Title :
A novel nonlinear filter for initial alignment in strapdown inertial navigation system
Author :
Li, Xiang ; Yu, Liu ; Baoku, Su ; Xiaoxiong, Jiang
Author_Institution :
Space Control & Inertial Technol. Res. center, Harbin Inst. of Technol., Harbin
Abstract :
The error model is nonlinear when the azimuth angle of strapdown inertial navigation system (SINS) on stable base is large, and a new filter results from using unscented Kalman filter for proposal distribution generation imbedding latest observed measurements in importance sampling step, and combining Gaussian mixture model and weighted expectation maximization (EM) algorithm to replace the traditional resampling step. And the "sample depletion" problem was lessened. It is demonstrated by simulation that this new approach has an improved estimation performance in initial alignment of large azimuth misalignment on static base of SINS.
Keywords :
Gaussian processes; Kalman filters; expectation-maximisation algorithm; importance sampling; inertial navigation; nonlinear filters; EM algorithm; Gaussian mixture model; azimuth angle; error model; importance sampling; large azimuth misalignment; nonlinear filter; sample depletion; strapdown inertial navigation system; unscented Kalman filter; weighted expectation maximization; Azimuth; Computer errors; Inertial navigation; Monte Carlo methods; Nonlinear equations; Nonlinear filters; Proposals; Silicon compounds; Space technology; Vehicles;
Conference_Titel :
Systems and Control in Aerospace and Astronautics, 2008. ISSCAA 2008. 2nd International Symposium on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-3908-9
Electronic_ISBN :
978-1-4244-2386-6
DOI :
10.1109/ISSCAA.2008.4776313
