简化自协方差最小二乘噪声估计的SINS静基座初始对准

目的 研究了观测噪声统计特性未知的情况下,简化的自协方差最小二乘噪声估计方法在捷联惯性导航系统静基座初始对准中的应用。该算法采用迭代计算的策略,同时进行噪声估计和初始姿态修正,估计精度较高。通过数值方法对此算法的正确性和有效性进行了验证。

SINS Stationary Initial Alignment Based on SimplifiedAutocovariance Least-Squares Method

Objective Initial alignment is one of the key technologies of the strapdown inertial navigation system.The applications of the strapdown inertial navigation system however,are directly affected by the ac-curacy of initial alignment.Kalman filtering is an effective algorithm for SINS initial alignment,butthe optimal estimates are based on the filtering model and the noise covariance matrices which are al-ready known.This paper focuses on the simplified autocovariance least-squares noise estimation meth-od in the strapdown inertial navigation system’s stationary initial alignment.The proposed method es-tablishes a relationship between unknown measurement noise and the autocovariance.The noise co-variance can be estimated by solving it as a linear least squares problem.The proposed method esti-mates measurement noise and corrects INS attitude by iterative calculation.Simulation results showthat the proposed method performs very well in noise covariance estimation and strapdown inertialnavigation system initial alignment.