Motion (physics)

Algorithm

Control (management)

Covariance matrix

Aperture (computer memory)

Telecommunications

Computer science

Acoustics

Adaptive beamformer

Interpolation (computer graphics)

Beamforming

Physics

Mathematics

Capon

Artificial intelligence

Control theory (sociology)

Coprime integers

Frame (networking)

Signal Processing

Recently, the coprime array has aroused wide concern due to its capability of achieving enhanced degrees of freedom (DOF) and increased array aperture compared to uniform linear arrays (ULAs). However, it experiences a certain DOF and aperture loss due to the existence of “holes” in the difference coarray. These drawbacks are adverse to enhance the performance of direction-of-arrival (DOA) estimation and adaptive beamforming. In this paper, we propose a new robust adaptive beamforming algorithm with the coprime array. The proposed algorithm yields the beamforming coefficients by estimating the steering vector of the signal-of-interest (SOI) and reconstructing the interference-plus-noise covariance matrix (INCM). Unlike previous techniques, we estimate the DOAs of the SOI and interferences using an interpolated virtual ULA, and further derive their steering vectors and powers. With the high-precision DOA estimates, the steering vectors and powers can be more accurately estimated. The proposed algorithm avoids the coarray aperture loss and enhances the accuracy of INCM reconstruction. Numerical results indicate that the proposed algorithm outperforms the existing approaches in high SNR regions.

Robust adaptive beamforming via coprime coarray interpolation