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Time: 2024-09-12  韋克威科技

The US Air Force reveals some functions of the 'Next Generation Air Dominator' fighter jet

According to an article published on the December 23, 2021 issue of the UK's "Flight International" website, the US Air Force's (USAF) "Next Generation Air Dominator" (NGAD) fighter jet is still in a state of secrecy, but some new platform functionalities have been revealed.

The NGAD fighter jet (the sixth generation fighter jet of the United States) completed its secret flight for the first time in 2020 and is scheduled to replace the US Air Force F-22 fighter jet starting in 2030.

According to the US Air Force and potential research and development teams, compared to the previous generation fighter jets that relied mainly on speed and maneuverability to form an advantage over the enemy, the NGAD fighter jet may mainly rely on stealth characteristics and high-performance computing capabilities to establish operational advantages. In addition, the latest disclosed information indicates that this stealth fighter with outstanding network node characteristics will use artificial intelligence technology to quickly process/parse multi-sensor data, helping combat personnel make quick decisions and establish combat advantages.

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The US Air Force disclosed in June 2021 that the NGAD is a multifunctional fighter jet, and establishing air superiority is its main mission. The US Air Force hopes that NGAD aircraft can carry more weapon payloads and have a greater range to meet the operational requirements in the Indo Pacific region.

Lockheed Martin stated that as the main competitor of the NGAD fighter jet project, it will apply new digital technologies to enable the NGAD platform to have "omniscient situational awareness" capabilities.

1) Big data application capability

The ability of "omniscient and omnipotent situational awareness" is also in line with the vision of the US Air Force's Advanced Combat Management System (ABMS), a new combat networking system that can assist pilots in making decisions faster based on global sensor data.

For example, ABMS may transmit intelligence, surveillance, and reconnaissance data collected by autonomous loyal wingmen to the NGAD platform, which can then use artificial intelligence systems to parse the data and assist pilots in making quick decisions. This approach is consistent with the "system cluster" concept previously constructed by the US Air Force, centered around NGAD manned fighter jets.

In October 2021, the US Air Force awarded Kratos and General Atomic Aviation Systems each a contract to develop the Off Board Sensing Station (OBSS) unmanned aerial vehicle. This loyal wingman may become a precursor platform for NGAD, utilizing its sensors (radar/infrared search and tracking sensors, etc.) to achieve target search and potentially serving as a weapon launch platform.

As an advanced radar manufacturer, Raytheon expects NGAD airborne sensors to automatically "coordinate" (autonomously) to achieve target detection/tracking/recognition tasks. At the same time, autonomy is also reflected in the intelligent management of sensor resources, that is, for complex electronic warfare scenarios, various types of sensors are adaptively applied autonomously to reduce the possibility of signal interception.

2) Intelligent technology surpassing the F-35 fighter jet

Due to the increasingly complex future combat scenarios, the NGAD platform will place greater emphasis on the application of artificial intelligence technology.

Firstly, from the perspective of airborne sensor applications, NGAD sensors have a higher degree of integration. By applying artificial intelligence technology, the adaptability of the NGAD platform environment and the efficiency of airborne sensor collaboration/management/application can be effectively improved. This means flexibly calling various types of sensors in a collaborative/intelligent manner based on the environment/task situation, ensuring the accuracy and effectiveness of task implementation.

Secondly, from the perspective of AI assisted decision-making, the NGAD platform will be based on F-35 sensors, software, and networking capabilities to further train AI systems and enhance the effectiveness of combat personnel driving the NGAD platform to carry out strikes.

At present, the US Air Force is training artificial intelligence (AI) systems by using computer simulations of combat scenarios to enhance their decision-making capabilities in diverse combat scenarios. For example, the latest ARTU μ machine learning program developed by the US Air Force Air Combat Command used over 500000 computer simulations to train the U-2 high-altitude reconnaissance aircraft radar system to achieve reconnaissance/positioning of enemy missile launchers. During the demonstration of the ARTU μ artificial intelligence system based on the U-2 aircraft platform at the end of 2020, ARTU μ was mainly responsible for sensor applications and tactical navigation, while the pilot was mainly responsible for U-2 piloting and collaborating with the artificial intelligence system. By comprehensively applying onboard sensor data and with the assistance of the artificial intelligence system, the pilot was able to more efficiently implement adversarial decisions against threat targets.

Thirdly, from the perspective of the application boundaries of artificial intelligence software, the US military plans to improve the migration of artificial intelligence software to various systems. The US Air Force has achieved secure command of artificial intelligence software by the US military system for the first time, opening up a new era of human-machine cooperation and algorithm competition. However, the full potential of artificial intelligence systems has not yet been fully realized, and how to further tap into the potential of artificial intelligence systems and make their application boundaries secure/widespread still requires further research by the US military. With the increasing complexity of systems, the scope of use of artificial intelligence software/systems will become more challenging.

Source: Global Aviation Information

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