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Stokes parameters and 2-D DOAs estimation of polarized sources with an L-shaped coprime array
- Source :
- Digital Signal Processing. 78:30-41
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- In this paper, a sparse reconstruction based approach to estimate Stokes parameters and 2-D DOAs of polarized sources is proposed in case of unknown number of sources. An L-shaped coprime array composed of dipole-dipole pairs, where a dipole in the dipole-dipole pair is placed on x-axis and the other is placed on z-axis, is used to reduce the mutual coupling across two dipoles in the dipole-dipole pair. In order to estimate the elevation of polarized sources, an orthogonal matching pursuit algorithm with the identification of the sources' number (OMP-isn) is proposed. In our proposed approach, the quasi deterministic maximum likelihood (qDML) test step is added in each iteration of algorithm. In addition, a refining grid step is also added in each iteration to reduce the estimation error incurred by the grid mismatch. The OMP algorithm and sparse iterative covariance-based estimation (SPICE) method are employed to estimate the azimuth of polarized sources. In order to pari the azimuth with the elevation, a pair-matching method is proposed based on the l 2 -norm and l 1 -norm ( l 2 / l 1 ) minimization. Based on the pairing azimuth and elevation, Stokes parameters of polarized sources are estimated by using Least Squares (LS) or Total Least Squares (TLS). The stochastic CRB is derived for the 2-D DOAs and Stokes parameters of polarized sources. Simulations are used to verify the performance of the proposed approach.
- Subjects :
- 020301 aerospace & aeronautics
Applied Mathematics
Spice
020206 networking & telecommunications
02 engineering and technology
Covariance
Grid
Azimuth
symbols.namesake
0203 mechanical engineering
Computational Theory and Mathematics
Artificial Intelligence
Norm (mathematics)
Signal Processing
0202 electrical engineering, electronic engineering, information engineering
symbols
Stokes parameters
Computer Vision and Pattern Recognition
Minification
Electrical and Electronic Engineering
Statistics, Probability and Uncertainty
Total least squares
Algorithm
Mathematics
Subjects
Details
- ISSN :
- 10512004
- Volume :
- 78
- Database :
- OpenAIRE
- Journal :
- Digital Signal Processing
- Accession number :
- edsair.doi...........3483da5eaaf495a724da3deb3d918d79
- Full Text :
- https://doi.org/10.1016/j.dsp.2018.02.016