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Multi-channel compressed sensing optimization method and system based on compressed sensing

A compressed sensing and compressed sensing technology, applied in the field of compressed sensing, can solve the problems of waste of sensor resources and redundant data collection, and achieve the effect of reducing correlation and improving reconstruction accuracy.

Active Publication Date: 2019-08-23
ANHUI UNIVERSITY
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Problems solved by technology

[0002] The current information acquisition technology is mainly based on the Nyquist sampling theorem, but it will lead to a large amount of data acquisition redundancy and waste of sensor resources during signal sampling.

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  • Multi-channel compressed sensing optimization method and system based on compressed sensing
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[0050] In order to further illustrate the features of the present invention, please refer to the following detailed description and accompanying drawings of the present invention. The accompanying drawings are for reference and description only, and are not intended to limit the protection scope of the present invention.

[0051] Such as figure 2 As shown, this embodiment adopts a multi-channel compressed sensing optimization method based on compressed sensing, including the following steps S1 to S3:

[0052] S1. Obtain the signal X of each channel, and use the measurement matrix to perform projection measurement on the signal of each channel to obtain the observed value vector Y MMV =ΦX+e=Aθ+e, wherein: X=[x 1 ,x 2 ,...,x j ,...,x J ], Φ is the measurement matrix, A is the perception matrix, θ is the projection coefficient, and e is the Gaussian noise;

[0053] S2. Use the singular value decomposition method to decompose the measurement matrix Φ to obtain the optimized...

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Abstract

The invention discloses a multi-channel compressed sensing optimization method and system based on compressed sensing, and belongs to the technical field of compressed sensing, and the method comprises the steps: carrying out the singular value decomposition of a measurement matrix, obtaining an optimized observation value vector, and reconstructing an original signal through employing a synchronous orthogonal matching pursuit joint reconstruction algorithm. Singular value decomposition is carried out on the measurement matrix, the separation design of the measurement matrix and the reconstruction matrix is achieved, the separable reconstruction matrix is obtained, the correlation between measurement values is reduced due to the fact that optimized reconstruction matrix lines are mutuallyorthogonal, the measurement values are used for reconstructing original signals, and the signal reconstruction precision is greatly improved.

Description

technical field [0001] The invention relates to the technical field of compressed sensing, in particular to a multi-channel compressed sensing optimization method and system based on compressed sensing. Background technique [0002] The current information collection technology is mainly based on the Nyquist sampling theorem, but it will lead to a large amount of data collection redundancy and waste of sensor resources during signal sampling. Compressed sensing (CS) theory shows that if a signal is sparse or compressible, a set of incoherent projections can be used from a small number of measurements below the Nyquist sampling rate under the condition of ensuring the accuracy of signal reconstruction. In order to accurately restore the original signal. This theory has been widely used in wireless sensor networks, image super-resolution reconstruction, seismic exploration and so on. [0003] At present, the CS theory only needs to be used for the internal signal structure o...

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Application Information

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IPC IPC(8): H03M7/30G06F17/16
CPCH03M7/3059H03M7/3082G06F17/16
Inventor 张成朱园园汤俊许海涛杨佐潘敏韦穗
Owner ANHUI UNIVERSITY
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