A Distributed Sequential Ellipsoidal Intersection (DSEI) fusion algorithm based on the conditional Kalman filtering method is proposed for the state estimation of a multisource asynchronous measurement system with measurement missing phenomena.The system measurement missing phenomena are modeled and described by a set of random variables obeying Bernoulli distribution.The synchronized state space module synchronizes the asynchronous measurement system at the measurement update moment using the state iteration method.The local filtering module is implemented by using the conditional Kalman filtering algorithm to ensure the integrity of the filtering results.In fusion estimation modulea DSEI fusion algorithm is designed to fuse the filtering results provided by each sensor without considering the correlation information among multiple sensors.The simulation example verifies the superior performance of the proposed algorithm with an accuracy improved by 35% and an iteration time less than 3 ms.