The joint use of data from GRACE-like gravity missions and various ocean altimetry missions in a global inversion approach allows to quantify the individual contributions to global and regional sea level budgets. However, the contribution from the Antarctic Ice Sheet (AIS) is subject to large uncertainties mainly depending on the applied strategy to account for effects due to glacial isostatic adjustment (GIA). The large uncertainty of GIA affects estimates of AIS contributions as well as other elements of sea level budgets. Here, we investigate strategies to improve the representation of AIS mass changes within an existing global inversion framework. The framework employs pre-defined, time-invariant spatial patterns, the so-called fingerprints, for representing the individual sea-level budget components, including AIS contributions. We improve this inversion method by including additional observations of satellite altimetry over ice sheets, and by further developing the parametrization of AIS ice mass changes. We extend from a basin-wise spatial resolution to a parametrization that resolves time-variable ice mass changes at about 50km, enabling a better localization of the AIS contributions to global and regional sea level change. From real-data experiments, we obtain ice mass balance estimates that are well within the uncertainty bounds of published reconciled estimates utilizing similar data sets. In particular, inclusion of ice altimetry improves the spatial resolution and at the same time keeps the global inversion results in line with those from regional GRACE analyses. We find differences between inversion results with and without including ice altimetry as an additional observation. These differences are smaller for the time period after 2010 with the availability of CryoSat-2 altimetry having improved sensor technology and high-latitude coverage. This indicates that these differences are caused by ice altimetry errors, whose further characterization and consideration within the estimation remains a future task. Furthermore, the spatial distribution of the differences suggests that they are also related to GIA errors. The improved representation of ice sheets in the global framework developed here provides a pre-requisite for working towards minimizing GIA-related errors while assessing the ice sheets’ mass balance.