Wireless sensor network node localization method based on K-medoids clustering

A wireless sensor and network node technology, applied in location information-based services, wireless communication, network topology, etc., can solve problems affecting positioning accuracy, measurement data errors, and algorithm positioning accuracy reduction, so as to improve positioning accuracy and improve reference value, reducing gross errors and the effects of random noise interference

Inactive Publication Date: 2016-06-01
HOHAI UNIV
View PDF2 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the actual environment, the signal is affected by many factors, and there will be certain errors in the measurement data. These errors include systematic errors with small amplitudes and gross errors with large amplitudes. The existence of errors directly affects the positioning accuracy, which leads to the algorithm The positioning accuracy of the

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
  • Wireless sensor network node localization method based on K-medoids clustering
  • Wireless sensor network node localization method based on K-medoids clustering
  • Wireless sensor network node localization method based on K-medoids clustering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0028] In order to further improve the accuracy of the ranging algorithm, the present invention mainly considers reducing the influence of coarse ranging errors on the positioning effect and introducing the K-medoid clustering algorithm, and proposes an improved positioning algorithm based on K-medoid clustering (multilateral localization algorithm based K-medoid clustering analysis, KCML ). The algorithm first uses trilateration positioning to obtain the initial positioning results, then performs cluster analysis on the initial positioning...

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 a wireless sensor network node localization method based on K-medoids clustering. The method firstly uses a trilateration localization algorithm to obtain a plurality of localization results, and takes the primary localization results as initial samples for clustering analysis. Then a K-medoids clustering algorithm is used to perform clustering analysis on the primary localization results. The division of the best cluster can be obtained through iteration. Through analysis of the cluster member number, beacon nodes with the large error are found and removed. Finally the localization calculation is performed on the preferable beacon nodes by using a multilateral localization method which is modified by reference values. The localization method of the invention effectively reduces node localization error, and improves the localization precision of wireless sensor network nodes.

Description

technical field [0001] The invention relates to a wireless sensor network node positioning method based on K center point clustering, and belongs to the technical field of wireless sensor network node positioning. Background technique [0002] Wireless Sensor Networks (Wireless Sensor Networks, WSN) is composed of sensor nodes with perception capabilities, computing capabilities, and wireless communication capabilities, and is widely used in military reconnaissance, production process monitoring, and environmental monitoring. The self-location of network nodes is the basis and important support for sensor network applications. In many application fields such as location-based routing, target monitoring and tracking, the specific location information of network nodes is required in order to use location information in network communication and node collaboration. Complete specific requirements. [0003] The sensor network node positioning method can be divided into two types...

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): H04W4/02H04W84/18
CPCH04W4/025H04W84/18
Inventor 顾燕张传锦李旭杰郭洁静大海王娴珏
Owner HOHAI UNIV
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