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Multi-dimensional fitting source positioning method

A technology of source location and source, which is applied in the field of communication, can solve the problems of large amount of calculation for source location and inaccurate source estimation, and achieve the effect of improving accuracy and simple calculation

Active Publication Date: 2018-01-12
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to provide a multi-dimensional fitting source location method, which can solve the problems of large amount of calculation and inaccurate source estimation in the prior art

Method used

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  • Multi-dimensional fitting source positioning method
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  • Multi-dimensional fitting source positioning method

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Experimental program
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Embodiment 1

[0018] The covariance matrix R(ξ 0 ) first-order Taylor expansion,

[0019]

[0020] Based on the method of covariance fitting,

[0021]

[0022] Differentiate it,

[0023]

[0024] and let the differential result Get HΔξ=r, where the i-th row and k-column elements of the matrix H are i-th element of vector r Then get the deviation vector Δξ=H -1 r.

[0025] This embodiment 1 provides a multi-dimensional fitting information source location method based on Taylor series expansion, including the following steps:

[0026] A. Continuously sample the source T times to obtain the sampling function x(t), and calculate the covariance matrix

[0027] B. Search for the minimum value of K two-dimensional spatial spectrum to obtain the initial estimate of the source

[0028] C. Calculate the signal power of the source separately and noise power Get the initial vector of the airspace parameters

[0029] D. Construction of the first-order Taylor expansion of t...

Embodiment 2

[0035] The covariance matrix R(ξ 0 ) first-order Taylor expansion,

[0036]

[0037] Based on the weighted least squares method,

[0038]

[0039] Differentiate it,

[0040]

[0041] and let the differential result Get H 1 Δξ=r 1 , where matrix H 1 The elements of row i and column k are vector r 1 the ith element of Then get the deviation vector Δξ=H 1 -1 r1 .

[0042] This embodiment 2 provides a multi-dimensional fitting information source location method based on Taylor series expansion, including the following steps:

[0043] A. Continuously sample the source T times to obtain the sampling function x(t), t=1, 2, 3, ... T, and calculate the covariance matrix

[0044] B. Search for the minimum value of K two-dimensional spatial spectrum to obtain the initial estimate of the source

[0045] C. Calculate the signal power of the source separately and noise power Get the initial vector of the airspace parameters

[0046] D. Construction of the...

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Abstract

The invention discloses a multi-dimensional fitting source positioning method and relates to the communication technology field. The method comprises steps that A, a signal source is continuously sampled, and a covariance matrix is calculated; B, the minimum value of multiple source spatial domain spectrums is searched to acquire an initial estimation source azimuth vector of a spatial domain parameter of the source; C, a signal power and a noise power of the source are respectively calculated to acquire an initial vector xi0; D, a first-order taylor expansion expression of the covariance matrix is constructed; E, a deviation vector delta xi making the square of the norm the minimum is calculated; F, xi0=xi0+delta xi is updated; and G, whether the square of the norm is smaller than an error is determined, if not, the progress turns to the step C, if yes, the algorithm is ended, and xi0 is outputted. Compared with the prior art, the method is advantaged in that problems of large sourceestimation computational complexity and inaccuracy are solved.

Description

technical field [0001] The invention relates to the technical field of communication, in particular to a multi-dimensional fitting information source location method. Background technique [0002] Early source location techniques were mainly aimed at independent point sources. In fact, in addition to point sources, there are also distributed source models. In the distributed information sources, there are two kinds of coherent distributed information sources and non-coherent distributed information sources. For source localization, there have been many estimated localization methods——beamforming method and signal subspace method, and these methods have the problem of large computational complexity. In addition, there is another estimation algorithm, that is, the source location method based on discrete Fourier transform. However, this method is sometimes inaccurate for multidimensional source estimation. [0003] Existing techniques include the first scheme: a beamformin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S5/00H04B17/327H04B17/345
Inventor 庄杰王威段成华张添
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA