
CLC number: TN961
On-line Access: 2026-03-02
Received: 2025-11-09
Revision Accepted: 2025-12-19
Crosschecked: 2026-03-02
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Citations: Bibtex RefMan EndNote GB/T7714
Yao JIN, Zhongliang DENG, He ZHANG, Zhenke DING, Xiongyan TANG, Zelin WANG. A review of UAV positioning in LAIN: toward a 5G-core “space-air-ground” integrated and cooperative architecture[J]. Journal of Zhejiang University Science C, 2026, 27(1): 1-16.
@article{title="A review of UAV positioning in LAIN: toward a 5G-core “space-air-ground” integrated and cooperative architecture",
author="Yao JIN, Zhongliang DENG, He ZHANG, Zhenke DING, Xiongyan TANG, Zelin WANG",
journal="Journal of Zhejiang University Science C",
volume="27",
number="1",
pages="1-16",
year="2026",
publisher="Zhejiang University Press & Springer",
doi="10.1631/ENG.ITEE.2025.0127"
}
%0 Journal Article
%T A review of UAV positioning in LAIN: toward a 5G-core “space-air-ground” integrated and cooperative architecture
%A Yao JIN
%A Zhongliang DENG
%A He ZHANG
%A Zhenke DING
%A Xiongyan TANG
%A Zelin WANG
%J Frontiers of Information Technology & Electronic Engineering
%V 27
%N 1
%P 1-16
%@ 1869-1951
%D 2026
%I Zhejiang University Press & Springer
%DOI 10.1631/ENG.ITEE.2025.0127
TY - JOUR
T1 - A review of UAV positioning in LAIN: toward a 5G-core “space-air-ground” integrated and cooperative architecture
A1 - Yao JIN
A1 - Zhongliang DENG
A1 - He ZHANG
A1 - Zhenke DING
A1 - Xiongyan TANG
A1 - Zelin WANG
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 27
IS - 1
SP - 1
EP - 16
%@ 1869-1951
Y1 - 2026
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/ENG.ITEE.2025.0127
Abstract: The rapid expansion of the low-altitude economy is driving strong demand for highly accurate and reliable positioning technologies to support diverse aerial operations. This review examines core positioning methodologies within the low-altitude intelligent network (LAIN) framework, beginning with an analysis of positioning requirements and performance metrics for low-altitude flight scenarios. It systematically assesses the principles, strengths, and limitations of mainstream positioning systems, including Global Navigation Satellite Systems (GNSS), terrestrial wireless positioning, and autonomous navigation, and it surveys prevalent integrated and cooperative positioning schemes. Our analysis demonstrates that standalone positioning technologies are inadequate in complex low-altitude settings, underscoring the pivotal role of multi-source fusion and unmanned aerial vehicle (UAV) swarm cooperative positioning as future trends. To address infrastructure gaps and high deployment costs in current LAIN systems, we propose a “space-air-ground” integrated and cooperative positioning architecture centered on GNSS and the 5th generation mobile communication technology (5G). The ground layer integrates 5G and GNSS for wide-area enhanced positioning. The aerial layer uses 5G aircraft-to-everything (A2X) and sidelink (SL) communications to build self-organizing networks for cooperative UAV localization. The space layer leverages low Earth orbit (LEO) satellites to overcome coverage limitations in communication and positioning. This hierarchical architecture reduces deployment costs through infrastructure reuse and enables deep integration of communication and navigation capabilities. By supporting collaborative enhancement across all three domains, the framework improves positioning robustness and delivers cost-effective, ubiquitous, and highly reliable positioning services. Finally, we outline promising research directions. This review aims to provide a systematic reference and a novel architectural perspective for the ongoing development of LAIN.
[1]3GPP, 2014. Study on LTE device to device proximity services. TR 36.843, V12.0.0. https://www.3gpp.org/ftp/Specs/archive/36_series/36.843 [Accessed on Nov. 9, 2025].
[2]3GPP, 2020a. Physical channels and modulation. TS 38.211, V16.6.0. https://www.3gpp.org/ftp/Specs/archive/38_series/38.211 [Accessed on Nov. 9, 2025].
