Self‐surveying techniques for matched‐field processing

Abstract

The classic problem of matched‐field processing is the detection and localization of (unknown) sources assuming a known oceanic environment and a calibrated vertical line array of known shape. If a broadcasting source is deployed at a known location, the array shape can be determined through assumptions on the environment, or the environmental characteristics (such as the sound‐speed profile) can be determined if the array shape is known. These two problems are investigated in the framework of matched‐field processing. First, the array shape calibration is discussed and a simple procedure, using a correlation measure and a standard multidimensional optimization algorithm, is proposed. This procedure is used on simulated data (where convergence is observed) and on real data collected at sea in September 1987 with a 900‐m‐long array with 120 sensors. The experimental results are found consistent with those obtained through previous analysis. Then, the problem of calibrating the oceanic environment is studied using a normal mode formulation. Bucker's self‐cohering approach to correct for tame environmental mismatch in the matched‐field processor output [H. Bucker, 4th MFP Workshop, 6–8 Sept. 1989, Victoria, Canada], provides a convenient measure of the environmental mismatch for a range‐independent medium. An approach to tomography, using a vertical line array that samples well the normal modes, is proposed. The preliminary simulation results show that the Bucker correction factors provide a smooth measure of sound‐speed mismatch and that the inversion for the sound‐speed profile should be possible through optimization. [Work supported by ONR.]