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Multiple signal classification method based on Sigmoid covariance matrix

A technology of multiple signal classification and covariance matrix, which is applied in the field of array signal processing, can solve the problems of performance deterioration and failure of multiple signal classification algorithms, and achieve the effect of good algorithm performance and good application prospects

Active Publication Date: 2016-08-31
DALIAN UNIV OF TECH
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Problems solved by technology

Under such non-Gaussian noise conditions, the performance of the multiple signal classification algorithm based on the traditional covariance matrix deteriorates significantly, or even fails.

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  • Multiple signal classification method based on Sigmoid covariance matrix
  • Multiple signal classification method based on Sigmoid covariance matrix
  • Multiple signal classification method based on Sigmoid covariance matrix

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Embodiment Construction

[0021] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The overall algorithm flow chart is as follows figure 1 Shown:

[0022] The first step is to estimate the parameters of the Sigmoid function based on the median of the signal amplitude containing noise

[0023] 1) First calculate the median of the signal amplitude containing noise, denoted as λ mid ;

[0024] 2) Then λ mid Into the formula (1), the Sigmoid nonlinear function suitable for the signal is obtained.

[0025] S(x)=λ 1 [1-exp(-λ 2 x)] / [1+exp(-λ 2 x)] (1)

[0026] Among them, λ 1 =1.5λ mid and lambda 2 =1.574λ mid is the scale factor used to adjust the approximate linear mapping region of the sigmoid nonlinear function.

[0027] The second step ...

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Abstract

The present invention belongs to the field of the array signal processing technology, and provides a multiple signal classification method based on a Sigmoid covariance matrix. The method has high inhibition capability for the pulse noise obeying the non-Gaussian distribution, and is able to realize the multiple signal classification in the condition of the pulse noise and estimate the wave reaching direction of each signal. The method comprises: 1) estimating the parameters of a Sigmoid function according to the median including the signal amplitude of noise; 2) estimating the Sigmoid covariance matrix outputted by the array through adaption of the Sigmoid function and the output vector of an uniform linear array; 3) performing characteristic constant decomposition of the Sigmoid covariance matrix and obtaining the estimation of the noise subspace; and 4) employing the noise subspace estimation for the space spectrum of the multiple signal classification, and estimating the wave reaching direction angle through adaption of the estimated value of the space spectrum. The multiple signal classification method based on a Sigmoid covariance matrix has good algorithm performance, and has a good application prospect in the real engineering application.

Description

technical field [0001] The invention belongs to the technical field of array signal processing, and relates to multiple signal classification and direction of arrival estimation methods under non-Gaussian noise conditions, in particular to a method for multiple signal classification and direction of arrival estimation based on a Sigmoid covariance matrix. Background technique [0002] Array signal processing technology is one of the theories in the field of signal processing. Since the multiple signal classification (Multiple Signal Classification, MUSIC) algorithm, which can classify multiple signals and estimate the direction of arrival, has been proposed, this algorithm has become an important part of array signal processing space spectrum. The iconic algorithm in the estimation theory system is also widely used in many military and national economic fields such as radar, communication, and sonar. [0003] Traditional multiple signal classification algorithms are mainly a...

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Application Information

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IPC IPC(8): G06K9/00
CPCG06F2218/14G06F2218/12
Inventor 邱天爽栾声扬朱永杰张金凤于玲刘涛马济通宋爱民
Owner DALIAN UNIV OF TECH
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