Multicorrelator signal tracking and signal quality monitoring for GNSS with extended Kalman filter

Andreas Iliopoulos, C. Enneking, Omar García Crespillo, T. Jost, S. Thoelert, F. Antreich
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引用次数: 4

Abstract

GNSS signals may present anomalies that degrade the positioning performance of GNSS receivers. Signal Quality Monitoring (SQM) is normally used to detect and to characterize these anomalies. This is required for the GNSS operators and integrity services to determine when a satellite should be considered as faulty and draw conclusions about the type of the fault. In this paper, we present a new SQM algorithm that tracks the GNSS signal and possible channel deformations by using a novel methodology based on the Extended Kalman Filter (EKF). The EKF is designed such that the measurement update is performed in post-correlation and using multiple correlators. After the estimation of the channel response, we add a detection step to determine if the channel deviates from the nominal signal transmission scenario (i.e., the single path propagation). Results suggests that the performance of the delay estimation with the proposed EKF structure outperforms the classical Delay-Locked-Loop (DLL) estimation, especially in the presence of distortions. Furthermore, it can reliably detect anomalous signal deformations as specified by ICAO threat model.
基于扩展卡尔曼滤波的GNSS多相关器信号跟踪与信号质量监测
GNSS信号可能出现异常,从而降低GNSS接收机的定位性能。信号质量监测(SQM)通常用于检测和表征这些异常。这是GNSS运营商和完整性服务确定何时应将卫星视为故障并得出有关故障类型的结论所必需的。在本文中,我们提出了一种新的SQM算法,该算法通过使用基于扩展卡尔曼滤波器(EKF)的新方法来跟踪GNSS信号和可能的信道变形。EKF的设计使得测量更新是在后相关和使用多个相关器进行的。在估计了信道响应之后,我们增加了一个检测步骤来确定信道是否偏离了标称信号传输场景(即单路径传播)。结果表明,该EKF结构的延迟估计性能优于经典的延迟锁环(DLL)估计,特别是在存在失真的情况下。此外,它还能可靠地检测到ICAO威胁模型规定的异常信号变形。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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