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Proceedings Paper

Integration of lidar with the NIITEK GPR for improved performance on rough terrain
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Paper Abstract

Vehicle-mounted ground-penetrating radar (GPR) has proved to be a valuable technology for buried threat detection, especially in the area of military route clearance. However, detection performance may be degraded in very rough terrain or o-road conditions. This is because the signal processing approaches for target detection in GPR rst identify the ground re ection in the data, and then align the data in order to remove the ground re ection. Under extremely rough terrain, antenna bounce and multipath eects render nding the ground re ection a dicult task, and errors in ground localization can lead to data alignment that distorts potential target signatures and/or creates false alarms. In this work, commercial-o-the-shelf light detection and ranging (LIDAR), global positioning system (GPS), and inertial measurement unit (IMU) were integrated with a GPR into a prototype route clearance system. The LIDAR provided high-resolution measurements of the ground surface prole, and the GPS/IMU recorded the vehicle's position and orientation. Experiments investigated the applicability of the integrated system for nding the ground re ection in GPR data and decoupling vehicle motion from the rough surface response. Assessment of ground-tracking performance was based on an experiment involving three prepared test lanes, each with dierent congurations of buried targets and terrain obstacles. Several algorithms for target detection in GPR were applied to the data, both with traditional preprocessing and incorporating the LIDAR and IMU. Experimental results suggest that the LIDAR and IMU may be valuable components for ground tracking in next-generation GPR systems.

Paper Details

Date Published: 11 May 2012
PDF: 11 pages
Proc. SPIE 8357, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVII, 83571U (11 May 2012); doi: 10.1117/12.919119
Show Author Affiliations
Christopher R. Ratto, Duke Univ. (United States)
Kenneth D. Morton, Duke Univ. (United States)
Ian T. McMichael, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Brian P. Burns, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
William W. Clark, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Leslie M. Collins, Duke Univ. (United States)
Peter A. Torrione, Duke Univ. (United States)


Published in SPIE Proceedings Vol. 8357:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVII
J. Thomas Broach; John H. Holloway, Editor(s)

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