Collaborative-UAS for Hostile Attribution, Surveillance, Emplacement, and Reconnaissance (CHASER): FY22 HP/ATC/Energy Program

Abstract

In Year 1 of the CHASER effort, we put together an initial testbed consisting of S1000 octocopter platforms, an onboard NVIDIA Jetson Xavier GPU, and an econ 4k e-CAM130CUXVR camera (see Figure 2). We successfully demonstrated a closed-loop, on-board, autonomous computer vision based detection, tracking, and controls system that is able to follow another sUAS in flight. Building off of the success of the Year 1 demonstration, in Year 2 we expanded our focus from just the airborne chase to include the initiation of the execution chain, consisting of autonomous launch from a surveillance cue, out to the cue point, and an efficient search of the space in the absence of mid flight update cues. We also developed a GPS/radar track correlation algorithm in order to identify the chase drone radar track and only send cues of the intruding drone.

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Document Details

Document Type
Technical Report
Publication Date
Apr 27, 2023
Accession Number
AD1201168

Entities

People

  • D. Jansky
  • Joseph E. Funk
  • Justin J. Yao
  • Keegan W. Quigley
  • Luis E. Alvarez
  • Virginia H. Goodwin
  • Y. S. Maclara

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Computer Vision
  • Computers
  • Control Systems
  • Data Sets
  • Department Of Defense
  • Detection
  • Detectors
  • Failure Mode And Effect Analysis
  • Grids
  • Ground Control Stations
  • Platforms
  • Security
  • Standards
  • Surveillance
  • Unmanned Aerial Systems
  • Unmanned Aerial Vehicles

Readers

  • Aviation Science / Aeronautics.
  • Sensor Fusion and Tracking Systems.
  • Space Exploration and Orbital Mechanics.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Space
  • Space - Space Objects
  • Space - Spacecraft Maneuvers