Vision Based Control and Target Range Estimation for Small Unmanned Aerial Vehicle

Abstract

In the tracking of a moving ground target by small unmanned air vehicle (UAV) via camera vision, the target position and motion cannot be measured directly. Two different types of filters were assessed for their ability to estimate target motion, namely target velocity, directional heading on flat ground and distance from the UAV to target. The first filter is a nonlinear deterministic filter with stability guarantee. The second filter is based on nonlinear Kalman Filter technique. The application and performance of these two filters are presented, for simulated vision based target tracking.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2005
Accession Number
ADA443306

Entities

People

  • Chin K. Quek

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Autonomy

DTIC Thesaurus Topics

  • Aircrafts
  • Airframes
  • Autonomous Underwater Vehicles
  • Control Systems
  • Coordinate Systems
  • Engineering
  • Equations
  • Filters
  • Global Positioning Systems
  • Guarantees
  • Guidance
  • Kalman Filtering
  • Kalman Filters
  • Line Of Sight
  • Moving Targets
  • Target Tracking
  • Unmanned Aerial Vehicles

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Sensor Fusion and Tracking Systems.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • Autonomy