Sensor network particle filters: motes as particles

We describe an algorithm for tracking an object using particle filtering in a sensor network comprised of smart dust-type motes. We investigate the situation where the motes are equipped with binary proximity sensors, low-power lasers and optical receivers for communication with nearby motes, and corner-cube arrays for communication with a central transceiver. The particle filter we describe is largely decentralized; a central transceiver performs no processing beyond a summation and weighted average. Individual motes act as the particles in that they represent candidate positions of the object. Propagation of the particle filter is performed through activation of appropriate neighbouring nodes with "weighted" messages. We provide simulation results of tracking a maneuvering object, comparing performance with a centralized particle filter