Pub Date : 2024-03-23DOI: 10.1134/s207510872470007x
M. Yu. Belyaev, P. A. Borovikhin, A. M. Esakov, D. Yu. Karavaev, I. V. Rasskazov
Abstract
The aim of the Uragan space experiment on board the International Space Station (ISS) is to adjust the scientific equipment and improve the methods for monitoring various objects and phenomena on the Earth. Part of this scientific equipment is already operated on board the station, and the other part is planned to be delivered in the orbit soon. In contrast to the Russian orbital stations Salyut and Mir, the ISS was not designed for pointing the installed equipment at the survey targets, because the gyrodines used on the American segment for the ISS attitude control had a too small kinematic momentum. For this reason, special methods and devices had to be developed for pointing the Uragan scientific equipment at the survey targets. This paper considers the methods for pointing the scientific equipment, which would optimize the research program of the Uragan experiment on board the ISS.
{"title":"Optimization of Scientific Equipment Pointing at Survey Targets in the Uragan Experiment On Board the ISS","authors":"M. Yu. Belyaev, P. A. Borovikhin, A. M. Esakov, D. Yu. Karavaev, I. V. Rasskazov","doi":"10.1134/s207510872470007x","DOIUrl":"https://doi.org/10.1134/s207510872470007x","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The aim of the Uragan space experiment on board the International Space Station (ISS) is to adjust the scientific equipment and improve the methods for monitoring various objects and phenomena on the Earth. Part of this scientific equipment is already operated on board the station, and the other part is planned to be delivered in the orbit soon. In contrast to the Russian orbital stations Salyut and Mir, the ISS was not designed for pointing the installed equipment at the survey targets, because the gyrodines used on the American segment for the ISS attitude control had a too small kinematic momentum. For this reason, special methods and devices had to be developed for pointing the Uragan scientific equipment at the survey targets. This paper considers the methods for pointing the scientific equipment, which would optimize the research program of the Uragan experiment on board the ISS.</p>","PeriodicalId":38999,"journal":{"name":"Gyroscopy and Navigation","volume":"103 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140203432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-23DOI: 10.1134/s2075108724700019
E. V. Dranitsyna, D. A. Egorov, A. A. Untilov
Abstract—
The paper describes the current state of fiber-optic gyroscope (FOG) development. An overview of the modern gyroscopic market for inertial navigation is made with a special focus on the FOG niche. The principle of operation is briefly described; classification of existing FOGs is presented; their advantages and disadvantages are discussed; and some examples are given. Key Russian and international manufacturers are mentioned in the paper. Finally, trends of FOG development are analyzed, and the future development of the gyroscope market is assessed.
摘要-本文介绍了光纤陀螺仪（FOG）的发展现状。文章概述了用于惯性导航的现代陀螺仪市场，并特别关注 FOG 细分市场。文中简要介绍了光纤陀螺仪的工作原理，对现有光纤陀螺仪进行了分类，讨论了其优缺点，并列举了一些实例。文中提到了俄罗斯和国际主要制造商。最后，分析了 FOG 的发展趋势，并对陀螺仪市场的未来发展进行了评估。
{"title":"Current State and Development Prospects of Fiber-Optic Gyroscopes","authors":"E. V. Dranitsyna, D. A. Egorov, A. A. Untilov","doi":"10.1134/s2075108724700019","DOIUrl":"https://doi.org/10.1134/s2075108724700019","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract—</h3><p>The paper describes the current state of fiber-optic gyroscope (FOG) development. An overview of the modern gyroscopic market for inertial navigation is made with a special focus on the FOG niche. The principle of operation is briefly described; classification of existing FOGs is presented; their advantages and disadvantages are discussed; and some examples are given. Key Russian and international manufacturers are mentioned in the paper. Finally, trends of FOG development are analyzed, and the future development of the gyroscope market is assessed.</p>","PeriodicalId":38999,"journal":{"name":"Gyroscopy and Navigation","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140203232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-23DOI: 10.1134/s2075108724700068
G. Yang, W. D. Meng, G. D. Hou, N. N. Feng
Abstract
To improve the localization accuracy and tracking robustness of monocular feature-based visual SLAM systems in low-texture environments, a visual-inertial odometry method combining line features and point features is proposed, taking advantage of the easy availability of line features in real-world environments and the high accuracy of feature-based methods. The combination of point and line features ensures accurate positioning of the SLAM system in low-texture environments, while the inclusion of IMU data provides prior information and scale information. The pose is optimized by minimizing the reprojection error of point and line features and the IMU error using bundle adjustment. An improved EDlines algorithm is introduced, which incorporates a pixel chain length suppression process to enhance the effectiveness of extracted line features and reduce the rate of line feature misalignment. Experimental results on the public EuRoC dataset and TUM RGB-D dataset show that the proposed method meets the real-time requirements and has higher localization accuracy and robustness compared with the visual SLAM method based on single point feature or the method adding traditional line features.
