Source localization performance and the array beampattern
Signal Processing
Digital processing of random signals: theory and methods
Digital processing of random signals: theory and methods
The Barankin bound and threshold behavior in frequency estimation
IEEE Transactions on Signal Processing
Bounds for estimation of multicomponent signals with randomamplitude and deterministic phase
IEEE Transactions on Signal Processing
Harmonics in Gaussian multiplicative and additive noise: Cramer-Raobounds
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Cramer-Rao bounds and maximum likelihood estimation for randomamplitude phase-modulated signals
IEEE Transactions on Signal Processing
Frequency estimation in the presence of Doppler spread: performanceanalysis
IEEE Transactions on Signal Processing
Bounds for estimation of complex exponentials in unknown colorednoise
IEEE Transactions on Signal Processing
Harmonics in multiplicative and additive noise: performanceanalysis of cyclic estimators
IEEE Transactions on Signal Processing
Extended Ziv-Zakai lower bound for vector parameter estimation
IEEE Transactions on Information Theory
Detecting the number of 2-D harmonics in multiplicative and additive noise using enhanced matrix
Digital Signal Processing
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We address the problem of harmonic retrieval in the presence of multiplicative and additive noise sources. In the new context of a complex-valued non-circular Gaussian multiplicative noise, we express the Cramér-Rao bound (CRB) as well as the asymptotic (large sample) CRB in closed form. Below a certain SNR threshold and/or when the number of samples is not large enough, the CRB becomes too optimistic and therefore we also derive the Barankin bound (BB). The new theoretical expressions for the CRB and BB are then used to study the behavior of the performance bound with respect to the signal parameters. We especially describe the region (in terms of SNR and number of samples) for which the CRB and the BB differ. Finally we compare the performance of the square-power-based frequency estimate, which is equivalent to the non-linear least-squares-based estimate, to these bounds.