Analyzing Radar Cross Section Signatures of Diverse Drone Models at mmWave Frequencies

Vasilii Semkin, Jaakko Haarla, Thomas Pairon, Christopher Slezak, Sundeep Rangan, Ville Viikari, Claude Oestges

Research output: Contribution to journalArticlepeer-review


In this work, we present quasi-monostatic Radar Cross Section measurements of different Unmanned Aerial Vehicles at 26-40 GHz. We study the Radar Cross Section signatures of nine different multi-rotor platforms as well as a single Lithium-ion Polymer battery. These results are useful in the design and testing of radar systems which employ millimeter-wave frequencies for superior drone detection. The data shows how radio waves are scattered by drones of various sizes and what impact the primary construction material has on the received Radar Cross Section signatures. Matching our intuition, the measurements confirm that larger drones made of carbon fiber are easier to detect, whereas drones made from plastic and styrofoam materials are less visible to the radar systems. The measurement results are published as an open database, creating an invaluable reference for engineers working on drone detection.

Original languageEnglish (US)
Article number9032332
Pages (from-to)48958-48969
Number of pages12
JournalIEEE Access
StatePublished - 2020


  • Drone detection
  • millimeter-wave
  • radar cross section
  • unmanned aerial vehicle

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering


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