We introduce a fixed lag smoother algorithm based on the integrated probabilistic data association (IPDA) algorithm. IPDA jointly estimates both the target state and its existence. In this paper the joint density of target state and existence is extended for fixed lag smoothing. The proposed smoothing algorithm is also tested against various multiple target tracking parameters like state RMS estimation, number of true target detected, number of false target confirmed and target termination time and simulation results are also presented in the paper.