Design Of Multi-Source Indoor Location System Based On Heterogeneous Fingerprint

In smart cities and other applications,personnel positioning is a very useful function,achieving high-precision indoor personnel positioning is a prerequisite for the realization of location-based services(LBS)prosperity.Combining the characteristics of different technologies and complementing each other,and using multi-source information to achieve a reliable positioning method with lower cost and higher precision has higher research value and practical significance.Effective positioning information can get the trajectory of the target to be located,and it is also important to implement a variety of location-based services(LBS).The indoor wireless positioning technology of wireless sensor networks based on 2.4GHz signals has unique advantages in closed or semi-enclosed indoor environments.However,this traditional RF positioning still has problems such as multipath interference,non-line-of-sight error and shadow fading and other interference factors affecting the positioning accuracy.Ranging and positioning face many new requirements and challenges,so it is urgent for finding a universal,efficient,highly reliable and easy-deploying indoor positioning method.This paper designs a multi-scenario indoor positioning system framework WSIPLoc(Wireless Smarter Interconnection Protocol Location).The system improves the traditional fingerprint localization algorithm,and the heterogeneous fingerprint localization algorithm combining multi-source sensor information is integrated.Solving the drawbacks of single-radio fingerprints in a higher dimension;in scenarios where multipath effects and shadow fading are lighter,or to reduce the workload of large sampling during the offline phase,In the positioning scenario where the accuracy of the part is sacrificed in exchange for an efficient and low-cost solution,the linear regression algorithm is used to obtain the relationship between the distance and the signal strength.This system proposes a floor recognition solution based on air pressure sensors.In order to solve the error introduced by the traditional wireless sensor positioning network due to the natural fluctuation of the signal,a four-level network topology including calibration nodes is designed.In addition,this framework proposes a reasonable use of optical communication technology to assist in positioning,and proposes a forced signature calibration algorithm for secondary positioning,which makes up for the defects of the fingerprint algorithm,and can effectively identify effective positioning frames that are not affected by non-line-of-sight errors,Eliminating the interference data from the source.The data they acquired complement and verify each other,which will greatly improve the anti-interference ability of the system,improve its robustness,and greatly expand its scope of application.According to the functional requirements,this system designed the hardware structure of the nodes and gateways required by WSIPLoc.Based on the analysis of user needs,we designed the human-computer interaction interface of the positioning system.The system adopts app&web architecture,The APP client and the back-end server equipped with the algorithm module are coded,which provides a good example for the implementation of WSIPLoc.