| 1. |
- Du, Lin, et al.
(författare)
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Review of user parameter-free robust adaptive beamforming algorithms
- 2009
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Ingår i: Digital signal processing (Print). - : Elsevier BV. - 1051-2004 .- 1095-4333. ; 19:4, s. 567-582
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Forskningsöversikt (refereegranskat)abstract
- This paper provides a comprehensive review of user parameter-free robust adaptive beamforming algorithms. We present the ridge regression Capon beamformers (RRCBs), the mid-way (MW) algorithm, and the convex combination (CC) as well as the general linear combination (GLC) approaches. The purpose of these methods is to mitigate the effect of small sample size and steering vector errors on the standard Capon beamformer (SCB). We also present sparsity based iterative beamforming algorithms, namely the iterative adaptive approach (IAA), maximum likelihood based IAA (referred to as IAA-ML) and M-SBL (multi-snapshot sparse Bayesian learning), which exploit sparsity to estimate the signal parameters. We provide a thorough evaluation of these beamforming methods in terms of power and spatial spectrum estimation accuracies. output signal-to-interference-plusnoise ratio (SINR) and resolution under various scenarios including coherent, non-coherent and distributed sources, steering vector mismatches, snapshot limitations and low signal-to-noise ratio (SNR) levels. Furthermore, we discuss the computational complexities of the algorithms and provide insights into which algorithm is the best choice under which circumstances.
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| 2. |
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| 3. |
- Li, Jian, et al.
(författare)
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Covariance beamforming, covariance matrix tapers and matrix beamforming are related
- 2008
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Ingår i: Electronics Letters. - : Institution of Engineering and Technology (IET). - 0013-5194 .- 1350-911X. ; 44:5, s. 383-384
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Tidskriftsartikel (refereegranskat)abstract
- It is shown that the covariance beamforming, covariance matrix tapers and matrix beamforming approaches, which were considered separately from one another in the previous array processing literature, are in fact related. The relationships between them in terms of both generality and design procedures are clarified.
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| 4. |
- Ling, Jun, et al.
(författare)
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Enhanced channel estimation and efficient symbol detection in MIMO underwater acoustic communications
- 2009
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Ingår i: Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers. - : IEEE Communications Society. - 9781424458257 ; , s. 600-604
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Konferensbidrag (refereegranskat)abstract
- Effective training sequences and reliable channel estimation algorithms are essential for enhancing the performance of multi-input multi-output (MIMO) underwater acoustic communications (UAC). Also, effective interference cancellation schemes are crucial for reliable symbol detection. In this paper, the problem of designing MIMO training sequences is considered. Moreover, we present a sparse learning via iterative minimization (SLIM) algorithm for enhanced channel estimation and reduced computational complexity. Furthermore, RELAX-BLAST, a linear minimum mean-squared error based symbol detection scheme, is implemented efficiently by exploiting the conjugate gradient method and diagonalization properties of circulant matrices. The proposed MIMO UAC techniques are evaluated using both simulated and experimental examples.
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| 5. |
- Ling, Jun, et al.
(författare)
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On Bayesian channel estimation and FFT-based symbol detection in MIMO underwater acoustic communications
- 2014
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Ingår i: IEEE Journal of Oceanic Engineering. - 0364-9059 .- 1558-1691. ; 39:1, s. 59-73
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Tidskriftsartikel (refereegranskat)abstract
- Reliable channel estimation and effective interference cancellation are essential for enhancing the performance of multiple-input-multiple-output (MIMO) underwater acoustic communication (UAC) systems. In this paper, an efficient user-parameter-free Bayesian approach, referred to as sparse learning via iterative minimization (SLIM), is presented. SLIM provides good channel estimation performance along with reduced computational complexity compared to iterative adaptive approach (IAA). Moreover, RELAX-BLAST, which is a linear minimum mean-squared error (MMSE)-based symbol detection scheme, is implemented efficiently by making use of the conjugate gradient (CG) method and diagonalization properties of circulant matrices. The proposed algorithm requires only simple fast Fourier transform (FFT) operations and facilitates parallel implementations. These MIMO UAC techniques are evaluated using both simulated and in-water experimental examples. The 2008 Surface Processes and Acoustic Communications Experiment (SPACE08) experimental results show that the proposed MIMO UAC schemes can enjoy almost error-free performance even under severe ocean environments.
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| 6. |
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| 7. |
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| 8. |
- Roberts, William, et al.
(författare)
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Sparse signal representation for MIMO radar imaging
- 2008
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Ingår i: Proceedings of the 42nd Asilomar Conference on Signals, Systems, and Computers: Oct 26-29, 2008, Pacific Grove, California, USA.
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Konferensbidrag (refereegranskat)
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