Tightly Integrating Optical And Inertial Sensors For Navigation Using The UKF

Abstract

The motivation of this research is to address the benefits of tightly integrating optical and inertial sensors where GNSS signals are not available. The research begins with describing the navigation problem. Then, error and measurement models are presented. Given a set of features, a feature detection and projection algorithm is developed which utilizes inertial measurements to predict vectors in the feature space between images. The unscented Kalman filter is applied to the navigation system using the inertial measurements and feature matches to estimate the navigation trajectory. Finally, the image-aided navigation algorithm is tested using a simulation and an experiment. As a result, the optical measurements combined with the inertial sensors result in improved performance for non-GNSS based navigation.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2008
Accession Number
ADA482871

Entities

People

  • Sedat Ebcin

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Computational Science
  • Differential Equations
  • Estimators
  • Filters
  • Global Positioning Systems
  • Guidance
  • Inertial Navigation
  • Inertial Navigation Systems
  • Kalman Filters
  • Mathematical Filters
  • Measurement
  • Monte Carlo Method
  • Navigation
  • Sequential Monte Carlo Methods
  • Target Recognition

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Vision.
  • Inertial Navigation Systems.

Technology Areas

  • Space
  • Space - Space Objects