  Chinese Remainder Theorem (CRT) is a powerful approach to solve ambiguity
resolution related problems such as undersampling frequency estimation and
phase unwrapping which are widely applied in localization. Recently, the
deterministic robust CRT for multiple numbers (RCRTMN) was proposed, which can
reconstruct multiple integers with unknown relationship of residue
correspondence via generalized CRT and achieves robustness to bounded errors
simultaneously. Naturally, RCRTMN sheds light on CRT-based estimation for
multiple objectives. In this paper, two open problems arising that how to
introduce statistical methods into RCRTMN and deal with arbitrary errors
introduced in residues are solved. We propose the extended version of RCRTMN
assisted with Maximum Likelihood Estimation (MLE), which can tolerate
unrestricted errors and bring considerable improvement in robustness.
