Active underwater electrolocation method with PSO-based adaptive threshold estimation.

Abstract

Target detection and localization are essential capabilities for underwater vehicles to perceive and understand the underwater environment. In turbid, dark and semi-enclosed waters, such as underwater caves, acoustic and optical sensing devices face serious problems of reverberation and attenuation of the detection range, respectively. Weakly electric fish use their electric organ in the tail to produce repetitive discharges, while their electric receptors in the head and trunk detect electrical signals. This enables them to locate targets, avoid predators and facilitate hunting. In this paper, a bio-inspired active underwater electrolocation method is proposed, in which an adaptive contour-ring based target localization method is applied to provide both robust and accurate localization results for vehicles. In particular, on the basis of the efficient generation of prior contour-ring maps with high confidence and high precision, a particle swarm optimization theory-based adaptive threshold estimation algorithm was proposed to overcome the problem of non-uniqueness in the traditional contour ring-based method, while an electrode array pattern that integrates positioning accuracy and number of electrodes is proposed. Tank experiments have demonstrated the positioning accuracy of the proposed method.