Real-time threat detection using magnetometer arrays

In this paper we present a discussion of using an array of atomic magnetometers to locate the presence of ferrous materials, such as concealed weapons, in real time. Ferrous materials create magnetic field anomalies. In order to determine the location of such objects, readings from many positions must be analyzed. This field inversion is typically done in post processing, once readings over a survey area or region of interest have been gathered. With the recent development of small and low power sensors, the dozen or so sensors required to provide information for magnetic field inversion may be deployed. We have built such an array and present here the results of using a realtime inversion algorithm. The inversion algorithm accurately determines target properties at a rate of 10 times per second as objects move past the array. Accuracies are as good as those obtained with target inversion methods used in analyzing data for unexploded ordnance detection. While those methods are typically applied in post processing, we show here those methods work even better when applied in real-time. We further present some analyses of the predicted performance of arrays in various geometries to address issues in security, such as crowd or perimeter monitoring. Target inversion methods may be accurately simulated, allowing for the development and testing of algorithms in an efficient manner. Additional processing may be done using the time history of the inversion results to remove false alarms and enhance detection. The key step is to start with an inversion method, utilizing the mathematical properties of magnetic fields and the known geometry of the measurements.