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An Adaptive Low-Cost GNSS/MEMS-IMU Tightly-Coupled Integration System with Aiding Measurement in a GNSS Signal-Challenged Environment

机译:GNSS信号挑战环境下具有辅助测量功能的自适应低成本GNSS / MEMS-IMU紧密耦合集成系统

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The main aim of this paper is to develop a low-cost GNSS/MEMS-IMU tightly-coupled integration system with aiding information that can provide reliable position solutions when the GNSS signal is challenged such that less than four satellites are visible in a harsh environment. To achieve this goal, we introduce an adaptive tightly-coupled integration system with height and heading aiding (ATCA). This approach adopts a novel redundant measurement noise estimation method for an adaptive Kalman filter application and also augments external measurements in the filter to aid the position solutions, as well as uses different filters to deal with various situations. On the one hand, the adaptive Kalman filter makes use of the redundant measurement system’s difference sequence to estimate and tune noise variance instead of employing a traditional innovation sequence to avoid coupling with the state vector error. On the other hand, this method uses the external height and heading angle as auxiliary references and establishes a model for the measurement equation in the filter. In the meantime, it also changes the effective filter online based on the number of tracked satellites. These measures have increasingly enhanced the position constraints and the system observability, improved the computational efficiency and have led to a good result. Both simulated and practical experiments have been carried out, and the results demonstrate that the proposed method is effective at limiting the system errors when there are less than four visible satellites, providing a satisfactory navigation solution.
机译:本文的主要目的是开发一种低成本的GNSS / MEMS-IMU紧密耦合集成系统,该系统具有辅助信息,可以在挑战GNSS信号时提供可靠的位置解决方案,从而在恶劣的环境中可见不到四颗卫星。为了实现此目标,我们引入了具有高度和航向辅助(ATCA)的自适应紧密耦合集成系统。该方法为自适应卡尔曼滤波器应用采用了一种新颖的冗余测量噪声估计方法,并且还增加了滤波器中的外部测量值以辅助位置解,以及使用不同的滤波器来处理各种情况。一方面,自适应卡尔曼滤波器利用冗余测量系统的差分序列来估计和调整噪声方差,而不是采用传统的创新序列来避免与状态矢量误差耦合。另一方面,该方法使用外部高度和航向角作为辅助参考,并为滤波器中的测量方程建立模型。同时,它还会根据跟踪的卫星数在线更改有效过滤器。这些措施越来越多地增强了位置约束和系统的可观察性,提高了计算效率,并取得了良好的效果。进行了仿真和实际实验,结果表明,当可见卫星少于四个时,该方法有效地限制了系统误差,提供了令人满意的导航解决方案。

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