The performance of passive acoustic signal-processing techniques can become severely degraded when the acoustic source of interest is obscured by strong interference. The application of matrix filters to suppress interference while passing a signal of interest with minimal distortion is presented. An algorithm for single-frequency matrix filter design is developed by converting a constrained convex optimization problem into a sequence of unconstrained problems. The approach is extended to broadband data by incoherently combining the responses of matrix filters designed at frequencies across a band of interest. The responses of single-frequency and multifrequency matrix filters are shown. Examples are given which demonstrate the effectiveness of matrix filtering applied to matched-field localization of a weak source in the presence of a strong interferer and noise. These examples show the matrix filter effectively suppressing the interference, thereby enabling the localization of the weak source. Standard matched-field processing, without matrix filtering, is not effective in localizing the weak source.
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