Indoor positioning method based on wireless sensor networks of fingerprint data

Abstract

The invention discloses an indoor positioning method based on wireless sensor networks of fingerprint data. According to the method, M anchor nodes are allocated in each room of a two-dimensional indoor planar graph, the anchor nodes have the precedence recognition range, blind nodes are located in any positioning area, and one wireless sensor network is formed by all the nodes in a self-organization mode; the blind nodes start the positioning process, a room number is determined according to the blind node signal strength values collected by the anchor nodes in the rooms, the room grade is positioned, the information of the anchor nodes in the room is received, signal strength fingerprint data of the positions where the anchor nodes are located are recorded, the coordinate values of the blind nodes are calculated according to the fingerprint data and are modified, and the coordinate grade is positioned. The adopted signal strength fingerprint data have real-time performance and environment adaptability, and the room grade and the coordinate grade can be positioned and applied. Compared with the traditional fingerprint database technology, the indoor positioning method is simpler, easy to operate, high in positioning accuracy and capable of meeting the requirement for indoor positioning.

Description

technical field [0001] The invention relates to communication technology and indoor positioning technology of a wireless sensor network, in particular to an indoor positioning method of a wireless sensor network based on fingerprint data. Background technique [0002] Wireless sensor networks (WSN) is a multi-hop self-organizing network formed by a large number of sensor nodes through wireless communication. WSN has network characteristics such as large scale, self-organization, dynamics, reliability, and data-centricity. Sensor nodes have the characteristics of small size, low hardware configuration requirements, low cost, and low power consumption. They are used in military, environmental monitoring and forecasting, There are a wide range of applications in various fields such as smart homes, building condition monitoring, and urban transportation. [0003] With the improvement of technology and living standards, people have increasingly strong demand for indoor positioni...

AI Technical Summary

Problems solved by technology

The indoor environment is complex, the multipath effect is significant, and considering the system cost, power consumption, volume and other issues, the communication nodes cannot accurately measure the distance or angle, resulting in poor positioning effect based on distance; the positioning method without distance itself is a This position estimation method has low positioning accuracy and often requires the deployment of a large number of nodes to work well. Since the building area is usually small-scale, it is not necessary to deploy a large number of sensor nodes, so it is not effective for indoor positioning.

Fingerprint database technology has been applied in positioning. From the early RADAR system to the widely researched wifi fingerprint positioning, it seems to be a better positioning solution at this stage, but fingerprint database technology requires a lot of data collection work, and Vulnerable to environmental changes; Wifi fingerprint positioning makes full use of AP nodes in buildings, and researchers have proposed methods such as automatic fingerprint data collection and path constraints, but wifi fingerprint positioning depends on AP distribution, and automatic fingerprint data collection is only a part of it. A rough estimation method, it is difficult to improve the accuracy, and needs to be further improved

[0005] At present, there are still many difficulties in the indoor positioning technology of WSN, and the positioning effect is not very ideal. When selecting the indoor positioning method of WSN, it is necessary to adopt a suitable positioning method according to the application occasion and positioning accuracy requirements.

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