A novel WiFi signal and RGB image fusion positioning method for manufacturing workshop

Nan Bai, Guangzhu Chen, Rui Hou, Feng Ying

Abstract: With the sustainable development of mobile communication technology and the increasing demand for indoor services, Location-based Service (LBS) is attracting more and more attention. Determining the mobile target’s location is a core problem of LBS. The traditional WiFi signal fingerprint-based positioning technology mainly determines the location information of the mobile target by received RSS, which has high real-time positioning but low positioning accuracy. The fingerprint-based positioning technology using image mainly determines the location information of the mobile target by matching the features of the foreground images, which has the high positioning accuracy but low real-time positioning. This paper presents an indoor positioning method fusing information of the WiFi signal and RGB image to improve the positioning performance. The WiFi signal is transformed into the W-image according to indoor space and correction radius parameters, then the W-image and RGB image information are fused with LBP feature by the uniform-LBP algorithm. A fusion positioning model based on the sparse representation is established and solved using Lasso and BPDN positioning method. The positioning methods are tested in manufacturing workshop, and the experimental results show that the proposed method can reduce the complexity of the positioning method and achieve the higher positioning accuracy under same conditions.