Abstract:

The optimal approach to tracking a moving source in an uncertain environment is one which incorporates a priori knowledge about both the continuity of the propagation environment and the nature of the source movement. The optimum uncertain field tracking algorithm (OUFTA) [S. L. Tantum and L. W. Nolte, ``Tracking and localizing a moving source in an uncertain shallow water environment,'' J. Acoust. Soc. Am. (submitted)] extends the optimum uncertain field processor (OUFP) [A. M. Richardson and L. W. Nolte, J. Acoust. Soc. Am. 89, 2280--2284 (1991)] to include modeling of the source motion as a Markov process. This differs from the suboptimal approach which performs a series of independent source localizations and then combines the results to estimate the path taken by the source. The performance of the OUFTA and the suboptimal approach is evaluated using the SWELLEX-1 data collected off the San Diego coast. Results using the SWELLEX-1 data are also presented which show how this optimal philosophy can be used to guide the modification of some popular beamformers, such as the minimum variance adaptive beamformer with environmental perturbation constraints (MV-EPC) [J. L. Krolik, J. Acoust. Soc. Am. 92, 1408--1419 (1992)], to incorporate source motion. [Work supported by ONR.]