A Robust Focused-and-Deconvolved Conventional Beamforming for a Uniform Linear Array

Abstract

In the field of array signal processing, uniform linear arrays (ULAs) are widely used to detect/separate a weak target and estimate its direction of arrival from interference and noise. Conventional beamforming (CBF) is robust but restricted by a wide mainlobe and high sidelobe level. Covariance-matrix-inversed beamforming techniques, such as the minimum variance distortionless response and multiple signal classification, are sensitive to signal mismatch and data snapshots and exhibit high-resolution performance because of the narrow mainlobe and low sidelobe level. Therefore, compared with the wideband CBF, this study proposes a robust focused-and-deconvolved conventional beamforming (RFD-CBF), utilizing the Richardson–Lucy (R-L) iterative algorithm to deconvolve the focused conventional beam power of a half-wavelength spaced ULA. Then, the focused-and-deconvolved beam power achieves a narrower mainlobe and lower sidelobe level while retaining the robustness of wideband CBF. Moreover, compared with the wideband CBF, RFD-CBF can obtain a higher output signal-to-noise ratio (SNR). Finally, the performance of RFD-CBF is evaluated through numerical simulation and verified by sea trial data processing.

Keywords

Wideband / Beamforming / Focusing transform / Deconvolution / High resolution / Robust

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