An evaluation of atmospheric models for GPS data retrieval by output from a numerical weather model
An evaluation of atmospheric models for GPS data retrieval by output from a numerical weather model
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通过数值天气模型的输出来评估用于 GPS 数据检索的大气模型
DOI：
10.2151/jmsj.2004.339
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发表时间：
2004
影响因子：
3.1
通讯作者：
S. Shimada
中科院分区：
文献类型：
--
作者：
H. Seko;Hajime Nakamura;S. Shimada
GPS处理中的大气延迟是通过将大气模型的参数与观测延迟进行拟合来估计的。GPS相关误差源包括多路径效应和相位中心变化，以及大气模型中的不确定性。如果要使误差最小化，大气模型必须准确地捕捉延迟分布。1997年3月7日，在伊豆半岛和东京西南约100公里处的初岛县，伴随着山间背风波，出现了较大的全球定位系统位置误差。大的位置误差与山脉背风波的重合表明，与背风波相关的水汽和空气密度的小尺度波动可能会引起大的位置误差。本研究采用高分辨率非静力模式模拟山体背风波。GPS卫星的倾斜延迟是用光线追踪法从再现的水汽和空气密度场计算出来的。大气延迟是通过将大气模型拟合到复制的倾斜延迟来获得的，而不是实际的延迟数据。通过确定复制延迟和模型拟合延迟之间的位置误差差来评估大气模型。利用山地背风波的个例，对三种不同的大气模式进行了评估。第一种是“常量模型”，它只把天顶延迟作为未知参数。在这种情况下，当使用常量模型来拟合数据时，出现了较大的位置误差。“线性梯度模型”在天顶参数的基础上增加了两个水平梯度参数，大大降低了水平位置误差。通过引入二阶项的“二阶模型”，进一步减小了水平和垂直位置误差。利用山地背风波对大气模型的评估表明，1)线性梯度模型不能表示复杂的大气扰动；2)二阶模型减少了水平和垂直位置误差。
Atmospheric delays in GPS processing are estimated by fitting parameters of atmospheric models to the observed delays. GPS-related error sources include multipath effects and phase center variations, as well as uncertainties in atmospheric models. An atmospheric model must accurately capture the delay distribution if errors are to be minimized. Large GPS position errors occurred on 7 March 1997 on the Izu Peninsula and at Hatsu-shima, about 100 km southwest of Tokyo, concomitant with a mountain lee wave. The coinciding of the large position errors and the mountain lee wave suggests that small-scale fluctuations in water vapor and air density associated with lee waves could cause large position errors. This study used a high-resolution non-hydrostatic model to simulate the mountain lee wave. Slant delays for the GPS satellites were calculated from the reproduced water vapor and air density fields using a ray-tracing method. The atmospheric delays are obtained by fitting the atmospheric models to the reproduced slant delays, instead of the actual delay data. The atmospheric models were evaluated by determining the difference in position error between the reproduced delays and the model-fitted delays. The mountain lee wave case was used to evaluate three different atmospheric models. The first, the “constant model”, has only zenith delay as an unknown parameter. Large position errors occurred when the constant model was used to fit the data in this case. The “linear gradient model”, adds two horizontal gradient parameters to the zenith parameter, and yielded significantly reduced horizontal position errors. Horizontal and vertical position errors were reduced further with a “second order model”, which adds second-order terms. Evaluation of the atmospheric models using the mountain lee wave case indicated that 1) the linear gradient model cannot express complicated atmospheric disturbances; and, 2) a second-order model reduces horizontal and vertical position errors.