The Effectiveness of Remotely Piloted Aircraft in a Permissive Hunter-Killer Scenario

The Effectiveness of Remotely Piloted Aircraft in a Permissive Hunter-Killer Scenario

Lance Menthe
Myron Hura
Carl Rhodes
Copyright Date: 2014
Published by: RAND Corporation
Pages: 68
https://www.jstor.org/stable/10.7249/j.ctt6wq9j9
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  • Book Info
    The Effectiveness of Remotely Piloted Aircraft in a Permissive Hunter-Killer Scenario
    Book Description:

    The Air Force has begun to evaluate new concepts of operation for remotely piloted aircraft to meet future needs. This report analyzes the operational effectiveness of several such concepts in a specific, permissive “hunter-killer” mission, which illuminates trade-offs between platform size and number; sensor performance; and the complicating effects of darkness, fog, and cloud cover.

    eISBN: 978-0-8330-8694-5
    Subjects: History, Technology

Table of Contents

  1. Front Matter
    (pp. i-ii)
  2. Preface
    (pp. iii-iii)
  3. Table of Contents
    (pp. iv-v)
  4. Figures
    (pp. vi-vii)
  5. Tables
    (pp. viii-viii)
  6. Summary
    (pp. ix-xiii)
  7. Acknowledgments
    (pp. xiv-xiv)
  8. Abbreviations
    (pp. xv-xvi)
  9. 1. Introduction
    (pp. 1-3)

    Air Force remotely piloted aircraft (RPAs)—in particular, the medium-altitude, multirole platforms, the MQ-1 Predator and MQ-9 Reaper—have provided crucial support to counterinsurgency and counterterrorism operations over the past decade.⁷ However, the last of the Predators has now rolled off the assembly line,⁸ and Air Force orders for new Reapers have reached a steady state.⁹ To meet future needs, the Air Force has now begun to assess concepts for a potential follow-on RPA system.10

    The research presented in this report is part of a larger study that examined the effectiveness of several notional design concepts for RPAs. Here, we...

  10. 2. Modeling Approach
    (pp. 4-15)

    The underlying modeling environment, SEAS, is a stochastic, programmable, multiagent simulation sponsored by the Air Force Space Command, Space and Missile Systems Center, Directorate of Development and Planning.13SEAS is part of the Air Force Standard Analysis Toolkit and the Air Force Space Command Modeling and Simulation Toolkit. SEAS has been in use in one form or another for over fifteen years. The latest stable release (March 2011) is version 3.9.14SEAS is written in C++ and runs on the Microsoft Windows platform.

    SCOPEM is RAND’s unique modular approach to scenario construction in SEAS, designed to add richness and to...

  11. 3. The Hunter-Killer Mission
    (pp. 16-29)

    The hunter-killer mission is understood best not as a specific mission but as a class of missions in which aircraft hunt for and ultimately kill a specific individual target on the ground. One or more aircraft may participate in the search; the search area may be large or small; the target may be mobile or stationary or may exhibit more-complex behaviors; the ROE may be loose or restrictive; and the environmental conditions can vary greatly.

    The class of missions is too broad for us to explore fully. Instead, we selected one particular scenario so that we could explore its variants....

  12. 4. Analysis and Results
    (pp. 30-39)

    We assessed the operational effectiveness of the four different RPA concepts described in Chapter Two (MQ-9, Group 5, Group 4, and Group 3), employing a multiplicity of 1, 2, or 3 platforms at a time, under six different weather conditions, with two different NIIRS requirements, yielding a grand total of 144 variants. We typically ran 300 to 500 replications of each variant for the final production runs.56The full results are tabulated in the appendix. In this section, we summarize the results, pausing to discuss the more interesting outcomes.

    The most favorable conditions we considered were broad daylight, clear weather,...

  13. 5. Conclusion
    (pp. 40-42)

    Analysis of the modeling results leads us to four broad findings.

    First,there is no silver bullet. Even in this one particular type of one particular hunter-killer mission, no single RPA concept performed well on all measures under all environmental conditions. In fact, there is at least one case in which each of the four RPA concepts performed better than the others. For example, with multiple aircraft, the low-flying Group 3 performed better at tracking and identification under cloud cover during the day, but Group 4 was somewhat better with cloud cover at night. Meanwhile, Group 5 generally performed best...

  14. Appendix. Full Results
    (pp. 43-49)
  15. References
    (pp. 50-52)