A Multilinear Singular Value Decomposition
SIAM Journal on Matrix Analysis and Applications
3-D Unitary ESPRIT for Joint 2-D Angle and Carrier Estimation
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
Model order selection for short data: an exponential fitting test (EFT)
EURASIP Journal on Applied Signal Processing
Multidimensional rank reduction estimator for parametric MIMO channel models
EURASIP Journal on Applied Signal Processing
Non-parametric detection of the number of signals: hypothesis testing and random matrix theory
IEEE Transactions on Signal Processing
Tensor algebra and multidimensional harmonic retrieval in signal processing for MIMO radar
IEEE Transactions on Signal Processing
Training sequence optimization in MIMO systems with colored noise
MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume I
Blind high-resolution localization and tracking of multiplefrequency hopped signals
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Harmonic retrieval in colored non-Gaussian noise using cumulants
IEEE Transactions on Signal Processing
Passive localization of near-field sources by path following
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Harmonic retrieval in mixed Gaussian and non-Gaussian ARMA noises
IEEE Transactions on Signal Processing
Total least squares phased averaging and 3-D ESPRIT for jointazimuth-elevation-carrier estimation
IEEE Transactions on Signal Processing
Real-time frequency and 2-D angle estimation with sub-Nyquistspatio-temporal sampling
IEEE Transactions on Signal Processing
Paper: Modeling by shortest data description
Automatica (Journal of IFAC)
A hybrid approach to harmonic retrieval in non-Gaussian ARMA noise
IEEE Transactions on Information Theory
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R-dimensional (R-D) harmonic retrieval (HR) in colored noise, where R=2, is required in numerous applications including radar, sonar, mobile communications, multiple-input multiple-output channel estimation and nuclear magnetic resonance spectroscopy. Tensor-based subspace approaches to R-D HR such as R-D unitary ESPRIT and R-D MUSIC provide super-resolution performance. However, they require the prior knowledge of the number of signals. The matrix based (1-D) ESTimation ERror (ESTER) is subspace based detection method that is robust against colored noise. To estimate the number of signals from R-D measurements corrupted by colored noise, we propose two R-D extensions of the 1-D ESTER by means of the higher-order singular value decomposition. The first R-D ESTER combines R shift invariance equations each applied in one dimension. It inherits and enhances the robustness of the 1-D ESTER against colored noise, and outperforms the state-of-the-art R-D order selection rules particularly in strongly correlated colored noise environment. The second R-D scheme is developed based on the tensor shift invariance equation. It performs best over a wide range of low-to-moderate noise correlation levels, but poorly for high noise correlation levels showing a weakened robustness to colored noise. Compared with the existing R-D ESTER scheme, both proposals are able to identify much more signals when the spatial dimension lengths are distinct.