[3]3GPP, 2020b. Stage 2 functional specification of User Equipment (UE) positioning in NG-RAN. TS 38.305, V16.0.0. https://www.3gpp.org/ftp/Specs/archive/38_series/38.305 [Accessed on Nov. 9, 2025].
[4]3GPP, 2021. NR positioning protocol a (NRPPa). TS 38.455, V16.5.0. https://www.3gpp.org/ftp/Specs/archive/38_series/38.455 [Accessed on Nov. 9, 2025].
[5]3GPP, 2024a. Aircraft-to-Everything (A2X) services in 5G system; Stage3. TS 24.577, V18.0.0. https://www.3gpp.org/ftp/Specs/archive/24_series/24.577 [Accessed on Nov. 9, 2025].
[6]3GPP, 2024b. Study on expanded and improved NR positioning. TR 38.859, V18.1.0. https://www.3gpp.org/ftp/Specs/archive/38_series/38.859 [Accessed on Nov. 9, 2025].
[7]Arafat MY, Alam MM, Moh S, 2023. Vision-based navigation techniques for unmanned aerial vehicles: review and challenges. Drones, 7(2):89.
[8]Bai L, Sun C, Dempster AG, et al., 2022. GNSS-5G hybrid positioning based on multi-rate measurements fusion and proactive measurement uncertainty prediction. IEEE Trans Instrum Meas, 71:8501415.
[9]Baldoni S, Battisti F, Brizzi M, et al., 2020. A hybrid position estimation framework based on GNSS and visual sensor fusion. IEEE/ION Position, Location and Navigation Symp, p.979-986.
[10]Bi SG, Li K, Hu SY, et al., 2024. Detection and mitigation of position spoofing attacks on cooperative UAV swarm formations. IEEE Trans Inform Forens Secur, 19:1883-1895.
[11]Boguspayev N, Akhmedov D, Raskaliyev A, et al., 2023. A comprehensive review of GNSS/INS integration techniques for land and air vehicle applications. Appl Sci, 13(8):4819.
[12]Cao SZ, Lu XY, Shen SJ, 2022. GVINS: tightly coupled GNSS-visual-inertial fusion for smooth and consistent state estimation. IEEE Trans Robot, 38(4):2004-2021.
[13]Cha HS, Lee G, Ghosh A, et al., 2025. 5G NR positioning enhancements in 3GPP Release-I8. IEEE Commun Stand Mag, 9(1):22-27.
[14]Chen C, Wang ZA, Gong Z, et al., 2022. Autonomous navigation and obstacle avoidance for small VTOL UAV in unknown environments. Symmetry, 14(12):2608.
[15]Chen K, Liang WC, Zeng CZ, et al., 2021. Multi-geomagnetic-component assisted localization algorithm for hypersonic vehicles. J Zhejiang Univ Sci A, 22(5):357-368.
[16]Chen R, Yang B, Zhang W, 2021. Distributed and collaborative localization for swarming UAVs. IEEE Int Things J, 8(6):5062-5074.
[17]Cheng Q, Li YH, Lu HD, 2023. UAV-aided localization based on extended Kalman filtering. Electr Opt Contr, 30(12):93-97, 103 (in Chinese).
[18]Couturier A, Akhloufi MA, 2021. A review on absolute visual localization for UAV. Rob Auton Syst, 135:103666.
[19]Dai J, Zhang CF, Liu SL, et al., 2024. GNSS-assisted visual dynamic localization method in unknown environments. Appl Sci, 14(1):455.
[20]Deng ZL, Yin L, 2015. Indoor positioning system based on TC-OFDM system. Telecommun Netw Technol, (3):32-35 (in Chinese).
[21]Deng ZL, Wang HH, Liu JR, 2022. Status and trend of communication-navigation integrated positioning technology. Navig Position Timing, 9(2):15-25 (in Chinese).
