A set of related signal processing techniques for remote sensing that involve matching measured signals obtained from an array of sensors to synthesized signals obtained from signal propagation simulations conducted in a model of the actual environment. Here the signals are typically acoustic or electromagnetic waves, but they may be water waves, seismic waves, structural waves, or any other measurable phenomenon that travels in a predictable manner from its source to a distant receiver. Matched-field processing is the extension of elementary sensor-array signal processing techniques for line-of-sight signal propagation in uniform unbounded environments to complicated, but predictable, signal propagation in nonuniform bounded environments. Matched-field processing is superior to these elementary techniques because it can explicitly account for reflection, refraction, and scattering of the signal as it propagates from its source to the sensors. However, this superior performance is possible only when the signal propagation simulations are accurate and the model environment matches the environment in which the signal propagation took place.