ReviewSensors (Basel, Switzerland)2025
LiDAR Technology for UAV Detection: From Fundamentals and Operational Principles to Advanced Detection and Classification Techniques.
Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- A Survey of Environmental Perception for Unmanned Ground Agricultural Machinery in Field Environments.Sensors (Basel, Switzerland) · 2026Review
- An adaptive confidence-driven framework for real-time lidar and visual data fusion in autonomous aerial vehicle landing site assessment.Scientific reports · 2026Article
- UAV-LiDAR dataset of Pangandaran coastal tourism hotspots for tsunami and climate risk valuation and exposure mapping.Data in brief · 2026Article
- AWG-Based Spectral Multiplexing for Unambiguous Range-Extended FMCW LiDAR.Sensors (Basel, Switzerland) · 2026Article
- A Ground-Based Visual System for UAV Detection and Altitude Measurement Deployment and Evaluation of Ghost-YOLOv11n on Edge Devices.Sensors (Basel, Switzerland) · 2025Article
- Secure LoRa Drone-to-Drone Communication for Public Blockchain-Based UAV Traffic Management.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As unmanned aerial vehicles (UAVs) are increasingly employed across various industries, the demand for robust and accurate detection has become crucial. Light detection and ranging (LiDAR) has developed as a vital sensor technology due to its ability to provide rich 3D spatial information, particularly in applications such as security and airspace monitoring. This review systematically explores recent innovations in LiDAR-based drone detection, deeply focusing on the principles and components of LiDAR sensors, their classifications based on different parameters and scanning mechanisms, and the approaches for processing LiDAR data. The review briefly compares recent research works in LiDAR-based only and its fusion with other sensor modalities, the real-world applications of LiDAR with deep learning, as well as the major challenges in sensor fusion-based UAV detection.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.