Cooperative group localization based on weighted factor graphs

Multiple-target localization in ill conditions is very important in wireless location for next-generation wireless networks. The cooperative group localization (CGL) has indicated the effectiveness on performance gain and simultaneous multiple-target localization for the ill-conditioned localization problem. However, two inherent difficulties exist in the CGL: the strict demand for CGL topology and the high complexity. In order to solve the above rub, we propose a novel weighted factor graph CGL algorithm by formulating the location problem into the factor graph (FG) framework. Belief information (BI) is iteratively passed in node-FG and inter-FG to realize the proposed algorithm. Simulation results show that the proposed algorithm not only achieves high accuracy, but also enjoys low complexity in ill conditions.