CN114167457A - GNSS system time deviation monitoring and evaluating method - Google Patents

GNSS system time deviation monitoring and evaluating method Download PDF

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Publication number
CN114167457A
CN114167457A CN202111406411.7A CN202111406411A CN114167457A CN 114167457 A CN114167457 A CN 114167457A CN 202111406411 A CN202111406411 A CN 202111406411A CN 114167457 A CN114167457 A CN 114167457A
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receiver
time
time difference
monitoring
gnss system
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刘峰宇
王宇谱
薛申辉
胡彩波
赵鹤
李博宇
程梦飞
曹湘君
许普润
李跃跃
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People's Liberation Army 61081 Unit
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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
    • G01S19/13—Receivers
    • G01S19/23—Testing, monitoring, correcting or calibrating of receiver elements
    • G01S19/235—Calibration of receiver components
    • 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
    • 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
    • G01S19/072—Ionosphere corrections
    • 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
    • G01S19/13—Receivers
    • G01S19/20—Integrity monitoring, fault detection or fault isolation of space segment

Abstract

The invention relates to the technical field of navigation, in particular to a GNSS system time deviation monitoring and evaluating method, which comprises the following steps of S01: building a GNSS system time difference monitoring platform; step S02: correcting clock error of the receiver; step S03: preprocessing data, namely preprocessing the time difference data obtained by direct measurement; step S04: and analyzing, evaluating and forecasting the time difference, and carrying out analysis and evaluation after preprocessing the measured time difference data. By adopting the method, the time deviation monitoring and evaluation of the time of the ground time frequency source and the satellite navigation system or the time deviation monitoring and evaluation between different satellite navigation systems are realized by building the GNSS time deviation monitoring platform which has high measurement precision, can monitor in real time and is suitable for system monitoring, evaluation and prediction and is based on the pulse-per-second measurement model, and a time difference prediction product is generated.

Description

GNSS system time deviation monitoring and evaluating method
Technical Field
The invention relates to the technical field of navigation, in particular to a GNSS system time deviation monitoring and evaluating method.
Background
With the popularization and development of satellite navigation applications, the superiority of multi-mode navigation is gradually recognized by people, and becomes one of the important development directions of satellite navigation systems, and has a larger development space. Multimode satellite navigation techniques refer to combining two or more satellite navigation systems together in a suitable manner to take advantage of their complementary characteristics in performance to achieve higher navigation performance than when either system is used alone. In multimode satellite navigation, different satellite navigation systems use different system times, and although all the systems trace to coordinated Universal Time (UTC), due to different reference frames of the systems, different system time generation methods and the like, the UTC values obtained by tracing different GNSS system times have certain deviation, which is called GNSS system time deviation, and is called system time difference (or time difference) for short. The system time difference changes along with the time, and it is one of the key problems that must be solved to realize the multi-navigation system combined navigation positioning and precisely determine the system time deviation among the navigation systems. In the existing satellite navigation system, a detailed time difference monitoring scheme is established between GALILEO and GPS; the time gazette of the international bureau of metering issues the difference between GPST/glonast and UTC, but the time difference data information thereof is a post-processing result and is not transmitted in real time through a navigation message.
Disclosure of Invention
The invention provides a method for monitoring and evaluating time deviation of different satellite navigation systems.
In order to solve the above technical problem, a GNSS system time offset monitoring and evaluating method of the present invention includes the following steps,
step S01: a GNSS system time difference monitoring platform is built, a time interval counter and a time difference monitoring computer build the GNSS system time deviation monitoring platform based on a pulse per second measurement model by utilizing a ground time frequency source and a multi-frequency GNSS common-view receiver;
step S02: correcting a receiver clock error, and reasonably setting a positioning model, a motion mode, an ionosphere model, a troposphere model, an anti-multipath model, an antenna type and a carrier smoothing pseudo range parameter of the receiver;
step S03: preprocessing data, namely preprocessing time difference data obtained by direct measurement, including error correction of discrete errors of a receiver signal, measurement gross error elimination and data filtering smoothing;
step S04: and performing time difference analysis evaluation and forecast, and performing analysis evaluation after preprocessing the measured time difference data, wherein the analysis evaluation comprises accuracy evaluation, drift rate evaluation, stability evaluation and uncertainty evaluation.
Preferably, in the step S01, time difference monitoring platforms of different working modes are set up according to different requirements of time difference monitoring, where the working modes include a monitoring mode and a mutual measurement mode.
