Chairs: Prof. Hai Liu (Guangzhou University),  Dr. Tian Lan (Beijing Institute of Technology)

Abstract:

Ground penetrating radar (GPR) is an important shallow non-destructive testing method, which is widely used in roads, walls, tunnels, archaeology, planetary exploration, plant protection and other fields. Compared with other radars, the working environment of GPR is complex, and it is more difficult to detect and identify buired targets, and the existing pulse/step frequency system mainly uses traditional data clutter suppression and manual interpretation of B-scan images, which is difficult to meet the needs of large depth, fast scanning, high resolution, precise imaging and recognition, and the needs of advanced detection and recognition of GPR are becoming increasingly urgent. 

With the continuous improvement of antenna, chip and circuit capabilities, the penetration and scanning capabilities of GPR systems can become higher and higher, and with the study of clutter suppression and imaging methods, it can provide high signal-to-noise ratio and intuitive position and morphological information for GPR data interpretation. Due to the promotion of artificial intelligence technology, the feature extraction, detection and recognition capabilities of GPR targets have received extensive attention, and have become an important direction for the development of GPR technology. In the face of higher detection requirements, how to integrate more radar features and other physical means is also a topic of discussion in the industry and academia in recent years. In the face of different detection environments, it has also become an important development direction of GPR to automatically plan path, depth, resolution and other parameters with fast and contactless detection methods, and broaden the application scenarios of GPR. Warmly welcome relevant experts and scholars engaged in GPR to actively submit!