China Debuts Stealth Unmanned Combat Aerial Vehicle
On October 1st, China celebrated its annual National Day with a gigantic military parade. New weaponry and upgrades for their military and defense are launched on this day in an effort to show off new developments to both their own people and the world.
Chinese military might is a great source of pride for its people. This year was no different. China showcased several notable new improvements and additions to the Peoples Liberation Army arsenal.
As technology continues to evolve, the Chinese military commitment to unmanned aircrafts "drones" also tremendously expands in both capacity and expertise.
The new Gongji-11 Unmanned Combat Aerial Vehicle is one of the new drones that debuted in this year’s parade and wowed both the crowd and international community.
Since the drone is intended to be an attack aircraft, it includes an internal weapons bay, which contains up to three types of bombs. Its stealth performance gives it the ability to sneak into enemy airspaces and persecute targets undetected.
The aircraft is an all-wing planform (no tail/fins are featured) with the single internal air-breathing turbofan engine. The aircraft is arrowhead-shaped, which maximizes aerodynamics and fuel efficiency for useful operational ranges.
The capacity of drones to generate large amounts of "actionable data" makes them powerful and reliable drivers of the drone industry. Unmanned aerial vehicles are only efficient if they are capable of quickly processing data without requiring any additional effort in the process.
The faster, the more accurate, and the easier the images can be evaluated, the better.
These drones also have image recognition capability, which entails the unmanned aerial vehicle perceiving and absorbing the environment and objects, and then capturing the raw sensor data, which is analyzed to make it meaningful.
Optimization is achieved through the use of data machine learning (ML) algorithms, which are capable of learning and improving over time with the analysis of new data. The learning process continues until accuracy is achieved, thus helping the drone to function autonomously.
Written by Rajath Singh
Lingjun Zhou & Alexander Fleiss
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