The paper deals with the $H_{infty}$ deconvolution fixed-lag smoothing problem for a linear time-invariant discrete-time system with both known and unknown input series. The $H_{infty}$ fixed-lag smoother is derived by proposing a new approach termed as re-organized innovation analysis in Krein space. Under the new approach, it is clearly shown that the central deconvolution smoother in an $H_{infty}$ setting is the same as the one in an $H_2$ setting associated with one self-constructed stochastic state-space model. This insight allows us to calculate the complicated $H_{infty}$ deconvolution smoother in an intuitive and simple way. The deconvolution smoother is calculated by performing Riccati equation with the same order as the original system.