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.
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