A major task in Functional Time Series Analysis is measuring the dependence within and between processes for which lagged covariance and cross-covariance operators have proven to be a practical tool in wellestablished spaces. This article focuses on estimating these operators of processes in Cartesian products of abstract Hilbert spaces. We derive precise asymptotic results for the estimation errors for fixed and increasing lag and Cartesian powers under very mild conditions, presumably even under the mildest that can be assumed, establish estimators for the principal components, and conduct a simulation study.