Robust cubature Kalman filter method for the nonlinear alignment of SINS

Nonlinear initial alignment is a significant research topic for strapdown inertial navigation system(SINS).Cubature Kalman filter(CKF)is a popular tool for nonlinear initial alignment.Standard CKF assumes that the statics of the observation noise are pre-given before the filtering process.Therefore,any unpredicted outliers in observation noise will decrease the stability of the filter.In view of this problem,improved CKF method with robustness is proposed.Multiple fading factors are introduced to rescale the obser-vation noise covariance.Then the update stage of the filter can be autonomously tuned,and if there are outliers exist in the observations,the update should be less weighted.Under the Gaussian assumption of KF,the Mahalanobis distance of the innovation vector is supposed to be Chi-square distributed.Therefore a judging index based on Chi-square test is designed to detect the noise outliers,determining whether the fading tune are required.The proposed method is applied in the nonlinear alignment of SINS,and vehicle experiment proves the effective of the proposed method.     

磁绝缘传输线阴极准直建模与仿真

大型脉冲功率装置的磁绝缘传输线(Magnetically Insulated Transmission Line,MITL)阴极长度可达十余米,在悬臂结构下由于重力引起的末端挠度变形将达数厘米.如果不进行准直,由此造成的阴阳极间隙误差可能引起较明显的电流损失.借鉴HermesⅢ装置基于倾斜垫片的直线度调节方案,设计了用...