Quantifying Human Performance of a Dynamic Military Target Detection Task: An Application of the Theory of Signal Detection.

Abstract

As crew aiding technologies are developed to assist military aviators in performing complex target detection tasks, evaluation metrics must be developed which are common to both human operators and automatic target recognition (ATR) systems so that performance comparisons can be efficiently conducted. The dynamic nature of the multiple target detection task introduces several unique problems in quantifying detection performance. Classical methods of implementing the Theory of Signal Detection (TSD) to quantify performance have proven to be insufficient, and ATR evaluators have developed unique metrics which have not been applicable to evaluating human performance. This research introduced a novel application of TSD to the dynamic, multiple target detection scenario, and a new method of evaluating human performance was developed by adapting an established ATR evaluation method to human subject performance. A linear relationship was discovered between the TSD metric d' and the new evaluation metric, validating the new evaluation method. The new method provided a common metric for evaluating both human and ATR performance of multiple target detection tasks.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1995
Accession Number
ADA308392

Entities

People

  • Stuart L. Turner

Organizations

  • Armstrong Laboratory

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Energy and Power Technologies
  • Human Systems
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Combinatorial Analysis
  • Databases
  • Detection
  • Detectors
  • Information Science
  • Infrared Detectors
  • Motor Skills
  • Multiple Targets
  • Recognition
  • Recording Systems
  • Regression Analysis
  • Signal Detection
  • Target Acquisition
  • Target Detection
  • Target Recognition
  • Test And Evaluation

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Vision.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.