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Method and assessment of BDS triple-frequency ambiguity resolution for long-baseline network RTK

机译：长基线网络RTK的BDS三频模糊度解析方法及评估

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Fast and reliable ambiguity resolution (AR) over long baselines is one of the major challenges for large-scale GNSS network real-time kinematic (RTK) positioning. In the dual-frequency case, wide-lane (WL) ambiguities are usually fixed firstly, followed by the procedure of determination of the narrow-lane (NL) ambiguity integers based on the ionosphere-free model. For long-baseline network RTK, there are still some problems faced, for instance the WL AR still needs to take over tens of epochs due to the influence of pseudorange noises and multipath effects; the NL AR model is weak since more parameters are introduced, thus much time is needed to guarantee the precision of float ambiguity solutions. Along with the deployment of modernized GPS, BDS and other GNSS, the triple-frequency AR with real data gradually becomes feasible. Many literatures have proven the third signal will make AR faster and more reliable. In this paper based on the characteristics of network RTK, a modified ionosphere-free model was proposed to improve EWL/WL AR performance for long baselines, followed by the comparison with several commonly-used EWL/WL AR models. The NL AR performance with triple-frequency and dual-frequency observations was also tested. In NL AR, a partial AR strategy is adopted to weaken the negative influence of new-rising or low-elevation satellites. Experiments were conducted using real BDS triple-frequency data on 74 km and 241 km baselines. Results show that the modified ionosphere-free model can balance the ambiguity precision and ambiguity bias better for the EWL/ WL AR. The NL AR with triple-frequency observations also performs significantly better than that in dual-frequency mode, with 29.9% and 32.9% improvement in time-to-first-fix (TTFF) for the 74 km and 241 km baselines respectively.
机译：在长基线上快速且可靠的歧义分辨率（AR）是大规模GNSS网络实时运动（RTK）定位的主要挑战之一。在双频情况下，通常首先确定宽车道（WL）的歧义，然后根据无电离层模型确定窄车道（NL）的歧义整数。对于长基线网络RTK，仍然面临一些问题，例如，由于伪距噪声和多径效应的影响，WL AR仍需要接管数十个时期。由于引入了更多的参数，NL AR模型很弱，因此需要大量时间来保证浮点模糊度解的精度。随着现代化GPS，BDS和其他GNSS的部署，具有真实数据的三频AR逐渐变得可行。许多文献已经证明，第三信号将使AR更快，更可靠。本文基于网络RTK的特点，提出了一种改进的无电离层模型，以改善长基线的EWL / WL AR性能，然后与几种常用的EWL / WL AR模型进行比较。还测试了具有三频和双频观测的NL AR性能。在NL AR中，采用部分AR策略来减弱新兴或低海拔卫星的负面影响。使用真实的BDS三频数据在74 km和241 km基线上进行了实验。结果表明，改进的无电离层模型可以更好地平衡歧义精度和歧义偏差。具有三频观测的NL AR的性能也明显优于双频模式，对于74 km和241 km的基线，首次定位时间（TTFF）分别提高了29.9％和32.9％。

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