Factor graph and damped expectation propagation based passive localization

The location awareness of a “passive” target has drawn much attention in recent years. Several papers have investigated passive localization in different scenarios. In this paper, we build a factor graph framework and show that the factor graph can be modified easily for different passive localization problems. Then the beliefs of unknown variables are obtained via message passing algorithms. To reduce the huge complexity of nonparametric message passing, we propose a damped expectation propagation method which restricts the messages on factor graph to Gaussian distributions. Simulations results verify the feasibility of proposed algorithm.