The optimum detection of an unknown object in an uncertain random wave scattering environment is considered. A physics-based approach to the design of the optimum detector is presented which merges statistical physical modeling of the acoustic scattering medium with a probabilistic description of environmental prior knowledge within a Bayesian decision-theoretic framework. For the high-frequency, shallow water, reverberation-limited environment considered herein, the parametrization of the acoustic medium is essentially limited to modeling acoustic interaction with anisotropic seafloor microroughness with unknown horizontal wave-number spectrum parameters. Simulation results, presented in terms of receiver operation characteristic (ROC) curves, aim to illustrate three principal points: (1) the cost of ignoring the bottom reverberation spatial coherence when it is present in the data; (2) the sensitivity of the likelihood ratio detector for a known environment to incorrect prior knowledge of the microroughness wave-number spectrum; and (3) the robust performance realizable by the optimum detection algorithm that properly accounts for environmental uncertainty within a Bayesian framework. © 1995, Acoustical Society of America. All rights reserved.