Journal Article

Optimization of Sparse Cross Array Synthesis via Perturbed Convex Optimization

Chen, Yaowu, Jiang, Rongxin, Liu, Xuesong, Gu, Boxuan

2020

Overview

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 also support 3-D imaging while dramatically reducing the number of sensors. Moreover, the use of an aperiodic sparse array can further reduce the number of sensors efficiently. In this paper, an optimized method for sparse cross array synthesis is proposed. First, the beamforming of a cross array based on a multi-frequency algorithm is simplified for both near-field and far-field. Next, a perturbed convex optimization algorithm is proposed for sparse cross array synthesis. The method based on convex optimization utilizes a first-order Taylor expansion to create position perturbations that can optimize the beam pattern and minimize the number of active sensors. Finally, a cross array with 100 + 100 sensors is employed from which a sparse cross array with 45 + 45 sensors is obtained via the proposed method. The experimental results show that the proposed method is more effective than existing methods for obtaining optimum results for sparse cross array synthesis in both the near-field and far-field.

• Publisher: MDPI AG,MDPI
• Subject: Acoustics / Arrays / compressed sensing / Convex analysis / Methods / multi-frequency algorithm / Optimization algorithms / perturbed convex optimization / phased array 3-D imaging sonar system / Sensors / Sonar / sparse cross array / Three dimensional imaging