":"1269_CR79","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.1016\/j.rse.2010.12.017","volume":"115","author":"SW Myint","year":"2011","unstructured":"S.W. Myint, P. Gober, A. Brazel, S. Grossman-Clarke, Q. Weng, High spatial resolution imagery. Per-pixel vs. object-based classification of urban land cover extraction using. Remote Sens. Environ. 115(5), 1145\u20131161 (2011)","journal-title":"Remote Sens. Environ."},{"key":"1269_CR80","first-page":"1","volume":"62","author":"Y Chen","year":"2023","unstructured":"Y. Chen, J. Jiang, An oblique-robust absolute visual localization method for GPS-denied UAV with satellite imagery. IEEE Trans. Geosci. Remote Sens. 62, 1\u201313 (2023)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"1269_CR81","doi-asserted-by":"publisher","unstructured":"M. Shan, F. Shan, F. Lin, Z. Gao, Y.Z. Tang, B.M. Chen, Google map aided visual navigation for uavs in gps-denied environment. In: 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 114\u2013119 (2015). https:\/\/doi.org\/10.1109\/ROBIO.2015.7418753","DOI":"10.1109\/ROBIO.2015.7418753"},{"issue":"1\u201310","key":"1269_CR82","first-page":"4","volume":"5","author":"J-Y Bouguet","year":"2001","unstructured":"J.-Y. Bouguet et al., Pyramidal implementation of the affine lucas kanade feature tracker description of the algorithm. Intel corporation 5(1\u201310), 4 (2001)","journal-title":"Intel corporation"},{"issue":"1","key":"1269_CR83","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/01431161.2024.2358543","volume":"46","author":"H Yang","year":"2025","unstructured":"H. Yang, Q. Zhu, C. Mei, P. Yang, H. Gu, Z. Fan, Trog: a fast and robust scene-matching algorithm for geo-referenced images. Int. J. Remote Sens. 46(1), 1\u201323 (2025)","journal-title":"Int. J. Remote Sens."},{"key":"1269_CR84","doi-asserted-by":"crossref","unstructured":"M. Calonder, V. Lepetit, C. Strecha, P. Fua, Brief: Binary robust independent elementary features. In: Computer Vision\u2013ECCV 2010: 11th European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings, Part IV 11, pp. 778\u2013792 (2010). Springer","DOI":"10.1007\/978-3-642-15561-1_56"},{"key":"1269_CR85","doi-asserted-by":"publisher","first-page":"304","DOI":"10.1016\/j.robot.2018.12.006","volume":"112","author":"M Mantelli","year":"2019","unstructured":"M. Mantelli, D. Pittol, R. Neuland, A. Ribacki, R. Maffei, V. Jorge, E. Prestes, M. Kolberg, A novel measurement model based on abbrief for global localization of a UAV over satellite images. Robot. Auton. Syst. 112, 304\u2013319 (2019). https:\/\/doi.org\/10.1016\/j.robot.2018.12.006","journal-title":"Robot. Auton. Syst."},{"key":"1269_CR86","doi-asserted-by":"publisher","DOI":"10.3390\/rs16163025","author":"J Liu","year":"2024","unstructured":"J. Liu, J. Xiao, Y. Ren, F. Liu, H. Yue, H. Ye, Y. Li, Multi-source image matching algorithms for uav positioning: benchmarking, innovation, and combined strategies. Remote Sens. (2024). https:\/\/doi.org\/10.3390\/rs16163025","journal-title":"Remote Sens."},{"issue":"11","key":"1269_CR87","first-page":"1727","volume":"46","author":"Y Yao","year":"2021","unstructured":"Y. Yao, Y. Zhang, Y. Wan, X. Liu, H. Guo, Heterologous images matching considering anisotropic weighted moment and absolute phase orientation. Geomatics and Information Sci. Wuhan University 46(11), 1727\u20131736 (2021)","journal-title":"Geomatics and Information Sci. Wuhan University"},{"key":"1269_CR88","doi-asserted-by":"crossref","unstructured":"V. Balntas, E. Riba, D. Ponsa, K. Mikolajczyk, Learning local feature descriptors with triplets and shallow convolutional neural networks. In: Bmvc, vol. 1, p. 3 (2016)","DOI":"10.5244\/C.30.119"},{"issue":"1","key":"1269_CR89","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-88089-y","volume":"15","author":"Y Wang","year":"2025","unstructured":"Y. Wang, X. Feng, F. Li, Q. Xian, Z.-H. Jia, Z. Du, C. Liu, Lightweight visual localization algorithm for uavs. Sci. Rep. 15(1), 6069 (2025)","journal-title":"Sci. Rep."},{"key":"1269_CR90","doi-asserted-by":"crossref","unstructured":"K. Han, Y. Wang, Q. Tian, J. Guo, C. Xu, C. Xu, Ghostnet: More features from cheap operations. