Abstract
Adaptive beamformers (ABFs) place deep beampattern notches near interferers to suppress the interferers’ power in the ABF output. The common sample matrix inversion (SMI) Minimum Variance Distortionless Response (MVDR) ABF computes the beamformer weights by substituting the sample covariance matrix (SCM) for the unknown ensemble covariance matrix in the MVDR expression. Errors in the SCM estimate of interferer direction due to limited sample support or interferer motion degrade the ABFs ability to suppress the interferer. This presentation exploits array polynomial properties to design a robust ABF. The array polynomial for a uniform linear array beamformer is the z-transform of the array weights. The array polynomial zeros on the unit circle correspond to the beampattern nulls. The proposed double zero (DZ) MVDR ABF solves for the MVDR weights using the SCM for a half-aperture subarray, then convolves the half-aperture weights with themselves to obtain the full aperture ABF weights. The resulting array polynomial for the DZ MVDR ABF has second-order zeros, producing broader and deeper notches in the interferer direction. The DZ MVDR ABF outperforms the SMI MVDR and covariance matrix tapered ABFs in simulations with stationary and moving interferers.