This paper considers the non-line-of-sight(NLOS)vehicle localization problem by using millimeter-wave(MMW)automotive radar.Several preliminary attempts for NLOS vehicle detection are carried out and achieve good resul...This paper considers the non-line-of-sight(NLOS)vehicle localization problem by using millimeter-wave(MMW)automotive radar.Several preliminary attempts for NLOS vehicle detection are carried out and achieve good results.Firstly,an electromagnetic(EM)wave NLOS multipath propagation model for vehicle scene is established.Subsequently,with the help of available multipath echoes,a complete NLOS vehicle localiza-tion algorithm is proposed.Finally,simulation and experimental results validate the effectiveness of the established EM wave propagation model and the proposed NLOS vehicle localization algorithm.展开更多
This paper proposes a robust vector tracking loop structure based on potential bias analysis. The influence of four kinds of biases on the existing two implementations of Vector Tracking Loops(VTLs) is illustrated by ...This paper proposes a robust vector tracking loop structure based on potential bias analysis. The influence of four kinds of biases on the existing two implementations of Vector Tracking Loops(VTLs) is illustrated by theoretical analysis and numerical simulations, and the following findings are obtained. Firstly, the initial user state bias leads to steady navigation solution bias in the relative VTL, while new measurements can eliminate it in the absolute VTL. Secondly, the initial code phase bias is transferred to the following navigation solutions in the relative VTL, while new measurements can eliminate it in the absolute VTL. Thirdly, the user state bias induced by erroneous navigation solution of VTLs can be eliminated by both of the two VTLs. Fourthly,the multipath/NLOS likely affects the two VTLs, and the induced tracking bias in the duration of the multipath/NLOS would decrease the performance of VTLs. Based on the above analysis,a robust VTL structure is proposed, where the absolute VTL is selected for its robustness to the two kinds of initialization biases;meanwhile, the instant bias detection and correction method is used to improve the performance of VTLs in the duration of the multipath/NLOS. Numerical simulations and experimental results verify the effectiveness of the proposed robust VTL structure.展开更多
Non-line-of-sight(NLOS)multipath effect is the main factor that restricts the application of global navigation satellite system(GNSS)in complex environments,especially in urban canyon.The effective avoidance of NLOS s...Non-line-of-sight(NLOS)multipath effect is the main factor that restricts the application of global navigation satellite system(GNSS)in complex environments,especially in urban canyon.The effective avoidance of NLOS signals can significantly improve the positioning performance of GNSS receiver.In this paper,an NLOS/LOS classification model based on recurrent neural network is proposed to classify satellite signals received in urban canyon environments.The accuracy of classification is 91%,and the recognition rate of NLOS is 89%;the classification performance is better than that of traditional machine learning classification models such as support vector machine.For BeiDou navigation satellite system/global positioning system(BDS/GPS)fusion system,the least square algorithm and extended Kalman filter are used to estimate the position.The experimental results show that the three-dimensional positioning accuracy after NLOS recognition is improved about 60%on average compared with the traditional methods,and the positioning stability is also improved significantly.展开更多
基金supported by the National Natural Science Foundation of China(62201510,62001091,61801435,61871080,61801435)the Initial Scientific Research Foundation of University of Science and Technology of China(Y030202059018051)+2 种基金Yangtze River Scholar Program,Sichuan Science and Technology Program(2019JDJQ0014)111 Project(B17008)Henan Provincial Department of Science and Technology Research Project(202102210315,212102210029,202102210-137).
文摘This paper considers the non-line-of-sight(NLOS)vehicle localization problem by using millimeter-wave(MMW)automotive radar.Several preliminary attempts for NLOS vehicle detection are carried out and achieve good results.Firstly,an electromagnetic(EM)wave NLOS multipath propagation model for vehicle scene is established.Subsequently,with the help of available multipath echoes,a complete NLOS vehicle localiza-tion algorithm is proposed.Finally,simulation and experimental results validate the effectiveness of the established EM wave propagation model and the proposed NLOS vehicle localization algorithm.
基金co-supported by the Scientific Research Program of Tianjin Municipal Education Commission, China (No. 2021KJ042)the Special Project of the National Science Foundation of China (No. U2133204)。
文摘This paper proposes a robust vector tracking loop structure based on potential bias analysis. The influence of four kinds of biases on the existing two implementations of Vector Tracking Loops(VTLs) is illustrated by theoretical analysis and numerical simulations, and the following findings are obtained. Firstly, the initial user state bias leads to steady navigation solution bias in the relative VTL, while new measurements can eliminate it in the absolute VTL. Secondly, the initial code phase bias is transferred to the following navigation solutions in the relative VTL, while new measurements can eliminate it in the absolute VTL. Thirdly, the user state bias induced by erroneous navigation solution of VTLs can be eliminated by both of the two VTLs. Fourthly,the multipath/NLOS likely affects the two VTLs, and the induced tracking bias in the duration of the multipath/NLOS would decrease the performance of VTLs. Based on the above analysis,a robust VTL structure is proposed, where the absolute VTL is selected for its robustness to the two kinds of initialization biases;meanwhile, the instant bias detection and correction method is used to improve the performance of VTLs in the duration of the multipath/NLOS. Numerical simulations and experimental results verify the effectiveness of the proposed robust VTL structure.
文摘Non-line-of-sight(NLOS)multipath effect is the main factor that restricts the application of global navigation satellite system(GNSS)in complex environments,especially in urban canyon.The effective avoidance of NLOS signals can significantly improve the positioning performance of GNSS receiver.In this paper,an NLOS/LOS classification model based on recurrent neural network is proposed to classify satellite signals received in urban canyon environments.The accuracy of classification is 91%,and the recognition rate of NLOS is 89%;the classification performance is better than that of traditional machine learning classification models such as support vector machine.For BeiDou navigation satellite system/global positioning system(BDS/GPS)fusion system,the least square algorithm and extended Kalman filter are used to estimate the position.The experimental results show that the three-dimensional positioning accuracy after NLOS recognition is improved about 60%on average compared with the traditional methods,and the positioning stability is also improved significantly.
