An optimal approach to tracking a moving source in the presence of environmental variability is presented. This tracking algorithm, called the optimum uncertain field tracking algorithm (OUFTA), incorporates a model for the source motion as well as the uncertain ocean environment. The performance of the OUFTA is evaluated over a range of signal-to-noise ratios (SNRs) as a function of the number of observations by examining its ability to correctly estimate both the current source position and the entire source track. The improvement in performance provided by the OUFTA is illustrated by comparison to two suboptimal tracking algorithms. Results show that incorporating a priori knowledge of both the source dynamics and the ocean model provides the most accurate estimates of the source track.