A Study on Conventional and Adaptive Narrowband Beamformer for MIMO RADAR

This paper presents a comparative study of Conventional and Adaptive beamforming algorithms which are processes of spatial filtering for narrowband signals. We have compared three algorithms on the basis of accuracy, complexity, speed of convergence and lower sidelobe level under jamming and clutter interference conditions. These beamformers create a beam pattern based on the received signal weight vector. Thermal noise, which can be modeled as gaussian distributed random noise, which is present in the received signal. Phase shift beamformers can extract this signal content in the presence of noise. Under strong interference conditions, a Minimum Variance Distortionless Response (MVDR) beamformer can retrieve the signal from the direction of interest and reject the signal from the direction of interference whereas a phase shift beamformer cannot recover the target signal that is masked by interfering signal under this condition. In case when the target signal is received somewhat in a different direction than that which is wanted, the MVDR beamformer mutes the signal. This effect of self-nulling can be prevented in Linear Constraint Minimum Variance (LCMV) beamformer. The Uniform Rectangular Array (URA) of 16 × 16 elements with spacing λ/2 are used for our simulation program in MATLAB software.