Since Out-of-Sequence Measurement(OOSM) problem may occur in target tracking system, a filtering algorithm using covariance intersection was proposed to solve the problem on the basis of forward prediction.Based on forward prediction, a reconstructed track containing delay measurement information was established.Then the covariance intersection method was applied to fuse the reconstructed track with the existing track to achieve the update again.Through adopting information filter and covariance intersection method, the complex operations, such as calculating the inverse of state transition matrix and track correlation, were not needed again.The new algorithm can deal with both the one-step-lag and multi-step-lag OOSM situations.Theoretical analysis and simulation results show that the new algorithm achieves better real-time performance with less storage and computation cost while keeping the filtering precision.