WO2021169318A1 - Parabola-based regional tropospheric wet delay calculation method - Google Patents

Parabola-based regional tropospheric wet delay calculation method Download PDF

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WO2021169318A1
WO2021169318A1 PCT/CN2020/120813 CN2020120813W WO2021169318A1 WO 2021169318 A1 WO2021169318 A1 WO 2021169318A1 CN 2020120813 W CN2020120813 W CN 2020120813W WO 2021169318 A1 WO2021169318 A1 WO 2021169318A1
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wet delay
tropospheric wet
tropospheric
delay
sounding
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PCT/CN2020/120813
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Chinese (zh)
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胡伍生
李小翠
聂檄晨
严宇翔
张志伟
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东南大学
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/03—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
    • G01S19/07—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing data for correcting measured positioning data, e.g. DGPS [differential GPS] or ionosphere corrections

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  • the invention relates to the field of global navigation systems, and in particular to a method for calculating the tropospheric wet delay according to the spatial position to be measured.
  • the delay caused by tropospheric refraction is usually divided into tropospheric dry delay and tropospheric wet delay (ZWD).
  • the tropospheric dry delay is also called the zenith static delay. It is caused by the dry atmosphere and does not involve the influence of water vapor.
  • the present invention discloses a method for calculating the tropospheric wet delay using the latitude and altitude of the ground to be measured.
  • the method is suitable for locations where radiosonde data cannot be obtained, and the influence of the season is taken into account to obtain a more accurate tropospheric wet delay. .
  • S1 Collect sounding data, annual accumulated days and spatial position data of each sounding station in the target area, and calculate the true value of tropospheric wet delay T ZWD for each sounding station based on the collected sounding data; the spatial position The data is the latitude value and the altitude value;
  • Q ZWD is the calculated value of tropospheric wet delay
  • lat is the latitude value
  • h 0 is the altitude value
  • doy is the accumulated days
  • A, B, C and A′, B′, C′ are model coefficients
  • the step of calculating the true value of the tropospheric wet delay T ZWD,n of the nth sounding station includes:
  • T ZWD,n S ZTD,n -A ZHD,n .
  • the least square method is used to determine the coefficients.
  • the parabolic-based regional tropospheric wet delay calculation method disclosed in the present invention integrates spatial position information such as latitude and altitude of the ground to be measured, as well as the influence of seasons. Compared with the traditional EGNOS model, the calculation method is improved. The accuracy of the tropospheric wet delay at the location of the null data.
  • Figure 1 is a flow chart of the method for calculating regional tropospheric wet delay disclosed in the present invention
  • Figure 2 shows the time change of ZWD at 86 sites from 2013 to 2017;
  • Figure 3 is a time series diagram of the pairwise comparison of the deviations between the ZWD(E) model and the QZWD model on the Harbian site from 2013 to 2018.
  • the invention discloses a parabola-based area tropospheric wet delay calculation method.
  • the process is shown in Fig. 1 and includes:
  • S1 Collect sounding data, annual accumulated days and spatial position data of each sounding station in the target area, and calculate the true value of tropospheric wet delay T ZWD for each sounding station based on the collected sounding data; the spatial position The data is the latitude value and the altitude value;
  • the radiosonde data of 86 sounding stations in the Chinese region from 2013 to 2017 are collected, and the latitude and altitude values of each sounding station are recorded at the same time.
  • 86 sounding stations are distributed in various regions of China, from Hailar District in the Inner Mongolia Autonomous Region in the north, Xisha Islands in the south, Kashgar in Xinjiang in the west, Yanji City in Jilin province in the east, denser in the middle and east than in the west, and denser in the south than in the north.
  • the station numbered 1028 Take the station numbered 1028 as an example, and its sounding data are shown in Table 1.
  • the sounding data provides atmospheric characteristic layer parameters at different altitudes, including detection elements such as atmospheric pressure (PRES), altitude (HGHT), air temperature (TEMP), and dew point temperature (DWPT).
  • detection elements such as atmospheric pressure (PRES), altitude (HGHT), air temperature (TEMP), and dew point temperature (DWPT).
  • PRES atmospheric pressure
  • HGHT altitude
  • TMP air temperature
  • DWPT dew point temperature
  • the main meteorological elements required are air pressure, temperature, humidity, and water vapor partial pressure.
  • the steps for calculating the true value of the tropospheric wet delay T ZWD,n of the radiosonde station based on the nth radiosonde data include:
  • the total tropospheric delay in the zenith direction can be expressed as the integral of the refractive index on the propagation path.
  • the refractive index N(s) at position s can be based on the Smith-Weintarub equation, and the air temperature T(s), pressure P(s), and water vapor pressure e at position s through sounding data.
  • the value of (s) is calculated using the following formula:
  • h is the height of the atmosphere from sea level
  • h T is the height of the tropopause
  • h 0 is the altitude of the sounding station
  • h 0,n is the altitude of the nth sounding station
  • N(h 0,n ) the refractive index of the GNSS radio signal on the ground of the nth sounding station
  • N(11000) is the height of 11km above the ground.
  • Refractive index c 1 is the refractive index attenuation coefficient at the ground
  • c 2 is the refractive index attenuation coefficient at a height of 11km from the ground;
  • the present invention uses the Saastamoinen model to calculate the atmospheric delay, and the specific formula is shown in formula (5):
  • lat n are the ground pressure at the nth radiosonde station, the correction of the gravitational acceleration changes caused by the earth's rotation, and the latitude;
  • T ZWD,n S ZTD,n -A ZHD,n
  • this embodiment adopts a programming method to implement data downloading, reading, fitting and calculation, and the language is java.
  • the language is java.
  • this example only uses the sounding data at 00 o’clock as the sounding data of the day, and the subsequent analysis is based on the data at 00 o’clock (the analysis principle of the data at 12 o’clock is the same as that at 00 o’clock. No longer described).
  • a total of 19,162 radiosonde data were finally qualified.
  • a, b, and c are model parameters respectively
  • doy is the accumulated days per year
  • M is the value of doy at the boundary of the parabola.
  • the values of b and M are 28 and 211 respectively.
  • the model represented by equation (6) takes into account the commonality of all stations-cycle time variation. In order to take into account the characteristics of each site, its spatial parameters are added.