Preferably, the GNSS system time difference monitoring platform specifically includes the following:
the ground frequency source provides a reference signal for the multi-frequency GNSS common-view receiver and the time interval counter, and provides a ground standard 1PPS signal for time difference comparison;
the multi-frequency GNSS common-view receiver consists of an antenna and a receiver, wherein the antenna is arranged at an appropriate position without shielding outdoors and is connected to an antenna interface of the receiver through an antenna cable;
the time interval counter is used for measuring the time difference comparison value of signals of the two input channels in real time and outputting data into the time difference monitoring computer through a serial port;
and the time difference monitoring computer is connected with the multi-frequency GNSS common-view receiver and the time interval counter through an interface and is provided with time difference monitoring processing software.
Preferably, the step S02 specifically includes,
(1) the position coordinates of the antenna are measured in advance through geodetic measurement or precise single-point positioning, a receiver is arranged in the antenna, and the clock error calculation error is reduced by improving the degree of freedom of equation solution;
(2) starting a receiver SBAS positioning mode, and correcting satellite ephemeris error and satellite clock error by using a broadcast message of an SBAS satellite;
(3) starting a dual-frequency positioning mode, and eliminating ionosphere errors by utilizing the ionosphere-free combined observed quantity;
(4) setting a troposphere delay model as Saastamoinen or MOPS, and deducting troposphere errors through the model;
(5) taking appropriate action to suppress multipath effects, including: selecting an Hertz coil antenna, placing the Hertz coil antenna at a high place without shielding, and simultaneously starting a function of a receiver for inhibiting the multipath effect;
(6) selecting and purchasing an antenna type of the authenticated absolute phase center correction model, correctly setting Marker offset parameters, and eliminating an antenna phase center error;
(7) and starting a carrier phase smoothing pseudorange function of the receiver, setting the number of smoothing points to be 300, and reducing pseudorange measurement noise through carrier phase smoothing pseudorange.
Preferably, the calculation formula of the dual-frequency ionosphere-free combined observed value in step S02 is as follows:
Figure BDA0003372675700000031
in the formula: p3The pseudo range is the pseudo range without the combination of the ionized layers;
f1、f2the frequencies of carrier 1 and carrier 2 respectively;
P1、P2pseudo-range observed values of a carrier wave 1 and a carrier wave 2 respectively;
ε3,Prespectively are pseudo-range non-ionosphere combined observed valuesThe noise of (2).
Preferably, the observation equation of the receiver pseudorange and the carrier phase in step S02 is as follows:
P＝ρ(ts,tr)+c(dtr-dts)+dtrop+dion+MP+εP，
Figure BDA0003372675700000041
in the formula, P is a pseudo range observed value; l is a carrier phase observed value; λ is the carrier wavelength; n is the integer ambiguity; t is tsA time of signal transmission for the satellite; t is trA time of receiving a signal for a receiver; dts、dtrRespectively, the clock error of the satellite and the receiver; c is the speed of light; dtrop、dionTropospheric and ionospheric delay amounts, respectively; mP、
Figure BDA0003372675700000042
Respectively the pseudo range and the multipath effect of the carrier phase; epsilonP、
Figure BDA0003372675700000043
Respectively, pseudo range and carrier phase observation noise; ρ (t)s,tr) Is tsSatellite arrival at time trThe geometric distance between the receiver antennas at the time;
the formed carrier phase smoothed pseudorange is as follows:
Figure BDA0003372675700000044
in the formula, Ps,k、Ps,k-1Respectively representing carrier phase smoothing pseudo range values of epoch k and epoch k-1;
Pka pseudorange observation representing epoch k;
Lk、Lk-1respectively representing carrier phase observed values of epoch k and epoch k-1;
m is called asSmoothing time constant, the larger the value of M, the larger PsThe smoother is.
Preferably, the discrete error correction formula in step S03 is as follows:
Tr＝Tm-D，
wherein Tm represents the time difference value measured by the counter, D represents the discrete error of the receiver, and Tr represents the real time difference value;
if the receiver works in the mutual measurement mode, discrete errors of two receivers need to be corrected at the same time, and the correction formula is as follows:
Tr＝Tm+D1-D2，
in the formula, D1Indicating a dispersion error of the door-opening receiver, D2The dispersion error of the door-closed receiver is shown, Tm is the time difference value measured by the counter, and Tr is the real time difference value.
Preferably, the coarse difference elimination of the time difference measurement value in the step S03 specifically includes:
removing gross error based on median method, and carrying out primary difference on time difference data to obtain frequency difference sequence yiWhen difference value yiSatisfies the following conditions:
|yi-m|>n·MAD
namely, determining as a coarse difference value;
in the formula: m is media (y)i)，MAD＝Median{|yi-m/0.6745, n is an adjustment factor set between 3 and 5, and Median represents the Median of a sequence.
