Modeling and simulation of the geomagnetic field vector measurement on the underwater vehicle

2015 ◽  
Author(s):  
Ta Zhao ◽  
Changhua Guo ◽  
Xiaoning Zhu ◽  
Zhijian Zhou ◽  
Defu Cheng
Keyword(s):  
Modeling And Simulation ◽  
Geomagnetic Field ◽  
Underwater Vehicle ◽  
Field Vector ◽  
Vector Measurement

Improved component compensation for geomagnetic field vector measurement using Lagrange multiplier method

2017 ◽  
Vol 11 (8) ◽  
pp. 1094-1098 ◽  
Author(s):  
Chengbiao Wan ◽  
Mengchun Pan ◽  
Qi Zhang ◽  
Hongfeng Pang ◽  
Xuejun Zhu ◽  
...  
Keyword(s):  
Lagrange Multiplier ◽  
Geomagnetic Field ◽  
Field Vector ◽  
Lagrange Multiplier Method ◽  
Multiplier Method ◽  
Vector Measurement

A new misalignment calibration method of portable geomagnetic field vector measurement system

Measurement ◽  
2020 ◽  
Vol 164 ◽  
pp. 108041
Author(s):  
Hongfeng Pang ◽  
Mengchun Pan ◽  
Wei Qu ◽  
Lei Qiu ◽  
Jun Yang ◽  
...  
Keyword(s):  
Measurement System ◽  
Geomagnetic Field ◽  
Calibration Method ◽  
Field Vector ◽  
Vector Measurement

The component compensation of geomagnetic field vector measurement system

2015 ◽  
Vol 381 ◽  
pp. 390-395 ◽  
Author(s):  
Hongfeng Pang ◽  
Xue Jun Zhu ◽  
Mengchun Pan ◽  
Qi Zhang ◽  
Chengbiao Wan ◽  
...  
Keyword(s):  
Measurement System ◽  
Geomagnetic Field ◽  
Field Vector ◽  
Vector Measurement

Autonomous navigation algorithm based on AUKF filter about fusion of geomagnetic and sunlight directions

2018 ◽  
Vol 11 (4) ◽  
pp. 471-485 ◽  
Author(s):  
Bing Hua ◽  
Zhiwen Zhang ◽  
Yunhua Wu ◽  
Zhiming Chen
Keyword(s):  
Orbit Determination ◽  
Geomagnetic Field ◽  
Autonomous Navigation ◽  
Unscented Kalman Filter ◽  
Satellite Orbit ◽  
Field Vector ◽  
Low Earth Orbit ◽  
Fusion Algorithm ◽  
Content Type ◽  
Navigation Algorithm

Purpose The geomagnetic field vector is a function of the satellite’s position. The position and speed of the satellite can be determined by comparing the geomagnetic field vector measured by on board three-axis magnetometer with the standard value of the international geomagnetic field. The geomagnetic model has the disadvantages of uncertainty, low precision and long-term variability. Therefore, accuracy of autonomous navigation using the magnetometer is low. The purpose of this paper is to use the geomagnetic and sunlight information fusion algorithm to improve the orbit accuracy. Design/methodology/approach In this paper, an autonomous navigation method for low earth orbit satellite is studied by fusing geomagnetic and solar energy information. The algorithm selects the cosine value of the angle between the solar light vector and the geomagnetic vector, and the geomagnetic field intensity as observation. The Adaptive Unscented Kalman Filter (AUKF) filter is used to estimate the speed and position of the satellite, and the simulation research is carried out. This paper also made the same study using the UKF filter for comparison with the AUKF filter. Findings The algorithm of adding the sun direction vector information improves the positioning accuracy compared with the simple geomagnetic navigation, and the convergence and stability of the filter are better. The navigation error does not accumulate with time and has engineering application value. It also can be seen that AUKF filtering accuracy is better than UKF filtering accuracy. Research limitations/implications Geomagnetic navigation is greatly affected by the accuracy of magnetometer. This paper does not consider the spacecraft’s environmental interference with magnetic sensors. Practical implications Magnetometers and solar sensors are common sensors for micro-satellites. Near-Earth satellite orbit has abundant geomagnetic field resources. Therefore, the algorithm will have higher engineering significance in the practical application of low orbit micro-satellites orbit determination. Originality/value This paper introduces a satellite autonomous navigation algorithm. The AUKF geomagnetic filter algorithm using sunlight information can obviously improve the navigation accuracy and meet the basic requirements of low orbit small satellite orbit determination.

scholarly journals Correlation based snapshot models of the archeomagnetic field

2020 ◽  
Vol 223 (1) ◽  
pp. 648-665
Author(s):  
S Mauerberger ◽  
M Schanner ◽  
M Korte ◽  
M Holschneider
Keyword(s):  
Model Uncertainty ◽  
Geomagnetic Field ◽  
A Priori ◽  
Field Vector ◽  
Parametric Approach ◽  
Full Field ◽  
The Past ◽  
Uncertainty Estimates ◽  
Improved Model ◽  
Field Estimate

