Detection of Small Unmanned Aerial Systems Using a 3D LiDAR Sensor is a Naval Post Graduate School thesis by Konstantinos Paschalidis.

This thesis explored the feasibility of utilizing a stationary 3D 360° Light Detection and Ranging (LiDAR) sensor to detect fast-moving small Unmanned Aerial Systems (sUAS).

Flight tests were conducted at two rural locations using a low-end Velodyne Puck Hi-Res LiDAR to collect data on various sizes of sUASs. Despite challenges associated with a rich and nonstationary background return, the LiDAR output and the developed algorithms were analyzed to detect moving sUASs. Principal Components Analysis (PCA) and masking were employed to overcome these challenges.

The results showed that a low-end LiDAR with a detection range of 100 meters could detect a sUAS with a cross-section of 0.3 meters, isolate it from other moving objects, and track it within a 25-meter range. Using a higher resolution LiDAR with the same algorithm could extend the detection range, making LiDAR-based counter-UAS technology a viable option for detecting UAS threats.

Publication Date- September 2021

Detection of Small Unmanned Aerial Systems Using a 3D LiDAR Sensor contains the following major sections:

  • Introduction
  • The Basics of 3D LiDAR Technology
  • Data Collection
  • Development of the sUAS Algorithm
  • Conclusions

Approved for public release.  Distribution is unlimited.

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Author-Konstantinos Paschalidis

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