Preferably, in step S03, the filtering and smoothing the time difference measurement value specifically includes:
data smoothing based on FIR filter, i.e. using the most recent N in the pastK+1-PIndividual observation values, x being calculated by discrete time convolutionP(n) unbiased FIR filter estimate
Figure BDA0003372675700000051
Figure BDA0003372675700000052
Calculating a high-order observation quantity by using discrete difference:
Figure BDA0003372675700000053
sequentially recursion to obtain each order estimated value of the clock error model
Figure BDA0003372675700000054
Preferably, in step S04, the comprehensive analysis and evaluation of the time difference measurement result specifically includes:
frequency accuracy:
Figure BDA0003372675700000061
frequency drift rate:
Figure BDA0003372675700000062
the Allan variance:
Figure BDA0003372675700000063
correcting Allan variance:
Figure BDA0003372675700000064
hadamard variance:
Figure BDA0003372675700000065
modified hadamard variance:
Figure BDA0003372675700000066
preferably, the analyzing and forecasting the GNSS system time difference in step S04 specifically includes:
and (3) adopting a polynomial model to perform time difference fitting, wherein the formula is as follows:
Figure BDA0003372675700000067
and continuously monitoring the time difference data of the GNSS system, solving fitting parameters of the primary model and the secondary model by a least square method, forecasting the time difference of the GNSS system for 1h and 6h, and evaluating a forecasting result.
Preferably, the step S04 of performing uncertainty evaluation on the fitting residual specifically includes:
the uncertainty of the residual errors of the primary fitting model and the secondary fitting model is respectively calculated by adopting an A-type uncertainty evaluation method, and the calculation formula is as follows:
Figure BDA0003372675700000071
by adopting the method, the time deviation monitoring and evaluation of the time of the ground time frequency source and the satellite navigation system or the time deviation monitoring and evaluation between different satellite navigation systems are realized by building the GNSS time deviation monitoring platform which has high measurement precision, can monitor in real time and is suitable for system monitoring, evaluation and prediction and is based on the pulse-per-second measurement model, and a time difference prediction product is generated.
Drawings
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Fig. 1 is a schematic diagram (monitoring mode) of a GNSS system time difference monitoring platform according to the present invention.
Fig. 2 is a schematic diagram of a GNSS system time difference monitoring platform architecture (inter-measurement mode) according to the present invention.
Fig. 3 is a schematic diagram of the phase center error of the antenna of the receiver according to the present invention.
Fig. 4 is a schematic diagram of the discrete error of the output signal of the receiver according to the present invention.
Fig. 5 is a schematic diagram of the principle of discrete error correction of the output signal of the receiver according to the present invention.
Fig. 6 is a schematic diagram of the FIR filtering algorithm according to the present invention.
Fig. 7 is an overall flow of the time difference monitoring and evaluating scheme according to the present invention.
Detailed Description
The invention designs a GNSS system time deviation monitoring and evaluating method, which comprises the following steps,
step S01: building a GNSS system time difference monitoring platform;
according to different requirements of time difference monitoring, time difference monitoring platforms of different working modes can be set up according to the graph 1 or the graph 2. According to different working modes, the time difference monitoring platform can be divided into a monitoring working mode and a mutual testing working mode when being set up.
And (3) monitoring the working mode: and erecting a GNSS multi-frequency receiver, and setting the output mode of the receiver as the corresponding GNSS system time reproduction. Inputting the ground standard second signal 1PPS into one channel of a high-precision time interval counter, inputting the 1PPS signal output by the multi-frequency GNSS common-view receiver into the other channel of the counter, measuring the time difference of the two channels of 1PPS signals by the time interval counter, and correcting through time delay compensation to obtain the time difference measurement value of the ground time source and the GNSS system time.
And (3) mutual detection working mode: two GNSS multi-frequency common-view receivers are erected simultaneously, the output modes of the two GNSS multi-frequency common-view receivers are set to be the GNSS1 system time recurrence and the GNSS2 system time recurrence respectively, the second signals 1PPS output by the two receivers are input into two measurement channels of a high-precision time interval counter respectively, and the time deviation of the GNSS1 system time and the GNSS2 system time can be obtained directly.
The monitoring working mode can obtain the time difference result between the time of the ground frequency source and the time of the GNSS system, and the mutual measuring mode can obtain the time difference comparison result between any two GNSS system times.
As shown in fig. 1 and 2, the time difference monitoring platform mainly comprises four parts: the ground frequency source, the multi-frequency GNSS common-view receiver, the time interval counter and the time difference monitoring computer are connected through different types of cables and interfaces to form a unified whole.
