Unconventional Array Antennas for Pervasive Imaging Multiple-Input Multiple-Output Radar Systems

This research pioneers the development of sparse aperiodic array antennas for multiple-input multiple-output (MIMO) radar systems, offering high-resolution and adaptive solutions crucial for the evolution of autonomous technologies. By merging radar performance metrics, propagation channel properties, and interference into the array design, this approach transcends conventional methods. It enhances radar efficiency, minimizes costs, and optimizes performance in diverse environments. Leveraging machine learning for adaptive beam forming, it produces scalable radar systems with superior resolution and interference mitigation, while reducing size, power consumption, and costs. These innovations have broad applications across automotive, agriculture, defense, and surveillance, significantly advancing the safety and reliability of autonomous systems.