Applying Reconfigurable Computing to Acoustic Sensors

Monday, December 01 2008

There is growing interest in the U.S. Armed Forces in the development of microsensor systems that are easily deployed and that support reconnaissance, surveillance, and target acquisition operations. Such systems contain sensors, signal conditioning and processing subsystems, a radio link, and a power source. The role of microsensors is to autonomously detect, classify, and localize targets of interest in a variety of environments. It is generally thought that a number of different sensor types (acoustic, seismic, magnetic, and imaging) may be used to provide orthogonal features to aid in this detection, classification, and localization. These systems must be small (hand-carried), light (100s of grams), inexpensive (less than $200), easily deployable, and have a long operating life.

In most instances, power consumption (and therefore system lifespan) is a key consideration. Communication bandwidth is often limited by such power constraints, so the amount of data that can be transmitted is minimal. In addition, limiting the amount of data transmission helps the microsensor avoid detection in instances where that is a concern. Communication is the largest consumer of battery power; therefore, much of the signal processing needed to implement the desired functionality must be performed within the previously mentioned size, power, and weight constraints of the microsensor itself to limit the amount of raw data transmitted and to maximize the amount of information. While these requirements highly constrain the microsensor components chosen, at the same time, they demand extremely high computational performance.

Finally, flexibility of the processing fabric is crucial to implement emerging algorithms and support a wide range of sensors and scenarios. Candidates for microsensor processing include application- specific integrated circuit (ASIC) technology, general-purpose processors (GPPs), and field-programmable gate arrays (FPGAs). Although ASIC technology can address the performance, power, and cost issues, an ASIC solution is fixed, requiring a unique design for each sensor type or a large ASIC that can support a finite number of preexisting sensors.