Maximum-likelihood direction-of-arrival estimation in the presenceof unknown nonuniform noise
IEEE Transactions on Signal Processing
Reduced-Rank MDL Method for Source Enumeration in High-Resolution Array Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Estimation of the Number of Sources in Unbalanced Arrays via Information Theoretic Criteria
IEEE Transactions on Signal Processing
Source number estimators using transformed Gerschgorin radii
IEEE Transactions on Signal Processing
Analysis of the performance and sensitivity ofeigendecomposition-based detectors
IEEE Transactions on Signal Processing
A multistage representation of the Wiener filter based on orthogonal projections
IEEE Transactions on Information Theory
Hi-index | 35.68 |
It is well known that the conventional eigenvalue-based minimum description length (MDL) approach for source number estimation suffers from high computational load and performs optimally only in the presence of spatially and temporally white noise. To improve the robustness of the MDL methodology, we propose to utilize the minimum mean square error (MMSE) of the multistage Wiener filter to calculate the required description length for encoding the observed data, instead of relying on the eigenvalues of the data covariance matrix. As there is no need to calculate the covariance matrix and its eigenvalue decomposition, our derived MMSE-based MDL (mMDL) method is also more computationally efficient than the traditional counterparts. Numerical examples are included to demonstrate the robustness of the mMDL detector in nonuniform noise.