[22]Deng ZL, Zhang ZC, Ding ZK, et al., 2025. Multi-source, fault-tolerant, and robust navigation method for tightly coupled GNSS/5G/IMU system. Sensors, 25(3):965.
[23]Dong J, Ren XY, Han SL, et al., 2022. UAV vision aided INS/odometer integration for land vehicle autonomous navigation. IEEE Trans Veh Technol, 71(5):4825-4840.
[24]Dong Y, Wang DJ, Zhang L, et al., 2020. Tightly coupled GNSS/INS integration with robust sequential Kalman filter for accurate vehicular navigation. Sensors, 20(2):561.
[25]Elamin A, Abdelaziz N, El-Rabbany A, 2022. A GNSS/INS/LiDAR integration scheme for UAV-based navigation in GNSS-challenging environments. Sensors, 22(24):9908.
[26]Fan CC, Wang QL, 2025. Adaptive federated deep reinforcement learning for edge offloading in heterogeneous AGI-MEC networks. Appl Intell, 55(7):585.
[27]Fan CC, Xu HY, Wang QL, 2024. Multi-agent deep reinforcement learning for trajectory planning in UAVs-assisted mobile edge computing with heterogeneous requirements. Comput Netw, 248:110469.
[28]Feng XY, Qiu MH, Wang T, et al., 2025. Noise-adaptive GNSS/INS fusion positioning for autonomous driving in complex environments. Vehicles, 7(3):77.
[29]Gao C, Huang Z, Zhao X, et al., 2024. Collaborative navigation method for 5G cluster UAV based on configuration optimization. J Syst Simulat, 36(4):981-990 (in Chinese).
[30]Gu ML, Li H, Zhang JW, et al., 2025. A review of vision-based UAV localization and navigation methods. Acta Electr Sin, 53(3):651-685 (in Chinese).
[31]Guo G, Sun XZ, Liu JG, 2024. 5G/GNSS integrated vehicle localization with adaptive step size Kalman filter. IEEE Trans Veh Technol, 73(11):16531-16542.
[32]Guo YH, Vouch O, Zocca S, et al., 2023. Enhanced EKF-based time calibration for GNSS/UWB tight integration. IEEE Sens J, 23(1):552-566.
[33]Gyagenda N, Hatilima JV, Roth H, et al., 2022. A review of GNSS-independent UAV navigation techniques. Rob Auton Syst, 152:104069.
[34]He MF, Liu JC, Gu PF, et al., 2024. Leveraging map retrieval and alignment for robust UAV visual geo-localization. IEEE Trans Instrum Meas, 73:2523113.
[35]Hu X, Olesen D, Knudsen P, 2021. Toward high-quality magnetic data survey using UAV: development of a magnetic-isolated vision-based positioning system. GPS Solut, 25(1):29.
[36]Huang Y, Zou RZ, Shi YM, 2025. A 3D localization algorithm for unmanned aerial vehicles in distributed air-ground integrated sensing and communication networks. J Electr Inform Technol, 47(4):1085-1092 (in Chinese).
[37]Huang Z, Wang HX, Huan XY, et al., 2024. A multi-UAV cooperative positioning method based on 5G signal asynchronous clock error compensation. Electr Opt Contr, 31(1):46-50, 103 (in Chinese).
[38]Jiang HT, Shi C, Li T, et al., 2021. Low-cost GPS/INS integration with accurate measurement modeling using an extended state observer. GPS Solut, 25(1):17.
[39]Jiao HJ, Tao XX, Chen L, et al., 2024. GNSS/5G joint position based on weighted robust iterative Kalman filter. Remote Sens, 16(6):1009.
[40]Jin Y, Zhou YM, Zhang H, et al., 2023. Research and application progress of BeiDou+5G fusion positioning technology. GNSS World of China, 48(4):12-18 (in Chinese).
[41]Jin Y, Zhang H, Deng ZL, et al., 2025. Application and prospect of 5G-A/6G+Beidou communication, sensing and navigation technology in low-altitude economy. Telecommun Sci, 41(3):1-16 (in Chinese).
