DocumentCode :
2630538
Title :
INS/VNS Fusion based on unscented particle filter
Author :
Yue, Dong-xue ; Huang, Xin-Sheng ; Tan, Hong-li
Author_Institution :
Nat. Univ. of Defense Technol., Changsha
Volume :
1
fYear :
2007
fDate :
2-4 Nov. 2007
Firstpage :
151
Lastpage :
156
Abstract :
In vision aided terminal inertial navigation system (INS), the INS use dead reckoning calculate the velocity and position of the vehicle based on the measurements of the strapdown inertial sensors. Using the parallel structure of the runway, vision navigation system (VNS) can estimate the relative position and velocity of vehicle to the runway, based on the error position of the feature points of the runway in perspective image and weak perspective image. For the fixed target point on the runway, the relationship of the velocities of INS and VNS are deduced, on which unscented particle filter (UPF) is designed to fuse the two sensors. The resulting output of the filter is the velocity error of the vehicle. When fixed bias exists in outputs of accelerometers or gyroscopes, the process noise is not Gaussian white noise any more. UPF can deal with any distribution and do not need increase states to model the noise as Kalman filter does. Simulation results show that the UPF fusion algorithm can increase the accuracy of the velocity and improve the performance of the navigation.
Keywords :
Gaussian noise; inertial navigation; particle filtering (numerical methods); sensor fusion; Gaussian white noise; dead reckoning; error position; inertial navigation system; sensor fusion; strapdown inertial sensors; unscented particle filter; vision navigation system; Dead reckoning; Fuses; Inertial navigation; Machine vision; Particle filters; Position measurement; Sensor fusion; Sensor systems; Vehicles; Velocity measurement; Inertial navigation system; information fusion; unscented particle filter; vision navigation system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1065-1
Electronic_ISBN :
978-1-4244-1066-8
Type :
conf
DOI :
10.1109/ICWAPR.2007.4420654
Filename :
4420654
Link To Document :
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