SUMMARY For the time stationary global geomagnetic field, a new modelling concept is presented. A Bayesian non-parametric approach provides realistic location dependent uncertainty estimates. Modelling related variabilities are dealt with systematically by making little subjective a priori assumptions. Rather than parametrizing the model by Gauss coefficients, a functional analytic approach is applied. The geomagnetic potential is assumed a Gaussian process to describe a distribution over functions. A priori correlations are given by an explicit kernel function with non-informative dipole contribution. A refined modelling strategy is proposed that accommodates non-linearities of archeomagnetic observables: First, a rough field estimate is obtained considering only sites that provide full field vector records. Subsequently, this estimate supports the linearization that incorporates the remaining incomplete records. The comparison of results for the archeomagnetic field over the past 1000 yr is in general agreement with previous models while improved model uncertainty estimates are provided.

scholarly journals Attitude Estimation of Underwater Vehicles Using Field Measurements and Bias Compensation

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 330 ◽  
Author(s):  
Nak Ko ◽  
Seokki Jeong ◽  
Suk-seung Hwang ◽  
Jae-Young Pyun
Keyword(s):  
Magnetic Field ◽  
Field Measurement ◽  
Field Measurements ◽  
Underwater Vehicle ◽  
Field Vector ◽  
Attitude Estimation ◽  
Magnetic Field Measurement ◽  
Euler Angles ◽  
Measured Field ◽  
The Magnetic Field

This paper proposes a method of estimating the attitude of an underwater vehicle. The proposed method uses two field measurements, namely, a gravitational field and a magnetic field represented in terms of vectors in three-dimensional space. In many existing methods that convert the measured field vectors into Euler angles, the yaw accuracy is affected by the uncertainty of the gravitational measurement and by the uncertainty of the magnetic field measurement. Additionally, previous methods have used the magnetic field measurement under the assumption that the magnetic field has only a horizontal component. The proposed method utilizes all field measurement components as they are, without converting them into Euler angles. The bias in the measured magnetic field vector is estimated and compensated to take full advantage of all measured field vector components. Because the proposed method deals with the measured field independently, uncertainties in the measured vectors affect the attitude estimation separately without adding up. The proposed method was tested by conducting navigation experiments with an unmanned underwater vehicle inside test tanks. The results were compared with those obtained by other methods, wherein the Euler angles converted from the measured field vectors were used as measurements.

A Composite Rigid Body Algorithm for Modeling and Simulation of an Underwater Vehicle Equipped With Manipulator Arms

2004 ◽  
Author(s):  
Mohammad Khalaj Amir Hosseini ◽  
Mohammad Banae ◽  
Ali Meghdari
Keyword(s):  
Rigid Body ◽  
Modeling And Simulation ◽  
Degrees Of Freedom ◽  
Oil And Gas ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Design Stage ◽  
Viscous Drag ◽  
Position Sensing ◽  
Drag Forces

In this paper modeling and simulation of an underwater vehicle equipped with manipulator arms, using Composite Rigid Body (CRB) algorithm will be discussed. Because of increasing need to Unmanned Underwater Vehicles (UUVs) in oil and gas projects in Persian Gulf, for doing operations such as inspection of offshore jackets, subsea pipelines and submarine cables and also pre installation survey and post laid survey of submarine pipelines and cables, design and construction of “SROV” was developed in Sharif University of Technology, and at design stage behavior of underwater vehicles was studied. In this paper, an efficient dynamic simulation algorithm is developed for an UUV equipped with m manipulators that each of them has N degrees of freedom. In addition to the effects of mobile base, the various hydrodynamic forces exerted on these systems in an underwater environment are also incorporated into the simulation. The effects modeled in this work are added mass, viscous drag, fluid acceleration, and buoyancy forces. For drag forces, the emphasis here is on the modeling of the pressure drag. Recent advances in underwater position and velocity sensing enable real-time centimeter-precision position measurements of underwater vehicles. With these advances in position sensing, our ability to precisely control the hovering and low-speed trajectory of an underwater vehicle is limited principally by our understanding of the vehicle’s dynamics and dynamics of the bladed thrusters commonly used to actuate dynamically-positioned marine vehicles. So the dynamics of thrusters, are developed, and an appropriate mapping matrix dependent on the position and orientation of the thrusters on the vehicle, is used to calculate resultant forces and moments of the thrusters on the center of gravity of the vehicle. It should be noted that hull-propeller and propeller-propeller interactions are considered in the modeling too. Finally the results of the simulations, for an underwater vehicle equipped with one 2 DOFs manipulator, are presented and discussed in details.

Sign in / Sign up

Export Citation Format

Share Document