Nonlinear smoothing algorithms are studied where the white noise disturbance in the observation is treated directly, instead of the usual modelling through its integrated version of Brownian motion. This framework yields results already in the robust form. Furthermore, the Itô integrals involving the observations do not appear in this approach, thereby eliminating complications arising out of considering backward Itô integrals in the smoothing problems.