Research On Technologies Of Cooperative Radio Localization And Environmental Sensing Towards Intelligent Connected Vehicles

The accurate positioning and environmental sensing for vehicles is one of the essential technologies for the Intelligent Connected Vehicles(ICV).However,the positioning methods relied on satellite system and ultra-wideband(UWB)are not stable enough when their Line of sight(LoS)links are blocked,and the positioning and sensing methods based on RADAR and camera also exhibit issues like limited-coverage and high deployment costs.In this context,the mobile communication networking systems have a wide range of user population and deployment advantages,meanwhile the development and evolution of mobile communication technologies also bring larger system bandwidth and larger antenna array.This would expectedly improve the accuracy for positioning and sensing,which have already been widely concerned by academia and industry.Therefore,how to process and model the wireless signals(including None Line of Sight(NLoS)component)under mobile communication networking systems,so as to achieve accurate positioning and environmental sensing has become an important issue that needs to be solved urgently.To cope with the above issue,taking hold of the advantage of wide-coverage and low-promotion-cost of the mobile communication networks in the context of positioning and sensing for ICVs,this paper proposed a wireless cooperative positioning and environmental sensing method based on signal processing(including NLoS component),which achieved environmental sensing and mapping based on the modeling and estimation of environmental feature estimation,and further improved the accuracy and stability of vehicular positioning based on the proposed cooperative and multiple-sensor fusing positioning method.Based on the experimental verification of the basic wireless positioning method as well as the design and verification of delay-caused positioning error calibration mechanism,this paper achieved reliable positioning and environmental sensing for IC Vs by exploring the relationship between the multiple path components from multiple vehicle and the environment features as well as the environmental sensing,and also the relationship between the cooperative fused positioning as well as the environmental mapping and the performance improvement of vehicular positioning.The major contributions of this paper can be concluded as followings:1.Research on radio positioning and tracking technologies based on environmental feature extraction:utilized the multiple path components from multiple ICVs to model and estimate the environmental features,so as to achieve accurate positioning and tracking for ICVs in a cooperative manner.This research point presented the Team Channel-based Simultaneous Localization and Mapping(Team Channel-SLAM)method to firstly explore the relationship between the multiple path component from multiple ICVs and the environment features so as to model them into the Common Virtual Transmitters(CVT)based on a clustering method.Then a Team Particle Filter(TPF)method was presented to explore the relationship between the environmental features and the accuracy improvement of vehicular positioning so as to achieve cooperative environmental feature estimation as well as multiple-vehicle positioning and tracking under the mobile communication networking framework.The simulation results show that the proposed method can achieve accurate vehicular positioning and tracking,which can improve the positioning accuracy over 40%compared with single vehicle-tracking case under a low vehicle density scenario.2.Research on simultaneous wireless positioning and environmental sensing:achieved environmental sensing and mapping,and explored its relationship with the performance improvement of vehicular positioning,so as to provide accurate positioning and sensing information for ICVs.This research point achieved the environmental sensing by estimating the positions and contour of the reflecting surfaces through an online learning approach,and utilized the environmental sensing information to:1)precisely model the False Alarm(FA)phenomenon in the multiple path component estimation process under mobile communication networks,which improved the accuracy of environmental feature tracking and also the vehicular positioning,2)improve the accuracy of environmental feature estimation through a pre-filtering strategy in its updating process,and 3)estimate the initial position,time synchronization bias and multiple path propagation rays for a newly connected vehicle(without the preknowledge of its position)to provide essential initial state for vehicular positioning and environmental sensing through a proposed radio geometrization method.The simulation results show that the proposed method can achieve accurate environmental sensing,based on which the positioning accuracy can reach around 30-centimeter under different levels of FA and Missed Detection(MD)of multiple path estimation.3.Mobile communication network and GNSS fused positioning and sensing system establishment:proposed a mobile communication network and GNSS(or other absolute positioning methods)fused positioning method to improve the accuracy of vehicular positioning and sensing,and further established a radio positioning and sensing system combined with the proposed cooperative positioning and environmental sensing methods.This paper constructs multipath positioning segment based on the multiple path observations from mobile communication network so as to explore the relationship between the positional information carried by the multiple path components and the relative positions among the nodes in the IoV.Thus the relative positions are fused with the absolute GNSS positioning information(may only accessed by partial ICVs in the IoV)to calculate the position of each ICVs.Meanwhile,this research point further verified basic radio positioning methods under real radio environment,and also designed and verified a delay-caused positioning error calibration mechanism,so as to provide practical evidence for the radio positioning and sensing system.The simulation results show that under the medium-level vehicle density and GNSS coverage,the fused positioning method can improve the average positioning accuracy of ICVs by nearly 40%compared with GNSS.