Adaptive mixed indoor positioning method based on Wi-Fi

Abstract

The invention discloses an adaptive mixed indoor positioning method based on a Wi-Fi, and the method comprises the steps: collecting the position coordinates of a few of sample points in an indoor central region and the corresponding signal intensity information, and the position coordinates of a large number of sample points in an indoor boundary region and the corresponding signal intensity information; calculating the three-side positioning coordinates of a test point through employing a three-side positioning algorithm, and calculating the fingerprint positioning coordinates of the test point through employing a position fingerprint positioning algorithm; carrying out the ordering of the Euclidean distances between the test point and all sample points, and selecting the former M groups of data with the minimum distance; determining the weight coefficients of the three-side positioning coordinates according to the number of sample points in the indoor central region of the M groups of data, determining the weight coefficients of the fingerprint positioning coordinates according to the number of sample points in the indoor boundary region of the M groups of data, and finally obtaining the final positioning coordinates of the test point. The positioning method can maintain higher positioning precision while reducing the sampling number of the indoor central region.

Description

technical field [0001] The invention relates to the technical field of indoor positioning, in particular to a Wi-Fi-based adaptive hybrid indoor positioning method. Background technique [0002] In recent years, under the wave of rapid development of the Internet, mobile intelligent terminals represented by smartphones and tablet computers have become popular rapidly, bringing a lot of convenience to our lives, and people are increasingly dependent on mobile intelligent terminals. . People in modern cities spend most of their daily work and life indoors, so indoor positioning and application services based on indoor positioning have attracted much attention. Technologies such as wireless networks, mobile communications, and terminal data processing, combined with location-based services (Location Based Services, LBS) and location-aware computing (Location Computing), have a broad application market. Location-based services of mobile devices support a variety of application...

AI Technical Summary

Problems solved by technology

The trilateration positioning algorithm is accurate in indoor open areas. The disadvantage is that in the case of many obstacles, the signal is greatly affected by the multipath effect, and the signal strength and ranging are not accurate, which will affect the positioning accuracy.

Its disadvantage is that it needs to collect a large number of sampling point data in the offline stage, which consumes a lot of time and manpower

Images