摘要
捷联惯导在动基座大方位失准角初始对准时可能会出现模型失配和滤波发散等现象,为提高对准性能,对强跟踪容积卡尔曼滤波算法(STCKF)进行改进,引入非线性系统Sage-Husa噪声估计器、模型失配判据和噪声估计器收敛性判据,根据判据对CKF和STCKF进行切换。仿真结果表明:改进后的STCKF算法可以有效地解决捷联惯导在动基座初始对准时出现的模型失配和滤波发散问题。
In initial alignment of SINS with large azimuth misalignment on the sea,the model mismatch and the filter divergence will cause performance degrading of initial alignment.To resolve this problem,the strong tracking cubature Kalman filter algorithm(STCKF)was improved by introducing the Sage-Husa adaptive nonlinear noise estimator,the model mismatch criterion and the convergence criterion of noise estimator.The simulation shows that the improved ASTCKF algorithm is effectual for the SINS initial alignment in the conditions of large heading error on swaying base.
作者
赵海军
高大远
王超
ZHAO Hai-jun;GAO Da-yuan;WANG Chao(Navy Submarine Academy,Qingdao Shandong 266199)
出处
《数字技术与应用》
2020年第7期106-110,共5页
Digital Technology & Application
关键词
捷联惯导
初始对准
STCKF算法
噪声估计器
strapdown inertial navigation system(SINS)
initial alignment
STCKF
noise estimator
