Cognitive dual coprime frequency diverse array MIMO radar network for target discrimination and main-lobe interference mitigation

Abstract

The authors propose a novel dual coprime frequency diverse array (FDA) multiple input multiple output (DCFDA-MIMO) radar network design, empowered by cognitive capabilities, aimed at target discrimination and mitigation of interference present in the standalone radar systems. That is, the proposed DCFDA-MIMO design capitalises on the complementary advantages of FDAs for target discrimination and coprime arrays for enhanced resolution, resulting in superior performance. Additionally, the proposed DCFDA-MIMO network employs a 2D multiple signal classification algorithm to achieve high-resolution target localisation. By incorporating cognitive techniques based on the action-perception cycle, the proposed approach demonstrates notable improvements in multiple target detection and tracking accuracy with fewer number of antenna elements as compared to existing techniques. Furthermore, it enhances individual radar beamforming performance for interference suppression and true target detection without prior information.