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.
Spectranetix has received a $28.7 million contract to develop a software-defined C4ISR/EW Modular Open Suite Of Standards (CMOSS) family-of-systems for fixed site, mounted and dismounted EW, offensive cyber and SIGINT missions for the US Army.
The firm fixed prototype project agreement has been awarded through an agreement with the Consortium Management Group on behalf of the Consortium for Command, Control and Communications in Cyberspace.
These army CMOSS standard (and air force Sensor Open Systems Architecture standard) software-defined radio systems will be adaptable to rapidly add capabilities to the field to combat evolving threats.
Work on this contract is expected to be complete by November 2020.
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.