Design And Implementation Of Indoor Positioning Algorithm Based On Geomagnetic And RSSI

With the development of mobile networks and intelligent terminals, the location-basedservices (LBS), such as information and location navigation of goods in big mall, precise addelivery, position guide of fire Rescue, has showed a broad application prospects. Positioningtechnology is a necessary prerequisite for LBS. Because of the wireless signal propagation processsusceptible to multipath effects, absorbed by the body, non-line-spread impact and so on in indoorenvironment, the current positioning method based on wireless signal strength couldn’t meet theaccuracy needs of indoor LBS, while the high accuracy positioning methods couldn’t be large-scaleapplications due to the high costs of hardware.With the development of micro-electromechanical systems (MEMS) sensor and thepopularization of intelligent terminals, sensors such as gravity, gyroscope, geomagnetic has beenvery popular. These sensors can perceptual characteristics of the indoor environment, so it can beused for positioning or assisted positioning. Based on the analysis of the current indoor positioningtechnology characteristics and trends, the paper presents a hybrid indoor positioning method basedon geomagnetic anomalies and RSSI, which calculate people’s location by the geomagnetic fieldand wireless signal characteristics.Firstly, the basic principles of geomagnetic matching positioning and wireless locationalgorithm theories were introduced, on the basis of above, we presented a hybrid positioningmethod based on geomagnetic field strength and the wireless signal RSSI. Subsequently, ageomagnetic matching positioning algorithm based on particle filter was designed, and analyzes theinfluence of various parameters on the performance of the algorithm by simulation. Against theinsufficient of singly use the geomagnetic to position, the paper proposed a wireless locationinformation assisted method to optimize the sampling process of origin algorithm, the simulationresults show that the improved algorithm has better match speed and robustness. Finally, we designand implement a prototype positioning system based on positioning method in this paper to verifythe actual performance of the algorithm. The design and implementation of each module wereintroduced, and then we deploys a test in a laboratory environment. The test results show that thealgorithm has good positioning accuracy, which demonstrated the feasibility of our hybridpositioning method.