Indoor antenna sensor network positioning method based on received signal strength indication

Abstract

The invention discloses an indoor antenna sensor network positioning method based on received signal strength indication. The method includes the steps of firstly, extracting indoor radiofrequency signal attenuation parameters; secondly, acquiring a received signal strength sample; thirdly, constructing confidence interval of a measuring distance by bootstrapping; fourthly, calculating a set of feasible solutions to estimated coordinates of unknown nodes in a set-membership estimation architecture; and fifthly, subjecting the set of feasible solutions to interval analysis to calculate node coordinates. The distance confidence interval is constructed by bootstrapping during distance estimation, so that positioning precision and robustness are improved and node energy consumption is reduced. During positioning, the set of feasible solutions to the node coordinates is subjected to interval analysis by set-membership estimation, and the estimated coordinates of the unknown nodes are calculated.

Description

Technical field [0001] The invention relates to the field of indoor wireless sensor network node positioning, in particular to distance-related wireless sensor network positioning based on received signal strength indication, that is, an indoor wireless sensor network positioning method based on received signal strength indication. Background technique [0002] The wireless sensor network originated from the traditional sensor system used by the US military to monitor the opposing military vehicle during the Vietnam War. Since the 21st century, with the development of sensor technology, computer technology and information technology, wireless sensor networks have entered the fourth generation of sensor networks. The wireless sensor network consists of a large number of micro sensor nodes in the deployment area, forming a self-organizing distributed network through wireless communication, which is responsible for monitoring the physical information (temperature and humidity, air p...

AI Technical Summary

Problems solved by technology

[0007] Although the above methods have achieved certain optimization results, there are still many defects in complex indoor environments.

For example, the directional antenna does not guarantee that its radiation direction covers unknown nodes; there is a signal delay in the dynamic update of signal attenuation parameters; there is a mismatch phenomenon in the fingerprint matching positioning method; the indoor environment noise distribution is unknown, etc.

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