Triggering Imagery with Unattended Seismic/Magnetic Sensing for Vehicle Classification

摘要

Acoustic sensing has traditionally been the preferred method for the detection and classification of ground vehicles. However, environmental conditions such as wind and rain pose a great challenge to prevent false detections and misclassifications. The recent work of McQ System Innovations has demonstrated the ability to successfully detect and classify vehicles with the fusion of seismic and magnetic sensing without false detections and only a small percentage of misclassifications. The algorithms developed were designed to detect single vehicles as well as vehicles in a convoy. Based on the classification of each vehicle, an imager can be triggered to find the best frame of the target, and store the image in onboard memory to send back to an operator display. The methodology of the algorithms designed for seismic / magnetic detection and classification of vehicles is shown, as well as results of testing the algorithms running in a remote sensor.