Enhanced Image-Aided Navigation Algorithm with Automatic Calibration and Affine Distortion Prediction

Abstract

This research aims at improving two key steps within the image aided navigation process: camera calibration and landmark tracking. The camera calibration step is improved by automating the point correspondence calculation within the standard camera calibration algorithm, thereby reducing the required time for calibration while maintaining the output model accuracy. The feature landmark tracking step is improved by digitally simulating affine distortions on input images in order to calculate more accurate feature descriptors for improved feature matching in high relative viewpoint change. These techniques are experimentally demonstrated in an outdoor environment with a consumer-grade inertial sensor and three imaging sensors, one of which is orthogonal to the rest. Using a tactical-grade inertial sensor coupled with GPS position data for comparison, the improved image aided navigation algorithm is shown to reduce navigation errors by 24% in position, 16% in velocity and 35% in attitude when compared to the standard image-aided navigation algorithm.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2012
Accession Number
ADA557733

Entities

People

  • Juan Jurado

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Computer Vision
  • Dead Reckoning
  • Detectors
  • Digital Images
  • Electrical Engineering
  • Geometry
  • Image Processing
  • Inertial Measurement Units
  • Inertial Navigation
  • Inertial Navigation Systems
  • Kalman Filters
  • Navigation
  • Nonlinear Dynamics
  • Three Dimensional
  • Two Dimensional
  • United States Government

Readers

  • Computational Modeling and Simulation
  • Human-Computer Interaction (HCI).
  • Inertial Navigation Systems.

Technology Areas

  • Space