In this paper, we consider the problem of jointly localizing a microphone array and identifying the direction of arrival of acoustic events. Under the assumption that the sources are in the far field, this problem can be formulated as a constrained low-rank matrix factorization with an unknown column offset. Our focus is on handling missing entries, particularly when the measurement matrix does not contain a single complete column. This case has not received attention in the literature and is not handled by existing algorithms, however it is prevalent in practice. We propose an iterative algorithm that works with pairwise differences between the measurements eliminating the dependence on the unknown offset. We demonstrate state-ofthe-art performance both in terms of accuracy and versatility.Index Terms-Low-rank matrix factorization, node localization, sensor array self-calibration, far field, missing and uncertain data.