(1) Ground frequency source
The ground frequency source provides a reference signal for the multi-frequency GNSS common-view receiver and the time interval counter, and provides a ground standard 1PPS signal for time difference comparison.
(2) Multi-frequency GNSS common-view receiver
The multi-frequency common-view receiver is a core component of a monitoring platform and comprises an antenna and a receiver, wherein the antenna is installed at an appropriate position without shielding outdoors and is connected to an antenna interface of the receiver through an antenna cable, and the receiver can be placed at a stable indoor position. The main functions are as follows:
receiving a multi-frequency GNSS satellite navigation signal to obtain a navigation message, and solving a positioning equation by using the navigation message to calculate a time difference between a receiver and a GNSS system, namely a receiver clock error;
adjusting the receiver to output 1PPS signals according to the clock error of the receiver, enabling the output 1PPS signals to track the time of the GNSS system in real time, and connecting to a time interval counter for time difference comparison measurement;
and thirdly, outputting the real-time data record generated by the receiver to a time difference monitoring computer for further processing and application.
(3) Time interval counter
The time interval counter is a time difference measuring device of a monitoring platform, and has the main functions of measuring the time difference comparison value of signals of two input channels in real time and outputting data into a time difference monitoring computer through a serial port.
(4) Time difference monitoring computer
The time difference monitoring computer is a control center and a data center of a monitoring platform, is connected with the multi-frequency GNSS common-view receiver and the time interval counter through an interface, is provided with time difference monitoring processing software, and has the main functions of:
firstly, configuring and monitoring working parameters and working modes of a multi-frequency GNSS common-view receiver;
receiving real-time data of the time interval counter and the multi-frequency common-view receiver and storing the real-time data into a database;
preprocessing, analyzing, evaluating and forecasting time difference comparison data;
and fourthly, visualization and result display of the time difference comparison result.
Step S02: clock error calculation error correction
In a real-time working state, the receiver obtains the receiver clock error by solving a pseudo-range equation, so that the GNSS system time is reproduced, and the accuracy of time difference monitoring directly depends on the accuracy of receiver clock error calculation. In general, receiver pseudorange and carrier phase observation equations may be represented by equations 1 and 2, respectively.
P＝ρ(ts,tr)+c(dtr-dts)+dtrop+dion+MP+εP
(1)
Figure BDA0003372675700000101
In the formulas 1 and 2, P is a pseudo-range observation value (m);
l is a carrier phase observation (m);
λ is the carrier wavelength (m);
n is the integer ambiguity;
ts-a signal time instant(s) for the satellite transmission;
trreceiving a signal instant(s) for a receiver;
dts、dtrsatellite clock error(s) and receiver clock error(s) respectively;
c is the speed of light (m/s);
dtrop、diontropospheric and ionospheric delay amounts (m), respectively;
MP、
Figure BDA0003372675700000102
respectively the pseudo range and the multipath effect (m) of the carrier phase;
εP、
Figure BDA0003372675700000103
respectively, pseudo range and carrier phase observation noise;
ρ(ts,tr) Is tsSatellite arrival at time trThe geometric distance between the receiver antennas at the moment contains the coordinates of the receiver antennas, the satellite orbit and the earth rotation parameters, and the like.
During the positioning process, the receiver antenna coordinates (x, y, z) and the receiver clock difference dtrThe parameters to be solved are all parameters, and in the time service process, the antenna can be fixed, so that the coordinates (x, y, z) of the antenna can be measured in advance in a geodetic measurement or precise single-point positioning mode and the like, and initial parameters of the receiver are embedded, so that the clock error solving error is reduced by increasing the freedom degree of solving equations.
Generally, errors affecting the clock error solving precision comprise satellite related errors, propagation path related errors and receiver related errors, and the related errors can be eliminated and limited by reasonably setting the working parameters and the positioning mode of the receiver, so that the solving precision of the clock error of the receiver is improved.
(1) Satellite error correction
The errors of the satellite terminal which greatly affect the positioning result are mainly satellite ephemeris errors and satellite clock error, for example, a modern GPS satellite, the satellite orbit clock error obtained by broadcasting ephemeris is about 5m, and the satellite clock error is about 8-10 ns. In order to improve pseudo-range positioning accuracy, a positioning mode of a receiver is set to be an SBAS mode, and satellite ephemeris and satellite clock error obtained by broadcast ephemeris are corrected through satellite ephemeris correction numbers, satellite clock error correction numbers and integrity information broadcast by an SBAS satellite. After difference correction, the satellite ephemeris error can be controlled within 2m generally, and the satellite clock error can be controlled below 5 ns.
