Nonlinear Initial Alignment of Strapdown Inertial Navigation System Using CSVM
According to the situation that the statistical characteristics of noise in initial alignment of sins of UKF filter is not agree with actually, the filtering precision will severely reduce or even divergent, a combination of support vector machine method of initial alignment is proposed. In this paper, the test samples are split into four groups. Three groups are trained for the first layer and the last group is trained for the second layer of support vector machine. The first layer is a group of support vector machine in parallel computing, the second layer is an information fusion of the single support vector machine in the first layer, and combined support vector machines. In this method initial alignment of strapdown inertial navigation system is achieved. Finally through the UKF filter, SVM, CSVM simulation contrast, the results show that CSVM has an improvement than a single SVM, better real-time than UKF filter and generalization ability.
Initial alignment Combination support vector machine (CSVM) Unscented Kalman filter (UKF) Information fusion
Wang He Nian Yi Guo Xing Wang Chang Hong Guan Yu
Space Control and Inertia Technology Research Center, Harbin Institute of Technology, China
国际会议
大连
英文
616-620
2011-10-19（万方平台首次上网日期，不代表论文的发表时间）