摘要 为了提高基于单目特征的视觉 SLAM 系统在低纹理环境中的定位精度和跟踪鲁棒性，我们提出了一种结合线特征和点特征的视觉惯性里程测量方法，利用了线特征在真实世界环境中的易得性和基于特征方法的高精度。点特征和线特征的结合确保了 SLAM 系统在低纹理环境中的精确定位，而 IMU 数据的加入则提供了先验信息和比例信息。通过最小化点和线特征的重投影误差以及使用捆绑调整的 IMU 误差来优化姿势。此外，还引入了一种改进的 EDlines 算法，其中包含一个像素链长抑制过程，以提高提取线特征的效果并降低线特征错位率。在公开的 EuRoC 数据集和 TUM RGB-D 数据集上的实验结果表明，与基于单点特征的视觉 SLAM 方法或添加传统线特征的方法相比，所提出的方法满足实时性要求，并具有更高的定位精度和鲁棒性。
{"title":"Real-Time Visual-Inertial Odometry Based on Point-Line Feature Fusion","authors":"G. Yang, W. D. Meng, G. D. Hou, N. N. Feng","doi":"10.1134/s2075108724700068","DOIUrl":"https://doi.org/10.1134/s2075108724700068","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>To improve the localization accuracy and tracking robustness of monocular feature-based visual SLAM systems in low-texture environments, a visual-inertial odometry method combining line features and point features is proposed, taking advantage of the easy availability of line features in real-world environments and the high accuracy of feature-based methods. The combination of point and line features ensures accurate positioning of the SLAM system in low-texture environments, while the inclusion of IMU data provides prior information and scale information. The pose is optimized by minimizing the reprojection error of point and line features and the IMU error using bundle adjustment. An improved EDlines algorithm is introduced, which incorporates a pixel chain length suppression process to enhance the effectiveness of extracted line features and reduce the rate of line feature misalignment. Experimental results on the public EuRoC dataset and TUM RGB-D dataset show that the proposed method meets the real-time requirements and has higher localization accuracy and robustness compared with the visual SLAM method based on single point feature or the method adding traditional line features.</p>","PeriodicalId":38999,"journal":{"name":"Gyroscopy and Navigation","volume":"293 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140203321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-23DOI: 10.1134/s207510872470010x
B. S. Rivkin
Abstract
This article is a review of publications on maritime cybersecurity with the focus made on navigation support. Cyber threats to electronic chart display and information system (ECDIS), automatic identification system (AIS), voyage data recorder (VDR), and integrated navigation system (INS) as a whole are considered. The specific features of cybersecurity of maritime autonomous surface ships (MASS) as well as the impact of the human factor on cybersecurity are discussed, and the regulatory framework for preventing cyber threats is analyzed.
{"title":"Maritime Cybersecurity. Navigational Aspect","authors":"B. S. Rivkin","doi":"10.1134/s207510872470010x","DOIUrl":"https://doi.org/10.1134/s207510872470010x","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>This article is a review of publications on maritime cybersecurity with the focus made on navigation support. Cyber threats to electronic chart display and information system (ECDIS), automatic identification system (AIS), voyage data recorder (VDR), and integrated navigation system (INS) as a whole are considered. The specific features of cybersecurity of maritime autonomous surface ships (MASS) as well as the impact of the human factor on cybersecurity are discussed, and the regulatory framework for preventing cyber threats is analyzed.</p>","PeriodicalId":38999,"journal":{"name":"Gyroscopy and Navigation","volume":"72 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140203315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-23DOI: 10.1134/s2075108724700081
D. Cilden-Guler, Ch. Hajiyev
Abstract
Small satellite attitude angles are estimated using measurements of star trackers and rate gyros in this study. The issue related to gyro drifts is overcome by adding the bias terms into the state vector in order to estimate them. As an estimation method, two-stage non-traditional filter is used. In the first stage, singular value decomposition (SVD) is used for determining the attitude measurements. As a second stage, an extended Kalman filter (EKF) is designed based on linear attitude measurements. These two stages are integrated for the whole estimation algorithm in order to have estimations with high accuracy, and it is called SVD-Aided EKF. The proposed SVD-Aided EKF is used with two attitude models of satellite: only the kinematics model which does not include the dynamics of a satellite, and both kinematics and dynamics relations. Several scales of uncertainties on the principal moment of inertia of the satellite are considered in order to determine the level when estimation error of the kinematics and dynamics-based filter exceeds the error of the case using only kinematics relations.
