Complex recurrent neural network for Synthetic Aperture Radar (SAR) target recognition

A synthetic aperture radar (SAR) system for target recognition with complex range profile, the SAR system comprising:

• a memory;
• a recurrent neural network (RNN);
• a multi-layer linear network in signal communication the recurrent neural network;
• a machine-readable medium on the memory, the machine-readable medium storing instructions that, when executed by the RNN, cause the SAR system to perform operations comprising:
• receiving raw SAR data associated with observed views of a scene, wherein the raw SAR data comprises information captured via the SAR system;
• radio frequency (RF) preprocessing the received raw SAR data to produce a processed raw SAR data;
• converting the processed raw SAR data to a complex SAR range profile data;
• processing the complex SAR range profile data with the RNN having RNN states;
• and
• mapping the RNN states to a target class with the multi-layer linear network;
• wherein:
• the complex SAR range profile data includes an in-phase component of the complex SAR range profile data and a quadrature component of the complex range profile data,
• the processing the complex SAR range profile data with the RNN includes processing the complex SAR range profile data with gated recurrent unit (GRU) neural network (GRUNN) having GRUNN states that includes processing both the in-phase component of the complex SAR range profile data and quadrature component of the complex SAR range profile data with a plurality of GRU processing cells within the GRUNN utilizing complex operations within each of the plurality of GRU processing cells.