Abstract :
We present an analysis of the signal-to-interference-plus-noise ratio (SINR) at the output of the minimum variance beamformer. The analysis is based on the assumption that the signals and noise are Gaussian and that the number of samples is large compared to the array size, and it yields an explicit expression for the SINR in terms of the different parameters affecting the performance, including signal-to-noise ratio (SNR), interference-to-noise ratio (INR), signal-to-interference ratio (SIR), angular separation between the desired signal and the interference, array size and shape, correlation between the desired signal and the interference, and finite sample size
Keywords :
Gaussian noise; array signal processing; correlation methods; interference (signal); parameter estimation; Gaussian noise; Gaussian signals; INR; SINR; SIR; SNR; adaptive beamforming; angular separation; array shape; array size; correlation; interference; interference to noise ratio; minimum variance beamformer; performance analysis; signal to interference plus noise ratio; signal to interference ratio; signal to noise ratio; Analysis of variance; Gaussian noise; Helium; Interference; Noise shaping; Performance analysis; Sensor arrays; Sensor phenomena and characterization; Signal analysis; Signal to noise ratio;
