We present a rigorous approach to nonlinear estimation of signals in additive white Gaussian noise using the innovations method. The general argument is deliberately chosen to follow the same lines as in the linear case given in a previous note. Although a much heavier use of martingales is necessary here, the parallelism is quite striking.