A Client-Assisted Approach Based On User Collaboration For Indoor Positioning

With the advancement of modern communication technologies,precise location services are becoming more and more important.However,in outdoor positioning,the global positioning system can provide accurate to the meter-level service,but in indoor positioning,due to obstacle occlusion and multipath effects,the global positioning system can not provide accurate positioning.At the same time,dedicated indoor positioning technology equipment is expensive,and the initial deployment cost is too high,which is not suitable for large-scale applications.At present,the indoor positioning technology based on Wi-Fi fingerprint is often used to deal with complex indoor positioning problems.However,constructing offline Radio Map is very time consuming,and the dynamic changes of the access point location and environment affect the positioning accuracy.When the user track data is collected,due to invalid data interference caused by the abnormal point generated by the drift,the data validity of the fingerprint map cannot be guaranteed.In response to the above questions,the research done in this paper is as follows:(1)The basic technology of indoor positioning is studied.The influence of different users and APs on the positioning accuracy is analyzed experimentally.The user co-location technology is analyzed in detail,and it is pointed out that the user collaborative indoor positioning method in the semi-supervised mode saves a lot of labor and time with higher positioning accuracy.The distribution density of user participation and the distribution density of AP points will affect the positioning.Therefore,the positioning error in each case is also studied.Based on the influence of signal attenuation,the attenuation formula of RSS and the calculation formula of edge signal are studied.(2)An indoor positioning algorithm based on multi-user collaboration is proposed.This method can improve the positioning accuracy of the Radio Map by iteratively calculating the distance between the user and the AP and converting it into spatial coordinates to correct the original AP data of the fingerprint.A client-assisted algorithm positioning system model based on multi-user collaboration is established.Experiments show that the indoor positioning algorithm effectively improves the indoor positioning accuracy.(3)Based on the user's customary positioning drift correction method,thepositioning efficiency is improved by reducing the computational complexity and solving the "data drift" problem.The drift point is filtered according to the continuity of the user's walking trajectory.Finally,combined with the extended Kalman filter method to remove the noise,the positioning trajectory is closer to the real.Finally,the experimental results show that the multi-user collaborative algorithm under the multi-user collaborative method can improve the positioning accuracy under the acceptable time cost.After the noise is filtered out by the positioning drift correction method based on the extended Kalman filter algorithm,the trajectory approaches the ideal..Radio Maps built with multi-user collaboration methods are automatically updated,robust,and evolve over time.