MSG-SET-183 Specialists' Meeting: Improving the Simulations of Radar Signatures of Small Drone (Report with Briefing Charts)

Abstract

Small drones have attracted significant research interest from law enforcement and defence agencies due to the challenge in detecting, tracking, and classifying them with radar, because of their small size and high manoeuvrability. As collecting experimental data for all possible drone models and scenarios is unfeasible, modelling work to simulate accurately the signatures of these platforms is an important task. This paper presents some preliminary results of research effort to enhance modelling capabilities of the radar signatures of individual small drones, and multiple drones flying together in the scene of interest.

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Document Details

Document Type
Technical Report
Publication Date
Apr 30, 2021
Accession Number
AD1151840

Entities

People

  • Alexander Yarovoy
  • D. B. Anderson
  • Francesco Fioranelli
  • Joongsup Yun
  • Oleg Krasnov
  • Yefeng Cai

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Ground and Sea Platforms
  • Sensors

DTIC Thesaurus Topics

  • Aircrafts
  • Artificial Intelligence Software
  • Bayesian Networks
  • Classification
  • Computational Science
  • Continuous-Wave Radar
  • Detection
  • Electromagnetic Scattering
  • Engineering
  • Frequency Bands
  • Machine Learning
  • Navigation
  • Radar
  • Radar Sensing
  • Radar Signatures
  • Signal Processing
  • Simulators
  • Supervised Machine Learning
  • Target Recognition
  • Unmanned Aerial Vehicles

Fields of Study

  • Computer science

Readers

  • Defense Technology Research and Development.
  • Radar Systems Engineering.
  • Theoretical Analysis.

Technology Areas

  • Autonomy