RFEL awarded for innovation in digital signal processing



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RFEL, a specialist in high-performance electronic signal processing, has been presented with The Queen's Award for Enterprise 2012 in the Innovation category, for its unique range of digital-signal-processing technologies. This is the second time it has won the award, the first being in 2009. RFEL's CEO Dr Kurt said "To be recognized for our innovation a second time is a great testament to the team of engineers who continually push the envelope to create signal processing solutions that are smaller, smarter and more flexible. As a result, we have companies coming to us to solve their problems when a standard, off-the-shelf approach just cannot deliver." The Queen's Award for Enterprise is the UK's most prestigious Award for business performance and recognises and rewards outstanding achievement by UK companies. The Innovation category is for continuous innovation and development, sustained over not less than five years, to levels that are outstanding for the size of a company's operations. RFEL's award-winning designs enable fast moving events occurring in the radio spectrum (even rapidly moving signals or fleeting, hopping signals) to be identified, acquired and then extracted for analysis. Designs are based on high-performance, state-of-the-art, digital-signal-processing techniques and are incorporated into an increasing number of RFEL's and customers' products. RFEL's approaches have a variety of applications such as in the design of efficient wireless-communication networks (satellite and terrestrial), test & measurement instrumentation, homeland-security surveillance systems, bespoke wideband receivers/transceivers, and in systems to detect signals from fast moving missiles or other military threats. RFEL's customers are mainly Tier-1 companies in each of its main markets, including Selex, Thales, UK Ministry of Defence, Rheinmetall (Germany), ITT Exilis (USA), Agilent (Switzerland), and Anritsu, as well as many other major international clients. RFEL Mixed-radix FFT deeplink