基于EKF和UKF的GNSS信号处理用于固定用户位置估计

Mert Sever, C. Hajiyev
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引用次数: 1

摘要

状态向量的精确估计是定位过程中的一个重要环节。本文采用扩展卡尔曼滤波(EKF)和Unscented卡尔曼滤波(UKF)对静止用户进行滤波,在地心惯性(ECI)坐标系下定义状态向量,并结合GNSS测量数据。它的目的是用方法进行估计。对EKF和UKF两种方法进行了比较。本文研究了非线性运动分析和线性化方法对状态向量估计的影响。通过本研究,对许多移动平台的具体任务所需的定位信息进行了估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GNSS Signal Processing with EKF and UKF for Stationary User Position Estimation
Precise and accurate estimation of state vectors is an important process during position determination. In this study, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) of stationary user, state vectors defined in Earth Centered Inertial (ECI) coordinate system, accompanied by GNSS measurement data. It is aimed to make estimations with methods. EKF and UKF methods were compared with each other. In this study, the effects of nonlinear motion analysis and linearization methods on state vector estimations were investigated. Thanks to this study, estimations of the positioning information required during the specific tasks of many moving platforms have been made.
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