Reliable and correct carrier phase ambiguity resolution is the key to global navigation satellite system (GNSS) high-precision navigation and positioning applications. For kinematic situations, such as moving-baseline-based positioning and attitude determination, the baseline length between two antennas is constant; such a priori information could contribute to integer ambiguity resolution, especially when only a few satellites are viewed. In this research, three different approaches using baseline information—the linearized joint adjustment method, validation method, and constrained LAMBDA (CLAMBDA) method—are comprehensively evaluated through theoretical and experimental analyses. The performance of each method is assessed in terms of the ambiguity success rate and baseline solution accuracy with static and kinematic GPS/BDS datasets. The additional baseline length constraint improves the precision of the float solution and the ambiguity fixed success rate (compared to the standard LAMBDA method), but there are differences in the performance of the three methods. Specifically, the performance of the linearized joint adjustment method primarily depends on baseline length and improves as the baseline length increases; however, caution should be exercised for short baselines. The validation method and CLAMBDA method both consider the quadratic form of ambiguity residuals and baseline length constraint for selecting the ambiguity solution. However, the validation method directly judges the ambiguity to obtain a locally optimal solution, whereas the CLAMBDA method constructs a rigorous mathematical formula to obtain a globally optimal solution. Moreover, because the linearized joint adjustment method and CLAMBDA method primarily contribute to the float and fixed solution, respectively, we fused the two methods to improve the ambiguity resolution success rate. The results confirm that the combined algorithm achieves better performance that exceeds that of either individual method for a baseline length of tens of meters.

可靠且正确的载波相位模糊度解决方案是全球导航卫星系统（GNSS）高精度导航和定位应用的关键。对于运动情况，例如基于运动基线的定位和姿态确定，两个天线之间的基线长度是恒定的；这样的先验信息可能有助于整数模糊度的解析，尤其是在仅查看少量卫星的情况下。在这项研究中，通过理论和实验分析综合评估了使用基线信息的三种不同方法，即线性联合调整方法，验证方法和约束LAMBDA（CLAMBDA）方法。每种方法的性能均通过静态和动态GPS / BDS数据集的歧义成功率和基线解的准确性进行评估。附加的基线长度约束提高了float解决方案的精度并提高了不确定性的固定成功率（与标准LAMBDA方法相比），但是这三种方法的性能有所不同。具体来说，线性化关节调整方法的性能主要取决于基线长度，并且随着基线长度的增加而提高；但是，应谨慎对待较短的基线。验证方法和CLAMBDA方法都考虑了歧义残差的二次形式和选择歧义解的基线长度约束。然而，验证方法直接判断了获得局部最优解的不确定性，而CLAMBDA方法构造了严格的数学公式以获得全局最优解。此外，由于线性联合调整方法和CLAMBDA方法分别分别对浮点法和固定解起作用，因此我们将这两种方法融合在一起以提高歧义度解析的成功率。结果证实，对于几十米的基线长度，组合算法可实现优于任何一种单独方法的更好性能。