Maximum-Entropy Spatial Processing of Array Data.

摘要

The procedure of maximum -entropy spectral analysis (MESA), used in the processing of time series data, also applies to wavenumber (bearing) analysis of signals received from a spatially distributed linear array of sensors. The method is precisely the use of autoregressive spectral analysis in the space dimension rather than in time. There are also close links to the predictive deconvolution method used in geophysical work, and to the process of constructing noise-whitening filters in communication theory, as well as to least-squares model building. In this note, the maximum-entropy procedure is reviewed and all these links are pointed out. The specific algorithm appropriate to a uniformly spaced line array of sensors is given as well as one possible algorithm for use in the case of nonuniform sensor spacing.