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摘要: 本文研究了卫星信号干扰下 RTK (Real-time kinematic) 整周模糊度固定问题, 提出了一种基于整数约束型渐进高斯滤波的 RTK 定位方法. 首先, 结合贝叶斯推理与同伦方法优势, 导出了一种兼容整数、浮点状态的渐进高斯滤波框架. 其次, 构造从先验分布到后验分布的同伦路径, 以目标浮点状态与模糊度固定的迭代求解, 来提高信号干扰情形下的整周模糊度固定率. 特别地, 通过渐进地融合卫星双差信息来降低线性化误差, 进而提升对目标状态后验分布的逼近精度. 最后, 通过车载 RTK 实验及后处理分析, 验证了所提方法的有效性和优越性.Abstract: This paper investigates the issue of real-time kinematic (RTK) integer ambiguity resolution under satellite signal interference and proposes a RTK positioning method based on integer-constrained progressive Gaussian filtering. Firstly, by combining the advantages of Bayesian inference and homotopy methods, a progressive Gaussian filtering framework that is compatible with both integer and floating-point states is derived. Secondly, a homotopic path is constructed from the prior distribution to the posterior distribution, and the target floating-point state and ambiguity resolution is solved iteratively for improving the integer ambiguity fixed rate under signal interference conditions. Specifically, the linearization error is reduced by progressively fusing satellite double-difference information, thus enhancing the approximation accuracy of the posterior distribution of the target state. Finally, the effectiveness and superiority of the proposed method are validated through vehicle-mounted RTK experiments and post-processing analysis.
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表 1 RMSE和固定率对比
Table 1 Comparison of RMSE and fixed rate
方法 EKF IREKF IEKF REKF 所提方法 提升 RMSE-水平 (m) 0.8718 1.0223 0.9600 0.9075 0.6696 23.19% RMSE-垂直 (m) 0.2959 0.6174 0.5150 0.2871 0.2062 28.18% 固定率 (%) 50.3300 61.5800 58.4800 71.1300 90.3800 19.25% 
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表 2 单个历元平均解算时间
Table 2 The average calculation time of each epoch
方法 EKF IREKF IEKF REKF 所提方法 时间 (s) 0.0821 0.1506 0.1490 0.0863 0.0899
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