An indoor cooperative localization method for high-density targets based on received signal strength indication (RSSI) is proposed for the indoor environment problem. In indoor environments, the true positions of the assisted localization targets are unknown and the cumulative error of the inertial navigation system becomes large when the localization module of some targets fail. Using the improved interactive multimodel extended Kalman filter (IMM-EKF) algorithm, the auxiliary target position was integrated as an unknown parameter into the state vector of each model. This integration effectively mitigates the effect of the auxiliary target position error on the positioning accuracy and prevents the accumulated error of the inertial navigation system after module failure. Simulation experiments demonstrated that the standard deviation of the positioning error in the X- and Y-directions was reduced by 32.19% and 23.45%, respectively, compared with that of the traditional IMM-EKF cooperative positioning method, thereby improving the positioning accuracy of indoor targets while maintaining a high positioning effect of the localized targets in the case of positioning module failure.