Review on Detection and Identification Positioning Technology of Surface Unexploded Submunitions

Abstract

Long-range multi-purpose cluster munitions with reconnaissance, identification, strike and evaluation functions are widely used, and a large number of unexploded submunitions will be generated on the surface, which will greatly hinder the battlefield maneuver, deployment and depth attack. Due to its special visual characteristics, surface unexploded submunitions use imaging technology and deep learning technology for long-distance, large-area, non-contact rapid and accurate detection and recognition. This paper introduces the common methods of unexploded submunition detection and their advantages and disadvantages, summarizes the imaging characteristics of unexploded submunitions under different imaging technology conditions and their identification and positioning methods, analyzes the signifi-cant advantages of deep learning in the field of unexploded submunition detection and recognition. Then, a UAV-borne rapid detection, identification and positioning method based on deep learning for surface unexploded submunitions is proposed.

Keywords

• |unexploded submunition|deep learning|imaging technology|identification and positioning