Design And Implementation Of Fusion Indoor Positioning System Based On Sound Signal And PDR

In today's high-tech background,electronic technology and sensor technology are developing rapidly,and mobile devices such as smartphones are widely popularized.People are using this as an opportunity to apply location-based services in indoor environments.Indoor positioning has good development prospects in today's society.In the commercial area,it helps users to obtain their own positions and plan travel routes;in industrial scenarios,it helps management personnel locate equipment and materials to facilitate industrial dispatch;in disaster scenes,it helps firefighters get the location of the person to be aided in time.So far,some traditional indoor positioning technologies have developed relatively maturely.Among them,sound localization technology and pedestrian dead reckoning technology have received extensive attention in recent years.Acoustic indoor positioning technology has good positioning accuracy;pedestrian dead reckoning technology has high independence and is not subject to environmental interference.However,there are still some limitations behind the mature technology.When working for a long time,the pedestrian dead reckoning technology is difficult to guarantee the positioning accuracy,and its measurement error will accumulate over time;The indoor positioning based on sound signals is prone to occasional errors in positioning in the indoor environment,which will lead to a decline in positioning performance.To this end,this paper studies related methods of fusion positioning,and discusses the design and implementation of a fusion indoor positioning system based on acoustic positioning and pedestrian dead reckoning.First of all,this article conducts research from two aspects of smart phone acoustic indoor positioning and pedestrian dead reckoning related technologies.In terms of sound localization,the current sound signal detection methods and positioning principles are studied,and a sound localization scheme is designed based on an asynchronous passive structure;The mobile phone sensor data is preprocessed,the traditional gait detection method is optimized,and the direction estimation is based on the fusion filtering method,the cumulative error of PDR is corrected by TDOA positioning.Finally,based on the aforementioned method,the overall PDR positioning scheme is designed.Secondly,based on the particle filter algorithm framework,this paper fuses the sound localization technology with the PDR technology.This method is characterized by using multiple data sources such as sound signals and smartphone IMU data to fuse the measurement values of the two technologies into the particle filter framework,then,build a constraint relationship to achieve the best estimate of the target.Finally,this paper implements the system based on the fusion positioning scheme.The client-server structure design is used to ensure the scalability of the system.The implementation of the client,server,and anchor node of the system is completed based on Android,Windows,and Arm Linux platforms.The system test was carried out in indoor scenes,from sound signal detection,sound signal positioning,pedestrian dead reckoning and fusion positioning.The experimental results show that the overall performance of the fusion positioning system in this paper is good and the fusion positioning method overcomes the limitations of single positioning technology,it improves positioning performance.