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OTHR multitarget tracking with a GMRF model of ionospheric parameters

机译:OTHR MultiTarget跟踪电离层参数的GMRF模型

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摘要

The ionosphere is the propagation medium for radio waves transmitted by an over-the-horizon radar (OTHR). Ionospheric parameters, typically, virtual ionospheric heights (VIHs), are required to perform coordinate registration for OTHR multitarget tracking and localization. The inaccuracy of ionospheric parameters has a significant deleterious effect on the target localization of OTHR. Therefore, to improve the localization accuracy of OTHR, it is important to develop accurate models and estimation methods of ionospheric parameters and the corresponding target tracking algorithms. In this paper, we consider the variation of the ionosphere with location and the spatial correlation of the ionosphere. We use a Gaussian Markov random field (GMRF) to model the VIHs, providing a more accurate representation of the VIHs for OTHR target tracking. Based on expectation-conditional maximization and GMRF modeling of the VIHs, we propose a novel joint optimization solution, namely ECM-GMRF, to perform target state estimation, multipath data association and VIHs estimation simultaneously. In ECM-GMRF, the measurements from both ionosondes and OTHR are exploited to estimate the VIHs, leading to a better estimation of the VIHs which improves the accuracy of data association and target state estimation, and vice versa. The simulation indicates the effectiveness of the proposed algorithm.
机译:电离层是由过度地平线雷达(OTHR)传输的无线电波的传播介质。通常需要电离层参数,通常需要虚拟电离层高度(VIHS),以便对OTHR Multitget跟踪和本地化进行坐标注册。电离层参数的不准确性对OTHR的目标定位具有显着的有害影响。因此,为了提高OTHR的本地化精度,重要的是开发电离层参数的准确模型和估计方法和相应的目标跟踪算法。在本文中,我们考虑与电离层的位置和空间相关的电离层的变化。我们使用高斯Markov随机字段(GMRF)来模拟VIHS,为OTHR目标跟踪提供更准确的VIHS表示。基于VIHS的期望条件最大化和GMRF建模,我们提出了一种新颖的联合优化解决方案,即ECM-GMRF,同时执行目标状态估计,多径数据关联和VIHS估计。在ECM-GMRF中,利用IONOSONDES和OTHR的测量来利用估计VIHS,从而更好地估计VIH,这提高了数据关联和目标状态估计的准确性,反之亦然。模拟表明所提出的算法的有效性。

著录项

  • 来源
    《Signal processing》 |2021年第5期|107940.1-107940.17|共17页
  • 作者单位

    School of Automation Northwestern Polytechnical University Xi'an Shaanxi 710072 China Key Laboratory of Information Fusion Technology Ministry of Education Xi'an Shaanxi 710072 China;

    School of Automation Northwestern Polytechnical University Xi'an Shaanxi 710072 China Key Laboratory of Information Fusion Technology Ministry of Education Xi'an Shaanxi 710072 China Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft 2826 CD the Netherlands;

    School of Automation Northwestern Polytechnical University Xi'an Shaanxi 710072 China Key Laboratory of Information Fusion Technology Ministry of Education Xi'an Shaanxi 710072 China;

    School of Automation Northwestern Polytechnical University Xi'an Shaanxi 710072 China Key Laboratory of Information Fusion Technology Ministry of Education Xi'an Shaanxi 710072 China;

    Nanjing Research Institute of Electronics Technology Nanjing Jiangsu 210039 China Sky-Rainbow United Laboratory Nanjing Jiangsu 210039 China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Target tracking; Over-the-horizon radar; Expectation-conditional maximization; Gaussian Markov random field;

    机译:目标跟踪;超越地平线雷达;期望 - 条件最大化;高斯马尔可夫随意字段;

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