Calculation of Vehicle Real-time Position Overcoming the GPS Positioning Latency with MEMS INS

被引:0
作者
Li Bowen [1 ]
Yao Danya
机构
[1] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
来源
2014 IEEE INTERNATIONAL CONFERENCE ON SERVICE OPERATIONS AND LOGISTICS, AND INFORMATICS (SOLI) | 2014年
关键词
GPS; INS; latency; real-time position; data synchronization; neural network; ERROR;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
GPS (Global Positioning System) always has the problem of positioning latency which make it can't output the real-time position. Different GPS may have different latencies. The positioning latency of consumer-grade GPS often used in vehicles is especially relatively larger. In this paper, we present a method to calculate the vehicle real-time position overcoming the GPS positioning latency with low-cost MEMS (Micro-Electro-Mechanical System) INS (Inertial Navigation System). We compute the latency through comparing the degree of correlation between the velocity difference time series obtained from the GPS output and the acceleration time series outputted by the accelerometer. Then fuse the GPS/INS data according to the latency in order to improve accuracy for the position that has been outputted by the GPS, and estimate the vehicle real-time with the acceleration time series outputted in the latency. At last, a neural network is established to correct the estimated position to reduce the error. Meanwhile, a GPS/INS data synchronization method is presented for the GPS which can't output 1 pps (Pulse Per Second) signal. The experimental results show the methods can calculate the accurate vehicle real-time eliminating the positioning error caused by the GPS latency. The methods achieve a good effect.
引用
收藏
页码:248 / 254
页数:7
相关论文
共 13 条
[1]  
[Anonymous], 2007, GLOBAL POSITIONING S
[2]  
Bonnifait P, 2001, IEEE INT CONF ROBOT, P1597, DOI 10.1109/ROBOT.2001.932839
[3]  
Bowen Li, J TSINGHUA IN PRESS
[4]   Optimal nonlinear filtering in GPS/INS integration [J].
Carvalho, H ;
DelMoral, P ;
Monin, A ;
Salut, G .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 1997, 33 (03) :835-850
[5]   Sigma-point Kalman filtering for integrated GPS and inertial navigation [J].
Crassidis, John L. .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2006, 42 (02) :750-756
[6]   Temperature variation effects on stochastic characteristics for low-cost MEMS-based inertial sensor error [J].
El-Diasty, M. ;
El-Rabbany, A. ;
Pagiatakis, S. .
MEASUREMENT SCIENCE AND TECHNOLOGY, 2007, 18 (11) :3321-3328
[7]   GPS error modeling and OTF ambiguity resolution for high-accuracy GPS/INS integrated system [J].
Grejner-Brzezinska, DA ;
Da, R ;
Toth, C .
JOURNAL OF GEODESY, 1998, 72 (11) :626-638
[8]  
Langley R. B., 1998, GPS World, V9, P70
[9]  
Lippmann R. P., 1988, Computer Architecture News, V16, P7, DOI [10.1109/MASSP.1987.1165576, 10.1145/44571.44572]
[10]   AN ALGORITHM FOR LEAST-SQUARES ESTIMATION OF NONLINEAR PARAMETERS [J].
MARQUARDT, DW .
JOURNAL OF THE SOCIETY FOR INDUSTRIAL AND APPLIED MATHEMATICS, 1963, 11 (02) :431-441