  • Q ZWD is the calculated value of tropospheric wet delay
  • lat is the latitude value
  • h 0 is the altitude value
  • doy is the accumulated days
  • A, B, C and A′, B′, C′ are model coefficients
  • S3 Substitute the true value of the tropospheric wet delay, annual accumulated days, latitude, and altitude values of the sounding station obtained in S1 into the tropospheric wet delay parabolic function model, determine various coefficients, and obtain the tropospheric wet delay parabolic function in the target area Model (denoted as QZWD model);
  • This example uses the true ZWD values of 86 radiosonde stations in China from 2013 to 2017 for fitting.
  • the least squares method is used to determine the coefficients.
  • the fitting accuracy is 38.8mm.
  • the obtained latitude in China is lat and the altitude is
  • the coefficients in the parabolic function model of the tropospheric wet delay at h 0 are:
  • S4 Obtain the latitude value, altitude value and annual accumulated days of the ground to be measured in the target area, and obtain the calculated value of the tropospheric wet delay in the target area determined by S3 according to the parabolic function model of the tropospheric wet delay in the target area.
  • the average error of the ZWD(E) model is about ⁇ 52.3mm; in contrast, the average error of the QZWD model is ⁇ 32.7mm, which is about 37.5% higher than that of the ZWD(E) model.
  • Table 3 shows that the accuracy of the QZWD model in 2018 is about 40.1% higher than that of the ZWD(E) model. From the data of 2013-2018, the accuracy of the QZWD model is better than that of the ZWD(E) model every year. Therefore, on the whole, the accuracy of the QZWD model is more suitable than the ZWD(E) model for the non-weather parameter ZWD model in China. .
  • the average deviation of the ZWD(E) model used at the Harbin station is -51.1mm, indicating that the ZWD(E) model used at the Harbin station has a systematic error; the average error is ⁇ 56.3mm, which is more accurate Low.
  • the average deviation of the QZWD model is only 0.7mm, and there is almost no systematic error; the average error is ⁇ 29.5mm, indicating that the accuracy of the QZWD model used at Harbin station is much higher than that of the ZWD(E) model, with an average increase of 47.6 %.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

A parabola-based regional tropospheric wet delay calculation method, comprising: 1, acquiring sounding data, the day of year and spatial position data of each sounding station in a target region, and calculating a tropospheric wet delay true value of each sounding station according to the acquired sounding data; 2, establishing a tropospheric wet delay parabola function model; 3, substituting the tropospheric wet delay true values, the days of year, latitude values and altitude values of the sounding stations obtained in step 1 into the tropospheric wet delay parabola function model, determining various coefficients, and obtaining a tropospheric wet delay parabola function model in the target area; and 4, obtaining a latitude value, an altitude value and the day of year of land to be measured in the target area, and obtaining a tropospheric wet delay calculation value of said land according to the tropospheric wet delay parabola function model in the target area. The described method is suitable for a position at which sounding data could not be obtained; in addition, the influence of the seasons is considered, and more accurate tropospheric wet delay may be obtained.

Description

一种基于抛物线的区域对流层湿延迟计算方法A parabola-based calculation method of regional tropospheric wet delay 技术领域Technical field
本发明涉及全球导航***领域，特别是涉及一种根据待测地空间位置计算对流层湿延迟的方法。The invention relates to the field of global navigation systems, and in particular to a method for calculating the tropospheric wet delay according to the spatial position to be measured.
背景技术Background technique
大气延迟误差主要包括由电离层折射产生的电离层延迟误差和由对流层折射产生的对流层延迟误差。地球大气的主要成分包括干空气、水汽以及各种微粒。约四分之三的大气和百分之九十九的水汽都集中在对流层中，因为地球重力的影响，大气在对流层垂直方向上呈现不均匀的分布，其密度大致随着高度增加而较少。当GNSS无线电信号传播通过对流层时，一方面信号的传播速度将产生变化，另一方面对流层将对电磁波产生非色散性折射，引起信号路径的改变，从而产生传播延迟。因为对流层折射率只与电磁波信号的传播速度有关，与其频率或波长是无关的，所以不能用解决电离层延迟误差的方法来消除或削弱对流层延迟。因此需要重点研究对流层延迟的修正精度。Atmospheric delay errors mainly include ionospheric delay errors caused by ionospheric refraction and tropospheric delay errors caused by tropospheric refraction. The main components of the earth’s atmosphere include dry air, water vapor, and various particulates. About three-quarters of the atmosphere and 99% of the water vapor are concentrated in the troposphere. Due to the influence of the earth's gravity, the atmosphere is unevenly distributed in the vertical direction of the troposphere, and its density generally decreases with the increase in altitude. . When a GNSS radio signal propagates through the troposphere, on the one hand, the propagation speed of the signal will change, and on the other hand, the troposphere will produce non-dispersive refraction of electromagnetic waves, causing a change in the signal path, resulting in propagation delay. Because the refractive index of the troposphere is only related to the propagation speed of the electromagnetic wave signal, and has nothing to do with its frequency or wavelength, the method of solving the ionospheric delay error cannot be used to eliminate or weaken the tropospheric delay. Therefore, it is necessary to focus on the correction accuracy of tropospheric delay.
