An indoor positioning method based on fingerprint similarity based on ap sequence

Abstract

The invention relates to an indoor positioning method based on AP (Access Point) sequence-based fingerprint similarity. The method includes the following steps that: distances between N reference points and NAP APs are calculated, so that a distance sequence is obtained; the first AP sequence of each reference point is generated according to the distance sequence; the N reference points are classified according to the first AP sequence, so that NC reference point sets are obtained; NC first AP pair sets and NC reference point set coordinates are acquired according to the NC reference point sets; a reference point fingerprint library is constructed according to the NC reference point sets, the NC first AP pair sets and the NC reference point set coordinates; to-be-measured point fingerprints are constructed according to ND to-be-measured points; and the fingerprint similarly of the reference point fingerprint library and the to-be-measured point fingerprints is calculated, and the coordinates of the to-be-measured points are obtained. With the method of the invention adopted, the fingerprint library is constructed, so that the overhead of an offline phase can be greatly reduced; thefingerprint similarity algorithm designed in the online phase sets larger weights for the APs with higher signal strength, and therefore, an environmental dynamic problem can be better solved, and positioning accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of wireless communication and indoor positioning, and in particular relates to an indoor positioning method based on fingerprint similarity of AP sequences. Background technique [0002] With the widespread deployment of WiFi infrastructure in indoor environments, WiFi-based fingerprint indoor localization methods have become one of the most promising technologies. [0003] Generally speaking, the fingerprint indoor positioning method based on WiFi can be divided into two stages: offline stage and online stage. In the offline stage, at different reference points (Reference Point, RP for short) in the positioning area, the received signal strength values ​​of all access points (AP for short) are collected to construct a fingerprint library. In the online stage, an appropriate positioning algorithm is used to match the fingerprints of the points to be measured, and the position of the points to be measured is...

AI Technical Summary

Problems solved by technology

[0004] However, the above indoor positioning methods all spend a lot of time and manpower to collect received signal strength values ​​to build offline fingerprint libraries, resulting in huge overhead in the offline stage.

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