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1580\u20131589 (2020)","DOI":"10.1109\/CVPR42600.2020.00165"},{"key":"1269_CR91","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2024.3359605","volume":"62","author":"Z Wang","year":"2024","unstructured":"Z. Wang, D. Shi, C. Qiu, S. Jin, T. Li, Y. Shi, Z. Liu, Z. Qiao, Sequence matching for image-based uav-to-satellite geolocalization. IEEE Trans. Geosci. Remote Sens. 62, 1\u201315 (2024). https:\/\/doi.org\/10.1109\/TGRS.2024.3359605","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"1269_CR92","doi-asserted-by":"crossref","unstructured":"R. Arandjelovic, P. Gronat, A. Torii, T. Pajdla, J. Sivic, Netvlad: Cnn architecture for weakly supervised place recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5297\u20135307 (2016)","DOI":"10.1109\/CVPR.2016.572"},{"key":"1269_CR93","doi-asserted-by":"crossref","unstructured":"G. Berton, C. Masone, B. Caputo, Rethinking visual geo-localization for large-scale applications. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4878\u20134888 (2022)","DOI":"10.1109\/CVPR52688.2022.00483"},{"issue":"4","key":"1269_CR94","doi-asserted-by":"publisher","first-page":"1350","DOI":"10.1007\/s11263-023-01942-3","volume":"132","author":"D Wilson","year":"2024","unstructured":"D. Wilson, X. Zhang, W. Sultani, S. Wshah, Image and object geo-localization. Int. J. Comput. Vis. 132(4), 1350\u20131392 (2024)","journal-title":"Int. J. Comput. Vis."},{"key":"1269_CR95","doi-asserted-by":"publisher","DOI":"10.3390\/drones8110622","author":"A Couturier","year":"2024","unstructured":"A. Couturier, M.A. Akhloufi, A review on deep learning for uav absolute visual localization. Drones (2024). https:\/\/doi.org\/10.3390\/drones8110622","journal-title":"Drones"},{"key":"1269_CR96","doi-asserted-by":"publisher","DOI":"10.3390\/rs14225879","author":"H Sui","year":"2022","unstructured":"H. Sui, J. Li, J. Lei, C. Liu, G. Gou, A fast and robust heterologous image matching method for visual geo-localization of low-altitude UAVs. Remote Sens. (2022). https:\/\/doi.org\/10.3390\/rs14225879","journal-title":"Remote Sens."},{"key":"1269_CR97","doi-asserted-by":"publisher","first-page":"2445","DOI":"10.1109\/JSTARS.2021.3054832","volume":"14","author":"MH Mughal","year":"2021","unstructured":"M.H. Mughal, M.J. Khokhar, M. Shahzad, Assisting uav localization via deep contextual image matching. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 14, 2445\u20132457 (2021)","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"1269_CR98","unstructured":"I. Rocco, M. Cimpoi, R. Arandjelovi\u0107, A. Torii, T. Pajdla, J. Sivic, Neighbourhood consensus networks. Advances in neural information processing systems 31 (2018)"},{"issue":"8","key":"1269_CR99","doi-asserted-by":"publisher","first-page":"18334","DOI":"10.3390\/s150818334","volume":"15","author":"DO Nitti","year":"2015","unstructured":"D.O. Nitti, F. Bovenga, M.T. Chiaradia, M. Greco, G. Pinelli, Feasibility of using synthetic aperture radar to aid uav navigation. Sensors 15(8), 18334\u201318359 (2015). https:\/\/doi.org\/10.3390\/s150818334","journal-title":"Sensors"},{"key":"1269_CR100","doi-asserted-by":"publisher","DOI":"10.1016\/j.rsase.2024.101358","author":"G Shennan","year":"2024","unstructured":"G. Shennan, R. Crabbe, A review of spaceborne synthetic aperture radar for invasive alien plant research. Remote Sens. Appl. Soc. Environ. (2024). https:\/\/doi.org\/10.1016\/j.rsase.2024.101358","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"1269_CR101","unstructured":"IMSAR: See hidden things. https:\/\/www.imsar.com\/portfolio\/synthetic-aperture-radar\/"},{"key":"1269_CR102","doi-asserted-by":"publisher","first-page":"77089","DOI":"10.1109\/ACCESS.2020.2989614","volume":"8","author":"M Chen","year":"2020","unstructured":"M. Chen, H. Wang, C.-Y. Chang, X. Wei, Sidr: a swarm intelligence-based damage-resilient mechanism for uav swarm networks. IEEE Access 8, 77089\u201377105 (2020)","journal-title":"IEEE Access"},{"key":"1269_CR103","doi-asserted-by":"publisher","first-page":"183856","DOI":"10.1109\/ACCESS.2020.3028865","volume":"8","author":"Y Zhou","year":"2020","unstructured":"Y. Zhou, B. Rao, W. Wang, Uav swarm intelligence: recent advances and future trends. IEEE Access 8, 183856\u2013183878 (2020)","journal-title":"IEEE Access"},{"issue":"1","key":"1269_CR104","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1109\/36.898664","volume":"39","author":"P Runkle","year":"2002","unstructured":"P. Runkle, L.H. Nguyen, J.H. McClellan, L. Carin, Multi-aspect target detection for sar imagery using hidden markov models. IEEE Trans. Geosci. Remote Sens. 39(1), 46\u201355 (2002)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"1269_CR105","volume":"127","author":"X Xiong","year":"2024","unstructured":"X. Xiong, G. Jin, Q. Xu, X. Liu, Q. Shi, Robust multi-view uav sar image registration based on selective correlation of log gradient descriptor. Int. J. Appl. Earth Obs. Geoinf. 