GNSS电磁波信号经过对流层时，考虑到对流层中干空气和水汽的不同影响，通常将对流层折射产生的延迟分为对流层干延迟和对流层湿延迟(ZWD)。对流层干延迟也叫天顶静力学延迟，是由干燥大气引起的，不涉及水汽的影响，变化比较缓慢，所以比较容易掌握对流层干延迟的变化规律；相对地，对流层湿延迟是由大气水汽引起的，由于对流层的水汽含量分布无规律，变化速度快，过程较为复杂，对流层湿延迟是目前众多学者难以掌握的问题。目前有效提高对流层延迟精度的方法主要有外部修正法，参数估计法和模型改正法等。模型改正法对对流层干延迟估计精度可达90％以上，但对流层湿延迟只有20％左右的精度。对流层湿延迟模型的研究对GNSS导航定位有重要意义。一方面通过对流层湿延迟模型计算出的对流层湿延迟值可以直接用于一些伪距单点定位的应用中；另一方面，目前在采用的精密单点定位(PPP)解算中，可以将模型计算出的对流层湿延迟值作为初始值，将有效提高PPP算法收敛的速度，满足对收敛时间有要求的PPP。When the GNSS electromagnetic wave signal passes through the troposphere, considering the different effects of dry air and water vapor in the troposphere, the delay caused by tropospheric refraction is usually divided into tropospheric dry delay and tropospheric wet delay (ZWD). The tropospheric dry delay is also called the zenith static delay. It is caused by the dry atmosphere and does not involve the influence of water vapor. The change is relatively slow, so it is easier to grasp the change law of the tropospheric dry delay; relatively, the tropospheric wet delay is caused by atmospheric water vapor However, due to the irregular distribution of the water vapor content in the troposphere, the rapid change rate, and the complicated process, the tropospheric wetness delay is a problem that many scholars are difficult to grasp at present. At present, the methods to effectively improve the accuracy of tropospheric delay mainly include external correction method, parameter estimation method and model correction method. The model correction method can estimate the tropospheric dry delay with an accuracy of more than 90%, but the tropospheric wet delay has an accuracy of only about 20%. The study of tropospheric wet delay model is of great significance to GNSS navigation and positioning. On the one hand, the tropospheric wet delay value calculated by the tropospheric wet delay model can be directly used in some pseudo-range single-point positioning applications; on the other hand, in the current precision single-point positioning (PPP) calculation, the model can be used The calculated tropospheric wet delay value is used as the initial value, which will effectively improve the convergence speed of the PPP algorithm and meet the PPP that requires the convergence time.
发明内容Summary of the invention
发明目的：本发明公开了一种利用待测地纬度和海拔计算对流层湿延迟的方法，该方法适用于无法获取探空数据的位置，且考虑了季节的影响，能够获取较为精确的对流层湿延迟。Objective of the invention: The present invention discloses a method for calculating the tropospheric wet delay using the latitude and altitude of the ground to be measured. The method is suitable for locations where radiosonde data cannot be obtained, and the influence of the season is taken into account to obtain a more accurate tropospheric wet delay. .
技术方案：本发明采用如下技术方案：Technical solution: The present invention adopts the following technical solutions:
一种基于抛物线的区域对流层湿延迟计算方法，包括：A method for calculating regional tropospheric wet delay based on parabola, including:
S1：采集目标区域中每个探空站点的探空数据、年积日和空间位置数据，根据采集到的探空数据计算每个探空站点的对流层湿延迟真值T ZWD；所述空间位置数据为纬度值、海拔高度值； S1: Collect sounding data, annual accumulated days and spatial position data of each sounding station in the target area, and calculate the true value of tropospheric wet delay T ZWD for each sounding station based on the collected sounding data; the spatial position The data is the latitude value and the altitude value;
S2：建立对流层湿延迟抛物线函数模型：S2: Establish a parabolic function model of tropospheric wet delay:
Figure PCTCN2020120813-appb-000001
Figure PCTCN2020120813-appb-000001
其中，Q ZWD为对流层湿延迟计算值，lat为纬度值，h 0为海拔高度值，doy为年积日，A,B,C和A′,B′,C′均为模型系数； Among them, Q ZWD is the calculated value of tropospheric wet delay, lat is the latitude value, h 0 is the altitude value, doy is the accumulated days, and A, B, C and A′, B′, C′ are model coefficients;
S3：将S1中获取的探空站点的对流层湿延迟真值、年积日、纬度值、海拔高度值代入对流层湿延迟抛物线函数模型中，确定各项系数，得到目标区域内对流层湿延迟抛物线函数模型；S3: Substitute the true value of the tropospheric wet delay, annual accumulated days, latitude, and altitude values of the sounding station obtained in S1 into the tropospheric wet delay parabolic function model, determine various coefficients, and obtain the tropospheric wet delay parabolic function in the target area Model;
S4：获取目标区域内待测地的纬度值、海拔高度值和年积日，根据S3确定的目标区域内对流层湿延迟抛物线函数模型得到待测地的对流层湿延迟计算值。S4: Obtain the latitude value, altitude value and annual accumulated days of the ground to be measured in the target area, and obtain the calculated value of the tropospheric wet delay in the target area determined by S3 according to the parabolic function model of the tropospheric wet delay in the target area.
所述步骤S1中计算第n个探空站点的对流层湿延迟真值T ZWD,n的步骤包括： In the step S1, the step of calculating the true value of the tropospheric wet delay T ZWD,n of the nth sounding station includes:
S1.1：计算第n个探空站点的对流层总延迟S ZTD,n： S1.1: Calculate the total tropospheric delay S ZTD,n of the nth sounding station:
Figure PCTCN2020120813-appb-000002
Figure PCTCN2020120813-appb-000002
其中，h 0,n为第n个探空站点的海拔高度，N(h 0,n)第n个探空站点地面处的GNSS无线电信号折射率，N(11000)为距地面11km高度处的折射率，c 1为地面处的折射率衰减系数，c 2是距地面11km高处的折射率衰减系数； Among them, h 0,n is the altitude of the nth sounding station, N(h 0,n ) the refractive index of the GNSS radio signal on the ground of the nth sounding station, and N(11000) is the height of 11km above the ground. Refractive index, c 1 is the refractive index attenuation coefficient at the ground, and c 2 is the refractive index attenuation coefficient at a height of 11km from the ground;
S1.2：计算第n个探空站点的大气延迟A ZHD,n： S1.2: Calculate the atmospheric delay A ZHD,n of the nth sounding station:
Figure PCTCN2020120813-appb-000003
Figure PCTCN2020120813-appb-000003
其中P S,n、f(lat n,h 0,n)、lat n分别为第n个探空站点的地面气压、地球自转所引起的重力加速度变化的修正、纬度； Among them, P S,n , f(lat n ,h 0,n ), lat n are the ground pressure of the nth radiosonde station, the correction of the gravitational acceleration change caused by the earth's rotation, and the latitude;
第n个探空站点的地球自转所引起的重力加速度变化的修正为：The correction of the change in gravitational acceleration caused by the rotation of the earth at the nth sounding station is:
f(lat n,h 0,n)＝1-0.00266cos2lat n-0.00028h 0,n。 f(lat n ,h 0,n )=1-0.00266cos2lat n -0.00028h 0,n .
S1.3：第n个探空站点的对流层湿延迟真值T ZWD,n为： S1.3: The true value of the tropospheric wet delay T ZWD of the nth sounding station, where n is:
T ZWD,n＝S ZTD,n-A ZHD,n。 T ZWD,n =S ZTD,n -A ZHD,n .
