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In practice, the fusion center of distributed multisensor system has to deal with out-of-sequence local estimated data. By considering the relation between local fusion estimation and fusion center, the estimation from local fusion nodes is regarded as a pseudo-measurement in this paper. Then the distributed estimation algorithm is turned to be two-level centralized fusion estimation and the new optimal distributed fusion estimation algorithm is obtained with Kalman filtering form, which in general only centralized estimation method has. Then, this paper develops optimal one-step-lag OOST(out-of-sequence tracks) method for distributed multisensor system by combining pseudo-measurement distributed fusion estimation algorithm and optimal one-step-lag OOSM - A1. Simulations show the developed algorithm has the excellent estimation performance.