Gyroscopy and Navigation最新文献

Optimization of Scientific Equipment Pointing at Survey Targets in the Uragan Experiment On Board the ISS 优化国际空间站上乌拉干实验中指向勘测目标的科学设备

Gyroscopy and Navigation Pub Date : 2024-03-23 DOI: 10.1134/s207510872470007x

M. Yu. Belyaev, P. A. Borovikhin, A. M. Esakov, D. Yu. Karavaev, I. V. Rasskazov

引用次数: 0

Current State and Development Prospects of Fiber-Optic Gyroscopes 光纤陀螺仪的现状和发展前景

Gyroscopy and Navigation Pub Date : 2024-03-23 DOI: 10.1134/s2075108724700019

E. V. Dranitsyna, D. A. Egorov, A. A. Untilov

引用次数: 0

Real-Time Visual-Inertial Odometry Based on Point-Line Feature Fusion 基于点-线特征融合的实时视觉惯性测距技术

Gyroscopy and Navigation Pub Date : 2024-03-23 DOI: 10.1134/s2075108724700068

G. Yang, W. D. Meng, G. D. Hou, N. N. Feng

{"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}

引用次数: 0

Maritime Cybersecurity. Navigational Aspect 海事网络安全。航行方面

Gyroscopy and Navigation Pub Date : 2024-03-23 DOI: 10.1134/s207510872470010x

B. S. Rivkin

引用次数: 0

SVD-Aided EKF for Nanosatellite Attitude Estimation Based on Kinematic and Dynamic Relations 基于运动学和动力学关系的 SVD 辅助 EKF 用于超小型卫星姿态估计

Gyroscopy and Navigation Pub Date : 2024-03-23 DOI: 10.1134/s2075108724700081

D. Cilden-Guler, Ch. Hajiyev

{"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}

引用次数: 0

Strapdown Inertial Navigation System Accuracy Improvement Methods Based on Inertial Measuring Unit Rotation: Analytical Review 基于惯性测量单元旋转的带下惯性导航系统精度改进方法：分析综述

Gyroscopy and Navigation Pub Date : 2024-03-23 DOI: 10.1134/s2075108724700020

E. V. Dranitsyna, A. I. Sokolov

{"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}

引用次数: 0

Identification of Motion Model Parameters for a Surface Ship under Disturbances 扰动下水面舰艇运动模型参数的识别

Gyroscopy and Navigation Pub Date : 2024-03-23 DOI: 10.1134/s2075108724700111

A. E. Pelevin

引用次数: 0

Gimballess Electrostatic Gyroscope with a Rotor without TiN Coating 带有无 TiN 涂层转子的无球静电陀螺仪

Gyroscopy and Navigation Pub Date : 2024-03-23 DOI: 10.1134/s2075108724700093

S. G. Romanenko, S. L. Levin, S. N. Fedorovich, A. Yu. Filippov, T. G. Leonova, A. A. Medvedkov

引用次数: 0

Use of Marine Gravimetric Survey Data for Correcting the Satellite Models of the Global Gravity Field in the World Ocean 利用海洋重力测量数据修正世界海洋全球重力场卫星模型

Gyroscopy and Navigation Pub Date : 2024-01-11 DOI: 10.1134/s2075108723030057

P. S. Mikhailov

引用次数: 0

Deep Learning-Based Inertial Navigation Technology for Autonomous Underwater Vehicle Long-Distance Navigation—A Review 基于深度学习的惯性导航技术在水下自主航行器远距离导航中的应用--综述

Gyroscopy and Navigation Pub Date : 2024-01-11 DOI: 10.1134/s2075108723030070

QinYuan He, HuaPeng Yu, YuChen Fang

{"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}

引用次数: 0