Fast and accurate covariance matrix reconstruction for adaptive beamforming using Gauss-Legendre quadrature

Most of the reconstruction-based robust adaptive beamforming (RAB) algorithms require covariance matrix reconstruction (CMR) by high-complexity integral computation. A Gauss-Legendre quadrature (GLQ) method with highest algebraic precision in interpolation-type is proposed to reduce complexity. The interference angular sector RAB regarded as GLQ range, and zeros three-order Legendre orthogonal polynomial selected nodes. Consequently, CMR can be efficiently obtained simple summation respect three nodes without integral. new has significantly reduced complexity compared most state-of-the-art techniques, it able provide similar performance close optimal. These advantages are verified numerical simulations.