Abstract:
Matched-field processing techniques can be both ambiguity-prone and sensitive to errors in the assumed environmental conditions. Although greater robustness to environmental variability can be obtained by the use of data adaptive methods, such as the MV-EPC beamformer [J. L. Krolik, J. Acoust. Soc. Am. 92, 1408--1419 (1992)] or joint estimation of source and channel parameters [D. F. Gingras and P. Gersoft, J. Acoust. Soc. Am. 97, 3589--3598 (1995)], these strategies require higher signal-to-noise ratios. The methods presented here concern the design of robust nonadaptive beamformer weights with sidelobe levels which are less signal-to-noise ratio dependent. As with Chebyshev filters, the weights are designed to minimize the maximum magnitude-squared sidelobe level. Robustness to environmental mismatch is achieved by defining the sidelobe level as the magnitude-squared response averaged over an ensemble of environmental conditions. The two algorithms proposed are a fast iterative constrained minimum variance method and the use of a minimax quadratic programming technique. For an uncertain Mediterranean environment, an improvement in the maximum average sidelobe level of as much as 3 dB over the Bartlett beamformer is achieved. [Work supported by NRaD/ONR.]