On information theoretic criteria for determining the number of signals in high resolution array processing

An important problem in high-resolution array processing is the determination of the number of signals arriving at the array. Information theoretic criteria provide a means to achieve this. Two commonly used criteria are the Akaike information criterion (AIC) and minimum descriptive length (MDL) criterion. While the AIC tends to overestimate even at a high signal-to-noise ratio (SNR), the MDL criterion tends to underestimate at low or moderate SNR. By excluding irrelevant parameters, a new log likelihood function has been chosen. Utilizing this new log likelihood function gives a set of more accurate estimates of the eigenvalues and in the establishment of modified information theoretic criteria which moderate the performance of the AIC and the MDL criterion. Computer simulations confirm that the modified criteria have superior performance