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.
Lockheed Martin will develop the Sentinel A4 radar system under a $281 million contract awarded by the US Army.
Sentinel A4 is a high-performance modification of the AN/MPQ-64A3 Sentinel A3 air and missile defence radar.
The development will provide updates to improve the existing Sentinel capability against cruise missiles, UAS, rotary wing and fixed wing threats, with improved surveillance, detection, and classification capabilities.
Rob Smith, vice president and general manager for Lockheed Martin's Radar and Sensor Systems, said: ‘By leveraging our open scalable radar architecture and production efforts, we believe we provide the lowest risk and best value solution for the US Army that will help protect our warfighters for years to come.’
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.