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Spatial domain information joint estimation method under directional electromagnetic coupling effect

An electromagnetic coupling effect and joint estimation technology, applied in the field of signal processing, can solve problems such as failure, performance deterioration of super-resolution direction finding algorithm, etc.

Pending Publication Date: 2021-03-30
NORTHWESTERN POLYTECHNICAL UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At this time, the performance of these super-resolution direction-finding algorithms will seriously deteriorate, or even fail.

Method used

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  • Spatial domain information joint estimation method under directional electromagnetic coupling effect
  • Spatial domain information joint estimation method under directional electromagnetic coupling effect
  • Spatial domain information joint estimation method under directional electromagnetic coupling effect

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Embodiment Construction

[0055] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0056] The present invention estimates the DOA under the condition that the mutual coupling angle of the array elements is unknown, and obtains the signal estimation angle, such as figure 1 As shown, the specific steps are:

[0057] Step 1 The specific steps are as follows:

[0058] When the mutual coupling matrix is ​​related to the angle, the array model is expressed as:

[0059]

[0060] Among them, N is the number of snapshots, is the steering vector, (k=1,2,…,K), s k (t) is a narrowband signal, n(t) has a mean of 0 and a variance of Gaussian white noise, λ is the wavelength, d is the array element spacing, K is the number of directions of arrival, N is the number of snapshots c(θ k ) = [c 0 ,c 1 ,...,c m ,...,c M ],|c 0 |=1>|c 1 |>…>|c m |>|c m+1 |=…=|c M |=0, M is the number of array elements, m is the mutual coupling length, C(...

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Abstract

The invention provides a spatial domain information joint estimation method under a directional electromagnetic coupling effect, and the method comprises the following steps: calculating a covariancematrix of a received signal, performing eigenvalue decomposition, constructing a matrix only related to an angle, constructing a fitting equation by using a weighted subspace fitting algorithm, and estimating DOA to obtain a preliminary DOA estimation result; estimating a cross-coupling coefficient matrix by using the preliminarily estimated DOA, solving an array flow pattern by using the estimated cross-coupling matrix, and estimating the DOA again by using a subspace fitting algorithm. According to the method, the mutual coupling matrix corresponding to each direction of arrival is estimated, DOA is precisely estimated by using the estimated mutual coupling matrix, a fitting equation is constructed by using a subspace fitting algorithm, and the equation can be solved through an optimization problem. And the estimation performance is excellent, and the performance of the method is obviously superior to that of a subspace decomposition algorithm especially when the signal-to-noise ratio is low and the snapshot number is small.

Description

technical field [0001] The present invention relates to the field of signal processing, especially target direction of arrival estimation in array signal processing [0002] The (direction-of-arrival, DOA) method is suitable for using a uniform linear array combined with a weighted subspace fitting algorithm to achieve high-precision target direction of arrival estimation in the case of mutual coupling angle dependence. Background technique [0003] In the process of theoretical research in recent years, the progress of DOA estimation algorithms has been relatively rapid, and many algorithms with high estimation accuracy have emerged. The representative one is the multiple signal classification algorithm (multiple signal classification, MUSIC), which divides the data space into signal subspace and noise subspace through mathematical decomposition of array output (such as eigenvalue decomposition and singular value decomposition, etc.). space, using the orthogonality of thes...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/16G06F17/11
CPCG06F17/16G06F17/11
Inventor 汪跃先马菲王伶谢坚张兆林杨欣陶明亮粟嘉邢自健韩闯刘龙
Owner NORTHWESTERN POLYTECHNICAL UNIV
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