Self Calibrating, Self Locating Seismic-Acoustic Sensor System

The ability to process seismic and acoustic data in order to estimate the range and bearing to a target is an important component of current remote ground sensing efforts. The accuracy of these estimates can be enhanced by networking multiple transducers and performing collaborative source localization, but such systems can be difficult to use and limited in their accuracy, size and capacity. We propose developing S-CLASS, a seismic and acoustic data collection system comprising many wireless satellite sensors and a central acquisition and processing resource. The coordinating resource controls connection admission, transmission timing and a human-machine interface. The sensor nodes each transmit up to four independent channels of sensed data to the coordinating resource, which applies a time and frequency correction function to all data channels to synchronize the data records relative to each other. The sensor network uses synthetic calibration signals to discover the positions of all its constituent nodes with great accuracy, and to calibrate the range and line of bearing measurements computed by the network.