  Localization based on received signal strength (RSS) has drawn great interest
in the wireless sensor network (WSN). In this paper, we investigate the
RSS-based multi-sources localization problem with unknown transmitted power
under shadow fading. The log-normal shadowing effect is approximated through
Fenton-Wilkinson (F-W) method and maximum likelihood estimation is adopted to
optimize the RSS-based multiple sources localization problem. Moreover, we
exploit a sparse recovery and weighted average of candidates (SR-WAC) based
method to set up an initiation, which can efficiently approach a superior local
optimal solution. It is shown from the simulation results that the proposed
method has a much higher localization accuracy and outperforms the other
