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ABSTRACT: : This paper formulates and solves a parameter estimation problem that shows how to combine, in a certain optimal and robust manner, measurements that arise from a finite collection of uncertain models. This scenario occurs, for example, in data fusion applications and in cases that involve systems that can operate under different failure conditions. An example in the context of macroscopic diversity in wireless cellular systems is considered. c fl2000 IFAC. Keywords: Robust estimation, data fusion, uncertain models, least-squares, regularization, CDMA, macroscopic diversity, cellular system. 1. INTRODUCTION Modeling errors in the data are common in practice and they can be due to several factors including the approximation of complex models by simpler ones, the introduction of experimental errors while collecting data, or even the presence of unmodeled or unknown effects. Regardless of their source, modeling errors can adversely affect the performance of otherwise optimal est...