Study of statistical signal models in low-frequency underwater acoustic applications

Modern acoustic signal processing is often a combination of sound propagation physics and advanced signal processing algorithms, which involves intensive acoustic, environmental, and statistical modeling. This paper discusses three different statistical signal models in low-frequency matched-field processing accounting for different source and channel conditions, and presents the Cramer-Rao bound (CRB) associated with each model. CRB evaluation examples show that under the same signal-to-noise ratios, the source localization performance degrades with increasingly-complicated as well more realistic data models.