A Method for Constructing Indoor Navigation Networks based on IMU

Indoor navigation network is the basis of indoor navigation research. How to automatically generate indoor navigation network has become a research hotspot in recent years. At present, the indoor network generation is often obtained through indoor architectural Computer Aided Design (CAD) drawings or lidar Simultaneous Localization and Mapping (SLAM) methods, which are cumbersome and costly to obtain. In order to solve these problems, this paper proposes an automatic extraction method of indoor navigation network. The method first uses the built-in inertial device of the mobile phone to obtain pedestrian indoor motion data, and then uses the Kalman filter algorithm to generate pedestrian motion trajectories. After that, the Douglas-Peucker algorithm and DBSCAN algorithm are used to process the trajectories and construct the indoor navigation network. At the same time, the network will automatically update and optimize the subsequent track when the subsequent track is obtained. The experiment proves that this method can obtain indoor navigation network more quickly and efficiently, and the cost is lower when facing unsuspected environment.

I. Introduction

In recent years, as modernization has accelerated, the number of large public buildings and places has increased rapidly [1], greatly expanding the scope of indoor space. The global spread of the Corona Virus Disease 2019 (COVID-19) has forced people to spend numerous time indoors [2]. On the other hand, with the rapid development of smart phones and Micro Electro-Mechanical System (MEMS) technology, the public demand for mobile information services based on indoor location is increasing gradually [3].