El 28/9/2021 se publicó el estándar técnico 1.0 para la arquitectura de referencia SOSA ("Sensor Open Systems Architecture"):
https://publications.opengroup.org/c212This document is the Technical Standard for SOSA™ Reference Architecture, Edition 1.0.
The goal of The Open Group SOSA Consortium is to develop open architecture at the right level for Communications (Comms), Electro-Optical/Infra-Red (EO/IR), Electronic Warfare (EW), Radar, and Signals Intelligence (SIGINT) systems. The open architecture supports airborne, subsurface, surface, ground, and space. The SOSA Consortium strives to develop an ecosystem that allows interoperability, reuse, and faster delivery of products to market through vertical integration from cables, mechanical interfaces, hardware, software, and system designs.
Long lead times, cumbersome improvement processes, lack of reuse, platform-unique design, and extensive testing requirements characterize the current Department of Defense (DoD) C5ISR (Command, Control, Communications, Computers, Cyber, Intelligence, Surveillance, and Reconnaissance) capability. This results in higher costs and the inability to deliver capabilities to the war fighter in a timely manner. To counter these trends, the United States Air Force (USAF) Air Force Life Cycle Management Center (AFLCMC), Naval Air System Command (NAVAIR), US Army C5ISR Center, and Program Executive Office (PEO)-Aviation program offices, enabled by the expertise and experience of the DoD’s industrial base, are adopting a revolutionary approach. The Technical Standard for SOSA Reference Architecture will enable rapid, affordable, cross-platform capability advancements based upon fundamentals of system, software, hardware, and electrical and mechanical engineering best practices and Modular Open Systems Approach (MOSA) principles to develop a solution that addresses DoD needs for a cohesive unified set of sensor capabilities. The goal of The Open Group SOSA Consortium is to reduce development and integration costs and reduce time to field new sensor capabilities.
Continuando con el mismo tema, GA-ASI está implementando MOSA para el Gray Eagle ER Inc. 2:
https://www.ga-asi.com/ga-asi-implement ... e-er-inc-2...
SAN DIEGO – 07 October 2021 – General Atomics Aeronautical Systems, Inc. (GA-ASI) is working with the U.S. Army to develop a
Modular Open Systems Approach (MOSA) for the Multi-Domain Operations (MDO)-capable Gray Eagle Extended Range (GE-ER) Unmanned Aircraft System (UAS). Incorporating MOSA on GE-ER Increment 2 spans the entire system,
including the aircraft and the Command and Control (C2) software suite. The implementation of MOSA will provide multiple new standards for C2,
Future Airborne Capability Environment (FACE), Open Mission Systems (OMS), Universal Armament Interface (UAI), as well as further segregating the Flight/Mission systems’ hardware and software.
“MOSA implementation on GE-ER Increment 2 supports rapid integration of best of breed capabilities,” said GA-ASI Vice President of Army Programs Don Cattell. “We share the Army’s vision for MOSA and want to help them create a system that makes interfacing from all platforms and users as easy as possible.”
MOSA for GE-ER Inc. 2 has an exceptional return on investment for the Army. On the aircraft, MOSA will enable rapid integration of advanced payloads, communication equipment, along with Artificial Intelligence and Machine Learning (AI/ML) capabilities. This will
reduce the sensor to shooter timelines, while simultaneously reducing the datalink bandwidth requirements in a contested environment, thus increasing range and resiliency.
The ‘edge processing’ capability will maximize the utility of the Medium Altitude aircraft providing, in near real time, threat Detection, Identification, Location and Reporting (DILR) to the U.S. Army and Joint Force. Furthermore,
the software components are being designed to be portable to other manned and unmanned aircraft systems the Army is developing, enhancing capability while reducing cost.
For the C2 suite on the ground, MOSA implementation will separate the Human Machine Interface (HMI) from the software business logic and will decrease the time associated with interfacing with evolving communication capability in the Joint and multi-national environment. This will allow the Army to tailor the HMI for each platform and minimize regression testing, a capability the Army has never had before.
GA-ASI is
currently testing the MOSA components on a simulator with plans to
begin flight testing early next year, along with other industry and government partners selected by the U.S. Army.
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Y otra más. Contrato para el MDACE ("Multi-Domain Agile Condor Enhancements", 8/10/2021):
https://www.defense.gov/News/Contracts/ ... e/2806191/...
AIR FORCE
SRC Inc., North Syracuse, New York, has been awarded a $14,486,066 cost-plus-fixed-fee contract for Multi-Domain Agile Condor Enhancements (MDACE) software prototype/hardware. This contract provides for the research and development of widely applicable technologies that increase perception, adaptability, re-configurability, resiliency, self-optimization, security, and autonomy for energy efficient agile Air Force platforms. Work will be performed in North Syracuse, New York. The work is expected to be completed by Oct. 8, 2024. This award is the result of a competitive acquisition in which two offers were received. Fiscal 2021 research, development, test and evaluation funds in the amount of $2,030,471 are being obligated at the time of award. Air Force Research Laboratory, Rome, New York, is the contracting activity (FA8750-22-C-0519).
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En este caso, los principales estándares asociados son el militar SOSA y el civil VITA ("
VMEbus International Trade Association"):
https://www.srcinc.com/products/intel-c ... uting.html...
Agile Condor Technology Features & Benefits
· Rugged, embedded high-performance computing technology that can be mounted in an airborne pod, vehicle or fixed location
· Cascadable to provide huge amounts of processing power (e.g. Multiple vehicle mounted Agile Condor systems simultaneously processing video from 100 UAS during a surveillance mission)
· Leverages machine learning to process large quantities of multi-INT data "at the edge"
· Processing "at the edge" leveraging machine learning (ML) and neuromorphic computing provides more actionable intel, reduces decision timelines and improves PED to maintain a competitive edge in the near-peer fight
· Open-architecture, modular and scalable low-SWaP design
· Developed in alignment with the SOSA™ Technical Standard
· All-source processing
· Supports COTS SBCs, GPUs, FPGAs and SSDs
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