Robust Mine Detection Algorithm for Acoustic and Radar Images.

摘要

Current research in minefield detection indicates that operationally no single sensor technology will likely be capable of detecting mines/minefields in a real-time manner and at a performance level suitable for a forward maneuver unit. Minefield detection involves a particularly wide range of operating scenarios and environmental conditions, which requires deployment of complementary sensor suites such as acoustic and ground penetrating radar sensors. To aid the sensor fusion required, we have focused on the development of a computationally efficient and robust detection algorithm applicable to a variety of these imaging sensors that exploits robust image processing techniques centered on meaningful target feature sets. This paper presents the detection technique, called the Ellipse Detector, emphasizing its robust architecture, and provides performance results for image data generated by complementary sensors.