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Beam domain doa estimation based on compressive sensing

A technology of compressed sensing and beam domain, applied in direction finders using radio waves, systems for determining direction or offset, radio wave direction/deviation determination systems, etc., can solve problems such as high resolution of unfavorable angles

Active Publication Date: 2019-03-26
DALIAN UNIV
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AI Technical Summary

Problems solved by technology

However, the DOA estimation spectrum peak of the DantzigSelector algorithm is relatively wide, which is not conducive to high angle resolution

Method used

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  • Beam domain doa estimation based on compressive sensing
  • Beam domain doa estimation based on compressive sensing
  • Beam domain doa estimation based on compressive sensing

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Embodiment Construction

[0077] Attached below figure 1 The implementation steps of the present invention are further described in detail:

[0078] 1 Compressed Sensing Model

[0079] (1) Sparse dictionary description

[0080] suppose is a signal vector of N×1, then x can be expressed as a linear combination of column vectors in the sparse dictionary Ψ, and the corresponding coefficient is set to z i , i=1,2,…,N, namely

[0081]

[0082] where Ψ=[ψ 1 ,ψ 2 ,…,ψ N ] is an orthogonal sparse dictionary of N×N, z=[z 1 ,z 2 ,…,z N ] is an N×1-dimensional information vector containing K0 =K0 l representing the information vector z 0 norm.

[0083] (2) Measurement matrix description

[0084] Compressed sensing theory shows that x can be approximately reconstructed by M=KO(logN) linear projection measurements obtained on the M×N projection measurement matrix Φ, where the projection measurement matrix The sparse dictionary Ψ is not related to each other, and the elements in the measurement mat...

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Abstract

The invention belongs to the field of signal processing, aims to solve the problem that a traditional DOA (direction of arrival) estimation algorithm is large in sampling data volume to cause high computation complexity, and provides a beam-domain-based multi-measurement-vector underdetermined system regularization focusing solving (BS-RMFOCUSS) algorithm on the basis of a compressed sensing theory by using airspace sparsity of target signals. According to the algorithm, a target compressing signal is mapped to a beam domain from an element domain, the shortcoming that a sparse reconstructing algorithm cannot be used under the condition of low signal to noise ratio is overcome to a certain degree, and the algorithm complexity is low. Numerical simulation shows that the property of the algorithm is superior to that of the traditional DOA estimation algorithm, and the algorithm has high angular resolution and estimation precision, and can carrying out effective DOA estimation on coherent signals.

Description

technical field [0001] The invention relates to beam domain DOA estimation based on compressed sensing, and belongs to the technical field of computer applications. Background technique [0002] Direction of arrival (DOA) estimation is one of the important research contents in array signal processing, and has been widely used in radar, sonar, mobile communication, wireless sensor network and other fields. Since the 1960s, researchers have proposed a large number of effective DOA estimation algorithms, mainly including the minimum variance distortionless response (MVDR) proposed by Capon and the multiple signal classification method (multiple signal classification) proposed by Schmidt. , MUSIC) as the representative subspace algorithm. However, the above DOA estimation algorithms are all based on the following assumptions: the source signal needs to be statistically fixed and uncorrelated, the number of snapshots is large enough, and the signal noise ratio (SNR) is large eno...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S3/14G01S3/802
CPCG01S3/14G01S3/802
Inventor 王洪雁裴炳南房云飞郑佳季科乔恵娇
Owner DALIAN UNIV
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