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 due to the failure of the localization module of some targets. With an improved Interactive Multi-Model Kalman Filter (IMM-EKF) algorithm, the auxiliary target position is 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 demonstrate that the standard deviation of the positioning error in the X-direction is reduced by 32.19% and the standard deviation of the positioning error in the Y-direction is reduced by 23.45% compared with the traditional IMM-EKF cooperative positioning method, which improves the positioning accuracy of indoor targets and maintains a high positioning effect of the localized targets in the case of failure of the positioning module.
