Recursive model-based target recognition for acoustic landmine detection

Ning Xiang; James M. Sabatier

doi:10.1117/12.479138

13 August 2002 Recursive model-based target recognition for acoustic land mine detection

Ning Xiang, James M. Sabatier

Proceedings Volume 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII; (2002) https://doi.org/10.1117/12.479138
Event: AeroSense 2002, 2002, Orlando, FL, United States

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 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.

Citation Download Citation

Ning Xiang and James M. Sabatier "Recursive model-based target recognition for acoustic land mine detection", Proc. SPIE 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII, (13 August 2002); https://doi.org/10.1117/12.479138

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