127, 103678 (2024)","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"issue":"4","key":"1269_CR106","doi-asserted-by":"publisher","first-page":"568","DOI":"10.1109\/LGRS.2018.2876661","volume":"16","author":"MA Ghannadi","year":"2019","unstructured":"M.A. Ghannadi, M. Saadaseresht, A modified local binary pattern descriptor for sar image matching. IEEE Geosci. Remote Sens. Lett. 16(4), 568\u2013572 (2019). https:\/\/doi.org\/10.1109\/LGRS.2018.2876661","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"12","key":"1269_CR107","doi-asserted-by":"publisher","first-page":"4477","DOI":"10.1080\/01431161.2022.2114112","volume":"43","author":"I Misra","year":"2022","unstructured":"I. Misra, M.K. Rohil, S. Manthira. Moorthi, D. Dhar, Feature based remote sensing image registration techniques: a comprehensive and comparative review. Int. J. Remote Sens. 43(12), 4477\u20134516 (2022)","journal-title":"Int. J. Remote Sens."},{"key":"1269_CR108","doi-asserted-by":"publisher","unstructured":"E. Najafi, S.V. Ivanov, Image registration by affine-orb on sar and uav images to find object geolocation. In: 2021 International Conference on Engineering and Emerging Technologies (ICEET), pp. 1\u20136 (2021). https:\/\/doi.org\/10.1109\/ICEET53442.2021.9659598","DOI":"10.1109\/ICEET53442.2021.9659598"},{"key":"1269_CR109","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2024.3366247","volume":"62","author":"Y Ye","year":"2024","unstructured":"Y. Ye, C. Yang, G. Gong, P. Yang, D. Quan, J. Li, Robust optical and sar image matching using attention-enhanced structural features. IEEE Trans. Geosci. Remote Sens. 62, 1\u201312 (2024). https:\/\/doi.org\/10.1109\/TGRS.2024.3366247","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"2","key":"1269_CR110","doi-asserted-by":"publisher","first-page":"939","DOI":"10.1109\/TGRS.2009.2034842","volume":"48","author":"S Suri","year":"2009","unstructured":"S. Suri, P. Reinartz, Mutual-information-based registration of terrasar-x and ikonos imagery in urban areas. IEEE Trans. Geosci. Remote Sens. 48(2), 939\u2013949 (2009)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"11","key":"1269_CR111","doi-asserted-by":"publisher","first-page":"9059","DOI":"10.1109\/TGRS.2019.2924684","volume":"57","author":"Y Ye","year":"2019","unstructured":"Y. Ye, L. Bruzzone, J. Shan, F. Bovolo, Q. Zhu, Fast and robust matching for multimodal remote sensing image registration. IEEE Trans. Geosci. Remote Sens. 57(11), 9059\u20139070 (2019)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"1269_CR112","first-page":"1","volume":"19","author":"H Zhang","year":"2020","unstructured":"H. Zhang, L. Lei, W. Ni, T. Tang, J. Wu, D. Xiang, G. Kuang, Optical and sar image matching using pixelwise deep dense features. IEEE Geosci. Remote Sens. Lett. 19, 1\u20135 (2020)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"1269_CR113","first-page":"1","volume":"19","author":"L Zhou","year":"2021","unstructured":"L. Zhou, Y. Ye, T. Tang, K. Nan, Y. Qin, Robust matching for sar and optical images using multiscale convolutional gradient features. IEEE Geosci. Remote Sens. Lett. 19, 1\u20135 (2021)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"1269_CR114","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2020.3040221","volume":"60","author":"H Zhang","year":"2021","unstructured":"H. Zhang, L. Lei, W. Ni, T. Tang, J. Wu, D. Xiang, G. Kuang, Explore better network framework for high-resolution optical and sar image matching. IEEE Trans. Geosci. Remote Sens. 60, 1\u201318 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["EURASIP Journal on Advances in Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13634-025-01269-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13634-025-01269-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13634-025-01269-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T12:03:13Z","timestamp":1768996993000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s13634-025-01269-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,17]]},"references-count":114,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["1269"],"URL":"https:\/\/doi.org\/10.1186\/s13634-025-01269-w","relation":{},"ISSN":["1687-6180"],"issn-type":[{"value":"1687-6180","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,17]]},"assertion":[{"value":"19 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no Conflict of interest to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"8"}}