WLAN indoor positioning algorithm based on linear discriminant analysis and gradient lifting tree

Abstract

The invention provides a WLAN indoor positioning algorithm based on the linear discriminant analysis and the gradient lifting tree. In order to reduce the influence of the time-varying characteristicof the received signal strength value (RSSI) in the indoor WLAN environment on the positioning accuracy, a positioning feature for extracting the original RSSI signals by using the LDA is provided, and the prediction of the position coordinates is realized by constructing a GBDT model. The method is mainly divided into four processes. (1) an RSSI signal value of the AP is collected at a referencepoint, and fingerprint data is formed at the position coordinate of the reference point, and is saved in a fingerprint database; (2) an intra-class divergence matrix and an inter-class divergence matrix of the fingerprint data are solved so as to obtain a projection matrix, and the extracting of the RSSI signal positioning features can be realized; (3) a forward distribution algorithm and an addition model are utilized, and a GBDT positioning model is generated through iteration; (4) in the online stage, the RSSI signal values of the AP at the periphery of the test points are collected, and anLDA is used to perform feature extraction and the GBDT positioning model is input to calculate position coordinate.

Description

Technical field: [0001] The invention belongs to the field of WLAN indoor positioning. It is an indoor positioning method that uses Linear Discriminant Analysis (LDA) to extract positioning features from fingerprint data in the offline phase of WLAN indoor positioning, and builds a positioning model through Gradient Boosting Tree (GBDT). The method can effectively improve the WLAN indoor positioning accuracy. Background technique: [0002] In recent years, with the breakthrough of smart devices and Internet technology, more and more scenarios that need to use location services have been derived, and people's needs for location services have also expanded from outdoor driving navigation to indoor positioning. However, the Global Positioning System (GPS), which is commonly used outdoors, cannot work in an indoor environment due to building walls blocking the signal. In order to enable users to obtain accurate location information indoors, researchers at home and abroad have ...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem that the time-varying characteristics of the RSSI signal reduce the positioning accuracy, the present invention proposes to use LDA to extract the positioning features in the RSSI signal, and realize the prediction of the position coordinates by constructing a GBDT positioning model

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