mm Wave MIMO Neuro-Adaptive Radar (mMINAR)

Toyon Research Corporation in collaboration with Duke University is proposing to leverage our successful Phase I analysis, preliminary radar design, simulation, algorithm development and experimentation, to demonstrate a compact, high resolution MIMO radar operating in Ka-band for small unmanned system detection, classification and tracking. Our proposed system is capable of detecting -20dBsm aerial targets at ranges up to 2 km in highly cluttered environments. Furthermore, by coupling innovative Toyon miniaturized hardware designs with advanced Duke AI enabled Neuro-adaptive algorithms, our proposed system is a single sensor solution to the highly asymmetric drone detection problem. Not only can our design provide wide area surveillance, our approach to MIMO beamforming allows us to detect targets of interest, discriminate them from clutter and classify as an unmanned system. Moreover, based on our Phase I results, we are proposing to go further in the classification stage and identify not only class of aerial system but potentially intent. Our innovative hardware design leverages significant advances in 5G technology and utilizes multiple commercial assemblies to both reduce technical risk and accelerate development. Our proposed solution will result in a low cost, all weather capability in a compact form factor allowing for wide deployment.