Indoor wireless terminal positioning method based on Bayes compression sensing

Abstract

The invention discloses an indoor wireless terminal positioning method based on Bayes compression sensing. The method includes the steps of performing grid division to an indoor area where wireless terminals needed to be positioned are located and ensuring the size of each grid equal to the needed positioning accuracy ; collecting the signal intensity from each wireless access point at each grid point respectively and uploading the signal intensity to a central server; enabling all the signal intensity data of a same wireless access point collected at all grid points to correspond to positions of corresponding grid points by the aid of the central server so as to acquire a location finger-print map of each wireless access point respectively; collecting the signal intensity from each wireless access point at the wireless terminal needed to be positioned in real time and uploading the signal intensity to the central server; and performing compressive sampling to received real-time signal intensity data collected at the wireless terminal needed to be positioned by utilizing the position finger-print map by the aid of the central server, performing multitask Bayes combined compression reconstruction algorithm to the signal intensity after being subjected to the compressive sampling, and finally acquiring a real position of each wireless terminal needed to be positioned.

Description

technical field [0001] The invention relates to a Bayesian compressed sensing technology and an indoor wireless terminal positioning method. Background technique [0002] With the maturity and rapid development of wireless communication technology, location-based wireless positioning services are becoming more and more important. As users have increasingly strong demands for timeliness and locality of information, more accurate location information is especially needed in military and medical emergencies. Therefore, various positioning service systems have sprung up and developed rapidly. The current wireless positioning service system mainly includes the Global Positioning System (GPS) and cellular wireless positioning. GPS utilizes the azimuth and distance of multi-satellite signals to realize global location positioning in an outdoor unobstructed environment. However, for indoor environments and cities with dense buildings, the positioning accuracy of the GPS system is ...

AI Technical Summary

Problems solved by technology

These all lead to inaccurate location based on signal strength

And because the positioning process is all carried out on wireless terminals, and wireless terminals are usually powered by batteries, and the processing speed is not high, so positioning will consume a lot of power, so it is necessary to find a more accurate and energy-saving positioning method

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