Keywords: multilateration method, unmanned aerial vehicle, swarm of aircraft, location determination, physical model, system of equations
The investigation capabilities of multilateration for the unmanned aerial vehicle autonomous navigation
UDC 004.94:519.876.2
DOI: 10.26102/2310-6018/2024.46.3.010
The paper discusses the multilateration method to ensure coordinated interaction of unmanned aerial vehicles as a part of a swarm during monitoring of fields in agriculture, checking of the environmental parameters, collecting of the weather data etc. Multilateration will improve the reliability of the control of unmanned aerial vehicles as a part of a swarm and will ensure the autonomy of the actions of individual vehicles. The goal of the work is to assess the potential of using the radiosignal multilateration method to determine the relative position of unmanned aerial vehicles and to create of the software and physical models to test this method. In order to achieve this goal, the work presents the algorithm for the interaction of unmanned aerial vehicles using the multilateration method, a method for solving the problem of determine the location of a signal source at low computational costs and the results of computer and physical modeling of the proposed approaches. The developed models demonstrated their adequacy to the set tasks and revealed some shortcomings of the proposed approach in practical implementation. The work also examines possible situations during the interaction of unmanned aerial vehicles in a swarm and notes the main ways to eliminate shortcomings.
1. Prosvirina N. Analysis and prospects for the development of unmanned aircraft. Moskovskii ekonomicheskii zhurnal = Moscow Economic Journal. 2021;(10):560–575. (In Russ.).
2. Zubarev Yu.N., Fomin D.S., Chashchin A.N., Zabolotnova M.V. Use of uncleaned aircraft in agriculture. Vestnik Permskogo federal'nogo issledovatel'skogo tsentra = Perm Federal Research Centre Journal. 2019;(2):47–51. (In Russ.). https://doi.org/10.7242/2658-705X/2019.2.5
3. Buzmakov S.A., Sannikov P.Yu., Sivkov D.E., Dziuba E.A., Khotyanovskaya Yu.V., Egorova D.O. Development of geoinformation systems for environmental management and environmental safety in the areas of exploited oil deposits. Antropogennaya transformatsiya prirodnoi sredy = Anthropogenic Transformation of Nature. 2021;7(1):102–127. (In Russ.).
4. Turk G.G., Karachev N.K. Use of unmanned aerial vehicles (UAVS) in geodesy. Vektor GeoNauk = Vector of Geosciences. 2023;6(2):56–60. (In Russ.). https://doi.org/10.24412/2619-0761-2023-2-56-60
5. Selin A.I., Turkin I.K. Review of target objects for the group-operated unmanned aerial vehicles application. Nauchnyi vestnik Moskovskogo gosudarstvennogo tekhnicheskogo universiteta grazhdanskoi aviatsii = Civil Aviation High Technologies. 2023;26(2):91–105. (In Russ.). https://doi.org/10.26467/2079-0619-2023-26-2-91-105
6. Borovik V.S., Gutsul V.I., Klestov S.A. et al. Kollektivy intellektual'nykh robotov. Sfery primeneniya. Tomsk: STT; 2018. 140 p. (In Russ.).
7. Javed S., Hassan A., Ahmad R. et al. State-of-the-Art and Future Research Challenges in UAV Swarms. IEEE Internet of Things Journal. 2024;11(11):19023–19045. https://doi.org/10.1109/JIOT.2024.3364230
8. Morales-Ferre R., Richter P., Falletti E. et al. A Survey on Coping With Intentional Interference in Satellite Navigation for Manned and Unmanned Aircraft. IEEE Communications Surveys & Tutorials. 2020;22(1):249–291. https://doi.org/10.1109/COMST.2019.2949178
9. Chen X., Gao W., Wang J. Robust all-source positioning of UAVs based on belief propagation. EURASIP Journal on Advances in Signal Processing. 2013;2013. https://doi.org/10.1186/1687-6180-2013-150
10. Zagorodnii N.A., Golovkin M.V. Analiz sistem korrektirovki polozheniya v prostranstve bespilotnykh letatel'nykh apparatov. Rossiiskaya nauka i obrazovanie segodnya: problemy i perspektivy. 2023;(5):40–42. (In Russ.).
11. Amelin K.S. Metod orientirovaniya sverkhlegkogo BPLA pri redkom obnovlenii dannykh o ego mestopolozhenii. Stokhasticheskaya optimizatsiya v informatike. 2014;10(2):3–14. (In Russ.).
12. Nabiyev R.N., Mammadov A.Z. Models of construction of inertial navigation system for unmanned aerial vehicle. Aviakosmicheskoe priborostroenie = Aerospace Instrument-Making. 2021;(1):12–22. (In Russ.). https://doi.org/10.25791/aviakosmos.1.2021.1197
13. Chernykh M.A., Chernykh D.A. Metody koordinatno-vremennogo obespecheniya bespilotnykh letatel'nykh apparatov. Molodoi uchenyi. 2023;(37):29–31. (In Russ.).
14. Zafari F., Gkelias A., Leung K.K. A Survey of Indoor Localization Systems and Technologies. IEEE Communications Surveys & Tutorials. 2019;21(3):2568–2599. https://doi.org/10.1109/COMST.2019.2911558
15. Ivanov D.Ya. Methods of swarm intelligence for control of groups of small-sized unmanned aerial vehicles. Izvestiya YuFU. Tekhnicheskie nauki = Izvestiya SFedU. Engineering Sciences. 2011;(3):221–229. (In Russ.).
16. Fetisov V.S., Artem'ev A.E. Integration of radio and video facilities in systems of local positioning of small unmanned aerial vehicles. Al'manakh sovremennoi nauki i obrazovaniya = Almanac of Modern Science and Education. 2016;(10):91–95. (In Russ.).
Keywords: multilateration method, unmanned aerial vehicle, swarm of aircraft, location determination, physical model, system of equations
For citation: Galantsev E.S. Ponomarev D.Y. The investigation capabilities of multilateration for the unmanned aerial vehicle autonomous navigation. Modeling, Optimization and Information Technology. 2024;12(3). Available from: https://moitvivt.ru/ru/journal/pdf?id=1614 DOI: 10.26102/2310-6018/2024.46.3.010 (In Russ).
Received 28.06.2024
Revised 08.07.2024
Accepted 19.07.2024