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A feature point processing method and device

A processing method and feature point technology, applied in the computer field, can solve problems such as non-line-of-sight error and non-line-of-sight propagation, and achieve the effect of reducing non-line-of-sight error and improving positioning accuracy

Active Publication Date: 2017-01-25
BEIJING UNIV OF POSTS & TELECOMM
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example, when the signal is blocked by buildings, non-line-of-sight propagation will occur, causing the signal propagation distance measured by the positioning terminal to be greater than the real distance between the positioning terminal and the communication base station, forming a non-line-of-sight error
[0003] As the density of communication base stations increases, the NLOS error is relatively reduced, but it can still cause errors of tens of meters or even hundreds of meters

Method used

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  • A feature point processing method and device
  • A feature point processing method and device
  • A feature point processing method and device

Examples

Experimental program
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Embodiment 1

[0026] Such as figure 1 As shown, this embodiment provides a feature point processing method, including:

[0027] 110. According to whether every two feature points in the N feature points can be clustered into one class, a matrix S is established, and the elements in the matrix S are used to identify whether every two feature points in the N feature points can be clustered into one class, Wherein N is an integer greater than or equal to 2.

[0028] Wherein, the feature points are selected in advance, and the embodiment of the present invention does not limit the selection method of the feature points. figure 2 is a schematic diagram of a specific indoor scene, figure 2 The middle point is the selected feature point.

[0029] 120. Merge the elements in the matrix S to obtain the matrix S 1 , and for the matrix S 1 The elements in are classified.

[0030] Optionally, the same elements in the matrix S can be combined to obtain the matrix S 1 .

[0031] 130. Remove the ...

Embodiment 2

[0036] Such as image 3 As shown, this embodiment provides a feature point processing method, including:

[0037] 210. According to whether every two feature points among the N feature points can be clustered into one class, a matrix S is established, and the elements in the matrix S are used to identify whether every two feature points among the N feature points can be clustered into one class , where N is an integer greater than or equal to 2.

[0038] In this embodiment, it can be based on

[0039] | Δe a , b ( 1 , 2 ) | ≤ 4 d ( 1 , 2 ) + n - - - ( 1 )

[0040] Determine whether every two feature points in the N feature points can be clustered int...

Embodiment 3

[0076] Figure 5 For a positioning method provided in this embodiment, after processing by the feature point processing method in the above-mentioned embodiment 1 or 2, the positioning method uses the processed feature points to realize positioning, and the method includes:

[0077] 510. The positioning device matches the received X-channel TDOA signal with the pre-stored feature signal to obtain the target feature point most similar to the TDOA, where X is an integer greater than or equal to 2.

[0078] Specifically, the positioning device matches the received multiple TDOA signals with pre-stored feature signals to obtain the feature point most similar to TDOA, which is the target feature point.

[0079] And according to the feature point processing method of embodiment 1 or 2, a total of M feature points of the same type as the target feature point are obtained.

[0080] 520. The positioning device classifies the N feature points including the target feature point, and det...

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Abstract

The invention discloses a feature point processing method and device which can be used for reducing non-line of sight errors and accordingly improving positioning accuracy. The method comprises the steps: building a matrix S according to whether each two feature points in N feature points can be gathered into one type, wherein elements of the matrix S are used for marking whether each two feature points in the N feature points can be gathered into one type, and the N is an integer greater than or equal to 2; merging the elements in the matrix S to obtain a matrix S1, and sorting the elements in the matrix S1; removing isolated points in feature points corresponding to each type of element in the matrix S1, and using the feature points, left after the isolated points are removed, in the feature points corresponding to each type of element to position. In this way, the feature points are sorted, and the isolated points are removed, so that the non-line of sight errors are reduced, and the positioning accuracy can be improved by the left feature points after the isolated points are removed.

Description

technical field [0001] The invention relates to the field of computers, in particular to a feature point processing method and device. Background technique [0002] The communication base station has a wide coverage and low promotion cost. The positioning based on the communication base station is an important means to realize the indoor location service. In indoor positioning based on communication base stations, non-line-of-sight (abbreviated as NLOS, English full name is None Line of Sight) error is an important source of error. For example, when the signal is blocked by buildings, non-line-of-sight propagation will occur, causing the signal propagation distance measured by the positioning terminal to be greater than the real distance between the positioning terminal and the communication base station, resulting in a non-line-of-sight error. [0003] As the density of communication base stations increases, the NLOS error is relatively reduced, but it can still cause erro...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W64/00
Inventor 邓中亮余彦培王克己安倩阮凤立李晓阳马文旭
Owner BEIJING UNIV OF POSTS & TELECOMM
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