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Signal sources estimation method and its DOA estimation method

A technology of direction-of-arrival estimation and the number of sources, which is applied to direction finders using radio waves, directional multi-channel systems using radio waves, space launch diversity, etc., can solve the problem of increasing hardware overhead, consuming calculations, and calculations reduction and other issues

Inactive Publication Date: 2012-08-15
INST OF ACOUSTICS CHINESE ACAD OF SCI
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Therefore, in order to obtain the correct direction of arrival, if the Geiger disc estimation method is used to estimate the number of sources, it is inevitable to perform two eigenvalue decompositions as just mentioned, which consumes a large amount of calculation. Increased hardware overhead
Again, it is difficult to perform operations in the real number space, and cannot obtain the benefits of reducing the amount of operations in the real number space

Method used

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  • Signal sources estimation method and its DOA estimation method
  • Signal sources estimation method and its DOA estimation method
  • Signal sources estimation method and its DOA estimation method

Examples

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example 1

[0145] In this example, the simulation calculation is carried out. The main parameters used in the simulation calculation are similar to the examples in the article by H.T.Wu et al. The example in the article by H.T.Wu et al. is to show the advantages of the Geiger disc estimation method. The results will show that the present invention is significantly superior to the prior art. The parameters of X(t) simulation calculation are: the spacing d between adjacent elements of a uniform linear array is half a wavelength, the number of elements M=6, the number of targets K=2, and the incident angle (θ 1 , θ 2 ) are -10° and 10° respectively, the signal-to-noise ratio |S| 2 / 2σ n 2 is 5db, the number of snapshots is 100, and the incident signal frequency is 150kHz. The results of the real number eigenspace method, the complex eigenspace method and the Geiger's disk method of the present invention are all shown in Fig. 2, and the criterion value of the former two is represented by...

example 2

[0147] Under the condition of equal power of the signal source, the success probability of the real number feature space method and the complex number feature space method of the present invention are compared with the signal-to-noise ratio. The parameters of X(t) simulation calculation are: a uniform linear array of 8 primitives, and the distance between primitives is half a wavelength. Three independent narrow-band signals of equal power are incident on the acoustic array at the incident angles of 10°, 20° and 30° respectively, the signal frequency is 150kHz, and the noise is spatial Gaussian white noise. The number of snapshots is 20, and the signal-to-noise ratio changes from -5db to 20db. The real number feature space method, the complex number feature space method and the Geiger's circle method independently estimate the number of information sources 200 times, and use the Monte Carlo method to obtain their respective success probabilities, see image 3 . It can be see...

example 3

[0149] Under the condition of unequal signal source power, the success probability of the real number feature space method and the complex number feature space method of the present invention are compared with the change of the signal-to-noise ratio of the source number estimation. The parameters of X(t) simulation calculation are: three independent signals of different powers are incident on the sound array, the incident angles are 40°, 45° and 60° respectively, the signal power ratio is 1:2:1, the signal-to-noise The ratio is based on the minimum signal power, and the number of snapshots is 50. Other conditions are the same as Example 2, and the calculation results are shown in Figure 4 . It can be seen from the figure that in the case of unequal signal source power, the real feature space method and the complex feature space method are still better than the Geiger circle method, and the real feature space method is the best. In addition, the Geiger's circle method requir...

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Abstract

The invention discloses a source number estimation method based on the feature space in the DOA estimation, which comprises the following steps: (1) obtaining the signal received by a uniform linear array; (2) calculating a covariance matrix by the received signal; (3) obtaining the covariance matrix of plural or plural which is changed into real number; (4) applying the eigenvalue decomposition of the covariance matrix to obtain the eigenvector matrix; (5) obtaining the source number criterion by the eigenvector; (6) obtaining the scale value; (7) estimating the source number. The source number estimation method can accurately estimate the source number, save a mass of calculated amount for the signal process of DOA estimation and reduce the hardware overload.

Description

technical field [0001] The invention relates to a signal processing method in direction of arrival estimation, in particular to a method for estimating the number of information sources based on feature space, and a method for estimating direction of arrival using the method for estimating the number of information sources. Background technique [0002] Most of the processing methods in direction of arrival estimation are based on the signal subspace algorithm. In this processing method, the number of signal sources (referred to as the number of signal sources) is required to be known, and the signal subspace and the noise subspace are orthogonal to each other. This results in a correct direction of arrival estimate. However, in practical situations, the number of sources is often not known when estimating the direction of arrival, so it is necessary to estimate the number of sources first. If the number of sources is incorrectly estimated, the signal subspace and the noise ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04B7/04H04L1/06
CPCG01S3/74
Inventor 朱维庆胡隽刘晓东刘治宇潘锋
Owner INST OF ACOUSTICS CHINESE ACAD OF SCI