{"title":"SVD-Aided EKF for Nanosatellite Attitude Estimation Based on Kinematic and Dynamic Relations","authors":"D. Cilden-Guler, Ch. Hajiyev","doi":"10.1134/s2075108724700081","DOIUrl":"https://doi.org/10.1134/s2075108724700081","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Small satellite attitude angles are estimated using measurements of star trackers and rate gyros in this study. The issue related to gyro drifts is overcome by adding the bias terms into the state vector in order to estimate them. As an estimation method, two-stage non-traditional filter is used. In the first stage, singular value decomposition (SVD) is used for determining the attitude measurements. As a second stage, an extended Kalman filter (EKF) is designed based on linear attitude measurements. These two stages are integrated for the whole estimation algorithm in order to have estimations with high accuracy, and it is called SVD-Aided EKF. The proposed SVD-Aided EKF is used with two attitude models of satellite: only the kinematics model which does not include the dynamics of a satellite, and both kinematics and dynamics relations. Several scales of uncertainties on the principal moment of inertia of the satellite are considered in order to determine the level when estimation error of the kinematics and dynamics-based filter exceeds the error of the case using only kinematics relations.</p>","PeriodicalId":38999,"journal":{"name":"Gyroscopy and Navigation","volume":"87 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140203318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-23DOI: 10.1134/s2075108724700020
E. V. Dranitsyna, A. I. Sokolov
Abstract
The paper presents the analytical review of an inertial measuring unit (IMU) rotation as a method to improve the accuracy of a strapdown inertial navigation system (SINS). There are two ways to improve the accuracy. One of them is based on the transformation of the error change pattern in the inertial sensors (IS) when using the IMU self-compensation rotation (SCR). The criteria for selecting an efficient SCR law to minimize the accumulated error in the parameters generated by SINS are presented. Along with the advantages of this technology, its weak points that may limit significantly the potentially achievable IMU accuracy are described. The other technique consists in increasing the observability of the IS error model components due to the IMU rotation while filtering the SINS errors. The IS error model is described, and the problem of recursive filtering of the SINS errors is stated to refine these errors, with the reference data on coordinates and motion velocity being available. The methods for quantifying the observability of the IS error model components are presented.
摘要 本文对惯性测量单元（IMU）旋转作为提高带式惯性导航系统（SINS）精度的一种方法进行了分析评述。提高精度有两种方法。其中一种是基于使用惯性测量单元自补偿旋转（SCR）时惯性传感器（IS）误差变化规律的转换。本文介绍了选择有效 SCR 法则的标准，以尽量减少 SINS 产生的参数累积误差。除了这项技术的优点之外，还介绍了它的弱点，这些弱点可能会大大限制 IMU 可能达到的精度。另一种技术是在过滤 SINS 误差的同时，增加 IMU 旋转导致的 IS 误差模型成分的可观测性。对 IS 误差模型进行了描述，并阐述了 SINS 误差的递归过滤问题，以便在坐标和运动速度参考数据可用的情况下完善这些误差。介绍了量化 IS 误差模型各组成部分可观测性的方法。
{"title":"Strapdown Inertial Navigation System Accuracy Improvement Methods Based on Inertial Measuring Unit Rotation: Analytical Review","authors":"E. V. Dranitsyna, A. I. Sokolov","doi":"10.1134/s2075108724700020","DOIUrl":"https://doi.org/10.1134/s2075108724700020","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The paper presents the analytical review of an inertial measuring unit (IMU) rotation as a method to improve the accuracy of a strapdown inertial navigation system (SINS). There are two ways to improve the accuracy. One of them is based on the transformation of the error change pattern in the inertial sensors (IS) when using the IMU self-compensation rotation (SCR). The criteria for selecting an efficient SCR law to minimize the accumulated error in the parameters generated by SINS are presented. Along with the advantages of this technology, its weak points that may limit significantly the potentially achievable IMU accuracy are described. The other technique consists in increasing the observability of the IS error model components due to the IMU rotation while filtering the SINS errors. The IS error model is described, and the problem of recursive filtering of the SINS errors is stated to refine these errors, with the reference data on coordinates and motion velocity being available. The methods for quantifying the observability of the IS error model components are presented<i>.</i></p>","PeriodicalId":38999,"journal":{"name":"Gyroscopy and Navigation","volume":"67 3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140203322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-23DOI: 10.1134/s2075108724700111
A. E. Pelevin
Abstract
An approach to identifying the parameters of the motion model for a surface ship subject to external disturbances is proposed. It uses the measurements of heading, yaw rate, speed through the water, and global satellite navigation system (GNSS) data. The model structure is set in the state space. We use the criterion of how close is the real vehicle response to a given control input to its motion model response under the same disturbances. It is proposed to apply the Kalman filter with the state vector including the disturbances, and an iterated procedure for estimating parameters by minimizing the criterion. It is shown that this ensures stable identification of model parameters under different disturbances. Simulation results are presented to evaluate the quality of identification. The approach was validated in full-scale tests of a high-speed boat.
