A method for sonar based recognition of walking people

Abstract

In this paper we investigate the problem of recognising a person based on the rhythmic features of human walking. The perceptual task is performed using in-air sonar sensors. A linear array sensing head with limited complexity is developed to achieve the stated goal; the method of sensory information processing implemented in the device is a blend of grid based mapping and wavelet based multiresolution analysis. Grid based mapping allows to perform detection and tracking of a moving object at the highest signal-to-noise ratios; wavelet based multiresolution analysis allows us to detect the features that are peculiar to walking people in the range measurement sequence extracted from a single sonar sensor of the sensing head. Experimental tests on a number of moving objects with highly time-varying target strengths are carried out; the results prove the feasibility of the approach in terms of recognition rate and acquisition time. The present study contributes to understanding how in-air sonar sensors behave and interact with complex scatterers such as the human body; also, it offers promise for novel applications of sonar technologies in the field of advanced robotics, where the close interaction between human users and robotic systems is on stage.