[42]Kabiri M, Cimarelli C, Bavle H, et al., 2024. Graph-based vs. error state Kalman filter-based fusion of 5G and inertial data for MAV indoor pose estimation. J Intell Robot Syst, 110(2):87.
[43]Kramarić L, Jelušić N, Radišić T, et al., 2025. A comprehensive survey on short-distance localization of UAVs. Drones, 9(3):188.
[44]Kurazume R, Hirose S, Nagata S, et al., 1996. Study on cooperative positioning system (basic principle and measurement experiment). Proc IEEE Int Conf on Robotics and Automation, p.1421-1426.
[45]Li DD, Zhang FB, Feng JX, et al., 2023. LD-SLAM: a robust and accurate GNSS-aided multi-map method for long-distance visual SLAM. Remote Sens, 15(18):4442.
[46]Li XW, Cheng F, Li YQ, et al., 2024. DGVINS: tightly coupled differential GNSS/visual/inertial for robust positioning based on optimization approach. Meas Sci Technol, 35(8):086307.
[47]Li ZY, Li HG, Liu Y, et al., 2024. Indoor fixed-point hovering control for UAVs based on visual inertial SLAM. Robot Intell Autom, 44(5):648-657.
[48]Liu A, Guo H, Yu M, et al., 2024. Research on GNSS/IMU/visual fusion positioning based on adaptive filtering. Appl Sci, 14(24):11507.
[49]Liu JR, Deng ZL, Hu EW, et al., 2023. GNSS-5G hybrid positioning based on joint estimation of multiple signals in a highly dependable spatio-temporal network. Remote Sens, 15(17):4220.
[50]Liu WX, 2025. The total number of 5G base stations in China has reached 4.758 million. People’s Daily. http://kpzg.people.com.cn/n1/2025/1203/c404214-40616120.html [Accessed on Dec. 9, 2025].
[51]Luo J, Yin ZS, Gui LQ, 2024. A GNSS UWB tight coupling and IMU ESKF algorithm for indoor and outdoor mixed scenario. Cluster Comput, 27(4):4855-4865.
[52]Lv HH, Liu MJ, Liu P, et al., 2025. Kalman filter-based high-accuracy indoor positioning with NLoS error mitigation and multi-motion model switching. IEEE Trans Veh Technol, 74(8):12673-12688.
[53]Meng Q, Song Y, Li SY, et al., 2023. Resilient tightly coupled INS/UWB integration method for indoor UAV navigation under challenging scenarios. Def Technol, 22:185-196.
[54]Mousa M, Al-Rubaye S, 2025. Intelligent 5G-aided UAV positioning in high-density environments using neural networks for NLOS mitigation. Aerospace, 12(6):543.
[55]Mousa M, Al-Rubaye S, Inalhan G, 2023. Unmanned aerial vehicle positioning using 5G new radio technology in urban environment. IEEE/AIAA 42nd Digital Avionics Systems Conf, p.1-9.
[56]Niu XJ, Liu ZW, Chen QJ, et al., 2024. Determining the MEMS INS initial heading using trajectory matching for UAV applications. IEEE Sens J, 24(1):543-553.
[57]Nouali IY, Slimane Z, Abdelmalek A, 2022. Change point detection-based TOA estimation in UWB indoor ranging systems. 45th Int Conf on Telecommunications and Signal Processing, p.329-332.
[58]Opshaug GR, Enge P, 2002. Integrated GPS and UWB navigation system: (motivates the necessity of non-interference). IEEE Conf on Ultra Wideband Systems and Technologies, p.123-127.
[59]Qi Y, Zhong YS, Shi ZY, 2020. Cooperative 3-D relative localization for UAV swarm by fusing UWB with IMU and GPS. J Phys Conf Ser, 1642(1):012028.
[60]Qu RK, Wang ZY, Liu YL, et al., 2025. UAV visual positioning technology for urban air mobility. Acta Aeronaut Astronaut Sin, 46(11):531168 (in Chinese).
[61]Shi C, Wang JL, Wang JT, et al., 2025. 5G control plane-based BDS high-precision spatiotemporal service system and research. J Navig Position, 13(4):1-11 (in Chinese).
