In this letter, a novel factor graph approach to target localization in distributed MIMO radars is proposed. To achieve robust localization in the presence of outliers, target localization can be formulated as a least absolute deviation (LAD) problem, which, however, is difficult to solve. We then reformulate the LAD problem as a reweighted least square (LS) one, which is converted to a product of some functions, enabling the use of factor graph techniques. Based on a factor graph representation, a highly efficient message passing algorithm is developed, where the target location is estimated in an iterative way. Comparisons with state-of-the-art methods show that the proposed method is superior in terms of computational complexity, robustness and accuracy.