Signal Processing Techniques for Detection of Buried Landmines using Ground Penetrating Radar
The present thesis deals with the problem of detecting and classifying buried objects. The application in mind when addressing this problem is the detection of buried landmines. According to the International Committee of the Red Cross, about 100 million landmines are buried in 62 countries around the world. Modern landmines are to a large extent made out of plastic and ceramic materials. This makes detection with traditional sensors, such as metal detectors and magnetometers almost impossible. Another problem with these sensors is the high false alarm rate induced by metallic debris from exploded bomb shells.
A sensor type that may have the capability to overcome these problems is the impulse radar. The impulse radar can detect non-metallic objects buried in the ground. The large bandwidth of the radar also gives additional information that can be used for classification purposes. The classification abilities enable discrimination between mines and stones and metallic debris, thus reducing the false alarm rate.
The thesis presents signal processing techniques used for impulse radar based detection and classification of buried objects. The work constitutes a complete chain of algorithms, from pre-processing of measured data to the presentation of final results to a system operator.
All experimental results presented in the thesis are based on real measured data from an experimental impulse radar system, called BURLOC, developed at the Swedish Defence Research Establishment (FOA), Sweden.
ground penetrating radar