scholarly journals An Aided Navigation Method Based on Strapdown Gravity Gradiometer

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 829
Author(s):  
Duanyang Gao ◽  
Baiqing Hu ◽  
Lubin Chang ◽  
Fangjun Qin ◽  
Xu Lyu
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Unscented Kalman Filter ◽  
Inertial Navigation ◽  
Gravity Potential ◽  
Gravity Gradient ◽  
Gravity Gradiometer ◽  
Attitude Error ◽  
Small Change ◽  
Navigation Method

The gravity gradient is the second derivative of gravity potential. A gravity gradiometer can measure the small change of gravity at two points, which contains more abundant navigation and positioning information than gravity. In order to solve the problem of passive autonomous, long-voyage, and high-precision navigation and positioning of submarines, an aided navigation method based on strapdown gravity gradiometer is proposed. The unscented Kalman filter framework is used to realize the fusion of inertial navigation and gravity gradient information. The performance of aided navigation is analyzed and evaluated from six aspects: long voyage, measurement update period, measurement noise, database noise, initial error, and inertial navigation system device level. When the parameters are set according to the benchmark parameters and after about 10 h of simulation, the results show that the attitude error, velocity error, and position error of the gravity gradiometer aided navigation system are less than 1 arcmin, 0.1 m/s, and 33 m, respectively.

Ocean Vehicle Inertial Navigation Method based on Dynamic Constraints

2018 ◽  
Vol 71 (6) ◽  
pp. 1553-1566
Author(s):  
Jiazhen Lu ◽  
Lili Xie
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
External Support ◽  
External Information ◽  
Identification Algorithm ◽  
Dynamic Identification ◽  
Dynamic Constraints ◽  
Attitude Error ◽  
Navigation Method

This paper proposes a dynamic aided inertial navigation method to improve the attitude accuracy for ocean vehicles. The proposed method includes a dynamic identification algorithm and the utilisation of dynamic constraints to derive additional observations. The derived additional observations are used to update the filters and limit the attitude error based on the dynamic knowledge. In this paper, two dynamic conditions, constant speed cruise and quasi-static, are identified and corresponding additional velocity and position observations are derived. Simulation and experimental results show that the proposed method can improve and guarantee the accuracy of the attitude. The method can be used as a backup method to bridge external information outages or unavailability. Both the features of independence of external support and integrity of the Inertial Navigation System (INS) are enhanced.

The Design for Twelve-Accelerometer Gravity Gradiometer

2009 ◽  
Vol 419-420 ◽  
pp. 221-224
Author(s):  
Lin Zhao ◽  
Feng Ming Liu ◽  
Hai Jing Yuan ◽  
Hong Bin Zhao
Keyword(s):  
Angular Velocity ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Gravity Gradient ◽  
Gravity Gradiometer ◽  
Mathematical Relationship ◽  
New Type ◽  
Design And Manufacture

The design and manufacture for GGI are different and only several countries have the ability to produce it. Devising the feasible scheme for gravity gradiometer is the primary question.In this paper, a new type of GGI is designed using twelve accelerometers. First, the mathematical relationship between the accelerometer and GGI is derived and the method to separate the angular velocity and gravity gradient is disscussed. Second, the model of twelve-accelerometer gravity gradiometer is provided. Third, the estimation of angular velocity is analyzed when the GGI is installed in the form of strapdown or stabilized state. Finally, it is concluded that a new type of inertial navigation system using gravity gradiometers will be configured when it becomes possible to precisely measure gravity gradient.

Application of Improved Unscented Kalman Filter to AUV Based on Terrain-Aided Strapdown Inertial Navigation System

2013 ◽  
Vol 389 ◽  
pp. 758-764 ◽  
Author(s):  
Qi Wang ◽  
Dong Li ◽  
Zi Jia Zhang ◽  
Chang Song Yang
Keyword(s):  
Kalman Filter ◽  
Information Fusion ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Unscented Kalman Filter ◽  
Autonomous Underwater Vehicles ◽  
Inertial Navigation ◽  
Strapdown Inertial Navigation System ◽  
Integrated Navigation ◽  
Strapdown Inertial Navigation

To improve the navigation precision of autonomous underwater vehicles, a terrain-aided strapdown inertial navigation based on Improved Unscented Kalman Filter (IUKF) is proposed in this paper. The characteristics of strapdown inertial navigation system and terrain-aided navigation system are described in this paper, and improved UKF method is applied to the information fusion. Simulation experiments of novel integrated navigation system proposed in the paper were carried out comparing to the traditional Kalman filtering methods. The experiment results suggest that the IUKF method is able to greatly improve the long-time navigation precision, relative to the traditional information fusion method.

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.

scholarly journals Landmark-Based Inertial Navigation System for Autonomous Navigation of Missile Platform

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3083
Author(s):  
Donghui Lyu ◽  
Jiongqi Wang ◽  
Zhangming He ◽  
Yuyun Chen ◽  
Bowen Hou
Keyword(s):  
Navigation System ◽  
Autonomous Navigation ◽  
Inertial Navigation System ◽  
Attitude Determination ◽  
Inertial Navigation ◽  
Inertial System ◽  
New Information ◽  
System Output ◽  
Navigation Method ◽  
Navigation Scheme

As a new information provider of autonomous navigation, the on-orbit landmark observation offers a new means to improve the accuracy of autonomous positioning and attitude determination. A novel autonomous navigation method based on the landmark observation and the inertial system is designed to achieve the high-accuracy estimation of the missile platform state. In the proposed method, the navigation scheme is constructed first. The implicit observation equation about the deviation of the inertial system output is derived and the Kalman filter is applied to estimate the missile platform state. Moreover, the physical observability of the landmark and the mathematical observability of the navigation system are analyzed. Finally, advantages of the proposed autonomous navigation method are demonstrated through simulations compared with the traditional celestial-inertial navigation system and the deeply integrated celestial-inertial navigation system.

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