兰德-The-Effectiveness-of-Remotely-Piloted-Aircraft-in-a-Permissive-Hunter_71页_1mb

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

Core Content

This report evaluates the operational effectiveness of three RPA design concepts and the MQ-9 Reaper in a permissive hunter-killer mission, which involves identifying and destroying a specific moving vehicle. The analysis is based on modeling results from a defined scenario and its variants, focusing on the impact of environmental conditions such as daylight, fog, and cloud cover on mission success. The study also considers the number of platforms (one or three) and the resolution requirements for positive identification (NIIRS 7.0 or 8.0).

Main Points

1. RPA Design Concepts

The report examines three RPA design concepts based on the Air Force's current classification of RPA groups:

• Group 3: Smaller RPA with limited payload and slower speed, using Raven Eye I as the primary sensor.
• Group 4: Medium-sized RPA with moderate payload and speed, using Raven Eye II.
• Group 5: Larger RPA with greater payload and speed, using MTS-B and Lynx sensors.

The MQ-9 Reaper is used as a baseline for comparison. These designs reflect what is currently practical rather than future possibilities.

2. Modeling Approach

• The analysis uses RAND's SCOPEM model, which is part of the Air Force's SEAS (System Effectiveness Analysis Simulation) environment.
• SCOPEM is a modular, agent-based approach that allows for the simulation of sensor, environment, and platform interactions.
• A Monte Carlo analysis was conducted on 144 variants of the hunter-killer scenario to assess performance under various conditions.
• The model includes sensor modules (Full-Motion Video, GMTI, SAR), environmental modules (line of sight, fog, cloud cover), and platform modules.

3. Mission Scenario

• The mission involves finding and destroying a moving vehicle in an urban environment.
• The initial cue is urgent but imprecise, indicating the vehicle will emerge from hiding within a 5 nmi² area in 15 minutes.
• The vehicle's ultimate destination is unknown but expected to be outside the area.
• The RPA must identify, track, and maintain track of the target to the kill zone.
• Rules of Engagement (ROE) require full-motion video (FMV) for positive identification and continuous tracking when weather conditions permit.
• The NIIRS (National Imagery Interpretability Rating Scale) is used to measure the quality of identification, with 7.0 and 8.0 as key thresholds.

4. Key Findings

• No single RPA concept is optimal across all conditions and metrics.
• Numbers can compensate for capability; smaller RPAs with fewer sensors can perform as well as or better than larger ones when multiple platforms are used.
• The MQ-9 Reaper performs consistently well across all scenarios, never being outperformed and rarely being the worst-performing platform.
• Improving MQ-9 sensor capabilities, particularly FMV, could enhance operational flexibility and effectiveness in hunter-killer missions.
• A continuous zoom feature in the MTS-B sensor could allow better balancing of mission objectives.

5. Assumptions and Limitations

• The threat environment is permissive, meaning the RPA faces negligible threats, allowing for unrestricted CONOPS.
• The RPA cannot detect or hear the enemy, and the target does not use camouflage or concealment.
• FMV is the only sensor modality capable of positive identification.
• Communications and PED (Processing, Exploitation, and Dissemination) capabilities are assumed to be sufficient.
• The study does not consider jamming or GPS loss, which could severely impact mission success.

Key Information

• The study was sponsored by the U.S. Air Force under Contract FA7014-06-C-0001.
• The modeling environment is SEAS, which is part of the Air Force Standard Analysis Toolkit.
• The analysis highlights trade-offs between platform size, sensor performance, and environmental conditions.
• The results are summarized in Figures S.1 and S.2, which show the probability of identification and maintaining track to the kill zone.
• The report also includes Appendix A with numerical modeling results and References for further reading.

Conclusion

• The study demonstrates that operational effectiveness in hunter-killer missions is influenced by sensor capabilities, number of platforms, and environmental conditions.
• The MQ-9 Reaper remains a reliable and effective platform despite the limitations of the study.
• The analysis provides insights into RPA design trade-offs and sensor performance, and suggests that enhancing sensor capabilities may be a cost-effective improvement.

References

• Menthe, Lance, Myron Hura, and Carl Rhodes. The Effectiveness of Remotely Piloted Aircraft in a Permissive Hunter-Killer Scenario. RAND Corporation, 2014.
• The report is part of the RAND Corporation Research Report Series, and its findings are based on agent-based modeling and simulation.