Iterative model-based automatic target recognition for acoustic landmine detection

Abstract

A model has been developed to allow the scanned data obtained using a laser Doppler vibrometer-based acoustic-to-seismic landmine detection system to be analyzed without operator interaction. The ground vibration data from the LDV are pre-processed to form images in a 2-D data format. A parametric model was established to describe the amplified magnitude velocity phenomena induced by buried landmines. This model incorporates amplitude, size, position, and background amplitude parameters into an automatic analysis process. An iterative regression approach is described which can perform the automatic recognition of landmines. The estimated parameters, such as the amplitude relative to the background, the size, and the shape of a target, are used to make the decision regarding the presence of a mine. Once a positive decision is made, the estimated position parameters are used to localize the target location. [Work supported by the United States Army Communications-Electronics Command Night Vision and Electronic Sensors Directorate.]