Analysis of the Extended Kalman Filter's Role in Oceanic Science

被引:0
作者
Obaideen, Khaled [1 ]
AlShabi, Mohammad [2 ]
Bonny, Talal [3 ]
机构
[1] RISE, Smart Automat & Commun Technol, BioSensing & BioSensors Grp, Sharjah, U Arab Emirates
[2] Univ Sharjah, Dept Mech & Nucl Engn, Sharjah, U Arab Emirates
[3] Univ Sharjah, Dept Comp Engn, Sharjah, U Arab Emirates
来源
OCEAN SENSING AND MONITORING XVI | 2024年 / 13061卷
关键词
Extended Kalman Filter; Kalman Filter; Oceanic Science; bibliometric; TIGHTLY-COUPLED NAVIGATION; GPS POSITION ESTIMATION; CUBATURE KALMAN; ROBOT LOCALIZATION; DATA-ASSIMILATION; HYBRID; FUSION; FORECASTS; GPS/INS; CALIBRATION;
D O I
10.1117/12.3013854
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study delves into the Extended Kalman Filter's (EKF) use in ocean science through a detailed bibliometric and text mining examination. Tracing its roots back to the original Kalman Filter from the 1960s, the EKF has become crucial for managing nonlinear dynamics, especially in oceanography. Our analysis, drawing from Scopus data covering 1980-2023, delivers an extensive overview of the EKF's growth, applications, and cross-disciplinary influence in this area. We employed sophisticated bibliometric methods, including Biblioshiny, and text mining approaches via VOSviewer to dissect trends, and thematic groupings in EKF-related ocean science research. The results demonstrate a steady increase in EKF applications, particularly in autonomous underwater vehicle navigation, forecasting ocean currents, and modeling marine ecosystems. The bibliometric findings show its broad interdisciplinary appeal, while the text analysis underscores the EKF's integration with cutting-edge computational techniques and its significance in burgeoning oceanographic technologies. The paper highlights the EKF's indispensable role in ocean science, reflecting its historical importance and versatility in addressing contemporary challenges in marine technology. The study not only sheds light on the EKF's historical and current uses but also suggests potential future directions for research and innovation. It aims to offer crucial insights to researchers, academicians, and policy makers, underlining the EKF's significance in the dynamic, ever-changing realm of ocean science.
引用
收藏
页数:9
相关论文
共 118 条
  • [1] Reflection on Ramadan Fasting Research Related to Sustainable Development Goal 3 (Good Health and Well-Being): A Bibliometric Analysis
    Abushihab, Katia
    Obaideen, Khaled
    Alameddine, Mohamad
    Alkurd, Refat Ahmad Fawzi
    Khraiwesh, Husam M.
    Mohammad, Yara
    Abdelrahim, Dana N.
    Madkour, Mohamed I.
    Faris, MoezAlIslam E.
    [J]. JOURNAL OF RELIGION & HEALTH, 2024, 63 (05) : 3329 - 3359
  • [2] Short-term electric load forecasting based on Kalman filtering algorithm with moving window weather and load model
    Al-Hamadi, HM
    Soliman, SA
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2004, 68 (01) : 47 - 59
  • [3] Kalman filtering strategies utilizing the chattering effects of the smooth variable structure filter
    Al-Shabi, M.
    Gadsden, S. A.
    Habibi, S. R.
    [J]. SIGNAL PROCESSING, 2013, 93 (02) : 420 - 431
  • [4] Al-Shabi M., 2011 IEEE JORD C APP, P1
  • [5] Al-Shabi M., 2015, SPIE, V9474, P464
  • [6] Al-Shabi M, 2017, 2017 IEEE 5TH INTERNATIONAL SYMPOSIUM ON ROBOTICS AND INTELLIGENT SENSORS (IRIS), P117, DOI 10.1109/IRIS.2017.8250108
  • [7] Al-Shabi M, 2017, INT CONF MODEL SIM
  • [8] Al-Shabi M, 2015, 2015 IEEE 12TH INTERNATIONAL MULTI-CONFERENCE ON SYSTEMS, SIGNALS & DEVICES (SSD)
  • [9] AlMallahi M., 2024, Energy Harvesting and Storage: Materials, Devices, and Applications XIII, V2513, P113
  • [10] Intelligent estimation: A review of theory, applications, and recent advances
    Alsadi, Naseem
    Gadsden, S. Andrew
    Yawney, John
    [J]. DIGITAL SIGNAL PROCESSING, 2023, 135