Space Development Agency satellites poised to track first missile test

On the same subject

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  January 17, 2024 | International, Aerospace

  Russia allocates another $1.23 bln to company buying planes from Western lessors

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  August 3, 2020 | International, C4ISR

  BAE Systems completes $1.9 billion acquisition of Raytheon’s military GPS business

  Nathan Strout WASHINGTON — BAE Systems has completed its $1.9 billion purchase of Collins Aerospace's military GPS business from Raytheon Technologies Corporation, BAE announced July 31. “Today marks the culmination of a tremendous team effort, and we are extremely proud to welcome the Military GPS employees to our company,” said John Watkins, vice president and general manager of precision strike and sensing solutions at BAE. “Together, we will build on our rich histories of providing superior, innovative capabilities to help protect our U.S. and allied warfighters.” The acquisition follows the merger of defense contracting giants United Technologies Corp. and Raytheon into Raytheon Technologies Corporation in June. The U.S. Department of Justice had approved that merger in March, but only on the condition the companies divest UTC's military GPS and large space-based optical systems businesses, as well as Raytheon's military airborne radios business. The two companies had already struck a deal with BAE in January, which saw BAE purchasing Collins Aerospace's military GPS business from UTC for $1.9 billion and Raytheon's airborne tactical radio business for $275 million. The military GPS business includes a workforce of 700 employees that design and build advanced, hardened, secure GPS products, including devices that can utilize M-Code, a more secure U.S. military GPS signal. The business boasts more than 1.5 million GPS devices installed on more than 280 weapons systems. “This partnership will enable us to build on our market leadership and bring new discriminating capabilities to our customers, including the U.S. Department of Defense and its allies,” said Greg Wild, director of military GPS. “We're excited to be joining the BAE Systems family. They appreciate our legacy of innovation and will provide opportunities for continued business growth and success.” https://www.c4isrnet.com/industry/2020/07/31/bae-systems-completes-19-billion-acquisition-of-raytheons-military-gps-business/

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  February 4, 2019 | International, C4ISR

  DARPA: Building Trusted Human-Machine Partnerships

  A key ingredient in effective teams – whether athletic, business, or military – is trust, which is based in part on mutual understanding of team members' competence to fulfill assigned roles. When it comes to forming effective teams of humans and autonomous systems, humans need timely and accurate insights about their machine partners' skills, experience, and reliability to trust them in dynamic environments. At present, autonomous systems cannot provide real-time feedback when changing conditions such as weather or lighting cause their competency to fluctuate. The machines' lack of awareness of their own competence and their inability to communicate it to their human partners reduces trust and undermines team effectiveness. To help transform machines from simple tools to trusted partners, DARPA today announced the Competency-Aware Machine Learning (CAML) program. CAML aims to develop machine learning systems that continuously assess their own performance in time-critical, dynamic situations and communicate that information to human team-members in an easily understood format. “If the machine can say, ‘I do well in these conditions, but I don't have a lot of experience in those conditions,' that will allow a better human-machine teaming,” said Jiangying Zhou, a program manager in DARPA's Defense Sciences Office. “The partner then can make a more informed choice.” That dynamic would support a force-multiplying effect, since the human would know the capabilities of his or her machine partners at all times and could employ them efficiently and effectively. In contrast, Zhou noted the challenge with state-of-the-art autonomous systems, which cannot assess or communicate their competence in rapidly changing situations. “Under what conditions do you let the machine do its job? Under what conditions should you put supervision on it? Which assets, or combination of assets, are best for your task? These are the kinds of questions CAML systems would be able to answer,” she said. Using a simplified example involving autonomous car technology, Zhou described how valuable CAML technology could be to a rider trying to decide which of two self-driving vehicles would be better suited for driving at night in the rain. The first vehicle might communicate that at night in the rain it knows if it is seeing a person or an inanimate object with 90 percent accuracy, and that it has completed the task more than 1,000 times. The second vehicle might communicate that it can distinguish between a person and an inanimate object at night in the rain with 99 percent accuracy, but has performed the task less than 100 times. Equipped with this information, the rider could make an informed decision about which vehicle to use. DARPA has scheduled a pre-recorded webcast CAML Proposers Day for potential proposers on February 20, 2019. Details are available at: https://go.usa.gov/xE9aQ. The CAML program seeks expertise in machine learning, artificial intelligence, pattern recognition, knowledge representation and reasoning, autonomous system modeling, human-machine interface, and cognitive computing. To maximize the pool of innovative proposal concepts, DARPA strongly encourages participation by non-traditional proposers, including small businesses, academic and research institutions, and first-time Government contractors. DARPA anticipates posting a CAML Broad Agency Announcement solicitation to the Federal Business Opportunities website in mid-February 2019. https://www.darpa.mil/news-events/2019-01-31