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WLAN indoor positioning error correction method and system based on location fingerprint

An indoor positioning and error correction technology, which is applied to services based on location information, services based on specific environments, positioning, etc., can solve problems such as unsatisfactory positioning accuracy, and achieve the effect of improving positioning accuracy

Active Publication Date: 2021-12-24
武汉创驰蓝天信息科技有限公司
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AI Technical Summary

Problems solved by technology

[0002] The existing technology uses online RSS average samples to calculate the position fingerprint positioning algorithm of the positioning results, and the RSS changes of the relevant reference points do not introduce correlation coefficients, resulting in unsatisfactory positioning accuracy

Method used

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  • WLAN indoor positioning error correction method and system based on location fingerprint
  • WLAN indoor positioning error correction method and system based on location fingerprint
  • WLAN indoor positioning error correction method and system based on location fingerprint

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Embodiment Construction

[0073] Such as figure 1 As shown, a WLAN indoor positioning error correction method based on location fingerprints, which includes the following steps:

[0074] S1. After the position fingerprint has been established, select a preset number of training points and record their position coordinates, collect RSS samples on the training points to establish a training point database; use the nearest neighbor selection algorithm to match the RSS samples with the static position fingerprint and calculate the positioning As a result, the location coordinates of the training points are used to calculate the positioning error; and the artificial neural network ANN is used to fuse the RSS samples and positioning coordinates of the training points as the input data of the ANN, and the positioning error of the training points is used as its output data to establish the relationship between input and output. The non-linear mapping relationship; use the genetic algorithm to optimize the init...

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Abstract

A WLAN indoor positioning error correction method based on location fingerprints, which includes the following steps: S1. After the location fingerprints have been established, select a preset number of training points and record their location coordinates, collect RSS samples on the training points to establish training point database; use the nearest neighbor selection algorithm to match the RSS samples and static location fingerprints to calculate the location results, and use the location coordinates of the training points to calculate the location error; and use the artificial neural network ANN to fuse the RSS samples and location coordinates of the training points as the input of the ANN Data, the positioning error of the training point is used as its output data to establish a nonlinear mapping relationship between input and output; S2, during online positioning, when the user receives the RSS samples from each AP, use the neighbor selection algorithm to calculate the positioning coordinates, Then the online RSS samples and localization coordinates are input into the ANN model trained in the offline stage to estimate the localization error.

Description

technical field [0001] The invention relates to the technical field of indoor positioning, in particular to a WLAN indoor positioning error correction method and system based on location fingerprints. Background technique [0002] In the prior art, the position fingerprint positioning algorithm using the online RSS average sample to calculate the positioning result does not introduce a correlation coefficient into the RSS change of the relevant reference point, resulting in unsatisfactory positioning accuracy. Contents of the invention [0003] In view of this, the present invention proposes a location fingerprint-based WLAN indoor positioning error correction method and system. [0004] A WLAN indoor positioning error correction method based on location fingerprints, comprising the steps of: [0005] S1. After the position fingerprint has been established, select a preset number of training points and record their position coordinates, collect RSS samples on the training...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S5/02H04W4/021H04W4/33
CPCG01S5/021G01S5/0252
Inventor 刘芬
Owner 武汉创驰蓝天信息科技有限公司
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