Indoor Wi-Fi positioning method

Abstract

The invention discloses an indoor Wi-Fi positioning method, comprising a plurality of positioning APs, a positioning client and a positioning server. The method further comprises the following steps:A: positioning system initialization: dividing a positioning area, and setting a collection point to install the positioning APs; B: signal data acquisition: constructing a signal strength matrix anda signal distribution matrix; C: skew distribution filtering: filtering out abnormal points according to a filtering threshold section T<D>= formula; and D: positioning: selecting coordinate weightingof a plurality of positioning area collection points to obtain the coordinates of a to-be-positioned point. The method in the invention has the advantages of effectively filtering out the signal abnormal points and improving the positioning accuracy.

Description

technical field [0001] The invention relates to a method for indoor Wi-Fi positioning. Background technique [0002] With the increasing maturity of wireless network technology, wireless network has been accepted by more and more enterprise users. At present, wireless local area network has become a hot spot in wireless network technology. Compared with wired network, wireless local area network has the advantages of flexible use and convenient expansion. , cost economy, simple installation and so on. [0003] In step C of "A Method for WiFi Positioning" with application number 201711220071.2, the method used to filter out signal abnormalities in the fingerprint database is: for the signal strength collected in a sampling period T, find the signal of each positioning AP The strength mean value μ and standard deviation σ, the selection principle is based on the larger mean value μ, and the first p APs with good signals are selected. If the mean value μ is equal, the standard...

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Problems solved by technology

[0003] In step C of "A Method for WiFi Positioning" with application number 201711220071.2, the method used to filter out signal abnormalities in the fingerprint database is: for the signal strength collected in a sampling period T, find the signal of each positioning AP The strength mean value μ and standard deviation σ, the selection principle is based on the larger mean value μ, and the first p APs with good signals are selected. If the mean value μ is equal, the standard deviation σ is larger. If both μ and σ are equal, the MAC address is selected. Small; the main problem of this method is that when the AP signal fluctuates, it will cause the AP signal to be particularly good or poor in a short period of time when the fluctuation occurs, and the particularly large or small RSSI value directly participates in the signal strength mean value μ and standard deviation In the operation of σ, the value that affects the signal strength mean value μ and standard deviation σ

[0004] The specific manifestations are as follows: Situation 1: When the sampling period T is very small, and the AP signal continues to fluctuate in the period T, often only when the AP signal is very good or very poor when it is unstable, the calculated signal mean value μ appears Polarization, either the large value of μ leads to APs with signal fluctuations being directly elected as APs with good signals, or the small value of μ causes APs with signal fluctuations to be directly filtered out as APs with poor signals; The essence of the situation is to use the RSSI value when the fluctuation occurs as the normal RSSI value to make a wrong evaluation of the overall signal strength mean μ and standard deviation σ of the AP, resulting in election errors and affecting positioning accuracy; Case 2: When the sampling period T is large At the same time, the AP signal fluctuates for a short period of time in the period T. The collected AP signal includes the fluctuating signal and the normal signal. The RSSI value of the fluctuating signal and the RSSI value of the normal signal simultaneously participate in the signal strength mean value μ and The calculation of the standard deviation σ affects subsequent elections; the essence of this situation is that the RSSI value when the fluctuation occurs is used as a part of the normal RSSI value to make a wrong evaluation of the overall signal strength mean μ and standard deviation σ of the AP, resulting in election errors Then affect the positioning accuracy; this method cannot avoid the impact on the positioning accuracy when AP signal fluctuations occur, that is, the method cannot effectively filter out the signal abnormal points in the fingerprint database; in step D, the signal used to filter out the positioning data is abnormal When the point method encounters signal fluctuations in the AP, the same reason cannot effectively prevent the signal fluctuations in the AP from affecting the positioning accuracy.

[0005] "A WiFi positioning method" with application number 201810626172.8 can only determine that the point to be positioned is in a certain area, but cannot determine the specific coordinates of the point to be positioned, and cannot meet the application scenarios with high positioning accuracy requirements

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