A Review of Autonomous Localization Technologies for Unmanned Aerial Vehicles in Complex Low-Altitude Environments
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1Unmanned Systems Research Institute, Northwestern Polytechnical University, Xi’an 710072, China;2School of Artificial Intelligence, Northwestern Polytechnical University, Xi’an 710072, China;3National Key Laboratory of Unmanned Aerial Vehicle Technology, Xi’an 710072, China

Clc Number:

V279

Fund Project:

National Natural Science Foundation of China (No.42504030); Fundamental Research Fund for the Central Universities (Science and Technology Program) (No.D5000250047).

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    Abstract:

    Complex low-altitude environments are typically characterized by the superposition of multi-source interference, drastic variations in sensing conditions, and incomplete environmental information, which collectively pose significant challenges to the continuity, reliability, and integrity of autonomous localization for unmanned aerial vehicles (UAVs). In such scenarios, Global Navigation Satellite System (GNSS) signals are prone to blockage and interference, visual perception suffers from weak textures, dynamic disturbances, and abrupt illumination changes, and inertial measurements inevitably accumulate long-term drift. The coupled degradation of these sensing modalities substantially undermines the stability and robustness of localization systems. To address these challenges, this paper systematically reviews representative types of degraded low-altitude environments and analyzes key technical bottlenecks under multi-source hybrid interference, including visual feature loss, inertial error divergence, and satellite positioning performance deterioration. Building upon this analysis, the developmental trajectory of vision-based navigation and localization techniques for UAVs is comprehensively surveyed, covering visual matching methods based on satellite signals or prior maps as well as recent advances in visual simultaneous localization and mapping (SLAM). Furthermore, visual-inertial fusion modeling and perception enhancement strategies are summarized, highlighting their technical advantages in improving localization accuracy and robustness. Subsequently, multi-sensor fusion navigation frameworks and robust fusion strategies tailored for GNSS-denied or degraded environments are discussed, with particular emphasis on collaborative modeling, degradation awareness, and integrity monitoring across heterogeneous modalities, including vision, inertial sensors, LiDAR, and satellite positioning. Finally, the paper outlines future directions for data-driven multimodal adaptive navigation methods, as well as the development trends of lightweight and intelligent high-integrity navigation technologies for unmanned aerial vehicles. This survey aims to provide a systematic reference for the research and engineering implementation of highly reliable autonomous localization technologies for UAVs operating in complex low-altitude environments.

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XU Yuelei, WANG Xuanbin, XUE Shangjie, XU Jinhai. A Review of Autonomous Localization Technologies for Unmanned Aerial Vehicles in Complex Low-Altitude Environments[J]. Journal of Data Acquisition and Processing,2026,(2):592-619.

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History
  • Received:January 12,2026
  • Revised:February 28,2026
  • Adopted:
  • Online: April 15,2026
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