scholarly journals A Method for SINS Alignment with Large Initial Misalignment Angles Based on Kalman Filter with Parameters Resetting

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xixiang Liu ◽  
Xiaosu Xu ◽  
Yiting Liu ◽  
Lihui Wang
Keyword(s):  
Kalman Filter ◽  
Covariance Matrix ◽  
Nonlinear Problem ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Error Model ◽  
The State ◽  
Alignment Method ◽  
Initial Alignment ◽  
Alignment Process

In the initial alignment process of strapdown inertial navigation system (SINS), large initial misalignment angles always bring nonlinear problem, which causes alignment failure when the classical linear error model and standard Kalman filter are used. In this paper, the problem of large misalignment angles in SINS initial alignment is investigated, and the key reason for alignment failure is given as the state covariance from Kalman filter cannot represent the true one during the steady filtering process. According to the analysis, an alignment method for SINS based on multiresetting the state covariance matrix of Kalman filter is designed to deal with large initial misalignment angles, in which classical linear error model and standard Kalman filter are used, but the state covariance matrix should be multireset before the steady process until large misalignment angles are decreased to small ones. The performance of the proposed method is evaluated by simulation and car test, and the results indicate that the proposed method can fulfill initial alignment with large misalignment angles effectively and the alignment accuracy of the proposed method is as precise as that of alignment with small misalignment angles.

scholarly journals An Improved ACKF/KF Initial Alignment Method for Odometer-Aided Strapdown Inertial Navigation System

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3896 ◽  
Author(s):  
Kang Gao ◽  
Shunqing Ren ◽  
Guoxing Yi ◽  
Jiapeng Zhong ◽  
Zhenhuan Wang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Observation Equation ◽  
Alignment Method ◽  
Misalignment Angle ◽  
Initial Alignment ◽  
Error Equation

For a land-vehicle strapdown inertial navigation system (SINS), the problem of initial alignment with large misalignment angle in-motion needs to be solved urgently. This paper proposes an improved ACKF/KF initial alignment method for SINS aided by odometer. The SINS error equation with large misalignment angle is established first in the form of an Euler angle. The odometer/gyroscope dead reckoning (DR) error equation is deduced, which makes the observation equation linear when the position is taken as the observation of the Kalman filter. Then, based on the cubature Kalman filter, the Sage-Husa adaptive filter and the characteristics of the observation equation, an improved ACKF/KF method is proposed, which can accomplish initial alignment well in the case of unknown measurement noise. Computer simulation results show that the performance of the proposed ACKF/KF algorithm is superior to EKF, CKF and AEKF method in accuracy and stability, and the vehicle test validates its advantages.

An Improved Initial Alignment Method of Strap-Down Inertial Navigation System on a Swaying Base

2013 ◽  
Vol 415 ◽  
pp. 143-148
Author(s):  
Li Hua Zhu ◽  
Xiang Hong Cheng
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Alignment Algorithm ◽  
Alignment Method ◽  
Initial Alignment ◽  
Vehicle Simulation ◽  
Robust Property ◽  
Simulation Results ◽  
Lever Arm Effect ◽  
The Impact

The design of an improved alignment method of SINS on a swaying base is presented in this paper. FIR filter is taken to decrease the impact caused by the lever arm effect. And the system also encompasses the online estimation of gyroscopes’ drift with Kalman filter in order to do the compensation, and the inertial freezing alignment algorithm which helps to resolve the attitude matrix with respect to its fast and robust property to provide the mathematical platform for the vehicle. Simulation results show that the proposed method is efficient for the initial alignment of the swaying base navigation system.

In-motion Alignment Algorithm for Vehicle Carried SINS Based on Odometer Aiding

2017 ◽  
Vol 70 (6) ◽  
pp. 1349-1366 ◽  
Author(s):  
Haijian Xue ◽  
Xiaosong Guo ◽  
Zhaofa Zhou ◽  
Kunming Wang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Measured Data ◽  
The Body ◽  
Alignment Algorithm ◽  
Alignment Method ◽  
Initial Angle ◽  
Body Frame ◽  
Measurement Equation

In-motion alignment plays an important role in improving the manoeuvring capability of a vehicle, and allows the initialisation of a Strapdown Inertial Navigation System (SINS) while moving. Odometer (OD) aided in-motion alignment is widely adopted owing to its fully self-contained characteristic. This paper proposes a complete in-motion alignment algorithm for a vehicle-carried SINS based on odometer aiding, in which an in-motion coarse alignment method using the integration form of the velocity update equation in the body frame to give a rough initial angle is introduced and a new measurement equation in the body frame with a Kalman filter (KF) for the in-motion fine alignment is established. The advantages of the proposed method are verified by simulation and measured data.

A fast alignment of marine strapdown inertial navigation system based on adaptive unscented Kalman Filter

2020 ◽  
pp. 014233122093429 ◽  
Author(s):  
Hossein Rahimi ◽  
Amir Ali Nikkhah ◽  
Kaveh Hooshmandi
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Unscented Kalman Filter ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Initial Alignment ◽  
External Perturbations ◽  
Adaptive Unscented Kalman Filter ◽  
Strapdown Inertial Navigation

This study has presented an efficient adaptive unscented Kalman filter (AUKF) with the new measurement model for the strapdown inertial navigation system (SINS) to improve the initial alignment under the marine mooring conditions. Conventional methods of the accurate alignment in the ship’s SINS usually fail to succeed within an acceptable period of time due to the components of external perturbations caused by the movement of sea waves and wind waves. To speed up convergence, AUKF takes into account the impact of the dynamic acceleration on the filter and its gain adaptively tuned by considering the dynamic scale sensed by accelerometers. This approach considerably improved the corrections of the current residual error on the SINS and decreased the influence due to the external perturbations caused by the ship’s movement. Initial alignment algorithm based on AUKF is designed for large misalignment angles and verified by experimental data. The experimental test results show that the proposed algorithm enhanced the convergence speed of SINS initial alignment compared with some state-of-the-art existing approaches.

Fast Fine Initial Self-alignment of INS in Erecting Process on Stationary Base

2017 ◽  
Vol 71 (3) ◽  
pp. 697-710 ◽  
Author(s):  
Jianli Li ◽  
Yiqi Li ◽  
Baiqi Liuxs
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Euler Angle ◽  
Alignment Method ◽  
State Variables ◽  
Initial Alignment ◽  
Angle Error ◽  
Alignment Model ◽  
System Observability

Fine initial alignment is vital to the Inertial Navigation System (INS) before the launching of a missile. The existing initial alignment methods are mainly performed on a stationary base after the missile has been erected to the vertical state. However, these methods consume extra alignment time and some state variables have poor degrees of observability, thus losing the rapidity of alignment. In order to solve the problem, a fast fine initial self-alignment method of a missile-borne INS is proposed, which is performed during the erecting process on a stationary base. The convected Euler angle error is modelled to optimise the erecting manoeuvre which can prevent large Euler angle errors and improve the system observability. The fine initial alignment model is established to estimate and correct the initial misalignment. Several experiments verify that the proposed method is effective for improving the rapidity of the fine initial alignment for a missile-borne INS.

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