所述步骤S3中采用最小二乘法确定各项系数。In the step S3, the least square method is used to determine the coefficients.
中国区域内纬度为lat，海拔高度为h 0处的对流层湿延迟抛物线函数模型： The parabolic function model of tropospheric wet delay at latitude lat and altitude h 0 in China:
Figure PCTCN2020120813-appb-000004
Figure PCTCN2020120813-appb-000004
其中的系数为：The coefficients are:
Figure PCTCN2020120813-appb-000005
Figure PCTCN2020120813-appb-000005
有益效果：本发明公开的基于抛物线的区域对流层湿延迟计算方法，综合了待测地纬度、海拔高度等空间位置信息，以及季节的影响，相比于传统的EGNOS模型，提高了在计算无探空数据的位置处对流层湿延迟的精度。Beneficial effects: The parabolic-based regional tropospheric wet delay calculation method disclosed in the present invention integrates spatial position information such as latitude and altitude of the ground to be measured, as well as the influence of seasons. Compared with the traditional EGNOS model, the calculation method is improved. The accuracy of the tropospheric wet delay at the location of the null data.
附图说明Description of the drawings
图1为本发明公开的区域对流层湿延迟计算方法的流程图；Figure 1 is a flow chart of the method for calculating regional tropospheric wet delay disclosed in the present invention;
图2为2013-2017年86个站点的ZWD时间变化；Figure 2 shows the time change of ZWD at 86 sites from 2013 to 2017;
图3为2013-2018年Harbian站点ZWD(E)模型和QZWD模型偏差值两两对比的时间序列图。Figure 3 is a time series diagram of the pairwise comparison of the deviations between the ZWD(E) model and the QZWD model on the Harbian site from 2013 to 2018.
具体实施方式Detailed ways
为使本发明的目的、技术方案和优点更加清楚，下面结合附图对本发明的具体实施案例做说明。In order to make the objectives, technical solutions, and advantages of the present invention clearer, the following describes specific implementation cases of the present invention with reference to the accompanying drawings.
本发明公开了一种基于抛物线的区域对流层湿延迟计算方法，其流程如图1所示，包括：The invention discloses a parabola-based area tropospheric wet delay calculation method. The process is shown in Fig. 1 and includes:
S1：采集目标区域中每个探空站点的探空数据、年积日和空间位置数据，根据采集到的探空数据计算每个探空站点的对流层湿延迟真值T ZWD；所述空间位置数据为纬度值、海拔高度值； S1: Collect sounding data, annual accumulated days and spatial position data of each sounding station in the target area, and calculate the true value of tropospheric wet delay T ZWD for each sounding station based on the collected sounding data; the spatial position The data is the latitude value and the altitude value;
表1 1028探空站点的气象数据Table 1 Meteorological data of 1028 radiosonde station
PRESPRES HGHTHGHT TEMPTEMP DWPTDWPT RELHRELH MIXRMIXR DRCTDRCT SKNTSKNT THTATHTA THTETHTE THTVTHTV
hPahPa mm CC CC ％% g/kgg/kg degdeg knotknot KK KK KK
10091009 1818 -3.5-3.5 -5.1-5.1 8989 2.62.6 135135 1212 269269 276.1276.1 269.4269.4
10031003 6565 -2.7-2.7 -6.8-6.8 7373 2.32.3 142142 1616 270.2270.2 276.6276.6 270.6270.6
10001000 8989 -2.9-2.9 -7-7 7373 2.272.27 145145 1717 270.2270.2 276.6276.6 270.6270.6
985985 208208 -3.9-3.9 -7.8-7.8 7575 2.172.17 150150 23twenty three 270.4270.4 276.5276.5 270.8270.8
948948 508508 -6.5-6.5 -9.7-9.7 7878 1.941.94 150150 3131 270.8270.8 276.3276.3 271.1271.1
925925 701701 -8.1-8.1 -10.9-10.9 8080 1.811.81 150150 2929 271271 276.1276.1 271.3271.3
896896 947947 -10.2-10.2 -11.8-11.8 8888 1.741.74 150150 2727 271.3271.3 276.3276.3 271.6271.6
879879 10951095 -11.5-11.5 -12.3-12.3 9494 1.71.7 140140 2525 271.5271.5 276.3276.3 271.8271.8
856856 12971297 -13.2-13.2 -14.8-14.8 8888 1.431.43 125125 21twenty one 271.7271.7 275.8275.8 271.9271.9
850850 13511351 -13.7-13.7 -15.4-15.4 8787 1.361.36 125125 21twenty one 271.8271.8 275.7275.7 272272
817817 16501650 -15.9-15.9 -17.1-17.1 9191 1.231.23 135135 2525 272.5272.5 276.1276.1 272.7272.7
794794 18661866 -17.5-17.5 -18.3-18.3 9393 1.151.15 106106 2020 273.1273.1 276.4276.4 273.3273.3
789789 19131913 -17.8-17.8 -18.8-18.8 9292 1.111.11 100100 1919 273.3273.3 276.5276.5 273.4273.4
781781 19891989 -18.2-18.2 -19.5-19.5 9090 1.051.05 9090 1919 273.6273.6 276.7276.7 273.7273.7
766766 21342134 -19.1-19.1 -20.9-20.9 8686 0.950.95 104104 22twenty two 274.2274.2 277277 274.3274.3
753753 22622262 -20.1-20.1 -23.6-23.6 7474 0.760.76 116116 2525 274.4274.4 276.7276.7 274.5274.5
733733 24612461 -20.5-20.5 -27.8-27.8 5252 0.530.53 135135 2929 276.1276.1 277.8277.8 276.2276.2
700700 28022802 -21.1-21.1 -35.1-35.1 2727 0.280.28 145145 3737 279.1279.1 280280 279.1279.1
697697 28342834 -21.1-21.1 -35.1-35.1 2727 0.280.28 146146 3737 279.4279.4 280.4280.4 279.5279.5
677677 30443044 -22.6-22.6 -35.7-35.7 2929 0.270.27 155155 4141 280.1280.1 281281 280.1280.1
653653 33063306 -24.4-24.4 -36.5-36.5 3232 0.260.26 155155 3535 280.9280.9 281.8281.8 281281
628628 35883588 -26.4-26.4 -37.3-37.3 3535 0.250.25 110110 2929 281.8281.8 282.6282.6 281.8281.8
617617 37163716 -27.3-27.3 -37.7-37.7 3737 0.240.24 115115 2727 282.2282.2 283283 282.2282.2
610610 37993799 -27.9-27.9 -38-38 3838 0.240.24 135135 2525 282.4282.4 283.2283.2 282.5282.5
596596 39673967 -29.1-29.1 -38.5-38.5 4040 0.230.23 165165 3131 282.9282.9 283.7283.7 283283
589589 40534053 -29.7-29.7 -38.7-38.7 4141 0.230.23 168168 3333 283.2283.2 284284 283.2283.2
563563 43704370 -31.8-31.8 -43-43 3232 0.150.15 180180 4141 284.5284.5 285285 284.5284.5
523523 48894889 -35.1-35.1 -50.1-50.1 2020 0.070.07 174174 3535 286.5286.5 286.8286.8 286.5286.5
