Robust matched-field processing using a coherent broadband white noise constraint processor

Abstract

Adaptive matched-field processing (MFP) is not only very sensitive to mismatch, but also requires the received sound levels to exceed a threshold signal-to-noise ratio. Furthermore, acoustic sources and interferers have to move slowly enough across resolution cells so that a full rank cross-spectral density matrix can be constructed. Coherent-broadband MFP takes advantage of the temporal complexity of the signal, and therefore offers an additional gain over narrow-band processing by augmenting the dimension of the data space. However, the sensitivity to mismatch is also increased in the process, since a single constraint is usually not enough to achieve robustness and the snapshot requirement becomes even more problematic. The white noise constraint method, typically used for narrow-band processing, is applied to a previously derived broadband processor to enhance its robustness to environmental mismatch and snapshot deficiency. The broadband white noise constraint theory is presented and validated through simulation and experimental data. The dynamic range bias obtained from the snapshot-deficient processing is shown to be consistent with that previously presented in the literature for a single frequency.