SVM-KNN (Support Vector Machine-K Nearest Neighbor)-based indoor positioning method

A technology for indoor positioning and positioning area, applied in electrical components, wireless communication and other directions, can solve the problems of large variation range and short real-time measurement time, and achieve the effect of improving stability and accuracy

Inactive Publication Date: 2015-05-13
SUN YAT SEN UNIV +1
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Problems solved by technology

[0005] The purpose of the present invention is to provide an indoor positioning method combining support vector machine and KNN, which is mainly used to solve the shortcomings of the traditional algorithm based on sampling point matching in dealing with nonlinear problems and the problems of short real-time measurement time and large variation range, thereby Improve the accuracy of indoor positioning and the stability of results

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  • SVM-KNN (Support Vector Machine-K Nearest Neighbor)-based indoor positioning method
  • SVM-KNN (Support Vector Machine-K Nearest Neighbor)-based indoor positioning method
  • SVM-KNN (Support Vector Machine-K Nearest Neighbor)-based indoor positioning method

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[0029] specific implementation

[0030] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0031] In order to solve the above-mentioned technical problems, the technical solution adopted in the present invention is: a kind of indoor positioning method based on the combination of support vector machine and KNN, comprising the following steps:

[0032] S1. Reasonably divide the positioning area into a grid according to the structural characteristics of the indoor building, measure and record the center coordinates of each grid, and select the size of the grid according to the actual situation;

[0033] S2. Sample points are collected in each grid area. It should be noted that the sample points are collected evenly, and the RSSI value and the number of the area where each sample point is recorded are used as the feature value and label of the support vector machine classification respectively;

[0034] ...

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Abstract

The invention discloses a SVM-KNN (Support Vector Machine-K Nearest Neighbor)-based indoor positioning method. Indoor positioning is specifically realized by combining the SVM with the KNN; the purpose is to improve the accuracy and the stability of positioning. The implementation process of the method comprises an off-line stage and an on-line stage, wherein the off-line stage comprises the following steps: 1, performing rational grid type classification on a region to be positioned; 2, rationally and uniformly collecting enough sample points in each grid region, and collecting signal intensity values of the sample points and numbers of belonging grids; 3, taking each grid as a category, and realizing classification modeling by using a support vector machine classification algorithm; the on-line stage comprises the following steps: classifying points to be positioned by using the constructed classification model, selecting K regions with the maximum probability obtained by classification, and calculating the final positional coordinates of the points to be positioned according to a KNN principle.

Description

technical field [0001] The invention relates to an indoor positioning method based on the combination of a support vector machine and KNN, and belongs to the application field of the Internet of Things. Background technique [0002] With the rise of Internet of Things technology, location-based services are getting more and more attention. For outdoor positioning, there are already very mature positioning technologies, and the applications are also very successful, such as the global positioning system and Beidou navigation system. Compared with outdoor positioning technology, due to the complexity of the indoor environment, the particularity of indoor wireless signal propagation, such as multipath effects, shadow effects, etc. These special circumstances prevent the mature outdoor positioning technology from being directly applied to indoor positioning. For this reason, scholars have studied many positioning methods to achieve indoor positioning. [0003] Support vector ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W64/00
CPCH04W64/00
Inventor 唐承佩张明李海良刘友柠
Owner SUN YAT SEN UNIV
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