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 :
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