Meanwhile, due to the effect of earth rotation, two geocentric earth-fixed coordinate systems at the time of signal transmission and the time of signal reception do not coincide any longer in space, thereby causing the position of the satellite to deviate. For example, the GPS signal has an average propagation time of about 78ms, and the resulting change in the satellite position in the coordinate system is about 100m, and the receiver will automatically subtract the effect of the earth rotation when solving the positioning equation.
(2) Ionospheric delay error correction
The ionosphere can refract the navigation signals, so that the phase speed is increased, the group speed is reduced, the influence on the distance measurement is 1-3 m at least and can reach 150m at most. For a single-frequency user, only a physical model can be used for calculating the ionospheric delay, taking the Klobuchar model adopted by the GPS as an example, 50% of the ionospheric delay influence can be generally eliminated, which can reach about 75% in an ideal case, and the error is about 1-5 m. For a multi-frequency receiver, the ionospheric delay contribution of about 95% can be eliminated by the dual-frequency ionospheric-free combination observations, and the error can be reduced to within 1 m. In order to improve the clock error calculation accuracy, an ionosphere correction model of the multi-frequency receiver needs to be set as a dual-frequency model during real-time monitoring.
The calculation formula of the dual-frequency ionosphere-free combined observed value is as follows:
Figure BDA0003372675700000121
in formula 3, P3The pseudo range is the pseudo range without the combination of the ionized layers;
f1、f2the frequencies of carrier 1 and carrier 2 respectively;
P1、P2pseudo-range observed values of a carrier wave 1 and a carrier wave 2 respectively;
ε3,Pand respectively, noise of the pseudo-range non-ionosphere combined observed value.
(3) Tropospheric delay error correction
The troposphere is a non-dispersive medium whose refractive index is independent of the frequency of the electromagnetic wave. The navigation message broadcast by the satellite does not contain a troposphere delay model and parameters, and the receiver generally corrects the troposphere delay through the troposphere delay model through real-time meteorological data. Common tropospheric delay models include Saastamoinen, MOPS, Niell, and others. After calibration, the troposphere delay error in the zenith direction is generally 0.1-1 m. In real-time monitoring, the receiver troposphere correction model is generally set to Saastamoinen or MOPS.
(4) Multipath mitigation
The electromagnetic wave is reflected or reflected for many times and then received by the receiver, so that the multipath effect is caused, and the positioning error is reduced. Multipath effects can be suppressed by a number of measures, including:
firstly, a receiver antenna is arranged at a high place without shielding, so that reflected electromagnetic waves are prevented from entering a receiver;
secondly, a current loop antenna is adopted to inhibit the multipath effect;
and thirdly, starting the APME + function of the receiver to inhibit the multipath effect.
After the mitigation is suppressed by taking effective measures, the observed value can be considered to be substantially unaffected by the multipath effect.
(5) Antenna phase center correction
The reference point for the receiver observations, referred to as the antenna Phase Center (PC), varies with the satellite height and frequency, and can range up to several centimeters.
In practical applications, however, the observed quantity needs to be calibrated according to a relatively fixed Point, namely an Antenna Reference Point (ARP), which generally selects the geometric center of the bottom surface of the antenna.
And the reference point for the receiver position is called Marker and there is sometimes a fixed offset from the ARP. The relative positions of the antennas PC, ARP and marker are shown in fig. 3.
In order to eliminate the influence of the antenna phase center error, the antenna type of an IGS or NGS certified absolute phase center correction model needs to be purchased, the corresponding antenna type is set before the receiver works, and the offset of a Marker relative to a PC is set to be zero, so that the receiver can automatically correct the antenna phase center deviation when a positioning equation is solved.
(6) Carrier phase smoothed pseudorange
Epsilon in formula 1 and formula 2PAnd εLObserved noise representing pseudo-range and carrier phase observations, respectivelyHowever, since the carrier frequency is hundreds of times higher than the pseudo-range random code frequency, epsilonPThe amount of error introduced is generally equivalent to εLHundreds times higher. During continuous observation, the observed quantities of the front and back epochs in the formula 1 and the formula 2 are differentiated, short-term changes of ionospheric delay are ignored, then the delta P and the delta L should be equal theoretically, and the pseudo range and the carrier phase observed quantity can be integrated on the basis of the difference, so that a pseudo range observed quantity which has no ambiguity and is relatively smooth is formed, namely, the carrier phase smoothed pseudo range is calculated by the following formula:
Figure BDA0003372675700000141
in formula 4, Ps,k、Ps,k-1Respectively representing carrier phase smoothing pseudo range values of epoch k and epoch k-1;
Pka pseudorange observation representing epoch k;
Lk、Lk-1respectively representing carrier phase observed values of epoch k and epoch k-1;
m is called a smoothing time constant, and the larger the value of M is, the larger P issThe smoother is.
