Fast conjugate gradient direction finding algorithm without constructing covariance matrix

A technology of covariance matrix and conjugate gradient, applied in computing, complex mathematical operations, computer components, etc., can solve the problems of high complexity of CG algorithm, reduce computational complexity, etc., and achieve the effect of avoiding high-complexity problems

Active Publication Date: 2021-08-06
HARBIN INST OF TECH AT WEIHAI
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  • Description
  • Claims
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Problems solved by technology

[0005] The present invention aims at the problem of the high complexity of the CG algorithm caused by the existing calculation of ACM, and proposes a method to replace the ACM with the received data matrix by improving the Wienerhoff equation to re...

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  • Fast conjugate gradient direction finding algorithm without constructing covariance matrix
  • Fast conjugate gradient direction finding algorithm without constructing covariance matrix
  • Fast conjugate gradient direction finding algorithm without constructing covariance matrix

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Embodiment

[0083] The performance of the present invention is illustrated below by embodiment simulation:

[0084] Simulation conditions: Assuming a ULA formation with 10 array elements and an array element spacing of d=λ2, the direction of the two incident signals is θ 1 = 10° and θ 2 = 30°. In order to further evaluate the performance of the present invention, the number of Monte Carlo experiments is set to 500, and the root mean square error (Root Mean Square Error, RMSE) is used as an evaluation index.

[0085] Simulation content and results:

[0086] Simulation 1 compares the spectral peak search diagram of the present invention, MUSIC algorithm and CG algorithm, the results are as follows figure 2 shown.

[0087] figure 2 Set the initial reference signal as d in 0 =Xa(θ) / ||Xa(θ)||, where θ∈(-90°, 90°). It can be seen from the figure that the spatial spectral peak of the least squares CG algorithm is sharper than that of the classical CG algorithm and the MUSIC algorithm, a...

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Abstract

The invention belongs to the technical field of array signal processing, and particularly relates to a fast conjugate gradient direction finding algorithm without constructing a covariance matrix, which can obviously reduce the calculation complexity under the condition of not losing precision, and is characterized in that after a radiation source signal is received, a Virnahoff equation is improved by using a least square method, a least square Winahoff equation is obtained, the least square Winahoff equation is used as a normal equation, a reference signal only related to received data is constructed by using the normal equation, an iteration initial value is set, conjugate gradient iteration is performed, a signal subspace is estimated according to an information source number, and a signal direction of arrival is acquired.

Description

Technical field: [0001] The invention belongs to the technical field of array signal processing, and specifically relates to a fast conjugate gradient direction-finding algorithm that significantly reduces the computational complexity and does not need to construct a covariance matrix without loss of precision. Background technique: [0002] Direction of arrival estimation of signals is an important research topic often encountered in applications such as radar, sonar, wireless communication, and passive positioning. The proposal of subspace algorithms represented by multiple signal classification and rotation invariant subspace has realized the leap from traditional spatial spectrum estimation to super-resolution angle measurement, but the huge amount of calculation of MUSIC algorithm and the low estimation accuracy of ESPRIT algorithm hinder The engineering progress of the super-resolution algorithm has been improved. In response to this problem, the birth of the Krylov s...

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Application Information

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IPC IPC(8): G06F17/11G06K9/00
CPCG06F17/11G06F2218/10
Inventor 闫锋刚刘帅王军赫靓李享孟祥天
Owner HARBIN INST OF TECH AT WEIHAI
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