[62]Song WW, Ding HJ, Zhang LH, et al., 2025. Performance verification of GNSS/5G tightly coupled fusion positioning in urban occluded environments with a smartphone. GPS Solut, 29(1):40.
[63]Song Y, Hsu LT, 2021. Tightly coupled integrated navigation system via factor graph for UAV indoor localization. Aerosp Sci Technol, 108:106370.
[64]Song Z, Zhang Y, Yu Y, et al., 2024a. Cooperative positioning algorithm based on manifold gradient filtering in UAV-WSN. IEEE Sens J, 24(8):12676-12688.
[65]Song Z, Zhang Y, Yu Y, et al., 2024b. Wide-area UAV networks cooperative positioning algorithm based on information geometry. IEEE Signal Process Lett, 31:2645-2649.
[66]State Administration for Market Regulation and Standardization Administration of the People’s Republic of China (SAMR and SAC), 2023. Safety Requirements for Civil Unmanned Aircraft System, GB/T 42590-2023. National Standards of the People’s Republic of China (in Chinese).
[67]State Administration for Market Regulation and Standardization Administration of the People’s Republic of China (SAMR and SAC), 2024. Technical Requirements and Test Methods for In-Band and Co-Band Positioning based on Mobile Communication Network, GB/T 44863-2024. National Standards of the People’s Republic of China (in Chinese).
[68]Sun R, Zhang WY, Zheng JZ, et al., 2020. GNSS/INS integration with integrity monitoring for UAV no-fly zone management. Remote Sens, 12(3):524.
[69]Tang CK, Wang YY, Zhang LL, et al., 2022. Multisource fusion UAV cluster cooperative positioning using information geometry. Remote Sens, 14(21):5491.
[70]Tang P, Li JY, Sun HQ, 2024. A review of electric UAV visual detection and navigation technologies for emergency rescue missions. Sustainability, 16(5):2105.
[71]Tang WJ, Chen JP, 2023. Key technology development and application of pseudolite system. World Sci-Tech R&D, 45(3):276-284 (in Chinese).
[72]Tian R, Cui ZY, Zhang SN, et al., 2021. Overview of navigation augmentation technology based on LEO. Navig Position Timing, 8(1):66-81 (in Chinese).
[73]Tong WH, Zou DC, Han T, et al., 2021. A new type of 5G-oriented integrated BDS/SON high-precision positioning. Remote Sens, 13(21):4261.
[74]Vital LAV, Ramos DC, 2025. Simultaneous localization and communication based on UWB for UAV applications. Brazilian Conf on Robotics, p.1-6.
[75]Wang GQ, Han Y, Chen J, et al., 2018. A GNSS/INS integrated navigation algorithm based on Kalman filter. IFAC-PapersOnLine, 51(17):232-237.
[76]Wang H, Pan SG, Gao W, et al., 2022. Multipath/NLOS detection based on K-means clustering for GNSS/INS tightly coupled system in urban areas. Micromachines, 13(7):1128.
[77]Wang L, Chen L, Li BY, et al., 2024. Development status and challenges of anti-spoofing technology of GNSS/INS integrated navigation. Front Phys, 12:1425084.
[78]Wang TY, Zheng ZD, Sun YQ, et al., 2024. Multiple-environment self-adaptive network for aerial-view geo-localization. Patt Recogn, 152:110363.
[79]Xiang ZR, Chen L, Wu QQ, et al., 2025. An improved UWB indoor positioning approach for UAVs based on the dual-anchor model. Sensors, 25(4):1052.
[80]Xin L, Tang ZM, Gai WQ, et al., 2022. Vision-based autonomous landing for the UAV: a review. Aerospace, 9(11):634.
[81]Xiong CS, Lu WS, Xiong H, et al., 2024. Onboard cooperative relative positioning system for micro-UAV swarm based on UWB/vision/INS fusion through distributed graph optimization. Measurement, 234:114897.
[82]Yan J, Yang C, Fan WY, et al., 2024. GNSS/UWB integrated positioning with robust Helmert variance component estimation. Adv Space Res, 73(5):2532-2547.
