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ENSCO Partners with DeepSig Inc. to Detect and Classify RF Signals for National Security Applications

By April 9, 2019September 29th, 2023No Comments

Springfield, Va., April 9, 2019

ENSCO is pleased to announce it has partnered with DeepSig Inc. as the launch customer for DeepSig’s OmniSIG™ SDK, a first-of-its-kind commercial real-time signal processing product that enables users to train their own deep learning-based signal detection and classification sensors. By employing deep learning artificial intelligence, OmniSIG can detect WiFi, Bluetooth, 3/4/5G, and other signals up to 1,000 times faster than existing technology.

With its significant expertise and experience in wireless signal processing and national security requirements, ENSCO is training the OmniSIG sensor to detect and classify wireless and radar signals of high interest for customers in the Department of Defense and U.S. Intelligence Community.

The OmniSIG sensor not only detects and classifies signals, but also understands the spectrum environment to inform contextual analysis and decision making. Compared to traditional approaches, OmniSIG provides higher sensitivity and is more robust in harsh and dynamic spectrum environments, while requiring fewer computational resources and hence less power.

“ENSCO has been a key partner in applying OmniSIG to tackle and solve extremely difficult challenges in national security. Their extensive technical and domain expertise is accelerating the utility and deployment of OmniSIG’s artificial intelligence-based capabilities for defense and intelligence customers,” states James Shea, CEO, DeepSig Inc.

“This partnership is a win-win for both companies and our U.S. government customers,” states Vernon Joyner, Vice President of National Security Solutions. “We are applying leading-edge commercial off-the-shelf radio frequency (RF) deep learning technology to overcome the performance limitations of conventionally designed RF systems, such as radar, signals intelligence, electronic warfare, and communications.”

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