摘要
引入惯性元件信息观测的初始对准方法能够快速提高SINS的对准速度,但同时存在滤波计算量大、系统噪声与观测噪声相关以及观测值中的高频噪声影响滤波精度的问题。针对这些问题提出了一种捷联惯导快速初始对准降维滤波器设计方法,通过剔除不可观测量和合理选取状态量以降低状态方程维数,并推导了观测方程,在采用低通滤波器对惯性器件原始信息预处理基础上应用噪声相关下的Kalman滤波进行状态估计。理论分析和试验结果表明,新方法提高了对准速度,减少了计算量,水平姿态角收敛速度提高了90%,计算量减少了83.33%,并可有效抑制高频噪声对状态估计的影响。
The initial alignment method of SINS（Strapdown Inertial Navigation System） with measurements of inertial components can efficiently improve the alignment speed, but it has large amount of filtering calculation, its system noise and measurement noise are correlated, and its measurements contain high frequency noise which can affect the filtering accuracy. To solve these problems, an order-reduced filter for fast alignment of the SINS is proposed, whose dimensions of state equation is reduced by removing no observable states and the reasonable selection, and the measurement equation is deduced. Then the state variables can be estimated by noise-related Kalman filter with the original information preprocessed by low-pass filter. Theory analysis and test results show that the new method can improve the convergence speed of horizontal misalignments by 90%, reduce the calculation amount by 83.33%, and effectively suppress the effect of the high frequency noise.
出处
《中国惯性技术学报》
EI
CSCD
北大核心
2016年第5期607-611,618,共6页
Journal of Chinese Inertial Technology
基金
国家自然科学基金资助项目(41406212,41201478)
关键词
捷联惯导
初始对准
降维滤波器
低通滤波器
可观测性
strapdown inertial navigation system
initial alignment
order-reduced filter
low-pass filter
observability
