Abstract: A cooperative localization factor graph for the autonomous underwater vehicle (AUV) swarm integrated with inverted ultrashort baseline (iUSBL) system is constructed. Two cooperative localization methods of slave-AUV in an AUV swarm are proposed, namely the extended Kalman filter (EKF)-based cooperative localization method and particle belief propagation (BP)-based cooperative localization method, where the effect of the leader-AUV’s positioning error is mitigated. For the EKF-based cooperative localization method, the state of the slave AUV is reconstructed with the positioning information of leader-AUV to achieve cooperative localization. In the particle-BP-based cooperative localization method, the measurement particles are generated to realize cooperative localization. The proposed methods can solve the problem of poor real-time of traditional methods, and only require one-way acoustic positioning transmission measurement to realize the localization of the slave-AUV. Simulation results show that the two proposed cooperative localization methods of slave-AUV in an AUV swarm work well for AUVs with different localization abilities. Compared with the dead-reckoning method, the localization errors of two proposed methods are reduced by more than 80%, and the positioning error accumulation is effectively suppressed. Furthermore, the proposed cooperative localization methods can operate normally under a high packet loss rate of the underwater acoustic channel, and the localization performance is not significantly degraded.