Byzantine tolerant target localization in wireless sensor networks over non-ideal channels

In [1], we have proposed an energy efficient localization scheme by modeling it as an iterative classification problem. We designed coding based iterative approaches for target localization where at every iteration, the Fusion Center (FC) solves an M-ary hypothesis test and decides the Region of Interest (ROI) for the next iteration. We also considered the presence of Byzantine (malicious) sensors in the network. In this paper, we further investigate the localization scheme proposed in [1] over non-ideal channels and propose the use of soft-decision decoding to compensate for the loss due to the presence of fading channels between the local sensors and the FC. We provide the performance evaluation of the soft-decision decoding approach in terms of the mean square error of location estimate and probability of detection of the target region.