In order to solve the problem of abnormal value of underwater acoustic communication noise caused by complex underwater environment， a multi-AUV cooperative localization algorithm based on factor graph and chi-square detection is proposed. A factor graph model is developed to transform the global function estimation problem into a local function and product estimation problem， using cardinality to detect ranging noise outliers. The proposed algorithm significantly reduces the localization error compared with the conventional Kalman filtering algorithm in the presence of ranging noise outliers. The study is validated with mathematical simulations， showing that the proposed algorithm can effectively improve the positioning stability of the system and deal with the effects of ranging noise outliers on the positioning performance.