Collaborative signal processing for sensor networks
Stephen R. Blatt · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2000
Networks of distributed sensors offer the promise of persistent and inexpensive surveillance of critical areas, while posing problems in the design of algorithms for processing sensor data into useful information. Specific issues include combining raw data from multiple nodes while minimizing the use of RF links. Collaborative processing techniques that restrict communications to between nearby nodes are discussed. Techniques have been developed to build a consensus among sensor nodes about what is happening in the physical world through controlling collaboration between neighboring nodes and using neighborhood information to develop track information. These techniques are applied while minimizing power consumption through dynamic distribution of processing, approximate processing approaches, and efficient digital encoding of measurements.