[83]Yang J, Xu J, Li X, et al., 2021. Integrated communication and localization in millimeter-wave systems. Front Inform Technol Electron Eng, 22(4):457-470.
[84]Yang LW, Shrestha R, Li WB, et al., 2022. SceneSqueezer: learning to compress scene for camera relocalization. IEEE/CVF Conf on Computer Vision and Pattern Recognition, p.8249-8258.
[85]Yao HL, Qu XM, Wu LK, et al., 2025. Vehicle cooperative localization based on UWB technology in GNSS-denied environments. IEEE Sens J, 25(18):34882-34893.
[86]Yao LH, Li M, Xu TH, et al., 2024. GNSS/UWB/INS indoor and outdoor seamless positioning algorithm based on federal filtering. Meas Sci Technol, 35(1):015135.
[87]Ye HQ, Liu YD, Shen SH, 2024. Lightweight visual-based localization technology. J Image Graph, 29(10):2880-2911 (in Chinese).
[88]Ye T, Liu WK, Hu J, et al., 2025. Improving the position accuracy via merged line and point features for GNSS/SINS/vision integration in a degradation environment. Meas Sci Technol, 36(1):016337.
[89]Yin L, Ni Q, Deng ZL, 2018. A GNSS/5G integrated positioning methodology in D2D communication networks. IEEE J Sel Areas Commun, 36(2):351-362.
[90]Yin L, Ma YZ, Li GW, et al., 2020. Research progress of communication-positioning integrated technology. Navig Position Timing, 7(4):64-76 (in Chinese).
[91]You WD, Li FB, Liao LQ, et al., 2020. Data fusion of UWB and IMU based on unscented Kalman filter for indoor localization of quadrotor UAV. IEEE Access, 8:64971-64981.
[92]Zhang D, Ma Y, Wang SL, et al., 2025. Precise positioning in complex environments with GNSS-RTK and weighted linear regression UWB observations. J Spat Sci, 70(1):1-28.
[93]Zhang H, Xiong HL, Hao SJ, et al., 2024. A novel multidimensional hybrid position compensation method for INS/GPS integrated navigation systems during GPS outages. IEEE Sens J, 24(1):962-974.
[94]Zhang SN, Wang ES, Wang YK, et al., 2024. A low-cost UAV swarm relative positioning architecture based on BDS/barometer/UWB. IEEE Sens J, 24(23):39659-39668.
[95]Zhang W, Yang YX, Zeng AM, et al., 2023. Robust BDS/5G integrated positioning based on resilient observation model. Adv Space Res, 71(10):4006-4017.
[96]Zhang XH, Hu JH, Ren XD, 2020. New progress of PPP/PPP-RTK and positioning performance comparison of BDS/GNSS PPP. Acta Geod Cartogr Sin, 49(9):1084-1100 (in Chinese).
[97]Zhao H, Ren KY, Yue TY, et al., 2024. TransFG: a cross-view geo-localization of satellite and UAVs imagery pipeline using transformer-based feature aggregation and gradient guidance. IEEE Trans Geosci Remote Sens, 62:4700912.
[98]Zhao JG, Sun W, Ding W, et al., 2025. Vehicle cooperative positioning with tightly coupled GNSS/INS/UWB integration based on improved multiple fading factors and adaptive cost function. IEEE Trans Intell Transp Syst, 26(7):9740-9754.
[99]Zheng QY, Jiang JG, Yan PH, et al., 2024. A robust and continuous carrier phase prediction strategy for GNSS/INS deeply coupled systems. GPS Solut, 28(4):168.
[100]Zhu XD, Lai JZ, Chen S, 2022. Cooperative location method for leader-follower UAV formation based on follower UAV’s moving vector. Sensors, 22(19):7125.
[101]Zhuang C, Zhao HB, Hu S, et al., 2021. Cooperative positioning for V2X applications using GNSS carrier phase and UWB ranging. IEEE Commun Lett, 25(6):1876-1880.
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