The empirical distributions of normalized matched‐filter echoes from a midfrequency active sonar with hyperbolic frequency‐modulated waveforms in a myriad of oceanic environments are studied for three broad clutter classes: bottom structures, diffuse compact clutter (e.g., seaweed), and compact nonstationary clutter (e.g., biologics). The distributions are characterized using the K distribution and the generalized Pareto distribution. Methods of parameter estimation are discussed, and parameters are computed for small subregions of the clutter fields. A plot of the Kolmogorov–Smirnov goodness‐of‐fit statistic of individual subregions is presented for each model and class to highlight the versatility of the models when applied to large quantities of data. Cumulants are computed from the data and are utilized as features in a classifier to demonstrate separability between the classes. An important aspect of this work is the use of distinct clutter classes as opposed to collectively characterizing all clutter as reverberation. Environmental effects are not considered, as the goal of this work is to determine the utility of local clutter estimation models in practical sonar processing systems where accurate environmental data is unavailable. [This work is sponsored by the Office of Naval Research undersea signal processing discovery and invention program.]