A sonar system using a sparse broadband 3D array for robotic applications

Abstract

We describe how, by combining broadband beamforming with a sparse, random array of receivers, we have constructed a low-cost, yet powerful, in-air sonar system which is suited for a wide range of robotic applications. In particular, we show how simple array beamforming techniques allow for the generation of 3D spatial filters that can be used to accurately localize objects in a large field of view without the need for mechanical scanning. Experimental validation of the sensor's capacity to produce 3D location measurements in the presence of multiple highly overlapping echoes is presented.