Correlated/coherent signal directions of arrival estimation method based on covariance low-dimension iterative sparse reconstruction

A direction-of-arrival estimation and sparse reconstruction technology, applied to radio wave direction/bias determination systems, direction finders using electromagnetic waves, direction finders using radio waves, etc., can solve the problem of reducing covariance sparse reconstruction algorithm calculations Complexity, high complexity, loss of degrees of freedom and other issues, to achieve good estimation accuracy and reduce computational complexity

Active Publication Date: 2018-01-12
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

[0004] The purpose of the present invention is to solve the problem of the loss of degrees of freedom caused by the use of space smoothing in the subspace method and the problem that the existing covariance sparse reconstruction algorithm has too high complexity when estimating the direction of arrival of related and coherent signals, and proposes a method based on Covariance low-dimen

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  • Correlated/coherent signal directions of arrival estimation method based on covariance low-dimension iterative sparse reconstruction
  • Correlated/coherent signal directions of arrival estimation method based on covariance low-dimension iterative sparse reconstruction
  • Correlated/coherent signal directions of arrival estimation method based on covariance low-dimension iterative sparse reconstruction

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[0031] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0032] This embodiment provides a method for estimating direction of arrival of correlated / coherent signals based on low-dimensional iterative sparse reconstruction of covariance, and its process is as follows figure 1 As shown, it specifically includes the following steps:

[0033] Step 1. Use a non-uniform array composed of N array elements to receive K far-field narrowband signals, and get:

[0034] x(t)=As(t)+v(t),t=1,2,...,T

[0035] Among them, x(t)=[x 1 (t),...,x N (t)] T is the received signal of the array, and v(t) is the zero-mean Gaussian white noise on the array;

[0036]

[0037]

[0038]

[0039] Among them, θ={θ 1 ,θ 2 ,...,θ K} is the direction set of K signals, A is the direction matrix, s(t) is the signal vector, s i (t), i=1,2,...,K represents the i-th spatial narrowband signal, a(θ i ), i=1,2,..., K repre...

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Abstract

The invention belongs to the field of array signal processing, and provides a correlated/coherent signal directions of arrival estimation method based on covariance low-dimension iterative sparse reconstruction. The method comprises establishing a low-dimension covariance sparse reconstitution model through the Khatri-Rao product, and estimating a main diagonal element on the signal covariance matrix; (2) expanding the sparse reconstruction dictionary according to the non-zero main diagonal element position, estimating the non-diagonal elements of the signal covariance matrix again by means ofa sparse reconstruction algorithm; (3) updating the sparse reconstruction model according to the non-diagonal elements, re-estimating the main diagonal elements of the signal covariance matrix by means of the sparse reconstruction algorithm; and repeating the steps (2) and (3), estimating the directions of arrival of the signal according to the final main diagonal element of the signal covariancematrix. According to the method, the degree of freedom caused by the geometrical distribution of the special array can be fully utilized, the calculation complexity can be effectively reduced, and good estimation precision can be obtained.

Description

technical field [0001] The invention belongs to the field of array signal processing, and specifically provides a correlation / coherent signal direction-of-arrival estimation method based on covariance low-dimensional iterative sparse reconstruction. Background technique [0002] Direction of arrival estimation is an important research direction of array signal processing, which is mainly used in many economic and military fields such as radar, sonar, communication, seismic exploration, medical diagnosis and radio astronomy. For space signals that are independent of each other, the sensor array can be used to receive observation data and use subspace algorithm or sparse reconstruction algorithm to estimate its direction of arrival. However, in the actual environment, due to multipath propagation and other reasons, there will be correlation or coherent signals. Although the DOA estimation based on the subspace algorithm can use spatial smoothing technology to achieve decorrela...

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Application Information

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IPC IPC(8): G01S3/14G01S3/782G01S3/802
Inventor 段惠萍殷允杰张新月梁瀚明方俊
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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