Research On Indoor Positioning Based On Crowdsourcing And Wi-Fi

In recent years,with the continuous development of mobile communication and Internet technology,shopping,catering,and transportation have become an important part of people's lives.These changes have led to a rapid increase in demand for location-based services.In the outdoor environment,the satellite navigation system is very mature,but it cannot be used in indoor environments.Indoor positioning technology has become a hot research topic.Among many existing positioning technologies,indoor positioning technology based on Wi-Fi signal strength has become a leader in indoor positioning technology because it does not require special hardware equipment and has been widely deployed in indoor environments such as large shopping malls and office buildings.At present,most of the indoor positioning technologies based on Wi-Fi signal strength require pre-deployment,which is inefficiency and time-consuming.Therefore,how to reduce the deployment cost in the Wi-Fi positioning system has become one of the urgent problems to be solved in the field of indoor positioning.At the same time,the development of the Internet has made the crowdsourcing model widely concerned,and has been applied in various fields.In indoor positioning,the crowdsourcing mode can effectively reduce the cost of the previous survey,and is one of the ideal solutions for low-cost indoor positioning.This paper researches a crowdsourcing-based Wi-Fi indoor positioning solution,which effectively reduces deployment costs.The scheme first uses the GPS and inertial sensors in the smartphone to estimate the indoor position coordinates,collects the Wi-Fi observation data,and then uses the wireless signal propagation model to model the indoor wireless environment.Finally,the optimized ranging location algorithm is used to solve the position of the node to be tested.In addition,this paper implements the indoor positioning experiment system based on Android platform,using crowdsourcing mode to complete all data collection work in the background,without the user's active participation,and integrating the positioning related algorithm on the server side,realizing online positioning and reflecting the working process of the algorithm.In this paper,several algorithm simulations and practical application tests are carried out on the scheme.The results show that the scheme can effectively reduce the system deployment cost under the premise of ensuring the positioning accuracy.The average positioning error is 6 meters and the minimum positioning error is less than 1 meter.