An Optimized Spatial Sampling Strategy for Wide-View Planar Array 3-D Sonar Sensors

Abstract

Array-based imaging sonar sensors often have the advantage that the sampling directions in which sensor data are processed can be arbitrarily chosen. The associated computational cost of the imaging algorithm scales linearly with the number of sampled directions, though, which may limit the use of such sensors for real-time applications such as robotics. This is especially true in the case of wide-field sensors, which generally require a larger number of sampled directions (e.g., to cover the full frontal hemisphere). For this reason, it is necessary to optimize the set of sampling directions and reduce its number to a minimum. In this article, we propose a spatial sampling strategy for array-based sonar sensors, which considers the point-spread function of the array sensor to obtain such a minimal set. We apply this strategy to optimize the set of sampling directions for a specific planar array sonar sensor and compare the efficiency of the resulting sampling grid with two commonly used sampling strategies.