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An indoor localization method with dual network architecture based on parameter constraints

A parameter constraint and indoor positioning technology, which is applied in specific environment-based services, neural architecture, network planning, etc., can solve problems such as difficult positioning, limited data feature extraction capabilities, and model positioning performance degradation, and achieve the effect of narrowing feature differences

Active Publication Date: 2022-01-28
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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AI Technical Summary

Problems solved by technology

However, the above two methods use the same network structure for feature extraction on data in different fields, which makes the network model only able to mine the common features of data in different fields, which greatly limits the feature extraction ability of the network for data in a certain field.
In addition, since the features extracted by the same network are the common parts of the two domains, the subsequent narrowing of the domain differences will be insufficient, especially when the data distribution of the two domains differs greatly, which will lead to a decrease in the positioning performance of the model.
Based on the above reasons, it is difficult for such methods to achieve accurate positioning in complex indoor positioning environments.

Method used

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  • An indoor localization method with dual network architecture based on parameter constraints
  • An indoor localization method with dual network architecture based on parameter constraints
  • An indoor localization method with dual network architecture based on parameter constraints

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Embodiment

[0087] This model is used to experiment with the RSS public data set collected at Jaume I University in Spain. The area of ​​the data collection area is about 308.4 square meters, which is divided into 48 grids and covers a total of 620 access points. Use the samples and labels of the first month as the source domain data, including a total of 8640 samples; use the samples of the nth month (n≥2) as the unlabeled target domain data, the number of samples is 3120; use the (n+ 1) Each piece of RSS data received in real time every month is used as test data to verify the effect of the model.

[0088] The neural network contains 5 fully connected layers, the number of neurons in each layer is 256, 128, 128, 128 and 48, and the initialization parameters are set to random initialization.

[0089] The present invention designs two groups of experiments to verify the superiority of the proposed algorithm. The first group of experiments is to compare the positioning cumulative error pe...

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Abstract

The invention belongs to the technical field of indoor positioning, and in particular relates to an indoor positioning method based on parameter constraints with a dual network architecture. The present invention uses a dual-network architecture based on parameter constraints to extract data features in different fields through different networks, breaking the limitation that a single network architecture can only extract common features, and can fully extract data features in different fields. The linear constraints imposed on the network parameters explicitly model the data distribution drift in the indoor positioning environment, and linearly compensate the distribution drift from the perspective of parameters to minimize domain differences, thereby enabling the model to effectively adapt to complex indoor positioning environments. surroundings. The invention can effectively reduce the difference of data distribution in different fields, so the invention is a method capable of realizing high-precision positioning in complex indoor environments.

Description

technical field [0001] The invention belongs to the technical field of indoor positioning, and in particular relates to an indoor positioning method based on parameter constraints with a dual network architecture. Background technique [0002] With the popularization of smart devices and the rapid development of Internet of Things technology, indoor positioning technology has gained great market opportunities. The growing demand for positioning services based on indoor environments in commercial, medical and military applications has stimulated the rapid development of indoor positioning technologies and systems. Common indoor positioning technologies include infrared, ultrasonic, visible light, UWB, and WiFi, among which infrared, ultrasonic, and visible light positioning requires the deployment of signal transmitters in advance, which requires a lot of manpower and financial resources, so the penetration rate is low; UWB positioning equipment is expensive, usually It is o...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W4/33H04W16/22H04W64/00G06N3/04G06N3/08H04B17/318
CPCH04W4/33H04W16/225H04W64/00H04W64/006G06N3/04G06N3/08H04B17/318
Inventor 郭贤生宋雅婕潘峰李林段林甫黄健万群李会勇殷光强
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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