A multiuser positioning algorithm in aid of user-to-user (U2U) distances is proposed in this paper. The cost function is the combination of non-linear least squares (NLS) of time of arrival (TOA) of multiple users and the NLS of U2U distances among users. Particle swarm optimization (PSO) is applied to search the best positions of the multiple users in a given hyper-dimensional space. The PSO is known to have the advantages of low complexity and easy for parallel computing. Simulations show that the multiuser positioning method can improve the overall positioning accuracy by up to four times compared to single user positioning.