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Artificial intelligence based indoor fingerprint positioning method and system

A fingerprint positioning and artificial intelligence technology, which is applied to navigation calculation tools, measuring devices, instruments, etc., can solve the problems of costing a lot of manpower and material resources, and is not conducive to the popularization of fingerprint positioning algorithms, so as to improve the accuracy of position estimation, improve the convergence speed and global convergence. The effect of high performance and prediction accuracy

Inactive Publication Date: 2018-07-20
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

In the offline stage, it is necessary to establish a fingerprint database and update the fingerprint database when the environment changes to ensure its positioning effectiveness. However, the establishment and update of the database requires a lot of manpower and material resources, which is not conducive to the popularization of fingerprint positioning algorithms, especially in large-scale positioning scenarios. application in

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  • Artificial intelligence based indoor fingerprint positioning method and system
  • Artificial intelligence based indoor fingerprint positioning method and system
  • Artificial intelligence based indoor fingerprint positioning method and system

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Embodiment Construction

[0048] Such as figure 1 Shown, a kind of indoor fingerprint localization method based on artificial intelligence, it comprises the steps:

[0049] S1. In the offline stage, use affine propagation clustering technology to cluster the fingerprints obtained by sampling the reference points of sparse density distribution to divide the indoor area into a specific number of sub-areas, and then use the sampling data of each sub-area to establish the Proposed RPM path loss propagation model, through which the fingerprints at other unmeasured reference points are predicted to reconstruct the complete fingerprint database;

[0050] S2. In the online position estimation and tracking phase, improve the convergence speed and global convergence performance of the algorithm by improving the initialization strategy of the PSO algorithm, thereby improving the position estimation accuracy; at the same time, combined with the Kalman filter algorithm to further correct the position estimation res...

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Abstract

An artificial intelligence based indoor fingerprint positioning method comprises following steps: step one, in the offline phase, using an affinity propagation clustering technology to sample sparselydistributed reference points to obtain fingerprint, carrying out clustering to divide an indoor area into N sub-areas (N is a specific integer), then utilizing the sampling data of each sub-area to establish a RPM route loss propagation model, and through the model, predicting the fingerprint of other unmeasured reference points so as to establish a complete fingerprint database; and step two, inthe online phase position estimation and tracing phase, improving the initialization strategy of a PSO algorithm to improve the convergence speed and global convergence performance of the algorithm so as to enhance the position estimation precision; and at the same time, utilizing a Kalman filtering algorithm to further correct and smoothen the position estimation result so as to obtain a terminal position tracing effect with higher precision.

Description

technical field [0001] The invention relates to the technical field of indoor positioning, in particular to an artificial intelligence-based indoor fingerprint positioning method and system. Background technique [0002] With the continuous development of wireless communication technology and the continuous growth of indoor location-based service (Location Based Service, LBS) business demand, indoor wireless positioning technology has been more and more extensively researched in recent years. High-performance wireless positioning technologies, such as high positioning accuracy, high real-time positioning, low computational complexity, and low development and application costs, determine the service quality of indoor LBS services. Received Signal Strength (RSS) fingerprint information positioning technology based on Wireless Local Area Network (WLAN) benefits from meter-level positioning accuracy performance, low development cost of smart terminals, and wide distribution of W...

Claims

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Application Information

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IPC IPC(8): G01C21/20H04W64/00
CPCG01C21/206H04W64/00
Inventor 刘芬
Owner 武汉创驰蓝天信息科技有限公司
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