基于XANV/ gnss的鲁棒滤波组合导航

Yang Zhou, Panlong Wu, Xingxiu Li
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引用次数: 1

摘要

为了提高卫星定轨精度,提出了基于x射线脉冲星导航(XNAV)/全球导航卫星系统(GNSS)的组合导航方案。提出了一种全局最优滤波算法鲁棒联邦扩展卡尔曼滤波(RFEKF)来实现数据融合。该算法采用测量噪声尺度因子自适应扩展卡尔曼滤波(EKF)作为局部滤波,降低了测量故障的影响,增强了定轨系统的鲁棒性。故障检测采用基于残差卡方检验的统计阈值检测方案。仿真结果验证了RFEKF算法在测量故障情况下的有效性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
XANV/GNSS-Based Integrated Navigation Using a Robust Filtering Algorithm
In order to improve the satellite orbit determination accuracy, an X-ray pulsar-based navigation (XNAV)/Global navigation satellite system (GNSS) integrated navigation scheme is proposed. A global optimal filtering algorithm called robust federated extended Kalman filter (RFEKF) is proposed to fulfill data fusion. In this algorithm, an adaptive extended Kalman filter (EKF) with measurement noise scale factor is derived as the local filters to reduce the influence of measurement malfunctions and enhance the robustness of orbit determination system. The statistical threshold detection scheme based on the residual chi-square test is used for the fault detection. The simulation results demonstrate the validity and feasibility of RFEKF algorithm in case of measurement malfunctions.
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