DocumentCode
1854242
Title
An incline alignment algorithm for vehicle-borne sensor system
Author
Huang Jianjun ; Guo Junting ; Wang Juanjuan
Author_Institution
ATR Key Lab., Shenzhen Univ., Shenzhen, China
Volume
3
fYear
2012
fDate
21-25 Oct. 2012
Firstpage
2016
Lastpage
2019
Abstract
Aiming at the problem of incline alignment for vehicle-borne sensor system, a UKF-LM based incline alignment algorithm is presented. Two Unscented Kalman Filters (UKF) are used to estimate a calibration target´s position in both sensor coordinate system and vehicle base-coordinate system, respectively. The nonlinear least-squares Levenberg-Marquardt (LM) algorithm is applied to estimate the incline angle and the incline vector between the two coordinate systems by the filtered target positions. Simulation results show that the proposed algorithm is effective and efficient.
Keywords
Kalman filters; calibration; least squares approximations; nonlinear filters; sensors; UKF-LM-based incline alignment algorithm; calibration target position estimation; coordinate systems; filtered target positions; inclination angle; inclination vector; nonlinear least-squares LM algorithm; nonlinear least-squares Levenberg-Marquardt algorithm; sensor coordinate system; unscented Kalman filters; vehicle base-coordinate system; vehicle-borne sensor system; Levenberg-Marquardt(LM); Unscented Kalman Filter(UKF); incline alignment; vehicle-borne sensor system;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing (ICSP), 2012 IEEE 11th International Conference on
Conference_Location
Beijing
ISSN
2164-5221
Print_ISBN
978-1-4673-2196-9
Type
conf
DOI
10.1109/ICoSP.2012.6491976
Filename
6491976
Link To Document