High-resolution 3-D imaging by a sparse array: array optimization and image simulation

In this paper, the design of a high-resolution three-dimensional acoustic imaging system based on a sparse planar array of sensors is presented. The aim is to generate useful acoustic 3D images in underwater context. Towards this end, a planar array is mandatory, as a linear aperture does not allow one to discriminate signals coming from a 3D space. One critical issue in the development of high-resolution 3D sonar systems is the hardware cost associated to the necessary huge number of sensors. In this paper, an innovative 3D imaging system able to operate at different resolution levels is proposed that is based on a single sparse planar array consisting of only 584 elements. Such a limited number of sensors represents an important stage in designing 3D acoustic imaging systems, making feasible the achieving of a drastic reduction in both costs and successive processing associated to the system. The array optimization is performed by an efficient stochastic method based on the simulated annealing algorithm, in which the positions and the weights of the array elements are optimized simultaneously. To test the validity of the proposed system, the signals received by the sparse array as the response of a given scene insonified by a pulse are simulated. To move from the simulated signals to the 3D image of the scene, a voxel-based beamforming in the time domain is designed. Images are obtained that exhibit a high fidelity to the geometrical and physical characteristics of the assumed underwater environment.