Hybrid robust beamforming for enhanced multiple moving object detection with phased array scanning radar

The deficiencies of conventional radar systems can be addressed by utilizing a phased array scanning radar with robust beamforming capable of detecting and tracking multiple moving objects while rejecting interferences under noisier environments. This paper offers the idea of a 30 × 30 Uniform Rectangular Array (URA)-based radar system with the employment of a hybrid robust beamformer, a combination of Minimum Variance Distortionless Response (MVDR) and Linearly Constrained Minimum Variance (LCMV) beamformer with diagonal loading. Initially, a simulation work with experimental validation of a 1 × 16 Uniform Linear Array (ULA)-based radar system with a conventional beamformer is performed under a well-conditioned scenario, and it shows an overall accuracy of 89.80% for object detection; however, it is not feasible for the noisier condition. In order to enhance radar performance in challenging situations, a new hybrid robust beamforming model on a 30 × 30 URA-based phased array scanning radar system is used. Comparing the proposed radar system to conventional radar systems, the proposed phased array radar shows an overall accuracy of 99.29% for multiple object detection and interference rejection, according to the simulation results.