Low Altitude Simulation/Prediction Techniques.

Abstract

Preparation of sensor predictions at the present time is a manual process requiring several hours of effort by highly trained personnel. This extremely slow response capability is unacceptable within the framework of most Air Force missions, particularly those of a tactical nature. The problem is accentuated in low-altitude missions where the effective sensor resolution places a greater burden on the existing sensor image prediction system and the supporting data bases. The purpose of the study was to analyze the use of image predictions in order to find a more compact set of prediction techniques that would result in a more efficient image prediction system. An experimental approach was used to determine the relationship between navigator performance and the type and amount of information in the prediction image. A number of subjects were given image predictions containing different image features and then asked to identify the predicted targets in corresponding dynamic flight sequences over scenes of cultural content. Three techniques were used to compress the amount of information contained in the image predictions. The techniques employed are edge representation, a reduction in resolution, and gray level quantization.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1981
Accession Number
ADA108183

Entities

People

  • Anthony J. Stenger
  • Susan A. Knobel
  • Warren R. Stone

Organizations

  • Technology Service Corporation

Tags

Communities of Interest

  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Altitude
  • Change Detection
  • Combinatorial Analysis
  • Databases
  • Detection
  • Detectors
  • False Alarms
  • Identification
  • Image Processing
  • Low Altitude
  • Mechanical Equipment
  • Photographic Equipment
  • Photographs
  • Simulations
  • Test Sets
  • Video Tapes

Readers

  • Image Processing and Computer Vision.
  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.