A Study On Hybrid Indoor Localization Algorithm Based On Geomagnetic Field And PDR

With the continuous development of the wireless communication technology and context aware service,Location Based Services(LBS)has shown broad application prospect.Recently,indoor localization methods are mainly based on wireless signal technology.However,the wireless signal will be absorbed by the human body and in-fected by multipath and non line of sight(NLOS),the localization accuracy is not high enough to meet the LBS' demand.As the inherent resources of the earth,the geomag-netic field has the advantages of stability and not being affected by human body.Due to the complex building construction materials,the geomagnetic field has great anomalies related to the positions in indoor environments.It is potentially to use this distinctive geomagnetic anomalies as fingerprints for high precision indoor positioning.Howev-er,indoor geomagnetic field is very weak and provides low discernibility,it's hard to use the geomagnetic filed for indoor localization.As the intelligent mobile terminal developed,more and more smartphones embed many sensors,such as magnetometer,accelerometer,gyroscope and so on.This makes it possible to use geomagnetic field for indoor localization.In this paper,we firstly introduce the characteristics of indoor magnetic field and the principle of geomagnetic field based localization methods.On this basis,we pro-pose the backward sequences matching algorithm(BSMA).BSMA can improve the low discernibility of single geomagnetic signal by vectorizing the backward consecutive ge-omagnetic signals to fingerprint sequences with the help of Pedestrian Dead Reckoning(PDR).We propose An Optimized hidden-markov-model(HMM)Based Localization System(Basmag)Using Backward Sequences Matching Algorithm Exploiting Geo-magnetic Information.Then we compare Basmag with Kalman filter and particle filter in the simulations.The simulation results demonstrate that Basmag can achieve higher localization accuracy,and Basmag is better than the kalman filter and particle filter algo-rithm.At last,we conducted indoor localization experiments on smartphones to verify the effectiveness and robustness among users with different walking styles of Basmag.