Sensor-Fused Detection of Explosive Hazards

摘要

Forward-looking ground-penetrating radar (FLGPR) has received a significant amount of attention for use in explosive hazards detection. A drawback to FLGPR is that it is sensitive to not only explosive hazards but also to benign objects, which results in an excessive number of false detections. This paper presents our analysis of the explosive hazards detection system developed by Planning Systems Inc (PSI). The PSI system combines FLGPR with an infrared (IR) camera. We present an FLGPR target detection algorithm that leverages the multiple observations aspect of FLGPR. The FLGPR target detections are then projected into the IR imagery. A Mahalanobis-metric classifier is then used to reduce the number of false detections. We show that our proposed FLGPR target detection algorithm, coupled with our IR-based false alarm reduction method, is effective at detecting explosive hazards while reducing the number of false alarms.