Photo: General Atomics
General Atomics is collaborating with the U.S. Army to develop a modular open system approach (MOSA) for its MQ-1C Gray Eagle drone. MOSA will allow for rapid integration of advanced payloads, communication systems, and machine learning capabilities on the aircraft.
Developed by General Atomics for the U.S. Army, the Gray Eagle Extended Range (GE-ER) aircraft can operate at altitudes up to 25,000 feet (7,600 m) and is capable of carrying a payload of 800 pounds (360 kg). The drone can also be armed with missiles and guided bombs.
It has a large nose fairing to house a synthetic aperture radar or ground moving target indicator system. By combining infrared imagery, its sensors can identify changes in terrain such as tire tracks, footprints, and buried improvised explosive devices.
The implementation of MOSA is designed to upgrade the entire MQ-1C system, including the aircraft’s command and control software suite. In a contested environment, it will also reduce sensor to shooter timelines while simultaneously lowering datalink bandwidth requirements, improving the drone’s range and resiliency.
MOSA is set to increase the MQ-1C’s computer processing power. This capability will allow the Gray Eagle to detect and identify threats in near real-time. Moreover, the software components will enable the Army to adapt them to other manned and unmanned aircraft systems, enhancing functionality while lowering costs.
For the command and control software suite on the ground, the modular open system approach implementation will separate the interface that allows users to interact with the machine from the software business logic. This way, the Army will be able to customize the interface for each platform and reduce regression testing.
Currently, General Atomics is testing the MOSA components on a simulator together with other industry and government partners chosen by the U.S. Army. The first flight test on a Gray Eagle drone is expected to occur next year.
It has a large nose fairing to house a synthetic aperture radar or ground moving target indicator system. By combining infrared imagery, its sensors can identify changes in terrain such as tire tracks, footprints, and buried improvised explosive devices.
The implementation of MOSA is designed to upgrade the entire MQ-1C system, including the aircraft’s command and control software suite. In a contested environment, it will also reduce sensor to shooter timelines while simultaneously lowering datalink bandwidth requirements, improving the drone’s range and resiliency.
MOSA is set to increase the MQ-1C’s computer processing power. This capability will allow the Gray Eagle to detect and identify threats in near real-time. Moreover, the software components will enable the Army to adapt them to other manned and unmanned aircraft systems, enhancing functionality while lowering costs.
For the command and control software suite on the ground, the modular open system approach implementation will separate the interface that allows users to interact with the machine from the software business logic. This way, the Army will be able to customize the interface for each platform and reduce regression testing.
Currently, General Atomics is testing the MOSA components on a simulator together with other industry and government partners chosen by the U.S. Army. The first flight test on a Gray Eagle drone is expected to occur next year.
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