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Indoor Localization Method Based on Global and Local Joint Constrained Transfer Learning

A technology of transfer learning and indoor positioning, applied in the field of indoor positioning based on global and local joint constraint transfer learning, can solve the problems of insufficient knowledge, difficult to form accurate, real-time and stable positioning, etc., to improve accuracy, positioning High precision and good robustness

Active Publication Date: 2020-07-10
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, only by constraining the consistency of the global structure, the knowledge obtained by transfer is often not sufficient
Therefore, due to the existence of the above problems, it is difficult for this type of method to form accurate, real-time and stable positioning in complex indoor environments.

Method used

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  • Indoor Localization Method Based on Global and Local Joint Constrained Transfer Learning
  • Indoor Localization Method Based on Global and Local Joint Constrained Transfer Learning
  • Indoor Localization Method Based on Global and Local Joint Constrained Transfer Learning

Examples

Experimental program
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Effect test

Embodiment

[0023] 1. Experimental Site Layout

[0024] The experimental environment is 308.4m 2 In the library environment, there are chairs, benches and bookshelves in the room. The number of WiFi access points that can be detected in the positioning area is 448. First, the site is divided into 230 grid points.

[0025] 2. Acquire data and form RSS fingerprint database

[0026] Place the mobile device in each grid point in turn, record the grid point number and the RSS value from each access point to form an RSS vector here n s is the number of all RSS samples marked for a known position, and the corresponding position mark is denoted as c i ∈{1,2,...,C}, C=230 is the number of grid points. RSS values ​​with corresponding location markers form a database of fingerprints, i.e. source domains in,

[0027] 3. Collect the RSS value of the device to be located

[0028] Collect the RSS value of the mobile device requesting location to form the target domain here Target domain d...

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Abstract

The invention belongs to the technical field of indoor positioning, particularly an indoor positioning method based on global and local joint constraint transfer learning. According to the method provided by the invention, through minimization of inter-domain marginal and conditional probability distribution discrepancy and maximization of a sample variance in a potential subspace, consistency ofa global structure is constrained. Through minimization of an intraclass variance and maximization of an interclass variance, dependency of each class and corresponding samples is kept. Through manifold regularization, a local neighborhood relationship is kept. Further, the consistency of local structures is constrained. The problem that an existing transfer learning method is insufficient in knowledge transfer can be solved. According to knowledge obtained from a source domain through transfer, positioning precision of a target domain can be effectively improved. The problem of RSS (ReceivedSignal Strength) fluctuation resulting from environment change is solved. The indoor positioning method based on the global and local joint constraint transfer learning provided by the invention is anew high precision positioning method applicable to a complex indoor environment.

Description

technical field [0001] The invention belongs to the technical field of indoor positioning, in particular to an indoor positioning method based on global and local joint constraint transfer learning. Background technique [0002] In recent years, indoor positioning technology has shown broad development prospects and commercial value. For example, the navigation of large shopping malls, the care of patients by medical staff, and the rescue of indoor personnel in emergency situations. Therefore, under the huge market demand, seeking a high-precision real-time positioning system suitable for complex and changeable indoor environments has become the research focus of the industry. [0003] In order to solve the impact of multipath effect and non-line-of-sight effect, a method based on RSS (Received Signal Strength, received signal strength) fingerprint is generally used for positioning. This method usually includes two stages: an offline stage and an online stage. In the offli...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W4/02H04W64/00H04W4/33G06K9/62
CPCH04W4/02H04W4/33H04W64/00
Inventor 郭贤生王磊李林胡芳姿万群段林甫沈晓峰李会勇
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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