Two-dimensional arrays offer the potential for producing three-dimensional acoustic imaging. The major problem is the complexity arising from the large number of elements in such arrays. In this paper, a synthesis method is proposed that is aimed at designing an aperiodic sparse two-dimensional array to be used with a conventional beam-former. The stochastic algorithm of simulated annealing has been utilized to minimize the number of elements necessary to produce a spatial response that meets given requirements. The proposed method is highly innovative, as it can design very large arrays, optimize both positions and weight coefficients, synthesize asymmetric arrays, and generate array configurations that are valid for every steering direction. Several results are presented, showing notable improvements in the array characteristics and performances over those reported in the literature.

Underwater exploration is becoming more and more important for many applications involving physical, biological, geological, archaeological, and industrial issues. This paper aims at surveying the up-to-date advances in acoustic acquisition systems and data processing techniques, especially focusing on three-dimensional (3-D) short-range imaging for scene reconstruction and understanding. In fact, the advent of smarter and more efficient imaging systems has allowed the generation of good quality high-resolution images and the related design of proper techniques for underwater scene understanding. The term acoustic vision is introduced to generally describe all data processing (especially image processing) methods devoted to the interpretation of a scene. Since acoustics is also used for medical applications, a short overview of the related systems for biomedical acoustic image for motion is provided. The final goal of the paper is to establish the state of-the art of the techniques and algorithms for acoustic image generation and processing, providing technical details and results for the most promising techniques, and pointing out the potential capabilities of this technology for underwater scene understanding.

Frequency-invariant beam patterns are often required by systems using an array of sensors to process broadband signals. If the spatial aperture is shorter than the involved wavelengths, using a superdirective beamforming is essential to get an efficient system. In this context, robustness of array imperfections is a crucial feature. In the literature, only a few approaches have been proposed to design a robust, superdirective, frequency-invariant beamformer based on filter-and-sum architecture; all of them achieve frequency-invariance by imposing a desired beam pattern. However, the choice of a suitable desired beam pattern is critical; an improper choice results in unsatisfactory performance. This paper proposes a new method of array synthesis that allows the design of a robust broadband beamformer with tunable tradeoff between frequency-invariance and directivity, without the need for imposing a desired beam pattern. The latter is defined as a set of variables that do not depend on frequency and are included in the vector of variables to be optimized. To this end, a suitable cost function has been devised whose minimum can be found in closed form. Therefore, the method is analytical and computationally inexpensive. In addition, a technique that allows obtaining a beam pattern with a linear phase over frequency is described. The results show the effectiveness of the proposed method in designing robust superdirective beam patterns for linear arrays receiving far-field signals, with special attention to microphone arrays of limited aperture.

In this paper, the preliminary design and assessment of a high-resolution 3-D acoustic imaging system based on a sparse planar array of sensors, which is particularly intended for underwater applications, are presented. Critical issues in the development of high-resolution 3-D sonar systems are 1) the cost of hardware, which is associated with the huge number of sensors that compose the planar array, and 2) the computational burden of processing the signals that were gathered. Here, such problems are overcome by the optimized synthesis of an aperiodic sparse array that allows the device to operate at different frequencies, yielding an acceptable sidelobe level and a good tradeoff between the field of view and the resolution. The array optimization is performed using an efficient stochastic method, in which the number of sensors is minimized, whereas their positions and weights are simultaneously optimized. To test the validity of the designed system, the signals that the sparse array received in response to the insonification of a scene with a wideband pulse are simulated, and voxel-based beamforming is applied to generate the 3-D image. The obtained images show high fidelity to the geometrical characteristics of the scene, in accordance with the expected performance of the 3-D sonar system.