Adaptive Beamforming Applied to a Cylindrical Sonar Array Using an Interpolated Array Transformation

In applications such as fishery sonar and navigation, cylindrical or spherical arrays are often used because of the need for a 360° field of view. However, adaptive beamforming methods, known for their high angular resolution and interference rejection capabilities, often rely on a Vandermonde structure of the steering vectors. This is generally not the case for nonlinear arrays. In this paper, we use an interpolated array transformation to map the data to a virtual linear array before adaptive beamforming. We evaluate the performance of two different adaptive beam- formers using simulations as well as experimental data from the SX90 fish finding sonar. We show that the adaptive minimum variance (MV) and amplitude and phase estimation of a sinusoid (APES) beamformers offer a significant improvement in azimuth resolution compared to the conventional delay-and-sum (DAS) beamformer. The APES beamformer offers slightly more reliable amplitude estimates in the direction of interest compared to the MV beamformer, at the cost of a somewhat lower azimuth resolution. When applied to data from the SX90 fish finding sonar, the MV beamformer offers a 40%-50% improvement in resolution, while the APES beamformer offers an improvement of 20%-30%.