US Space Force increases efforts to plug training capabilities gaps
The service has been seeking simulation and emulation solutions capable of reproducing multiple in-orbit threats.
Saab will supply components and subsystems for full rate production systems for the US Marine Corps Ground/Air Task Oriented Radar (G/ATOR) under an order announced on 9 December.
The $31.9 million order has been placed under the company’s five-year contract for G/ATOR, which is known as AN/TPS-80 in US service.
G/ATOR provides the US Marine Corps with air surveillance, air defence and ground weapon locating mission capabilities in a single ground-based radar solution.
Saab received the order from Northrop Grumman, which is the prime contractor for G/ATOR to the US Marine Corps. Saab’s order includes options for additional sets of assemblies and associated spares.
Deliveries are anticipated to take place between 2020 and 2024.
The service has been seeking simulation and emulation solutions capable of reproducing multiple in-orbit threats.
The service has been conducting several acquisition and upgrading efforts involving artificial intelligence and machine learning to improve communication, data analysis and ISR systems.
The Syracuse 4B communications satellite, developed by Airbus and Thales Alenia Space, was launched last year, bolstering secure military satellite communications for the French Armed Forces. Thales has now been selected to provide terminals for vehicles.
The growing importance of space in modern warfare, advancements in satellite technology, and increasing threats from rivals like China and Russia were among the topics of a Eurosatory 2024 panel on military space operations.
AN/ARC-232A is a Starfire radio that provides VHF/UHF communications to airborne platforms and the transceiver is software-programmable, allowing for multiple waveform support as well as optional national electronic counter counter-measure (ECCM) capability.
During the 18-month period of the contract, Lockheed Martin will apply Artificial Intelligence (AI) and Machine Learning (ML) techniques to create surrogate models of aircraft, sensors, electronic warfare and weapons within dynamic and operationally representative environments.