As one significant component of space environmental weather, the ionosphere has to be monitored using Global Positioning System (GPS) receivers for the Ground-Based Augmentation System (GBAS). This is because an ionospheric anomaly can pose a potential threat for GBAS to support safety-critical services. The traditional code-carrier divergence (CCD) methods, which have been widely used to detect the variants of the ionospheric gradient for GBAS, adopt a linear time-invariant low-pass filter to suppress the effect of high frequency noise on the detection of the ionospheric anomaly. However, there is a counterbalance between response time and estimation accuracy due to the fixed time constants. In order to release the limitation, a two-step approach (TSA) is proposed by integrating the cascaded linear time-invariant low-pass filters with the adaptive Kalman filter to detect the ionospheric gradient anomaly. The performance of the proposed method is tested by using simulated and real-world data, respectively. The simulation results show that the TSA can detect ionospheric gradient anomalies quickly, even when the noise is severer. Compared to the traditional CCD methods, the experiments from real-world GPS data indicate that the average estimation accuracy of the ionospheric gradient improves by more than 31.3%, and the average response time to the ionospheric gradient at a rate of 0.018 m/s improves by more than 59.3%, which demonstrates the ability of TSA to detect a small ionospheric gradient more rapidly.
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机译：作为空间环境天气的重要组成部分，必须使用地面增强系统（GBAS）的全球定位系统（GPS）接收器来监测电离层。这是因为电离层异常会给GBAS支持安全性至关重要的服务带来潜在威胁。传统的码载波发散（CCD）方法已被广泛用于检测GBAS的电离层梯度变化，它采用线性时不变低通滤波器来抑制高频噪声对噪声的影响。电离层异常。但是，由于固定的时间常数，响应时间和估计精度之间存在平衡。为了消除这种局限性，通过将级联的线性时不变低通滤波器与自适应卡尔曼滤波器集成在一起以检测电离层梯度异常，提出了一种两步法（TSA）。分别使用模拟数据和实际数据测试了该方法的性能。仿真结果表明，即使噪声更严重，TSA仍可以快速检测电离层梯度异常。与传统的CCD方法相比，实际GPS数据的实验表明，电离层梯度的平均估计精度提高了31.3％以上，电离层梯度的平均响应时间以0.018 m / s的速度提高了超过59.3％，这表明TSA能够更快地检测出较小的电离层梯度。
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