Hardware PSO for sensor network applications

This paper addresses the problem of emission source localization in an environment monitored by a distributed wireless sensor network. Typical application scenarios of interest include emergency response and military surveillance. A nonlinear least squares method is employed to model the problem of estimation of the emission source location and the intensity at the source. A particle swam optimization (PSO) approach to solve this problem produces solution qualities that compete well with other best known traditional approaches. Moreover, the PSO solution achieves the best runtime performance compared to the other methods investigated. However, when it is targeted on to low capacity embedded processors PSO itself suffers from poor execution performance. To address this problem a direct, flexible and efficient hardware implementation of the PSO algorithm is developed, resulting in tremendous speedup over software solutions on embedded processors.