A Bayesian approach to high-resolution beamforming

The ideas involved in the application of Bayesian statistics to the areas of spectral analysis and parameter estimation are here extended to provide a high-resolution algorithm for direction-of-arrival estimation. The simplest form of the algorithm, essentially a Bayesian maximum likelihood (BML) technique, is discussed and it is found that in the case of very low signal-to-noise ratios and closely-separated sources, the BML algorithm outperforms methods such as MUSIC and other eigen-decomposition techniques. One of the advantages of the present method is that it is able to handle special cases such as coherent and correlated signals and it does not assume the receivers to be equally spaced. It is also particularly well suited to the problem of estimating the directions of signals of quite different frequencies, and in such a case, the frequency and bearing estimation can be obtained simultaneously