Lessons Learned from Information Superiority Experiment 1.1 (ISX 1.1)

Abstract

ISX 1.1 was conducted in the Summer 1998 in concert with the USAF Expeditionary Force Experiment (EFX) 98. The broad objectives of ISX 1.1 were two-fold. Substantively, ISX 1.1 was to confirm the hypothesis that information from multiple sources could be fused into engagement quality data and distributed in real time to achieve joint suppression of enemy air defenses (JSEAD) mission objectives against mobile medium-to-high altitude surface to air missiles (SAMs). Second, since this was the first in a planned set of experiments, there was interest in deriving lessons learned to support the efficient and effective performance of future ISXs. Based on an assessment of ISX 1.1, several significant experimental successes and residual challenges have been identified. These successes include the innovative use of models, the implementation of a creative experimental design, and the data collection efforts. The major residual challenges include the difficulties in piggybacking on other experimental activities and the importance in viewing an experiment in the context of a campaign in which a variety of assessment techniques are employed (e.g., model, test, model,...).

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1999
Accession Number
ADA461970

Entities

People

  • David S. Alberts
  • F. R. Richards
  • Stuart H. Starr

Organizations

  • United States Assistant Secretary of Defense

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • C4I
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Accumulators
  • Aeronautics
  • Air Defense
  • Aircrafts
  • Application Software
  • Best Practices
  • Cloud Cover
  • Command And Control
  • Fighter Aircraft
  • High Altitude
  • Information Operations
  • Information Warfare
  • Lessons Learned
  • Observation
  • Situational Awareness
  • Training
  • Vehicles

Readers

  • Regression Analysis.
  • Sensor Fusion and Tracking Systems.
  • Systems Analysis and Design