Abstract:
The optimal approach to tracking a moving source in an uncertain environment is one which incorporates both the continuity of the environment in which the source is located and the nature of the source movement. This differs from the suboptimal approach which performs a series of optimal independent source localizations and then combines the results to estimate the path taken by the source. The optimum uncertain field processor (OUFP) [A. M. Richardson and L. W. Nolte, J. Acoust. Soc. Am. 89, 2280--2284 (1991)] is a class of algorithms which incorporates parameter estimation theory into source localization, making it a method of matched-field processing which is robust to uncertainties in the propagation environment and source parameters. However, previous applications of the OUFP have been for stationary sources. Incorporating the nature of the source motion into the OUFP results in a more accurate method of estimating the path taken by a moving source. The performance of this processor is evaluated by examining the probability of correctly estimating the source path and the mean absolute errors in range and depth of the estimated path. Specific results are presented for a shallow water environment. [Research supported by ONR (Ocean Acoustics).]