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Direction of arrival estimation method based on rank-one denoising model

A direction-of-arrival estimation and model technology, applied to radio wave measurement systems, instruments, etc., can solve problems such as time-consuming, loss of signal covariance matrix information, and high computational complexity

Active Publication Date: 2019-09-17
XIDIAN UNIV
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Problems solved by technology

However, this method is time-consuming due to the iterative process, and the removal operation may cause some information contained in the signal covariance matrix to be lost
[0007] The traditional sparse reconstruction algorithm mentioned above is not very ideal for DOA estimation performance of dense sources and multi-targets, and the computational complexity is large

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Embodiment Construction

[0056] The embodiments and effects of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0057] refer to figure 1 , the implementation steps of the present invention are as follows:

[0058] Step 1, establish the received signal model x(t) of the radar, and determine the measurement matrix X of the received signal.

[0059] (1.1) Set the signal receiving radar as a uniform linear array containing M array elements, then the echo signal x(t) of the target source received at time t, its expression is:

[0060] x(t)=As(t)+n(t)

[0061] Wherein, A is steering matrix, s(t) is signal waveform vector, n(t)=[n 1 (t),n 2 (t),...,n M (t)] T is a zero-mean additive non-uniform complex Gaussian white noise vector, and n(t)~CN(0,Q), Q is the noise covariance matrix related to n(t).

[0062] (1.2) The expression of steering matrix A is:

[0063] A=[a(θ 1 ), a(θ 2 ), a(θ l ),…,a(θ L )];

[0064] Among them, L is the nu...

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Abstract

The invention discloses a direction of arrival estimation method based on a rank-one denoising model. The method comprises the following specific steps: establishing a receiving signal model of radar, and determining a measurement matrix of receiving signals; according to the measurement matrix of receiving signals, constructing a signal covariance matrix based on the rank-one denoising model; carrying out sparse reconstruction on the signal covariance matrix based on the rank-one denoising model; and according to sparse reconstruction signal vectors, using an alternated grid optimization algorithm to estimate direction of arrival of a target signal source. According to the method, under unknown non-uniform noise conditions, based on the rank-one denoising model, non-uniform noise is eliminated by redesigning the covariance matrix of dimensionality reduction signals, then equivalent source vectors are obtained by using vectorization operation, and finally high-resolution direction of arrival estimation with a limited number of snapshots and high robustness of non-uniform noise prevention are realized by using and determining the direction of arrival of signals.

Description

technical field [0001] The invention belongs to the technical field of radar signal processing, in particular to a direction-of-arrival estimation method based on a rank-one denoising model. Background technique [0002] Determining the direction of arrival (DOA) of a signal from a sensor array is a fundamental problem in the field of array signal processing, involving radar, sonar, communication, and radio astronomy. [0003] Existing studies have shown that traditional signal subspace methods for DOA estimation, such as the Multiple Signal Classification (MUSIC) algorithm and the Rotation Invariant Subspace (ESPRIT) algorithm, with enough snapshots of Gaussian white noise, can Achieve relatively high-precision and ultra-high-resolution DOA estimation. The matching pursuit (MP) algorithm and the orthogonal matching pursuit (OMP) algorithm use the sparse characteristics of the signal obtained by the sensor array, and greatly improve the performance of the direction of arriv...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/41
CPCG01S7/41
Inventor 朱圣棋王如杰房云飞刘婧曾操王博王磊
Owner XIDIAN UNIV
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