Recursive model-based target recognition for acoustic land mine detection

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 be used as a major part of the automatic landmine recognition. 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.