Landmine detection with ground penetrating radar using fuzzy K-nearest neighbors

This paper introduces a system for landmine detection using sensor data generated by a Ground Penetrating Radar (GPR). The GPR produces a three-dimensional array of intensity values, representing a volume below the surface of the ground. First, a constant false alarm rate (CFAR) detector is used to focus attention and identifv candidates that resemble mines. Next, we apply a feature extraction algorithm based on projecting the data onto the dominant eigenvectors in the training data. The training signatures are then clustered to identify few representatives, and a fuzzy k-nearest neighbor rule is used to distinguish true detections from false alarms.