The emerging tensor beamformers are capable of structurally filtering multi-dimensional
signals of sensor arrays. Although the popular sparse arrays have been utilized to enhance …

Adaptive beamforming using sparse arrays can alleviate system burden with a sub-Nyquist
sampling rate while achieving high resolution. To process multi-dimensional signals without …

In the past few years, multidimensional array processing emerged as the generalization of
classic array signal processing. Tensor methods exploiting array multidimensionality …

Sparse array direction-of-arrival (DOA) estimation using tensor model has been developed
to handle multidimensional sub-Nyquist sampled signals. Furthermore, augmented virtual …

Sparse arrays are popular for performance optimization while keeping the hardware and
computational costs down. In this paper, we consider sparse arrays design method for …

Sparse arrays are favored due to their inherent capability of optimizing the hardware and
computational resources in executing the prescribed performance. The main emphasis on …

Three-dimensional (3-D) imaging sonar systems require large planar arrays, which incur
hardware costs. In contrast, a cross array consisting of two perpendicular linear arrays can …

An adaptive beamforming scheme based on vector-sensor arrays is implemented using two
different matrix contractions of the 4th order covariance tensor. This tensorial beamformer …

Robustness is of great importance in array beamforming. With the purpose of improving the
robustness of the array beamforming, methods using tensor operations are explored in this …

Imaging and mapping sonars such as forward-looking sonars (FLS) and side-scan sonars
(SSS) are sensors frequently used onboard autonomous underwater vehicles. To acquire …