An indoor positioning algorithm based on multimode data

Abstract

Abstract:

To solve the indoor positioning problem, an indoor positioning algorithm based on WiFi and visual information is proposed. Firstly, the mathematical relationship between the image plane coordinates and the coordinates of the world coordinate system is analyzed and established by using the principle of coordinate transformation. Secondly, the mathematical equation is established with the distance between two beacons as the constraint condition, and the elevation angle of the camera is solved. Thirdly, the plane distance between the observation point and the two beacons is calculated according to the elevation angle. Finally, the distance between the observation point and the beacon is calculated. The marker can locate the observation point. According to the above positioning process, the virtual coordinates of the observation points will be obtained. Using SAE and DNN model and taking multiple custom WiFi features as input and 11 distance categories as labels, the valid values of positioning coordinates can be identified by the distance between nodes. The experimental results show that the algorithm can provide high precision real-time positioning in indoor environment, and the reliability of the algorithm is fully verified.

Key words: monocular vision, coordinate transformation, indoor positioning, convolutional neural network (CNN), WiFi feature similarity

JIA Yu-fu1,LIU Wen-ping1,HU Sheng-hong2. An indoor positioning algorithm based on multimode data[J]. Computer Engineering & Science.

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