LAUSR

In an assault on a military fortress, the attacking side often attacks the fortress through the use of underground mining, so that the defensive side cannot be prepared. The existing monitoring methods make it difficult to monitor such underground excavation. One effective way to monitor for tunneling activity is to detect and identify seismic signals generated by underground excavation. However, the main problem facing the practical application of this technology is that many behaviors on the ground may generate seismic signals, and the monitoring system cannot identify whether a signal is generated by underground excavation or by someone walking on the ground, resulting in a high false alarm rate. To effectively identify underground excavation signals, we propose an approach for estimating speed based on a double point synchronization measurement. In our approach, we first formulate mathematical models of the velocities of underground and ground-level objects. Then, signals acquired by different seismic detectors are used to estimate the velocities of underground and ground-level objects. By analyzing the differences between velocities, signals due to human movement and underground excavation are effectively identified. Lastly, simulations and a field test are performed. It is found that the proposed approach can effectively distinguish between signals generated by a human moving at ground-level and underground excavation. Our approach can be helpful for reducing the false alarm rate of a monitoring system.