High Accuracy Vehicle Localization Technology Based On Non-line-of-sight Communication Link Identification

The rapid development of fifth-generation mobile communication(5G)and Internet of Vehicles(Io V)technologies have deeply changed the whole automotive industry.A variety of emerging in-vehicle applications and services such as driverless car and automatic parking have emerged.These new applications lead the development of the automotive industry but also change people’s lifestyle.However,such technologies also pose many new challenges to some key technologies.Specifically,as one of the basic technologies of Io V,vehicle localization technology plays an important role in ensuring the safe driving of vehicles.However,the localization error of existing vehicle localization methods is usually very large.It is difficult to fully meet the needs of the above-mentioned emerging on-board applications to obtain high-precision vehicle location information.In particular,non-line-of-sight(NLOS)communication link is ubiquitous in Io V,which adds an extra error to the measurement distance and results in a significant increase in the localization error of vehicles.Therefore,the lack of vehicle localization accuracy in the NLOS environment has become a key factor restricting the safety and reliability of Io V technology.In order to solve the problems mentioned above,this paper researches the method to improve the vehicle localization accuracy in NLOS scenarios.This paper first introduces the basic knowledge of vehicle wireless localization,and clarifies the impact,causes,and countermeasures of NLOS propagation on localization.Secondly,this paper analyzes the performance of vehicle localization in NLOS environment,and summarizes the main factor that affects the accuracy of vehicle localization for different cases.Finally,this paper proposes a high-accuracy vehicle localization algorithm based on statistical methods and NLOS identification,and through simulation,it is verified that the proposed algorithm has good performance in NLOS scenarios.Specifically,the main innovations and contributions of this paper are as follows:(1)This paper studies the effect of NLOS misidentification on the localization performance of vehicle localization in the presence of NLOS propagation between vehicles.The influence of the two types of misidentifications on vehicle localization accuracy under different NLOS probabilities and different localization strategies is analyzed.Through simulations,it is found that different types of NLOS misidentification have different influences on the localization accuracy.The magnitude of the influence will vary with the change of NLOS probability,the localization strategy,the range of vehicle communication and other factors.Finally,it is comprehensively analyzed that why the two types of NLOS misidentification in different scenarios have different effects on the localization accuracy,and recommend the localization strategy that can achieve higher accuracy in various localization scenarios.(2)This paper proposes a high-accuracy vehicle localization algorithm based on statistical methods and NLOS identification.The algorithm consists of two sections:NLOS identification based on hypothesis testing,and multi-vehicle cooperative vehicle networking localization.In the first section,we construct a new test statistic and derive its probability density functions(pdf)in NLOS and LOS states accordingly,and uses the link’s pdfs to determine the NLOS state.In the second part,the cooperative localization of vehicles within Io V is exploited using links between vehicles.The performance of proposed algorithm is verified with generated and measured data.The results show that the algorithm has the following advantages: 1)It can obtain high localization accuracy in the NLOS environment,and the localization accuracy will also further increase with the increase of vehicles in the network.2)The localization error of the proposed algorithm is concentrated in a small range,and the situation where the localization error is extremely large is rare,i.e.,the proposed algorithm has good robustness.3)The proposed algorithm can work not only in the case of known NLOS prior information,but also in the environment without NLOS prior information.4)The localization accuracy of the algorithm proposed will be further increased with the improvement of GPS localization accuracy.To sum up,this paper deeply and comprehensively analyzes the factors that affect the performance of vehicle localization in NLOS environment,and proposes a new vehicle localization algorithm,which effectively improves the performance of vehicle localization in NLOS scenarios.Therefore,this paper makes a certain contribution to the development of vehicle localization technology.