Theoretical Results on Sparse Representations of Multiple-Measurement Vectors

Chen, Jie; Huo, Xiaoming

doi:10.1109/tsp.2006.881263

Cited by 739 publications

(641 citation statements)

References 36 publications

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“…According to [6] Theories of clutter degree of freedom (DOF) [7] indicate that clutter can be represented by only Q ¼ rankðÈÞ vectors of È, Eq. (8) can thus be transformed to where…”

Section: Mmv-jsr Model Of Mimo Radar Received Signalmentioning

confidence: 99%

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MMV-JSR based STAP method using MIMO radar

Feng

Zhang²

2016

IEICE ComEX

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To improve the performance of sparse representation based space-time adaptive processing methods, the multiple measurement vectors joint sparse representation (MMV-JSR) model of MIMO radar received signal of testing range cell is established. Then, MMV FOCal Underdetermined System Solver is applied to estimate clutter-target space-time spectrum. At last, clutter plus noise covariance matrix and the weight vector of STAP processor are calculated based on the clutter distribution obtained by using the rough priori knowledge of target. Numerical results demonstrate that our method has great performance of clutter suppression and target detection. Keywords: MIMO radar, space-time adaptive processing, multiple measurement vectors, joint sparse representation Classification: Sensing References

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“…According to [6] Theories of clutter degree of freedom (DOF) [7] indicate that clutter can be represented by only Q ¼ rankðÈÞ vectors of È, Eq. (8) can thus be transformed to where…”

Section: Mmv-jsr Model Of Mimo Radar Received Signalmentioning

confidence: 99%

“…To overcome the problems mentioned above, we apply MMV-JSR [5,6] technique and MIMO radar to the CNCM estimation. We first demonstrate how MIMO radar received signal of testing range cell can be expressed as multiple snapshots with joint sparsity.…”

Section: Introductionmentioning

confidence: 99%

MMV-JSR based STAP method using MIMO radar

Feng

Zhang²

2016

IEICE ComEX

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“…Compressed sensing algorithms can be divided into two broad categories: (i) Single Measurement Vector (SMV) [5], [11] where the solution is a vector; and (ii) Multiple Measurement Vectors (MMV) [9], [10] where the solution is a two-dimensional array, or matrix.…”

Section: Compressed Sensingmentioning

confidence: 99%

“…The OMP technique and its variants developed for SMV have been extended to tackle MMV [9]. In this paper, we focus on the Orthogonal Matching Pursuit for MMV algorithm (OMPMMV) proposed in [10]. The steps of this iterative algorithm are summarized in Table 1.…”

Section: Compressed Sensingmentioning

confidence: 99%

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A New Approach to Sparse Image Representation Using MMV and K-SVD

Yang

Bouzerdoum

Phung

2009

Advanced Concepts for Intelligent Vision Systems

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A new approach to sparse image representation using MMV and K-SVD AbstractThis paper addresses the problem of image representation based on a sparse decomposition over a learned dictionary. We propose an improved matching pursuit algorithm for Multiple Measurement Vectors (MMV) and an adaptive algorithm for dictionary learning based on multi-Singular Value Decomposition (SVD), and combine them for image representation. Compared with the traditional K-SVD and orthogonal matching pursuit MMV (OMPMMV) methods, the proposed method runs faster and achieves a higher overall reconstruction accuracy. Abstract. This paper addresses the problem of image representation based on a sparse decomposition over a learned dictionary. We propose an improved matching pursuit algorithm for Multiple Measurement Vectors (MMV) and an adaptive algorithm for dictionary learning based on multi-Singular Value Decomposition (SVD), and combine them for image representation. Compared with the traditional K-SVD and orthogonal matching pursuit MMV (OMPMMV) methods, the proposed method runs faster and achieves a higher overall reconstruction accuracy.

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Geometrical Methods – Illustration with Hyperspectral Unmixing

Bioucas‐Dias,

2023

Source Separation in Physical‐Chemical Sensing

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Theoretical Results on Sparse Representations of Multiple-Measurement Vectors

Cited by 739 publications

References 36 publications

MMV-JSR based STAP method using MIMO radar

MMV-JSR based STAP method using MIMO radar

A New Approach to Sparse Image Representation Using MMV and K-SVD

Geometrical Methods – Illustration with Hyperspectral Unmixing

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