The Implementation Of Magnetic Field Data Indoor Positioning Based On Particle Filter Algorithm

With location-based positioning services based on outdoor satellite advancing,location-based business model rapidly starts to gain popularity.GPS applications can be said to change the way people live.And the demand for high-accuracy positioning is increasing.Besides,the precision and accuracy of the positioning are also raised to a new height.All the great tech companies,such as Google and Amazon,are focusing on the "last kilometer" positioning-----indoor positioning,spending countless effort and giant investment.According to Japanese scientists,human beings spend no less than 87% of the whole time in the indoor environment,including work and life.Thus,compared to the outdoor environment,the indoor environment localization will have more demand and will be viewed as higher commercially valuable.For a long time,indoor positioning are problematic.Modern building materials shielded GPS signal so that GPS signals cannot pass through these materials.Or,after crossing the walls,the signal will be diminished quickly.And due to the reflection effect of the wall,the use of GPS signals will encounter a variety of obstacle,such as multipath effects.For a long time,indoor positioning algorithm based on Wi-Fi,RSSI LED and RF wireless signals are famous for the high accuracy.However,due to radio navigation signals of these fields are active navigation.Its signal transmitter layout is very important and plan design is very complicated.And the active signal will encounter rapid signal attenuation.For example,indoor objects block signals.Therefore,scientists and various research teams start to concentrate on geomagnetic data.As we all know,the Earth’s geomagnetic field is generated by itself,in any place on Earth,even within 2,000 meters underground.Compared with the radio signals,the magnetic field will not decay.In indoor environment,because of the presence of electronic devices,metal objects,the magnetic field will rapidly increase,significantly different from other places.We call this phenomenon magnetic anomaly.This cliff-like mutants just provides us with the possibility of fingerprint identification features.In recent years,with the explosive development of smart phones,we can use mobile phones to detect the location of people and monitor their behavior.Therefore,we propose a fusion algorithm based on smart phones multi-sensor data in this article.We try to use the data from the phone pedometer,a magnetic field sensor,three-axis accelerometer,an electronic compass and other equipment.The algorithm is constructed in the basis of the main logical framework-------particle filter.Steps range model design,turning determination model,a geomagnetic matching module,confidence analysis module,all of these models are analyzed in this article.The geomagnetic data for the similarity matching is the main step,and at last,the algorithm will provide the targeting location information.