513513 50235023 -36.1-36.1 -44.1-44.1 4444 0.150.15 172172 3333 286.9286.9 287.4287.4 286.9286.9
500500 52005200 -37.5-37.5 -45.5-45.5 4343 0.130.13 170170 3131 287.3287.3 287.7287.7 287.3287.3
489489 53535353 -38.9-38.9 -45.8-45.8 4848 0.130.13 170170 2929 287.4287.4 287.9287.9 287.5287.5
465465 57005700 -41.9-41.9 -46.5-46.5 6161 0.130.13 173173 3333 287.8287.8 288.2288.2 287287
本实施例中采集中国区域内86个探空站点在2013-2017年的的探空数据，同时记录各探空站点的纬度值和海拔高度值。86个探空站点分布在中国各个地区，北至内蒙古自治区的海拉尔区，南至西沙群岛，西至新疆喀什地区，东至吉林省延吉市，中东部比西部更加密集，南方比北方更密集。以编号为1028的站点为例，其探空数据如表1。In this embodiment, the radiosonde data of 86 sounding stations in the Chinese region from 2013 to 2017 are collected, and the latitude and altitude values of each sounding station are recorded at the same time. 86 sounding stations are distributed in various regions of China, from Hailar District in the Inner Mongolia Autonomous Region in the north, Xisha Islands in the south, Kashgar in Xinjiang in the west, Yanji City in Jilin Province in the east, denser in the middle and east than in the west, and denser in the south than in the north. Take the station numbered 1028 as an example, and its sounding data are shown in Table 1.
从表1可以看到，探空数据提供了不同高度下的大气特性层参数，包括气压(PRES)、高度(HGHT)、气温(TEMP)、露点温度(DWPT)等探测要素。基于探空资料获取GNSS对流层延迟，需要的气象要素主要有气压、温度、湿度和水汽分压。It can be seen from Table 1 that the sounding data provides atmospheric characteristic layer parameters at different altitudes, including detection elements such as atmospheric pressure (PRES), altitude (HGHT), air temperature (TEMP), and dew point temperature (DWPT). To obtain GNSS tropospheric delay based on sounding data, the main meteorological elements required are air pressure, temperature, humidity, and water vapor partial pressure.
根据第n个探空数据计算该探空站点的对流层湿延迟真值T ZWD,n的步骤包括： The steps for calculating the true value of the tropospheric wet delay T ZWD,n of the radiosonde station based on the nth radiosonde data include:
S1.1：计算第n个探空站点的对流层总延迟S ZTD,n； S1.1: Calculate the total tropospheric delay S ZTD,n of the nth sounding station;
天顶方向的对流层总延迟可以表示为折射率在传播路线上的积分。The total tropospheric delay in the zenith direction can be expressed as the integral of the refractive index on the propagation path.
Figure PCTCN2020120813-appb-000006
Figure PCTCN2020120813-appb-000006
S为GNSS无线电信号的传播路线，位置s处的折射率N(s)可以根据Smith-Weintarub方程，通过探空数据在位置s处的气温T(s)、压强P(s)、水汽压e(s)的值，利用下式计算：S is the propagation route of the GNSS radio signal. The refractive index N(s) at position s can be based on the Smith-Weintarub equation, and the air temperature T(s), pressure P(s), and water vapor pressure e at position s through sounding data. The value of (s) is calculated using the following formula:
Figure PCTCN2020120813-appb-000007
Figure PCTCN2020120813-appb-000007
由于在高度超过11km之后，湿分量折射率几乎为0，考虑此因素，在建立大气折射率模型时，应该以此高度为界建立分段的函数模型，由此可以得到分段的大气折射率函数模型如下：Since the refractive index of the wet component is almost 0 after the altitude exceeds 11km, considering this factor, when establishing the atmospheric refractive index model, a segmented function model should be established based on this height, so that the segmented atmospheric refractive index can be obtained. The function model is as follows:
Figure PCTCN2020120813-appb-000008
Figure PCTCN2020120813-appb-000008
其中h为大气层距海平面高度，h T为对流层顶高度，h 0为探空站点的海拔高度；因此对流层的总延迟函数模型为： Where h is the height of the atmosphere from sea level, h T is the height of the tropopause, and h 0 is the altitude of the sounding station; therefore, the total delay function model of the troposphere is:
Figure PCTCN2020120813-appb-000009
Figure PCTCN2020120813-appb-000009
则第n个探空站点的对流层总延迟S ZTD,n为： Then the total tropospheric delay S ZTD of the nth radiosonde station, n is:
Figure PCTCN2020120813-appb-000010
Figure PCTCN2020120813-appb-000010
其中，h 0,n为第n个探空站点的海拔高度，N(h 0,n)第n个探空站点地面处的GNSS无线电信号折射率，N(11000)为距地面11km高度处的折射率，c 1为地面处的折射率衰减系数，c 2是距地面11km高处的折射率衰减系数； Among them, h 0,n is the altitude of the nth sounding station, N(h 0,n ) the refractive index of the GNSS radio signal on the ground of the nth sounding station, and N(11000) is the height of 11km above the ground. Refractive index, c 1 is the refractive index attenuation coefficient at the ground, and c 2 is the refractive index attenuation coefficient at a height of 11km from the ground;
S1.2：计算第n个探空站点的大气延迟A ZHD,n： S1.2: Calculate the atmospheric delay A ZHD,n of the nth sounding station:
本发明采用Saastamoinen模型来计算大气延迟，具体公式见式(5)：The present invention uses the Saastamoinen model to calculate the atmospheric delay, and the specific formula is shown in formula (5):
Figure PCTCN2020120813-appb-000011
Figure PCTCN2020120813-appb-000011
其中P S,n、f(lat n,h 0,n)、lat n分别为第n个探空站点的地面气压、地球自转所引起的重力加速度变化的修正、纬度； Where P S,n , f(lat n ,h 0,n ), lat n are the ground pressure at the nth radiosonde station, the correction of the gravitational acceleration changes caused by the earth's rotation, and the latitude;
第n个探空站点的地球自转所引起的重力加速度变化的修正为：The correction of the change in gravitational acceleration caused by the rotation of the earth at the nth sounding station is:
f(lat n,h 0,n)＝1-0.00266cos2lat n-0.00028h 0,n。 f(lat n ,h 0,n )=1-0.00266cos2lat n -0.00028h 0,n .
