A high DOF and azimuth resolution beamforming via enhanced virtual aperture extension of joint linear prediction and inverse beamforming

Beamforming is a significant technique applied in many fields to infer the azimuth parameters of the acoustic source and improve the output signal-to-noise ratio (SNR) of the array. However, both the azimuth resolution and the degrees of freedom (DOF) for multi-source detection are limited by the finite array aperture. In this paper, a high-resolution, DOF-improved beamforming azimuth spectrum estimation method using an enhanced virtual aperture (EVA) extension is proposed. Firstly, a spectrum selection algorithm is presented, which effectively reduces the computation time through the time–frequency domain transformation. Secondly, an EVA extension algorithm is conducted through the joint expansion of bidirectional linear prediction (LP) and inverse beamforming (IBF) for increasing the number of the virtual array element significantly. Thirdly, the modified minimum variance distortion-less response (MVDR) based on the EVA array is proposed to obtain a sufficiently high azimuth resolution, improved DOF, and low sidelobes with relatively few calculations. For verification, the effectiveness of the proposed EVA-MVDR method is simulated by using MATLAB and experimented by adopting a shipborne platform on the lake, and the performance advantages in multi-source detection and background noise suppression over existing techniques are confirmed.