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首页> 外文期刊>Aerospace science and technology >Improved high-degree cubature Kalman filter based on resampling-free sigma-point update framework and its application for inertial navigation system-based integrated navigation
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Improved high-degree cubature Kalman filter based on resampling-free sigma-point update framework and its application for inertial navigation system-based integrated navigation

机译：基于重采样的Sigma-Point更新框架改进的高度Cubature Kalman滤波器及其应用于基于惯性导航系统的集成导航

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摘要

Sigma-point based Kalman filters have been widely applied to nonlinear filtering problems, where cubature Kalman filter (CKF) is considered to be an ideal solution to tightly coupled GNSS/INS. Different sigma-point update frameworks (SUFs) for CKF have been reported in our previous work, where instead of being abandoned after the moment matching, the instantiated points are used to approximate the likelihood function and update the posterior sigma points directly, which leads to a resampling-free SUF. By propagating more cubature points through the filtering model, the High-degree CKF (HCKF) achieves more accurate moments approximation result than CKF. In this paper, the performance of different SUFs for HCKF is analyzed by simulation on tightly coupled GNSS/INS, and observations missing during different maneuvers are simulated to evaluate the performance of resampling-free HCKF. The simulation result gives an insight into the uncertainty propagation in the two-stage update of Gaussian filter for GNSS/INS application. (C) 2021 Elsevier Masson SAS. All rights reserved.
机译：基于Sigma点的Kalman滤波器已被广泛应用于非线性滤波问题，其中Cubature Kalman滤波器（CKF）被认为是紧密耦合GNSS / INS的理想解决方案。在我们以前的工作中报告了CKF的不同Sigma-Point更新框架（SUF），而不是在匹配的那一刻之后被放弃，所实例化的点用于近似似然函数并直接更新后Σ点，这导致自由求采样的suf。通过通过滤波模型传播更多的Cubature点，高度CKF（HCKF）比CKF实现更准确的时刻近似结果。在本文中，通过对紧密耦合的GNSS / INS模拟进行了分析了HCKF的不同SUF的性能，并且模拟了不同机动期间缺失的观察以评估自由采样的HCKF的性能。仿真结果对GNSS / INS应用的高斯滤波器的两级更新中的不确定性传播提供了深度识别。 （c）2021 Elsevier Masson SAS。版权所有。

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  • 来源
    《Aerospace science and technology》 |2021年第10期|106905.1-106905.11|共11页
  • 作者

    Cui Bingbo; Wei Xinhua; Chen Xiyuan; Wang Aichen;

  • 作者单位

    Jiangsu Univ Key Lab Modern Agr & Technol Minist Educ & Jiangsu Prov Zhenjiang 212013 Jiangsu Peoples R China;

    Jiangsu Univ Key Lab Modern Agr & Technol Minist Educ & Jiangsu Prov Zhenjiang 212013 Jiangsu Peoples R China;

    Southeast Univ Sch Instrument Sci & Engn Key Lab Microinertial Instrument & Adv Nav Techno Minist Educ Nanjing 210096 Peoples R China;

    Jiangsu Univ Key Lab Modern Agr & Technol Minist Educ & Jiangsu Prov Zhenjiang 212013 Jiangsu Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Aerial vehicle navigation; Cubature Kalman filter; Sigma-point update framework; Tight GNSS/INS;

    机译：空中车辆导航;Cubature Kalman滤波器;Sigma点更新框架;紧密GNSS / INS;

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