SBIR-STTR Award

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

There is an immediate need in urban conflicted areas for networks of disposable sensors that are rapidly deployable and that provide a sufficiently high data rate to move the burden of signal processing for data fusion to a central acquisition and processing resource. Although such a wide area sensing system promises gains in the utility of sensor networks, it presents several unique hardware and software challenges that must be addressed, especially in network management, data synchronization and sensor geolocation. Nova Engineering proposes Phase II seminal research culminating in the demonstration of the first “Self Calibrating, Self Locating Acoustic Seismic Sensor System” (S-CLASS). S-CLASS answers the need for large scale processing of sensor data distributed over a wide area, in applications such as event detection, source localization and target tracking. S-CLASS replaces legacy systems with tethered transducers and highly limited collection capacity, enabling large-baseline array processing over a large time aperture. S-CLASS is meant as a high-rate, shorter mission complement to existing and future low-rate sensor systems whose primary objective is a long service life. The prototype system consists of a COTS sensor controller, networked radio, and a software defined network controller that hosts the network management function and human interface.

Keywords:
Sensor Networks, Geolocation, Acoustic, Seismic, Sensors, First Responders, Situational Awareness, Force Protection