Position coordinate estimation method based on partial least square regression

Abstract

The invention relates to a position coordinate estimation method based on partial least square regression, and belongs to the technical field of indoor positioning. The method comprises the following steps: S1, constructing initial independent variable and dependent variable matrixes X0 and Y0 by using the position fingerprints, wherein position fingerprints and position coordinates of Nf reference points are known; S2, preprocessing X0 and Y0 to obtain X and Y; S3, constructing an optimization problem according to the first pair of principal components t1 and u1 of X and Y and the axial vectors w1 and c1, and solving t1 and u1 according to a covariance maximum principle under certain constraints; S4, performing regression modeling on the principal components t1 and u1; S5, taking residual matrixes E1 and G1 in X and Y as new X and Y, continuing to extract new principal components, and repeating the steps until the number of the principal components reaches an upper limit; S6, based on a PLSR algorithm, obtaining a regression equation of mapping X to Y; and S7, obtaining position fingerprints of the test points, and then obtaining position coordinates of the test points by using the independent variable coefficient matrix A in the regression equation. According to the method, the operation complexity is reduced, and meanwhile, the estimation precision of the position coordinates is ensured.

Description

technical field [0001] The invention belongs to the technical field of indoor positioning, and relates to a method for estimating position coordinates based on partial least squares regression. Background technique [0002] As intelligent home appliances and terminals are gradually being widely used in people's lives, the user's demand for location information services is also becoming increasingly strong. Although the widely used Global Positioning System (full name in English: Global Positioning System, English abbreviation: GPS) can enable users to obtain the location information of things in outdoor environments, but because GPS signals cannot penetrate buildings, users cannot use them in indoor environments. GPS signals get precise location information. [0003] With the popularization of the mobile Internet and the widespread use of smart devices, location-based service requests based on indoor environments have become a huge traffic portal. It has many application sc...

AI Technical Summary

Problems solved by technology

The traditional fingerprint-based positioning method needs to collect a large number of samples for offline training in order to ensure the accuracy of the location coordinates obtained in the final test. However, a large number of training samples leads to large calculations and slow calculation speed of the algorithm.

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