By starting the function of smoothing the pseudo range of the carrier phase of the receiver and setting M to be 300, the receiver gradually smoothes the pseudo range observation value, so that the pseudo range observation noise can be reduced, and the clock error resolving precision can be improved.
Step S03: preprocessing measurement data;
the measured data preprocessing comprises three steps of discrete error correction, measurement gross error elimination and FIR filtering smoothing.
(1) Discrete error correction
The receiver output signal dispersion error refers to the dispersion deviation between the 1PPS signal reproduced by the receiver and the actual GNSS system second signal. While the receiver is in tracking mode, although its output 1PPS signal is set to be synchronized to the GNSS system time, since the actual 1PPS pulse generated by the receiver is generated based on the latest "tick" flag of the receiver's internal clock, it still has some error from the true GNSS system time, and the relationship between them is shown in fig. 4.
In the time difference estimation analysis, the discrete error between the 1PPS signal generated by the receiver and the true 1PPS signal of the GNSS system must be corrected and compensated, the correction process is as shown in fig. 5, Tm represents the time difference measured by the counter, D represents the discrete error of the receiver (the GNSS system is positive in time and can be read from the receiver data file), and Tr represents the true time difference, and then:
Tr＝Tm-D (5)
in the time difference monitoring process, the value D is obtained from the data stream of the receiver in real time, and then the real value Tr of the time difference monitoring can be obtained by calculating with the real value Tm of the counter according to the formula 5. If the receiver works in the mutual measurement mode, discrete errors of two receivers need to be corrected at the same time, and the correction formula is as follows:
Tr＝Tm+D1-D2 (6)
in formula 6, D1Indicating a dispersion error of the door-opening receiver, D2Represents the dispersion error of the door-closed receiver, and Tr and Tm have the same meaning as equation 5.
(2) Measurement gross error rejection
In the long-term measurement process, measurement gross errors are inevitably generated, the gross errors are required to be detected and removed before time difference analysis and evaluation, and a median Method (MAD) can be adopted for the gross errors. Specifically, the time difference data is differentiated once to obtain a frequency difference sequence yiWhen difference value yiSatisfies the following conditions:
|yi-m|>n·MAD (7)
that is, it is determined as a coarse difference, where m is media (y) in equation 7i)，MAD＝Median{|yi-m/0.6745, n is an adjustment factor that can be set between 3 and 5, and Median represents the Median of a sequence.
(3) FIR filtering smoothing
The filtering smoothing is an effective method for suppressing noise, the GNSS system time deviation sequence contains superposition of various noises, the characteristic of the GNSS system time deviation sequence cannot be regarded as white noise, and a FIR filter commonly used for atomic clock time data processing can be adopted for data smoothing.
In general, the time bias model between different GNSS systems can be expressed by taylor polynomials, so that within the range of N points where the starting N is 0, the taylor polynomial of the time bias model is expressed as:
Figure BDA0003372675700000161
in formula 8, n is 0,1n-tn-1Is the time step, tnIs a discrete unit of time, xl+1(0)，l∈[0,K]，x1Refers to the time offset, x2Means frequency deviation, x3Refers to the rate of frequency drift, and is,
Figure BDA0003372675700000167
refers to receiver clock noise induced bias. The degree K is the number of filters in the N-point range determined by the clock characteristics, and typically, for example, K is 0 for a cesium clock, K is 1 for a rubidium clock, K is 1 or 2 for a crystal oscillator, and K is 3 for a crystal oscillator with low accuracy.
Due to the influence of random errors of the hardware of the receiver, the actually measured system time deviation value is as follows:
ξ1(n)＝x1(n)+ν(n) (9)
v (n) in formula 9 is an error caused by hardware delay and measurement noise of the receiver, and the receiver is accessed with a high-precision external frequency standard in practical application
Figure BDA0003372675700000168
Is much less than v (n), i.e.
