Subspace-based frequency estimation of sinusoidal signals in alpha-stable noise
Signal Processing - Signal processing with heavy-tailed models
Direction finding in non-Gaussian impulsive noise environments
Digital Signal Processing
High-resolution source localization algorithm based on the conjugate gradient
EURASIP Journal on Advances in Signal Processing
IEEE Transactions on Signal Processing
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The MUSIC algorithm is well known for its high-resolution capability, and various aspects of its statistical performance have been investigated. However, rigorous asymptotic analysis of one of its most important performance measures, the probability of resolution, is not available yet. We analyze the probability of the MUSIC algorithm resolving two spatially separated signal sources in the context of array processing. By formulating the resolution problem in the framework of statistical decision theory and directly determining the probability density function (PDF) of the indefinite and singular quadratic form that defines the resolution event, we arrive at an exact asymptotic formula for the probability of resolution. This is accomplished by a multistep procedure. Computer simulations have been performed to confirm the validity of the theory