S1.3：计算第n个探空站点的对流层湿延迟真值T ZWD,n为： S1.3: Calculate the true value of the tropospheric wet delay T ZWD of the nth sounding station, where n is:
T ZWD,n＝S ZTD,n-A ZHD,n T ZWD,n =S ZTD,n -A ZHD,n
由于数据量较大，本实施例采用编程的方式实现数据下载、读取、拟合与计算，语言为java。考虑到构建无探空数据处的天顶对流层湿延迟模型，因此每个站点的每一天都只选用一条探空数据，且考虑到因为剔除数据的原因，也无法选用每天的00时和12时的平均探空数据，因此本实施例只选用00时的探空数据作为当天的探空数据，同样之后的分析都是基于00时的数据(12时数据的分析原理与00时的相同，便不再叙述)。最终合格的探空数据共有19162个。Due to the large amount of data, this embodiment adopts a programming method to implement data downloading, reading, fitting and calculation, and the language is java. Considering the construction of the zenith tropospheric wet delay model where there is no sounding data, only one sounding data is selected for each day at each station, and it is also not possible to use 00 o'clock and 12 o'clock every day because of the data excluded. Therefore, this example only uses the sounding data at 00 o’clock as the sounding data of the day, and the subsequent analysis is based on the data at 00 o’clock (the analysis principle of the data at 12 o’clock is the same as that at 00 o’clock. No longer described). A total of 19,162 radiosonde data were finally qualified.
S2：建立对流层湿延迟抛物线函数模型；S2: Establish a parabolic function model of tropospheric wet delay;
为更能描述ZWD的时间变化规律首先作86个站点所有数据的ZWD时间变化图如图2所示。由图2可发现，ZWD值在一年中呈现从冬季由低逐渐升高，到夏季时达到最高值，再逐渐降低，变化幅度范围基本在0～400mm。且每年的上升与下降的程度基本相同，变化曲线几何图形与“抛物线函数”最为接近。根据ZWD的“二次函数”时间变化规律，设立一个计算对流层湿延迟的抛物线函数方程。在不考虑闰年的情况下，该抛物线函数模型如式(6)所示：In order to better describe the time change law of ZWD, first make the ZWD time change diagram of all the data of 86 stations as shown in Figure 2. It can be found from Figure 2 that the ZWD value gradually increases from low in winter, reaches the highest value in summer, and then gradually decreases. The range of change is basically 0-400mm. And the annual rise and fall are basically the same, and the geometry of the change curve is the closest to the "parabolic function". According to the time change law of the "quadratic function" of ZWD, a parabolic function equation is established to calculate the tropospheric wet delay. Without considering leap years, the parabolic function model is shown in equation (6):
Figure PCTCN2020120813-appb-000012
Figure PCTCN2020120813-appb-000012
式(6)中，a、b和c分别为模型参数，doy为年积日，M表示抛物线边界时的doy值。为便于模型的拟合，将b和M分别取值28和211。In formula (6), a, b, and c are model parameters respectively, doy is the accumulated days per year, and M is the value of doy at the boundary of the parabola. In order to facilitate the fitting of the model, the values of b and M are 28 and 211 respectively.
式(6)所表示的模型是考虑了所有站点的共性——周期时间变化。为了考虑到每个站点自身的特点，再加入其空间参数。ZWD的振幅AZWD和年均值KZWD与站点的纬度lat和海拔h 0都有较强的负相关，因此可以假设a＝Alat+Bh 0+C，c＝A'lat+B'h 0+C'，对式(6)进行修正，建立对流层湿延迟抛物线函数模型： The model represented by equation (6) takes into account the commonality of all stations-cycle time variation. In order to take into account the characteristics of each site, its spatial parameters are added. The amplitude AZWD of ZWD and the annual mean KZWD have a strong negative correlation with the latitude lat and altitude h 0 of the site. Therefore, it can be assumed that a=Alat+Bh 0 +C, c=A'lat+B'h 0 +C' , Revise the formula (6), establish the tropospheric wet delay parabolic function model:
Figure PCTCN2020120813-appb-000013
Figure PCTCN2020120813-appb-000013
其中，Q ZWD为对流层湿延迟计算值，lat为纬度值，h 0为海拔高度值，doy为年积日，A,B,C和A′,B′,C′均为模型系数； Among them, Q ZWD is the calculated value of tropospheric wet delay, lat is the latitude value, h 0 is the altitude value, doy is the accumulated days, and A, B, C and A′, B′, C′ are model coefficients;
S3：将S1中获取的探空站点的对流层湿延迟真值、年积日、纬度值、海拔高度值代入对流层湿延迟抛物线函数模型中，确定各项系数，得到目标区域内对流层湿延迟抛物线函数模型(记作QZWD模型)；S3: Substitute the true value of the tropospheric wet delay, annual accumulated days, latitude, and altitude values of the sounding station obtained in S1 into the tropospheric wet delay parabolic function model, determine various coefficients, and obtain the tropospheric wet delay parabolic function in the target area Model (denoted as QZWD model);
本实施例使用2013年-2017年中国区域86个探空站点的ZWD真值进行拟合，采用最小二乘法确定各项系数，拟合精度38.8mm，得到的中国区域内纬度为lat，海拔高度为h 0处的对流层湿延迟抛物线函数模型中的系数为： This example uses the true ZWD values of 86 radiosonde stations in China from 2013 to 2017 for fitting. The least squares method is used to determine the coefficients. The fitting accuracy is 38.8mm. The obtained latitude in China is lat and the altitude is The coefficients in the parabolic function model of the tropospheric wet delay at h 0 are:
Figure PCTCN2020120813-appb-000014
Figure PCTCN2020120813-appb-000014
S4：获取目标区域内待测地的纬度值、海拔高度值和年积日，根据S3确定的目标区域内对流层湿延迟抛物线函数模型得到待测地的对流层湿延迟计算值。S4: Obtain the latitude value, altitude value and annual accumulated days of the ground to be measured in the target area, and obtain the calculated value of the tropospheric wet delay in the target area determined by S3 according to the parabolic function model of the tropospheric wet delay in the target area.
