Subarray split L-type co-prime array direction-of-arrival estimation method based on fourth-order sampling covariance tensor denoising

A technology of direction of arrival estimation and sampling covariance, which is applied to radio wave direction/deviation determination systems, measurement devices, and direction detectors for direction determination, etc., can solve the interference of high-order virtual domain statistical noise items, multi-dimensional sparse array reception Problems such as signal structure damage

Pending Publication Date: 2022-03-18
ZHEJIANG UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to propose a sub-array splitting formula based on fourth-order sampling covariance tensor denoising for the problem of damaged multi-dimensional sparse array receiving signal structure and high-order virtual domain statistic

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  • Subarray split L-type co-prime array direction-of-arrival estimation method based on fourth-order sampling covariance tensor denoising
  • Subarray split L-type co-prime array direction-of-arrival estimation method based on fourth-order sampling covariance tensor denoising
  • Subarray split L-type co-prime array direction-of-arrival estimation method based on fourth-order sampling covariance tensor denoising

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[0151] Simulation example: The incident signal is received by the sub-array separated L-shaped coprime array, and its parameters are selected as That is, the L-shaped coprime array of architectures contains antenna elements. Assuming that there are 22 incident narrowband signals, the two-dimensional parameter μ of the direction of arrival 1 (k) and μ 2 (k) are uniformly distributed on [-0.97, 0.97] respectively. subvariance combination weight λ 1 = 1, λ 2 =0.25,λ 3 =1. The method for estimating the direction of arrival of sub-array split type L-type coprime array based on the fourth-order sampling covariance tensor denoising proposed by the present invention is compared with the traditional Tensor Multiple Signal Classification (Tensor MUSIC) method, and the signal-to-noise ratio SNR= -5dB, under the condition that the number of sampling snapshots is T=500, the two-dimensional direction of arrival estimation performance of the above method under the underdetermined ...

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Abstract

The invention discloses a sub-array split L-type co-prime array direction-of-arrival estimation method based on fourth-order sampling covariance tensor denoising, which mainly solves the problems that a signal structure is damaged and high-order virtual domain statistics are interfered by noise items in the existing method, and comprises the following implementation steps of: constructing a linear sub-array split L-type co-prime array; modeling a received signal of the L-type co-prime array and deriving a second-order cross-correlation matrix; deriving a fourth-order covariance tensor based on the cross-correlation matrix; fourth-order sampling covariance tensor denoising is realized based on kernel tensor thresholding processing; deriving a fourth-order virtual domain signal based on a denoising sampling covariance tensor; constructing a de-noised structured virtual domain tensor; and obtaining a direction of arrival estimation result through structured virtual domain tensor decomposition. According to the method, high-order tensor statistical distribution characteristics of the constructed sub-array split L-shaped co-prime array are fully utilized, high-precision two-dimensional direction-of-arrival estimation is realized through de-noising virtual domain tensor signal processing, and the method can be used for target positioning.

Description

technical field [0001] The invention belongs to the technical field of array signal processing, and in particular relates to a statistical signal processing technology based on multi-dimensional sparse array high-order virtual domain statistics, specifically a sub-array split L-type coprime based on fourth-order sampling covariance tensor denoising An array direction-of-arrival estimation method can be used for target location. Background technique [0002] As a sparse array with a systematic structure, the coprime array has the advantages of large aperture, high resolution, and high degree of freedom. It can break through the limitation of the Nyquist sampling rate and improve the comprehensive performance of DOA estimation. In order to achieve DOA estimation matching the Nyquist sampling rate in the coprime array scenario, the common practice is to derive the coprime array received signal to a high-order statistical model, and realize the virtual domain based signal by con...

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Application Information

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IPC IPC(8): G01S3/14
CPCG01S3/143G01S3/74G01S3/043H01Q21/00
Inventor 陈积明郑航周成伟史治国王滨
Owner ZHEJIANG UNIV
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