This article presents an adaptive hybrid-tracking (AHT) algorithm designed to process GNSS-R signals with a sufficient coherent component. Coherent GNSS-R signals have the potential to enable high-precision and high-resolution carrier-phase measurements for altimetry, sea-level monitoring, soil-moisture monitoring, flood mapping, snow–water equivalent measurements, and so on. The AHT algorithm incorporates the model inputs typically used in the master–slave open-loop (MS-OL) architecture into a closed-phase lock loop. Raw IF data recorded by the CYGNSS satellites over in-land water, land, and open-ocean surface are used to demonstrate the performance of the AHT. The results show that the AHT algorithm achieves comparable robustness with the MS-OL implementation while maintaining centimeter-level accuracy and excellent carrier-phase continuity that can be achieved with a fine-tuned Kalman filter (KF)-based adaptive closed-loop (ACL) system. Moreover, the AHT is suitable for real-time implementation and is applicable to other radio signals-of-opportunity.

中文翻译：

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适用于高精度和高分辨率星载应用的相干GNSS反射信号处理

本文介绍了一种自适应混合跟踪（AHT）算法，旨在处理具有足够相干分量的GNSS-R信号。相干的GNSS-R信号具有实现高精度，高分辨率载波相位测量的潜力，可用于测高，海平面监测，土壤水分监测，洪水测绘，雪水当量测量等。AHT算法将通常在主从开环（MS-OL）体系结构中使用的模型输入合并到一个闭相锁定环中。CYGNSS卫星在内陆水，陆地和海洋表面上记录的原始IF数据用于证明AHT的性能。结果表明，AHT算法在实现厘米级精度和出色的载波相位连续性的同时，可以与MS-OL实现相媲美的鲁棒性，这可以通过基于微调卡尔曼滤波器（KF）的自适应闭环（ACL）实现）系统。此外，AHT适用于实时实施，并且适用于其他机会性无线电信号。