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.
AN/SPN-50(V)1 ATC radar. (Photo: NAWCAD)
Saab has received a $30.29 million contract modification from Naval Air Systems Command for production and delivery of two AN/SPN-50(V)1 shipboard air traffic control (ATC) radars, the DoD announced on 29 August.
The company will also provide two onboard repair kits, and two depot spares kits.
Work is expected to be completed in September 2024.
The AN/SPN-50(V)1 radar system is a US version of the Saab Sea Giraffe agile multi-beam (AMB) radar.
It functions as the primary radar for ATC surveillance aboard USN nuclear-powered aircraft carriers.
The AN/SPN-50(V)1 advanced to phase two LRIP in the USN Shipboard Air Traffic Radar programme with a contract for Saab in April 2021.
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.