{"title":"Identification of Motion Model Parameters for a Surface Ship under Disturbances","authors":"A. E. Pelevin","doi":"10.1134/s2075108724700111","DOIUrl":"https://doi.org/10.1134/s2075108724700111","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>An approach to identifying the parameters of the motion model for a surface ship subject to external disturbances is proposed. It uses the measurements of heading, yaw rate, speed through the water, and global satellite navigation system (GNSS) data. The model structure is set in the state space. We use the criterion of how close is the real vehicle response to a given control input to its motion model response under the same disturbances. It is proposed to apply the Kalman filter with the state vector including the disturbances, and an iterated procedure for estimating parameters by minimizing the criterion. It is shown that this ensures stable identification of model parameters under different disturbances. Simulation results are presented to evaluate the quality of identification. The approach was validated in full-scale tests of a high-speed boat.</p>","PeriodicalId":38999,"journal":{"name":"Gyroscopy and Navigation","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140203320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-23DOI: 10.1134/s2075108724700093
S. G. Romanenko, S. L. Levin, S. N. Fedorovich, A. Yu. Filippov, T. G. Leonova, A. A. Medvedkov
Abstract
The article compares the test results for gimballess electrostatic gyroscopes containing rotors with a light-contrast pattern applied to titanium nitride (TiN) coating or to beryllium. The criteria for comparing the devices with different types of rotors are proposed and justified. The need to modify the rotor manufacturing technology in order to improve the rotor design and mature some technological operations is analyzed. It has been shown that at a certain stage it is rational to mark the raster pattern on the titanium nitride coating, and currently the pattern can be again applied directly to the rotor beryllium surface.
{"title":"Gimballess Electrostatic Gyroscope with a Rotor without TiN Coating","authors":"S. G. Romanenko, S. L. Levin, S. N. Fedorovich, A. Yu. Filippov, T. G. Leonova, A. A. Medvedkov","doi":"10.1134/s2075108724700093","DOIUrl":"https://doi.org/10.1134/s2075108724700093","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The article compares the test results for gimballess electrostatic gyroscopes containing rotors with a light-contrast pattern applied to titanium nitride (TiN) coating or to beryllium. The criteria for comparing the devices with different types of rotors are proposed and justified. The need to modify the rotor manufacturing technology in order to improve the rotor design and mature some technological operations is analyzed. It has been shown that at a certain stage it is rational to mark the raster pattern on the titanium nitride coating, and currently the pattern can be again applied directly to the rotor beryllium surface.</p>","PeriodicalId":38999,"journal":{"name":"Gyroscopy and Navigation","volume":"293 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140203433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-11DOI: 10.1134/s2075108723030057
P. S. Mikhailov
Abstract—
The article studies the possibilities of using the high-precision marine gravimetric survey data to correct the global models of the Earth’s gravity field in the World Ocean. The accuracy of modern models in water areas on a regional scale is determined by the capabilities of the satellite altimetry method and depends on the gravity field characteristics. On the gradient structures of the field, the amplitudes of real anomalies are suppressed in the models; therefore, for the models to be used more efficiently, it is necessary to restore high frequencies of anomalies in these models. On the abyssal structures, the main error in models is high-frequency noise. This paper describes the techniques for correcting the data obtained from these models, which makes it possible to increase the accuracy over fairly large areas, using a limited number of marine gravimetric measurements. The paper also provides the practical assessments of the new global altimetry model of the Earth’s gravity field Sandwell and Smith v.32 in various regions of the World Ocean.
