BAYESIAN MODEL SELECTION APPLIED TO SPATIAL SIGNAL-PROCESSING

In the paper, inference is applied to the problem of direction of arri val estimation and the determination of the number of sources present in the case of signals impinging on a linear array of sensors. The met hod is discussed, and the algorithm is found to outperform methods suc h as AIC and MDL even in the case of very low signal-to-noise ratios a nd closely spaced sources. The two levels of inference involved in any data analysis problem are introduced and this inference methodology, using the concept of evidence, is then applied to this problem. Simula tion results illustrate the power of the method and it is shown that o ne of the advantages of the present approach is that it is able to han dle special cases such as coherent and correlated signals of any funct ional form, and it does not assume the receivers to be equally spaced.