Frederick, MD – The United States Navy has selected Ipsolon Research’s SBIR for a phase II follow-on contract after a successful phase I demonstration of its Deep Learning (DL) techniques.
“We used DL techniques to replace or extend the PDW-based approach to radar signal detection, “explained Ipsolon Research CEO, John Shanton.
Deep learning (DL) algorithms are a form of Machine Learning (ML) that use neural network (NN) architectures to process data and predict the presence of data patterns often called prediction or inference.
The specific goal of this project is to develop a deployable electronic sensor optimized to use ML techniques for real-time detection of radar signals and other signals of interest.
“The phase I results demonstrated that ML is a viable method for detection of a known radar signal type in power- and space-efficient FPGA devices,” Shanton said.
Ipsolon Research specializes in ultra-small form factor high-performance Software Defined Radios. Ipsolon SDRs are suitable for development but designed for deployment in harsh environments. We work collaboratively with business and government organizations to quickly advance communication technology and drive success.