摘要--文章研究了利用高精度海洋重力测量数据修正世界海洋地球重力场全球模型的可能性。区域尺度水域现代模型的精度取决于卫星测高方法的能力和重力场特征。在重力场的梯度结构中，实际异常的振幅在模型中被抑制；因此，为了更有效地利用模型，有必要在这些模型中恢复高频异常。在深海结构中，模型的主要误差是高频噪声。本文介绍了对从这些模型中获得的数据进行修正的技术，这使得利用有限的海洋重力测量数据提高相当大面积的精度成为可能。本文还对新的全球地球重力场测高模型 Sandwell 和 Smith v.32 在世界海洋各区域的实际应用情况进行了评估。
{"title":"Use of Marine Gravimetric Survey Data for Correcting the Satellite Models of the Global Gravity Field in the World Ocean","authors":"P. S. Mikhailov","doi":"10.1134/s2075108723030057","DOIUrl":"https://doi.org/10.1134/s2075108723030057","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract—</h3><p>The article studies the possibilities of using the high-precision marine gravimetric survey data to correct the global models of the Earth’s gravity field in the World Ocean. The accuracy of modern models in water areas on a regional scale is determined by the capabilities of the satellite altimetry method and depends on the gravity field characteristics. On the gradient structures of the field, the amplitudes of real anomalies are suppressed in the models; therefore, for the models to be used more efficiently, it is necessary to restore high frequencies of anomalies in these models. On the abyssal structures, the main error in models is high-frequency noise. This paper describes the techniques for correcting the data obtained from these models, which makes it possible to increase the accuracy over fairly large areas, using a limited number of marine gravimetric measurements. The paper also provides the practical assessments of the new global altimetry model of the Earth’s gravity field Sandwell and Smith v.32 in various regions of the World Ocean.</p>","PeriodicalId":38999,"journal":{"name":"Gyroscopy and Navigation","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139460190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-11DOI: 10.1134/s2075108723030070
QinYuan He, HuaPeng Yu, YuChen Fang
Abstract
Autonomous navigation technology is the key technology for Autonomous Underwater Vehicle (AUV) to achieve automated, intelligent operation and task processing. Inertial navigation technology is the core of autonomous navigation technology for AUV. Traditional inertial navigation technology has been developed for many years, and it is necessary to find new breakthroughs. Deep learning can automatically select and extract key features of input data, which has been widely used in image recognition, speech recognition, natural language processing and other fields, and has good results in processing sequential data such as text and speech. Inertial navigation data clearly belongs to this type of data, and many scholars in the industry have conducted related research and design, and found that deep neural network models can be used to calibrate the noise of inertial sensors, reduce the drift of inertial navigation mechanisms, and fuse inertial information with other sensor information, with good effects in solving the prediction and error suppression of inertial navigation during long-term underwater voyages. This article provides a comprehensive review of deep learning-based inertial navigation for AUV, including the latest research progress and development trend direction.
{"title":"Deep Learning-Based Inertial Navigation Technology for Autonomous Underwater Vehicle Long-Distance Navigation—A Review","authors":"QinYuan He, HuaPeng Yu, YuChen Fang","doi":"10.1134/s2075108723030070","DOIUrl":"https://doi.org/10.1134/s2075108723030070","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Autonomous navigation technology is the key technology for Autonomous Underwater Vehicle (AUV) to achieve automated, intelligent operation and task processing. Inertial navigation technology is the core of autonomous navigation technology for AUV. Traditional inertial navigation technology has been developed for many years, and it is necessary to find new breakthroughs. Deep learning can automatically select and extract key features of input data, which has been widely used in image recognition, speech recognition, natural language processing and other fields, and has good results in processing sequential data such as text and speech. Inertial navigation data clearly belongs to this type of data, and many scholars in the industry have conducted related research and design, and found that deep neural network models can be used to calibrate the noise of inertial sensors, reduce the drift of inertial navigation mechanisms, and fuse inertial information with other sensor information, with good effects in solving the prediction and error suppression of inertial navigation during long-term underwater voyages. This article provides a comprehensive review of deep learning-based inertial navigation for AUV, including the latest research progress and development trend direction.</p>","PeriodicalId":38999,"journal":{"name":"Gyroscopy and Navigation","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139460307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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