OBJECTIVE: Develop an on-aircraft system to recognize and quantify the real-time turbulence levels being experienced by an unmanned aircraft and provide actionable information to a remotely located operator.
DESCRIPTION: Atmospheric turbulence is encountered to some degree on nearly every flight, and the disturbances caused are compensated for by the pilot and/or flight control system. Aircraft are designed and built to withstand defined levels of turbulence based on planned missions and operating areas. Once built, aircraft are required to operate within corresponding flight limitations that keep the aircraft within those specified levels of turbulence severity. Encountering atmospheric turbulence beyond the flight limits can lead to aircraft structural damage, and in extreme cases, aircraft loss of control. For the Navy’s manned platforms, the pilot determines the severity of the turbulence, based on experience and real-time aircraft behavior, and acts appropriately with both the flight safety and preserving mission objectives in mind. However, with the Navy’s continuing investment in the development and fielding of Unmanned Air Systems (UAS), this functionality needs to be performed by the vehicle management system using on-aircraft sensor data, and reliably reported as actionable information to the operator.
An on-aircraft system for fixed-wing vehicles that converts measurable data into quantified atmospheric turbulence levels which are appropriate to the host platform is sought. The implementation should integrate into existing aircraft with minimal physical configuration modifications (e.g., changes to air vehicle outer mold line and required on-aircraft sensor space, weight, and power (SWaP) requirements). For the purposes of responding to this announcement, assume the vehicle management systems can supply vehicle position, velocities, accelerations, and air data parameters (e.g., angle of attack, angle of sideslip, dynamic and static pressure). The relative cost, in terms of SWaP required for any additional sensor information should be documented. Sensor source data selection should investigate the required accuracy to achieve an accurate final turbulence level output. The approach should have an open architecture that is capable of working on different aircraft configurations, including weights, wing loadings, and operating speeds such that it may be implemented on as many Navy UAS platforms as possible.
It is desirable that the level of turbulence output by the system correlates the reported turbulence level with existing forecast products available in the maritime environment and manned aircraft standards, including pilot reports from other aircraft in the same geographic area. The system outputs should account for specific aircraft characteristics, such as wing loading and flight condition, to generate safety-critical turbulence classification and intensity information for the operators relevant to the platform the system is installed in.
PHASE I: Develop an on-aircraft methodology for reporting turbulence based on measured aircraft and/or external sensor parameters. The system should support the range of atmospheric turbulence conditions experienced within the operating environments for large fixed-wing DoD UAS (e.g., MQ-9, Global Hawk, MQ-4C, and X-47B). The output of the system should accommodate for aircraft parameters such as wing loading and airspeed, and be consistent with forecast products available in the maritime environment to the maximum extent possible.
Perform a limited demonstration of the resulting recognition and quantification technologies using modeling and simulation against MIL-STD-1797 turbulence models or other proposed method(s) deemed more appropriate for UAS applications. Excitation of an air vehicle model may be done with publicly available air vehicle dynamics, turbulence models, simulation architectures, and/or other available data. Investigate notional methods and aircraft requirements to integrate the technology into existing and future aircraft systems, test verification methods, and information representation to operators. The Phase I effort will include the development of prototype plans of the technology for Phase II.
PHASE II: Extend the Phase I capabilities to address the full spectrum of atmospheric variations that impact turbulence intensity and characteristics on multiple unmanned air vehicle classes (e.g., high and low wing loadings), including smaller UAS down to RQ-21A. Evaluate the impacts of aircraft state and/or sensor errors (e.g., noise, bias, and drift). Demonstrate the prototype turbulence reporting capabilities with variations in aircraft parameters such as weight, wing loading, and flight speed and in different atmospheric conditions, consistent with Navy UAS relevant operating environments. Correlate the approach to turbulence levels experienced by the air vehicle under evaluation with available flight test data, forecast products, and pilot reports, if available. Develop integration and test guidelines, including display of information to operators, for future system installation on a demonstration aircraft. Investigate and propose updates to existing atmospheric turbulence models used by dynamic simulation environments (e.g., Dryden and Von Karman as documented in MIL-STD-1797) to make them more appropriate for direct application to UAS systems which span a much broader range of aircraft size, speed, and wing loadings than traditional manned aircraft.
PHASE III: Integrate and demonstrate the system on an existing Navy platform. Develop draft updates to existing turbulence models used in dynamic simulation environments for utilization in development and training. Commercial UAS operations may benefit from a system that provides a reliable turbulence report that quantifies the severity in a meaningful way for that platform, giving the operator a means to keep the aircraft within the approved operating envelope and in an environment that is conducive to optimal sensor performance.
REFERENCES: 1: Cornman, L., Morse, C. & Cunning, G. "Real-time Estimation of Atmospheric Turbulence Severity From In-Situ Aircraft Measurements." Journal of Aircraft, 1995, Vol. 32, No. 1. https://arc.aiaa.org/doi/abs/10.2514/3.46697?journalCode=ja2: Daniels, T. "Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Sensor Development." SAE Technical Paper 2002-01-1523, 2002. http://papers.sae.org/2002-01-1523/3: Aeronautical Information Manual, Sec. 7-1-23. United States Department of Transportation, Federal Aviation Administration. https://www.faa.gov/air_traffic/publications/media/aim.pdfKEYWORDS: UAS; Turbulence; AVO; Flight Certification; Flight Safety; Autonomous Recognition
CONTACT(S):
Ryan Paul
(301) 995-2788
ryan.paul@navy.mil
John Leonard
(301) 995-2038
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