The Research And Application Of Indoor Positioning Algorithm Based On Speed Limitation And Environment Constraint

With the development of mobile communication and wireless sensor networks,location-based services have attracted extensive attention.At present,the global navigation satellite system can position precisely and be widely used in outdoor positioning systems,which not only has short observation time without intervisibility,but also has high positioning accuracy.However,there are some limitations,restricted by the complex environment.The denser the environment is,the greater the intensity attenuation of the satellite signal is,which leads to the severe limitation of its positioning function in the complex indoor environment and the accuracy cannot meet the positioning requirements.As we all know,people spend most of their time in indoor environment,but the existing outdoor positioning technology is difficult to meet the requirements of indoor field for high precision location information.What's more,indoor location service is playing an increasingly important role in people's production and life,so the study of indoor location has a great development prospect.Compared with other positioning technologies,UWB(Ultra Wide Band)technology has better characteristics of anti-interference and high precision.Therefore,it is significant to study indoor positioning algorithm based on UWB.The main work of this dissertation includes:1.This dissertation designs an indoor positioning system based on UWB from two aspects of hardware and software.The hardware system is mainly responsible for collecting data,while the software system is mainly responsible for analyzing data and displaying the real-time positioning of the target in the software interface.The research and development of the positioning system provides a practical basis for the subsequent algorithm research.2.An indoor positioning algorithm based on speed and area limitation is studied.The actual positioning scene actually has certain characteristics,such as indoor pedestrians moving at a low speed,immovable obstacles in the indoor positioning environment or impenetrable walls around the room.Based on the above mentioned characteristics,this dissertation proposes an indoor positioning algorithm based on speed limitation and an indoor positioning algorithm based on area limitation,respectively for speed-limited and area-limited scenarios.Then the similarities and differences between the two are studied and combined.Simulation results show that the fusion algorithm can improve the positioning accuracy and ensure high robustness.3.On the basis of the above,this dissertation further analyzes the positioning algorithm research under complex indoor environment,adds map information into the positioning algorithm,and proposes a particle set adaptive correction based particle filter indoor positioning algorithm.The algorithm studies the target particle set and differentiates the particle points in the inaccessible region.The ratio of particles to the total number of particles in inaccessible region is analyzed,and an adaptive optimization model of particle set is proposed.Simulation results show that the algorithm can improve the positioning accuracy and has good robustness.