Figure BDA0003372675700000162
So can neglect
Figure BDA0003372675700000169
When estimating the clock state by using the unbiased FIR filter algorithm, it is necessary to obtain the estimator of the clock state x (n)
Figure BDA0003372675700000163
And the observed quantity xi (n) ═ xi1(n)，ξ2(n)，...，ξM(n)]TP component xi ofP(n) as an estimator
Figure BDA0003372675700000164
Has a relative discrete time deviation of
Figure BDA0003372675700000165
Using the last NK+1-PPoint, xP(n) unbiased FIR filter estimate
Figure BDA0003372675700000166
Obtained by discrete-time convolution operations
Figure BDA0003372675700000171
C in formula 11PIs a discrete convolution operator, hl(i,Nl)，l∈[0,K]Is the convolution coefficient in the unbiased FIR filter, and the calculation formula is:
Figure BDA0003372675700000172
Figure BDA0003372675700000173
Figure BDA0003372675700000174
taking K as an example for 1 in the filtering process of the unbiased FIR filter, firstly, the observed quantity is measured at N by directly obtained first-order observed quantity1Coefficient of convolution h within range1(i,N1) Performing convolution to obtain a first-order state estimator
Figure BDA0003372675700000175
Then use
Figure BDA0003372675700000176
Calculating to obtain second-order observed quantity, and using N2Second order observations, with convolution system h0(i,N0) Performing convolution calculation to obtain second-order state estimator
Figure BDA0003372675700000177
By analogy, the principle is shown in fig. 6.
Step S04: analyzing, evaluating and forecasting the time difference;
the time difference measurement data can be used for time difference analysis evaluation and forecast research after being subjected to data preprocessing. According to the difference of the receiver reappearing the GNSS system, the time deviation between the ground time-frequency source and the GNSS system can be analyzed and evaluated. Meanwhile, the time deviation value of any two GNSS system times can be directly obtained through an inter-measurement working mode for analysis and evaluation.
The overall flow of the GNSS system time difference monitoring evaluation is shown in fig. 7.
(1) Evaluation of comprehensive Properties
And the comprehensive performance evaluation is to evaluate the frequency accuracy, the frequency drift frequency and the frequency stability of the measurement result, wherein the frequency accuracy requires to calculate the maximum value and the average value of the relative frequency deviation, the frequency drift frequency requires to give corresponding linearity, and the frequency stability requires to calculate the Allen variance, correct the hadamard variance and correct the hadamard variance.
Let τ0For measuring time intervals, τ ═ m τ0Smoothing time calculated for stability, m is smoothing factor, xiFor measuring time difference data sequences, N is the number of time difference sequences, N ═ floor (N/m), floor is the largest integer not greater than a given value, yi＝[xi-xi-1]/τ0Is the frequency difference data. The frequency accuracy is calculated as:
Figure BDA0003372675700000181
the frequency drift rate calculation formula is:
Figure BDA0003372675700000182
in the formula 16, D is a frequency drift rate,
Figure BDA0003372675700000183
is a relative frequency deviation yiMean value of (d), tiIn order to measure the time of day,
Figure BDA0003372675700000184
the corresponding correlation coefficient R is calculated as:
Figure BDA0003372675700000185
the calculation of the Allan variance is:
Figure BDA0003372675700000186
the calculation formula for the corrected Allan variance is:
Figure BDA0003372675700000187
the hadamard variance is calculated as:
Figure BDA0003372675700000188
the modified hadamard variance is calculated as:
Figure BDA0003372675700000191
(2) time difference fitting forecast
The real-time difference monitoring data can be used for time difference forecasting, a polynomial model is generally adopted for time difference fitting, and the mathematical expression of the polynomial model is as follows:
Figure BDA0003372675700000192
in formula 22, xiMeasured value of time difference in epoch i; t is tiIs the time value of epoch i; sigmaiIs the prediction model error for epoch i. Alpha is alpha0、α1、α2、…、αmThe model parameters are predicted for m +1 moveout times, typically by least squares solution.
And forecasting the time difference of the GNSS system for 1h and 6h according to the continuous time difference data of the GNSS system obtained by monitoring, and evaluating the forecasting result. And comparing the model fitting result with the actually measured time difference value, and carrying out uncertainty evaluation on the fitting residual error.
(3) Uncertainty assessment
Calculating the uncertainty of the fitting residual error of the time difference sequence by adopting a standard uncertainty A-type evaluation method, wherein the calculation formula is as follows:
Figure BDA0003372675700000193
in formula 23, U represents the calculated class a uncertainty value;
σirepresenting a sequence of time differences xiDeduction of predictive model fit values
Figure BDA0003372675700000195
Of residual data, i.e.
Figure BDA0003372675700000194
n is the number of data sequences.
After the fitting parameters of the actually measured GNSS time difference data are solved, residual uncertainty of the first fitting model and the second fitting model can be calculated respectively.
Although specific embodiments of the present invention have been described above, it will be appreciated by those skilled in the art that these are merely examples and that many variations or modifications may be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims.

