Indoor and outdoor positioning switching method based on characteristic signal fingerprint database

Abstract

The invention proposes an indoor and outdoor positioning switching method based on a characteristic signal fingerprint database. The indoor and outdoor positioning switching method comprises the following steps of: S1, arranging a plurality of detection points in an indoor and outdoor positing switching region, repeatedly detecting characteristic signals emitted from a plurality of signal emitters in each detection point, and building a characteristic signal database; S2, judging whether a signal generator meets a preset condition or not, if yes, calculating the intensity average value of multiple received characteristic signals emitted from the signal generator; S3, pre-processing data; S4, training the pre-processed characteristic signals to obtain a classifier; and S5, processing the target characteristic signal obtained by real-time sampling through the step and the step 3 to obtain a first vector, substituting the classifier and outputting a classification result, judging the target is in the outdoors if the classification result is less than 0, or judging the target is in the indoors. With the method proposed by the invention, seamless switching between an indoor positioning system and an outdoor positioning system can be rapidly and accurately achieved, and omnibearing positioning is provided for a user.

Description

technical field [0001] The invention relates to the technical field of wireless positioning, in particular to an indoor and outdoor positioning switching method based on a characteristic signal fingerprint database. Background technique [0002] With the development of human society and the rise of smart cities, the demand for positioning technology is increasing. The global navigation satellite system (Global Navigation Satellite System, GNSS) has very high positioning accuracy in outdoor positioning. However, due to signal attenuation and multipath problems that occur when satellite navigation signals pass through buildings, GNSS cannot effectively locate indoor environments. [0003] The currently popular indoor positioning methods are mainly eigenvalue matching methods. The feature values ​​measured in real time (such as wifi, bluetooth, RFID, etc.) are matched with the feature values ​​in the database to obtain the specific location of the target. It is generally div...

AI Technical Summary

Problems solved by technology

The indoor positioning method based on eigenvalue matching will generate a large amount of fingerprint data in the offline stage. Due to the limitation of the database capacity and the real-time performance of the algorithm, this kind of positioning technology is only suitable for indoor environment positioning in a certain area, and cannot achieve the goal of outdoor large-scale positioning. Positioning when range moves

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