Application of Adaptive Robust CKF in SINS/GPS Initial Alignment with Large Azimuth Misalignment Angle

Zhang Bing,Hao Zhaojun,Wang Xiaodong,Gu Changchao,Lu Hao,Laurent Mevel

doi:10.1155/2021/7398706

Abstract

When the strapdown inertial navigation system does not perform coarse alignment, the misalignment angle is generally a large angle, and a nonlinear error model and a nonlinear filtering method are required. For large azimuth misalignment, the initial alignment technology with a large azimuth misalignment angle is researched in this paper. The initial alignment technology with a large azimuth misalignment angle is researched in this paper. First, the SINS/GPS nonlinear error model is established. Secondly, in the view of observation gross errors and inaccurate noise statistical characteristics, an adaptive robust CKF algorithm is proposed. Finally, according to the simulation analysis and experiment, the adaptive robust CKF algorithm can augment the stability and improve the filter estimation precision and convergence rate.

Highlights

As an important means for exploring oceans, underwater vehicles are widely applied in civilian and military
Initial alignment mainly contains the rough alignment process and fine alignment process; once the underwater vehicle encountered bad sea conditions, rough azimuth information is difficult to obtain in the rough alignment process so that the condition of initial alignment is usually with large azimuth misalignment angle. erefore, in view of the work process and actual application requirements for the underwater vehicle, this paper aims to study the technology of initial alignment with large azimuth misalignment angle
In view of the problems above, the cubature Kalman filtering (CKF) based on the spherical-radial cubature criterion is widely applied at the present time. is algorithm avoids the linearization of the nonlinear model and overcomes the shortcomings of EKF and other traditional nonlinear filtering algorithms [2]

Summary

Introduction

As an important means for exploring oceans, underwater vehicles are widely applied in civilian and military. Erefore, in view of the work process and actual application requirements for the underwater vehicle, this paper aims to study the technology of initial alignment with large azimuth misalignment angle. Initial alignment with large azimuth misalignment angle is the key technology of SINS [1, 2]. According to the characteristics of the nonlinear error model, nonlinear EKF and UKF are usually applied on tradition. 2. SINS Large Azimuth Misalignment Angle Error Model e conversion matrix between the navigation coordinate system n used which is described by the Euler platform error angle φ 􏽨 φx φy φz. E measurement error of the accelerometer is mainly random normal zero deviation ∇b and zero-mean Gaussian white noise wa. If the horizontal misalignment angle is small and the height error is not considered, the SINS large azimuth error model is. Gw is the process noise input matrix; h(t) is the measuring matrix, and h(t) [02×3I2×202×5]; w(t) is the process noise; v(t) is the measurement noise and follows Gaussian distribution v(t) ∼ N(0, R)

Robust Kalman Filtering Algorithm

Adaptive Kalman Filtering Algorithm

Simulation

Experiment Test

Conclusion