Joint weighting K neighbor indoor positioning method based on logarithmic path loss model

Abstract

The invention discloses a joint weighting K neighbor indoor positioning method based on a logarithmic path loss model. The method comprises the following steps: 1) establishing an offline fingerprint database; 2) scanning indoor access point information by a to-be-positioned terminal in real time, forming online fingerprint according to the access point information obtained by scanning, and then calculating function values of a joint weighting distance matching measurement function based on the logarithmic path loss model between the online fingerprint and offline fingerprint in the offline fingerprint database; 3) sorting the function values of the joint weighting distance matching measurement function based on the logarithmic path loss model between the online fingerprint and the offline fingerprint in the offline fingerprint database obtained in step 2), and selecting K reference points corresponding to K minimum function values as candidate reference points according to a sorting result; and 4) estimating position coordinates of the to-be-positioned terminal according to the candidate reference points selected in step 3). By adoption of the method, accurate positioning of the indoor positioning terminal can be realized.

Description

technical field [0001] The invention belongs to the fields of wireless communication, pattern recognition and indoor positioning, and relates to a joint weighted K-nearest neighbor indoor positioning method based on a logarithmic path loss model. Background technique [0002] With the rapid development of wireless communications, computers, and smart terminals, location-based services (Location Based Services, LBS) have increasingly attracted people's attention and attention. Although the Global Positioning System (GPS) is currently widely used in outdoor scenarios, the radio signals emitted by satellites are too weak to penetrate tall buildings and walls, resulting in the "urban canyon" effect. Therefore, people are looking for new indoor positioning method. At present, there are many methods and means to achieve precise positioning in the indoor environment, among which, the fingerprint indoor positioning system based on Wireless Local Area Networks (WLAN) is widely welco...

AI Technical Summary

Problems solved by technology

[0006] At the same time, the attenuation speed of the signal under the logarithmic distance path loss model (Logarithmic Distance Path Loss Model, LDPL) will slow down as the distance increases, such as figure 2 As shown, this will lead to the fact that the offline reference point with the same inter-signal distance as the online test point does not necessarily have the same spatial physical distance as the online test point (d 2 ≈3d 1 )

Therefore, the signal strength values ​​at different value levels reflect different functions in the distance matching metric function, which seriously affects the positioning accuracy.

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