为验证QZWD模型的可靠性，使用同样是无探空数据的EGNOS-ZWD模型(记作ZWD(E))进行对比。模型精度使用平均偏差BIAS和均方根误差RMSE作为指标，比较2013-2017年两种模型每年的精度对比见表2：In order to verify the reliability of the QZWD model, the same EGNOS-ZWD model without sounding data (denoted as ZWD(E)) was used for comparison. The accuracy of the model uses the average deviation BIAS and the root mean square error RMSE as indicators. The comparison of the accuracy of the two models from 2013 to 2017 is shown in Table 2:
表2 2013-2017年两种ZWD模型的精度对比(单位:mm)Table 2 Accuracy comparison of the two ZWD models from 2013 to 2017 (unit: mm)
Figure PCTCN2020120813-appb-000015
Figure PCTCN2020120813-appb-000015
从表2中可以看出：It can be seen from Table 2:
(1)2013-2017年两种模型的每年平均偏差值浮动变化都不大，中误差变动也不超过15mm，说明两种模型都是比较稳定的。(1) From 2013 to 2017, the annual average deviation of the two models fluctuates little, and the median error does not exceed 15mm, indicating that the two models are relatively stable.
(2)平均偏差方面，ZWD(E)模型的平均偏差平均值为-46.5mm，说明ZWD(E)模型运用在中国区域有明显的***误差；而QZWD模型的平均偏差平均值只有-1.1mm，说明使用中 国站点的ZWD值进行拟合模型，更能有效的削弱模型的***误差。(2) In terms of average deviation, the average average deviation of the ZWD(E) model is -46.5mm, indicating that the ZWD(E) model has obvious systematic errors when used in China; while the average average deviation of the QZWD model is only -1.1mm , Which shows that using the ZWD value of the Chinese site to fit the model can more effectively reduce the systematic error of the model.
(3)中误差方面，ZWD(E)模型中误差平均值约±52.3mm；相比之下，QZWD模型的中误差平均值为±32.7mm，比ZWD(E)模型提高了约37.5％。(3) In terms of medium error, the average error of the ZWD(E) model is about ±52.3mm; in contrast, the average error of the QZWD model is ±32.7mm, which is about 37.5% higher than that of the ZWD(E) model.
通过2013-2017年数据拟合出QZWD模型后，再用2018年的数据对QZWD模型进行精度验证，并与ZWD(E)模型对比，结果见表3：After fitting the QZWD model with the data from 2013 to 2017, the accuracy of the QZWD model was verified with the data from 2018 and compared with the ZWD(E) model. The results are shown in Table 3:
表3两种ZWD模型的中误差对比(单位:mm)Table 3 Comparison of the median errors of the two ZWD models (unit: mm)
模型Model 内符合精度Internal coincidence accuracy 外符合精度External coincidence accuracy
ZWD(E)ZWD(E) ———— ±53.6±53.6
QZWDQZWD ±32.7±32.7 ±32.1±32.1
表3可以看出：2018年QZWD模型的精度比ZWD(E)模型提高了约40.1％。从2013-2018年的数据来看，每年QZWD模型的精度均优于ZWD(E)模型，因此从整体来看QZWD模型精度是比ZWD(E)模型更为适合中国区域的无气象参数ZWD模型。Table 3 shows that the accuracy of the QZWD model in 2018 is about 40.1% higher than that of the ZWD(E) model. From the data of 2013-2018, the accuracy of the QZWD model is better than that of the ZWD(E) model every year. Therefore, on the whole, the accuracy of the QZWD model is more suitable than the ZWD(E) model for the non-weather parameter ZWD model in China. .
再从单个站点来比较两种模型的精度，为此选取Harbian站点。如表4为2013-2018年Harbian站点三种ZWD模型的平均偏差BIAS和均方根误差RMSE。如图3为2013-2018年Harbian站点ZWD(E)模型和QZWD模型偏差值两两对比的时间序列图。Then compare the accuracy of the two models from a single site, and select the Harbian site for this purpose. As shown in Table 4, the average deviation BIAS and the root mean square error RMSE of the three ZWD models on the Harbian site from 2013 to 2018. Figure 3 shows the time series of the comparison of the deviation values of the ZWD(E) model and the QZWD model of the Harbian site from 2013 to 2018.
表4 2013-2018年Harbian站点两种ZWD模型的精度对比(单位:mm)Table 4 Accuracy comparison of the two ZWD models on the Harbian site from 2013 to 2018 (unit: mm)
Figure PCTCN2020120813-appb-000016
Figure PCTCN2020120813-appb-000016
对比两种模型可知，ZWD(E)模型运用在Harbin站点平均偏差的平均值为-51.1mm，说明ZWD(E)模型运用在Harbin站有***误差；中误差平均值为±56.3mm，精度较低。而QZWD模型的平均偏差的平均值仅为0.7mm，几乎没有***误差；中误差平均值为±29.5mm，说明QZWD模型运用在Harbin站比ZWD(E)模型精度有很大提高，平均提高47.6％。Comparing the two models, it can be seen that the average deviation of the ZWD(E) model used at the Harbin station is -51.1mm, indicating that the ZWD(E) model used at the Harbin station has a systematic error; the average error is ±56.3mm, which is more accurate Low. The average deviation of the QZWD model is only 0.7mm, and there is almost no systematic error; the average error is ±29.5mm, indicating that the accuracy of the QZWD model used at Harbin station is much higher than that of the ZWD(E) model, with an average increase of 47.6 %.
从以上的几个结论中可以看出，无论是从整体还是单个站点来看，QZWD模型的精度较ZWD(E)模型精度都有很大提高。因此对于中国区域，可以利用本发明提出的方法计算对流层湿延迟。From the above conclusions, it can be seen that the accuracy of the QZWD model is much higher than that of the ZWD(E) model, no matter from the perspective of the whole or a single site. Therefore, for the Chinese region, the method proposed by the present invention can be used to calculate the tropospheric wet delay.

Claims (5)

  1. 一种基于抛物线的区域对流层湿延迟计算方法，其特征在于，包括：A method for calculating regional tropospheric wet delay based on parabola, which is characterized in that it includes:
    S1：采集目标区域中每个探空站点的探空数据、年积日和空间位置数据，根据采集到的探空数据计算每个探空站点的对流层湿延迟真值T ZWD；所述空间位置数据为纬度值、海拔高度值； S1: Collect sounding data, annual accumulated days and spatial position data of each sounding station in the target area, and calculate the true value of tropospheric wet delay T ZWD for each sounding station based on the collected sounding data; the spatial position The data is the latitude value and the altitude value;
    S2：建立对流层湿延迟抛物线函数模型：S2: Establish a parabolic function model of tropospheric wet delay:
    Figure PCTCN2020120813-appb-100001
    Figure PCTCN2020120813-appb-100001
    其中，Q ZWD为对流层湿延迟计算值，lat为纬度值，h 0为海拔高度值，doy为年积日，A,B,C和A′,B′,C′均为模型系数； Among them, Q ZWD is the calculated value of tropospheric wet delay, lat is the latitude value, h 0 is the altitude value, doy is the accumulated days, and A, B, C and A′, B′, C′ are model coefficients;
    S3：将S1中获取的探空站点的对流层湿延迟真值、年积日、纬度值、海拔高度值代入对流层湿延迟抛物线函数模型中，确定各项系数，得到目标区域内对流层湿延迟抛物线函数模型；S3: Substitute the true value of the tropospheric wet delay, annual accumulated days, latitude, and altitude values of the sounding station obtained in S1 into the tropospheric wet delay parabolic function model, determine various coefficients, and obtain the tropospheric wet delay parabolic function in the target area Model;
    S4：获取目标区域内待测地的纬度值、海拔高度值和年积日，根据S3确定的目标区域内对流层湿延迟抛物线函数模型得到待测地的对流层湿延迟计算值。S4: Obtain the latitude value, altitude value and annual accumulated days of the ground to be measured in the target area, and obtain the calculated value of the tropospheric wet delay in the target area determined by S3 according to the parabolic function model of the tropospheric wet delay in the target area.
  2. 根据权利要求1所述的区域对流层湿延迟计算方法，其特征在于，所述步骤S1中计算第n个探空站点的对流层湿延迟真值T ZWD,n的步骤包括： The method for calculating regional tropospheric wet delay according to claim 1, wherein the step of calculating the true value of the tropospheric wet delay T ZWD,n of the nth radiosonde station in the step S1 comprises:
    S1.1：计算第n个探空站点的对流层总延迟S ZTD,n： S1.1: Calculate the total tropospheric delay S ZTD,n of the nth sounding station:
    Figure PCTCN2020120813-appb-100002
    Figure PCTCN2020120813-appb-100002
    其中，h 0,n为第n个探空站点的海拔高度，N(h 0,n)第n个探空站点地面处的GNSS无线电信号折射率，N(11000)为距地面11km高度处的折射率，c 1为地面处的折射率衰减系数，c 2是距地面11km高处的折射率衰减系数； Among them, h 0,n is the altitude of the nth sounding station, N(h 0,n ) the refractive index of the GNSS radio signal at the nth sounding station ground, and N(11000) is the height of 11km above the ground. Refractive index, c 1 is the refractive index attenuation coefficient at the ground, and c 2 is the refractive index attenuation coefficient at a height of 11km from the ground;
    S1.2：计算第n个探空站点的大气延迟A ZHD,n： S1.2: Calculate the atmospheric delay A ZHD,n of the nth sounding station:
    Figure PCTCN2020120813-appb-100003
    Figure PCTCN2020120813-appb-100003
    其中P S,n、f(lat n,h 0,n)、lat n分别为第n个探空站点的地面气压、地球自转所引起的重力加速度变化的修正、纬度； Among them, P S,n , f(lat n ,h 0,n ), lat n are the ground pressure of the nth radiosonde station, the correction of the gravitational acceleration change caused by the earth's rotation, and the latitude;
    S1.3：第n个探空站点的对流层湿延迟真值T ZWD,n为： S1.3: The true value of the tropospheric wet delay T ZWD of the nth sounding station, where n is:
    T ZWD,n＝S ZTD,n-A ZHD,n。 T ZWD,n =S ZTD,n -A ZHD,n .
  3. 根据权利要求1所述的区域对流层湿延迟计算方法，其特征在于，所述步骤S3中采用最小二乘法确定各项系数。The method for calculating regional tropospheric wet delay according to claim 1, characterized in that, in the step S3, a least square method is used to determine various coefficients.
  4. 根据权利要求1所述的区域对流层湿延迟计算方法，其特征在于，中国区域内纬度为lat，海拔高度为h 0处的对流层湿延迟抛物线函数模型： The method for calculating regional tropospheric wet delay according to claim 1, wherein the parabolic function model of tropospheric wet delay at latitude and altitude h 0 in China is:
    Figure PCTCN2020120813-appb-100004
    Figure PCTCN2020120813-appb-100004
    其中的系数为：The coefficients are:
    Figure PCTCN2020120813-appb-100005
    Figure PCTCN2020120813-appb-100005
  5. 根据权利要求2所述的区域对流层湿延迟计算方法，其特征在于，所述步骤S1.2中，第n个探空站点的地球自转所引起的重力加速度变化的修正为：The method for calculating regional tropospheric wet delay according to claim 2, characterized in that, in the step S1.2, the correction of the change in gravitational acceleration caused by the rotation of the earth at the nth radiosonde station is:
    f(lat n,h 0,n)＝1-0.00266cos2lat n-0.00028h 0,n。 f(lat n ,h 0,n )=1-0.00266cos2lat n -0.00028h 0,n .
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