Interference from noise and uncertainties in the environmental parameters are arguably the two most serious limitations in matched-field processing (MFP). Among the techniques that have been developed for handling these difficulties are the noise-canceling processor [M. D. Collins, N. C. Makris, and L. T. Fialkowski, “Noise cancellation and source localization,” J. Acoust. Soc. Am.96, 1773–1776 (1994)] and focalization [M. D. Collins and W. A. Kuperman, “Focalization: Environmental focusing and source localization,” J. Acoust. Soc. Am.90, 1410–1422 (1991)]. The noise-canceling processor is a generalization of the Bartlett processor that is based on matching the covariance matrix of the data with replica covariance matrices of the signal and the noise. Simulations are presented to illustrate the performance of the noise-canceling processor when there are errors in the noise replica. Focalization is a generalization of MFP in which environmental parameters are included along with source parameters in the search space. An implementation of this approach that is suitable for applications is developed and tested. The noise-canceling processor and focalization are used to simulate the localization of a source buried in noise in an uncertain environment.