Subspace signal processing structured noise
Subspace signal processing structured noise
Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
On the resolution performance of spectral analysis
Signal Processing
Signal processing applications of oblique projection operators
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Statistical resolution limits and the complexified Crame´r-Rao bound
IEEE Transactions on Signal Processing
Fundamental Limitations on the Resolution of Deterministic Signals
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Nonmatrix Cramer-Rao bound expressions for high-resolutionfrequency estimators
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Statistical Angular Resolution Limit for Point Sources
IEEE Transactions on Signal Processing
The Cramer-Rao bound on frequency estimates of signals closelyspaced in frequency
IEEE Transactions on Signal Processing
On the resolvability of sinusoids with nearby frequencies in the presence of noise
IEEE Transactions on Signal Processing
Bounds for sparse planar and volume arrays
IEEE Transactions on Information Theory
Imaging below the diffraction limit: a statistical analysis
IEEE Transactions on Image Processing
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The asymptotic statistical resolution limit (SRL), denoted by @d, characterizing the minimal separation to resolve two closely spaced far-field narrowband sources for a large number of observations, among a total number of M=2, impinging on a linear array is derived. The two sources of interest (SOI) are corrupted by (1) the interference resulting from the M-2 remaining sources and by (2) a broadband noise. Toward this end, a hypothesis test formulation is conducted. Depending on the a priori knowledge on the SOI, on the interfering sources and on the noise variance, the (constrained) maximum likelihood estimators (MLEs) of the SRL subject to @d@?R and/or in the context of the matched subspace detector theory are derived. Finally, we show that the SRL which is the minimum separation that allows a correct resolvability for given probabilities of false alarm and of detection can always be linked to a particular form of the Cramer-Rao bound (CRB), called the interference CRB (I-CRB), which takes into account the M-2 interfering sources. As a by product, we give the theoretical expression of the minimum signal-to-interference-plus-noise ratio (SINR) required to resolve two closely spaced sources for several typical scenarios.