Indoor fingerprint quick positioning method based on support vector regression

A technology that supports vector regression and positioning methods, applied in location-based services, measurement devices, radio wave measurement systems, etc., can solve the problems of huge fingerprint matching database, original data interference noise, poor real-time performance, etc., to reduce the complexity of matching Accuracy, reducing noise interference, and improving real-time performance

Active Publication Date: 2017-11-07
HANGZHOU CCRFID MICROELECTRONICS
View PDF5 Cites 24 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems of too large fingerprint matching database, poor real-time performance, and interference noise in the original data in the traditional WLAN fingerprint positioning method, the present invention discloses a fast indoor fingerprint positioning method based on support vector regression

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Indoor fingerprint quick positioning method based on support vector regression
  • Indoor fingerprint quick positioning method based on support vector regression
  • Indoor fingerprint quick positioning method based on support vector regression

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] This embodiment discloses a method for quickly positioning indoor WLAN fingerprints based on support vector regression, which includes the following steps: it consists of two parts: an offline stage and an online stage, wherein the offline stage is responsible for establishing a feature fingerprint database of reference points and training feature fingerprints and reference points. The relationship model between point positions; in the online stage, the relationship model between the feature fingerprint and the reference point position obtained in the offline stage is used for rough positioning, and then the weighted K nearest neighbor algorithm is used for accurate positioning. The block diagram of the whole system is as figure 1 shown.

[0054] The coarse positioning adopts svm coarse positioning, and the accurate positioning adopts knn fine positioning.

[0055] The present invention is different from the traditional positioning method using the fingerprint database...

Embodiment 2

[0083] like Figure 1-3 As shown, this embodiment discloses a fast indoor WLAN fingerprint positioning method based on support vector regression. As a further embodiment of Embodiment 1, specific numerical values ​​are used to illustrate, and the steps are as follows:

[0084] Step 1: Construct the feature fingerprint database in the offline stage;

[0085] Step 1.1: Determine the position of the reference point according to the principle of uniform sampling according to the indoor map, according to image 3 As shown, 5 WLAN wireless APs are placed and 23 reference points are selected for illustration. Different reference points can be selected for different scenarios in actual applications. At each reference point position, the signal strength RSS of all WLAN wireless APs around is collected 100 times, which can be expressed as a set L={l 1 ,l 2 ,...,l N}, where l i Represents the fingerprint information of the i-th reference point, Indicates the signal strength of t...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an indoor WLAN fingerprint quick positioning method based on support vector regression. The method comprises the steps of 1 an off-line stage, wherein a feature fingerprint database of reference points is built, and a relation model of feature fingerprints and reference point locations is trained; and 2 an on-line stage, wherein coarse positioning is conducted through the relation model, and then precise positioning is conducted through a weighted K nearest neighbor algorithm. By adopting the indoor fingerprint quick positioning method based on support vector regression, the on-line fingerprint matching range can be narrowed, noise jamming is reduced by extracting a characteristic value of signal intensities, therefore, the positioning precision is improved, and the fingerprint matching speed is increased.

Description

technical field [0001] The invention belongs to the technical field of indoor positioning, and in particular relates to a fast indoor fingerprint positioning method based on support vector regression. Background technique [0002] With the continuous expansion and deepening of the application of the Internet of Things, location-based services (Location-based Services, LBS) have become more and more widely used, and people's demand for timely, fast and accurate acquisition of location information is becoming stronger and stronger. Traditional GPS and cellular network technologies can achieve high positioning accuracy outdoors, but in indoor environments, due to the influence of buildings on signals, the positioning capability is greatly limited. Wireless Local Area Network (WLAN) is widely and densely deployed in indoor environments to provide communication services for users due to its simple deployment and low cost. Indoor positioning based on WLAN has become a research hot...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): H04W4/02H04W64/00G01S11/06G06F17/30
CPCG01S11/06G06F16/2425G06F16/2468H04W4/023H04W64/006
Inventor 姚英彪毛伟勇刘兆霆严军荣冯维
Owner HANGZHOU CCRFID MICROELECTRONICS
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap