阅读说明：本技术 一种基于双差模式的实时精密时间传递方法 (Real-time precise time transfer method based on double-difference mode ) 是由 涂锐 卢晓春 张鹏飞 张睿 韩军强 范丽红 鲁洋为 于 2020-05-27 设计创作，主要内容包括：本发明涉及时间传递技术领域,具体是涉及一种基于双差模式的实时精密时间传递方法,首先,基于时间主站和用户站的卫星观测数据,建立双差数学模型并约束测站坐标进行解算,获得双差模糊度的浮点解和对应的方差阵,并进行双差模糊度固定；其次,选定参考卫星,并给定该颗卫星站间单差模糊度的基准值,进而基于固定的双差整周模糊度,反算出所有卫星的站间单差模糊度；再后,建立站间单差的数学模型,将反算出的单差模糊度代入到站间单差观测方程,求解两站之间的时差参数,实现实时的时间传递。(The invention relates to the technical field of time transfer, in particular to a real-time precise time transfer method based on a double-difference mode, which comprises the steps of firstly, establishing a double-difference mathematical model and constraining coordinates of a measuring station to carry out resolving based on satellite observation data of a time master station and a user station, obtaining a floating solution of double-difference ambiguity and a corresponding variance matrix, and fixing the double-difference ambiguity; secondly, selecting a reference satellite, giving a reference value of single-difference ambiguity among the satellite stations, and then reversely calculating the single-difference ambiguity among all the satellite stations based on the fixed double-difference integer ambiguity; and then, establishing a mathematical model of single difference between stations, substituting the inversely calculated single difference ambiguity into a single difference observation equation between the stations, solving a time difference parameter between the two stations, and realizing real-time transmission.)

1. A real-time precise time transfer method based on a double difference mode is characterized by comprising the following steps:

and S1, acquiring and preprocessing data: acquiring dual-frequency pseudo-range and phase observation data of satellites on a time master station and a subscriber station and auxiliary data required by data processing; screening the data, detecting the cycle slip and giving a cycle slip detection result;

s2, error correction and model establishment: correcting errors of the data preprocessed in the step S1, and establishing a double-difference observation equation and a random model according to the corrected data;

s3, determining double-difference ambiguity: estimating an initial value of the double-difference ambiguity and a corresponding variance-covariance matrix based on the double-difference observation equation and the random model in the step S2, and then fixing the double-difference ambiguity;

s4, determining a single difference ambiguity reference value: selecting a satellite with the largest altitude angle and no cycle slip as a reference satellite, and giving a single-difference ambiguity reference value of the satellite;

s5, determining the single-difference ambiguity between stations and establishing a mathematical model of the single-difference between stations: inversely calculating the interstation single-difference ambiguities of all public satellites based on the double-difference ambiguities determined in the step S3 and the single-difference ambiguity reference values determined in the step S4, and establishing an interstation single-difference mathematical model according to the interstation single-difference ambiguities;

and S6, determining the time difference parameter: and calculating a time difference parameter based on the single difference mathematical model established in the step S5 to realize real-time transmission.

2. The method according to claim 1, wherein in step S1, the auxiliary parameters include broadcast ephemeris, antenna phase center, earth rotation parameters, accurate coordinates of the survey station, and tidal parameters.

3. The method according to claim 1, wherein the step S2 of correcting the error of the data comprises: relativity, tide, antenna phase center, troposphere and earth rotation error correction;

the relativistic and tidal corrections were corrected using the model specified in the IERS Conventions 2010, the antenna phase center correction was corrected using the igs14.atx model; tropospheric corrections were corrected using the Saastamoinen model and earth rotation error corrected using the IERS EOP C04 model.

4. The method according to claim 1, wherein in step S2, the double-difference observation equation of the satellite is established based on the inter-station and inter-satellite differences of all public satellites, and is specifically expressed by formula (1):

the random model of the satellite is established based on the altitude angle of the satellite, and is specifically represented by the formula (2):

in the formula: p is a pseudo-range value, phi is a phase observation value, A is a unit direction vector between the station and the satellite, x is a three-dimensional baseline vector,

5. The method as claimed in claim 1, wherein the step S3 is performed by estimating the correlation data by: carrying out strong constraint estimation on the coordinate parameters of the observation station; carrying out random walk estimation on troposphere residual errors; and under the condition that the double-difference ambiguity is continuous and has no cycle slip, the double-difference ambiguity is taken as a constant estimation, and the double-difference ambiguity is reinitialized when the cycle slip exists.

6. The method according to claim 1, wherein the mathematical model of single difference between stations is as follows:

the random model is the same as formula (2);

wherein C is the light velocity, dt is the time difference, Delta is the single difference between stations, and other symbol meanings are the same as those in formula (1).

Technical Field

The invention relates to the technical field of time transfer, in particular to a real-time precise time transfer method based on a double-difference mode.

Background

The time transfer method based on the satellite navigation system has the characteristics of low cost, good continuity, all weather, all-time and the like and is widely applied. Satellite time transfer methods based on pseudo-range observation include common view method (CV) and full view method (AV); satellite time transmission methods based on carrier phase observation include a non-differential precise point positioning method (PPP) and an inter-station single difference method (SD). Since carrier phase observation accuracy is 100 times that of pseudo range observation, a time transfer technique based on a carrier phase observation value is currently the mainstream technique. However, the current carrier phase time transfer method has three limitations, one is that a non-difference or single difference mode is adopted, many errors in an observed value are difficult to process efficiently, and the precision of time transfer is influenced; secondly, the carrier phase ambiguity does not have the integer cycle characteristic in the current time transfer calculation, the integer cycle ambiguity can not be fixed, and the convergence and the precision of parameter estimation are influenced; thirdly, the current carrier phase time transfer methods are all in post-processing modes, need precise ephemeris support and are inconvenient for real-time application.

How to efficiently correct observation errors, improve the precision of time transfer, realize the normalization and fixation of the ambiguity of the carrier phase observation value, further accelerate the convergence rate of parameter estimation, and simultaneously, the method is easy to operate in real time and has important application value for real-time service.

Disclosure of Invention

In order to overcome the defects of the prior art and supplement the prior art, the invention provides a real-time precise time transfer method based on a double-difference mode. Firstly, based on satellite observation data of a time master station and a user station, establishing a double-difference mathematical model and constraining coordinates of the measurement station to carry out resolving to obtain a floating solution of double-difference ambiguity and a corresponding variance matrix, and fixing the double-difference ambiguity; secondly, selecting a reference satellite, giving a reference value of single-difference ambiguity among the satellite stations, and then reversely calculating the single-difference ambiguity among all the satellite stations based on the fixed double-difference integer ambiguity; and then, establishing a mathematical model of single difference between stations, substituting the inversely calculated single difference ambiguity into a single difference observation equation between the stations, solving a time difference parameter between the two stations, and realizing real-time transmission. The specific technical scheme is as follows:

first, data acquisition. And acquiring dual-frequency pseudo-range and phase observation data of satellites on a time master station and a subscriber station and auxiliary data required by data processing, wherein the auxiliary data comprises broadcast ephemeris, an antenna phase center, earth rotation parameters, accurate coordinates of a survey station and tide parameters.

And secondly, preprocessing data. Firstly, checking the quality of all data, eliminating gross errors, deleting data without satellite ephemeris or incomplete observation values, deleting satellite data which is not observed in public to obtain clean and available data, detecting cycle slip, and giving a cycle slip detection result.

And thirdly, correcting an error model. And (4) correcting relativity, tide, antenna phase center, troposphere and earth rotation error of the preprocessed clean data. Where relativity and tide corrections were corrected using the model specified in IERS convections 2010, antenna phase center correction was corrected using the igs14.atx model, troposphere correction was corrected using the Saastamoinen model, and earth rotation error correction was corrected using the IERS EOP C04 model. It is noted that for short distance temporal delivery, these error corrections are negligible due to the strong spatial correlation of the errors.

And fourthly, establishing a double-difference mathematical model. For all public satellites, performing inter-station and inter-satellite difference to form a double-difference observation equation as follows:

in the formula: p is pseudo range value, phi is phase observed value, A isUnit direction vector between the satellites, x is a three-dimensional baseline vector,the method is characterized in that the method is a double difference, R is a main station, U is a user station, i and j represent different satellite numbers, trp represents troposphere residual errors, F is a projection coefficient, rho is a station satellite geometric distance, and model represents the sum of various modeling errors and represents observation noise.

And a stochastic model was determined as follows:

a is the precision of the observed value, the pseudo-range observed value is generally set to be 0.2-0.3 m, the phase observed value is generally set to be 0.002-0.003 m,

is the average value of the satellite altitude angles of the two stations, and the unit is radian.

And fifthly, double-difference resolving and double-difference ambiguity fixing. And (3) performing least square solution based on the double-difference observation equation (1) and the random model (2), and estimating to obtain initial values of the parameters and corresponding variance-covariance matrixes. Wherein, the coordinate of the measuring station is subjected to strong constraint estimation; estimating tropospheric residual random walk; and under the condition that the double-difference ambiguity is continuous and has no cycle slip, the double-difference ambiguity is taken as a constant estimation, and the double-difference ambiguity is reinitialized when the cycle slip exists. And based on the estimated bivariate ambiguity initial value and the corresponding variance-covariance matrix, performing bivariate ambiguity fixing by adopting a Lambda algorithm.

And sixthly, determining a reference star and a single-difference ambiguity standard. And selecting the satellite with the largest altitude angle and no cycle slip as a reference satellite, and giving a single-difference ambiguity reference value of the satellite.

And seventhly, performing inverse calculation on the single-difference ambiguity between the stations. And inversely calculating the inter-station single-difference ambiguity of all the public satellites based on the fixed double-difference ambiguity in the fifth step and the single-difference ambiguity reference value given in the sixth step.

And eighthly, establishing a single difference mathematical model between stations. The single difference function model is as follows:

in the formula, C is the light velocity, dt is the time difference, delta represents the single difference between stations, and other symbol meanings are the same as those in the formula (1); the stochastic model is the same as equation (2).

And step nine, calculating time difference parameters. And performing least square calculation based on the mathematical model of the single difference to obtain a time difference parameter. The method comprises the following steps of coordinate parameter strong constraint, troposphere residual random walk estimation, single difference ambiguity direct substitution and time difference parameter white noise estimation.

Compared with the prior carrier phase time transfer method, the method has the beneficial effects that:

(1) compared with the conventional carrier phase time transfer method in which the error of a non-differential or single-differential observation value is difficult to be efficiently corrected, the method can well eliminate or weaken common error or non-modeling error by establishing a double-differential observation equation, improve the correction level of the error of the observation value and further improve the time transfer precision.

(2) Compared with the conventional carrier phase time transfer method in which the ambiguity does not have the whole-cycle characteristic, the method uses the double-difference observation value, realizes the normalization of the ambiguity, can fix the ambiguity, not only accelerates the convergence speed of parameter estimation, but also improves the time transfer precision.

(3) The technical method provided by the invention adopts a double-difference model, is similar to an RTK positioning method, can adopt a broadcast ephemeris for processing, and is convenient for real-time application.

Drawings

FIG. 1 is a flow chart of the real-time precise time transfer technique based on double-difference mode of the present invention;

fig. 2 is a comparison graph of time difference sequences acquired by an observation station of the present invention.

In fig. 2: line a is the time transfer result using the ephemeris (PPP) and line B is the time transfer result using the broadcast ephemeris of the present invention.

Detailed Description

To further illustrate the manner in which the present invention is made and the effects achieved, the following description of the present invention will be made in detail and completely with reference to the accompanying drawings.