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Far-field coherent signal direction-of-arrival estimation method based on sub-space and interpolation transformation

A technology of direction of arrival estimation and coherent signals, applied in radio wave direction/deviation determination systems, direction finders using radio waves, complex mathematical operations, etc., can solve problems such as the difficulty of satisfying the ideal conditions of uniform linear array

Active Publication Date: 2019-12-03
XI AN JIAOTONG UNIV
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Problems solved by technology

However, the ideal condition of a uniform linear array is difficult to satisfy in practical applications.

Method used

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  • Far-field coherent signal direction-of-arrival estimation method based on sub-space and interpolation transformation
  • Far-field coherent signal direction-of-arrival estimation method based on sub-space and interpolation transformation
  • Far-field coherent signal direction-of-arrival estimation method based on sub-space and interpolation transformation

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Embodiment Construction

[0065] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0066] To divide the subspace of the real array, use the interpolation transformation technology to transform any array into a virtual uniform line array through the interpolation matrix, so as to realize the promotion of the SUWWE algorithm; the far-field coherent signal is incident on the non-uniform line array p coherent narrowband signals The non-uniform linear array includes M omnidirectional sensor array elements, and the value range of M is M>p, and the angle is the orientation information of the incident signal, where θ i Indicates the direction of arrival angle of the i-th incident signal, which is the counterclockwise angle of the i-th incident signal with respect to the y-axis, such as figure 1 shown.

[0067] A method for estimating the direction of arrival of far-field coherent signals based on subspace and interpolation transformati...

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Abstract

The invention discloses a far-field coherent signal direction-of-arrival estimation method based on sub-space and interpolation transformation. The method specifically includes: calculating correlation vectors on all sub-intervals; calculating optimal interpolation matrices; carrying out solving on correlation vectors of a virtual matrix by the interpolation matrices and the correlation vectors ofa real array; then constructing correlation matrices of the real array and the virtual array; then constructing a linear operator and an orthogonal projection operator; and finally, calculating polynomial roots, and obtaining a far-field coherent signal direction-of-arrival estimation by solving. The linear array sub-space is constructed, solving is carried out on the correlation vectors, and feature decomposition operation of computation complexity in a traditional sub-space algorithm is avoided on the premise of ensuring accuracy; interpolation is carried out on non-uniform arrays to form uniform arrays, then a root seeking algorithm is used to estimate a direction-of-arrival angle, and frequency spectrum searching of computation complexity is avoided; and in addition, the method generalizes an application range from uniform linear arrays to arbitrary linear arrays, and is effective even when the number of sensors is larger or a real-time estimation is needed.

Description

technical field [0001] The invention belongs to the technical field of array signal processing, and in particular relates to a method for estimating the direction of arrival of far-field coherent signals based on subspace and interpolation transformation. Background technique [0002] Source location has important applications in the fields of radar, sonar, wireless communication, etc. In practical applications, due to multi-path propagation of signals or intelligent interference in military affairs, the received signals are often coherent. In recent decades, subspace-based DOA estimation algorithms represented by Multiple Signal Classification (MUSIC) have been favored due to their good estimation accuracy. However, these traditional subspace algorithms are all based on the eigendecomposition of the covariance matrix, which is computationally complex and difficult to meet the requirements of large-scale arrays or real-time estimation. In order to avoid the computationally ...

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Application Information

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IPC IPC(8): G01S3/14G06F17/16
CPCG01S3/14G06F17/16
Inventor 辛景民肖同陈筱左炜亮郑南宁
Owner XI AN JIAOTONG UNIV
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