Claims (12)

1. A GNSS system time deviation monitoring and evaluating method is characterized in that the method comprises the following steps,
step S01: a GNSS system time difference monitoring platform is built, a time interval counter and a time difference monitoring computer build the GNSS system time deviation monitoring platform based on a pulse per second measurement model by utilizing a ground time frequency source and a multi-frequency GNSS common-view receiver;
step S02: correcting a receiver clock error, and reasonably setting a positioning model, a motion mode, an ionosphere model, a troposphere model, an anti-multipath model, an antenna type and a carrier smoothing pseudo range parameter of the receiver;
step S03: preprocessing data, namely preprocessing time difference data obtained by direct measurement, including error correction of discrete errors of a receiver signal, measurement gross error elimination and data filtering smoothing;
step S04: and analyzing and evaluating and forecasting the time difference, and carrying out analysis and evaluation after preprocessing the time difference data, wherein the analysis and evaluation comprises accuracy evaluation, drift rate evaluation, stability evaluation and uncertainty evaluation.
2. The GNSS system time bias monitoring and evaluating method according to claim 1, wherein: and in the step S01, different time difference monitoring platforms with different working modes are set up according to different time difference monitoring requirements, wherein the working modes comprise a monitoring mode and a mutual measurement mode.
3. The GNSS system time offset monitoring and evaluating method according to claim 1, wherein the GNSS system time difference monitoring platform specifically includes the following:
the ground frequency source provides a reference signal for the multi-frequency GNSS common-view receiver and the time interval counter, and provides a ground standard 1PPS signal for time difference comparison;
the multi-frequency GNSS common-view receiver consists of an antenna and a receiver, wherein the antenna is arranged at an appropriate position without shielding outdoors and is connected to an antenna interface of the receiver through an antenna cable;
the time interval counter is used for measuring the time difference comparison value of signals of the two input channels in real time and outputting data into the time difference monitoring computer through a serial port;
and the time difference monitoring computer is connected with the multi-frequency GNSS common-view receiver and the time interval counter through an interface and is provided with time difference monitoring processing software.
4. The GNSS system time deviation monitoring and evaluating method according to claim 1, wherein the step S02 specifically includes,
(1) the position coordinates of the antenna are measured in advance through geodetic measurement or precise single-point positioning, a receiver is arranged in the antenna, and the clock error calculation error is reduced by improving the degree of freedom of equation solution;
(2) starting a receiver SBAS positioning mode, and correcting satellite ephemeris error and satellite clock error by using a broadcast message of an SBAS satellite;
(3) starting a dual-frequency positioning mode, and eliminating ionosphere errors by utilizing the ionosphere-free combined observed quantity;
(4) setting a troposphere delay model as Saastamoinen or MOPS, and deducting troposphere errors through the model;
(5) taking appropriate action to suppress multipath effects, including: selecting an Hertz coil antenna, placing the Hertz coil antenna at a high place without shielding, and simultaneously starting a function of a receiver for inhibiting the multipath effect;
(6) selecting and purchasing an antenna type of the authenticated absolute phase center correction model, correctly setting Marker offset parameters, and eliminating an antenna phase center error;
(7) and starting a carrier phase smoothing pseudorange function of the receiver, setting the number of smoothing points to be 300, and reducing pseudorange measurement noise through carrier phase smoothing pseudorange.
5. The GNSS system time bias monitoring and evaluating method of claim 4, wherein the calculation formula of the dual-frequency ionospheric-free combined observation in step S02 is as follows:
Figure FDA0003372675690000031
in the formula: p3The pseudo range is the pseudo range without the combination of the ionized layers;
f1、f2the frequencies of carrier 1 and carrier 2 respectively;
P1、P2pseudo-range observed values of a carrier wave 1 and a carrier wave 2 respectively;
ε3,Pand respectively, noise of the pseudo-range non-ionosphere combined observed value.
6. The GNSS system time bias monitoring and evaluating method of claim 4, wherein the receiver pseudorange and carrier phase observation equations of step S02 are as follows:
P＝ρ(ts,tr)+c(dtr-dts)+dtrop+dion+MP+εP，
Figure FDA0003372675690000032
in the formula, P is a pseudo range observed value; l is a carrier phase observed value; λ is the carrier wavelength; n is the integer ambiguity; t is tsA time of signal transmission for the satellite; t is trA time of receiving a signal for a receiver; dts、dtrRespectively, the clock error of the satellite and the receiver; c is the speed of light; dtrop、dionTropospheric and ionospheric delay amounts, respectively; mP、
Figure FDA0003372675690000033
Respectively the pseudo range and the multipath effect of the carrier phase; epsilonP、
Figure FDA0003372675690000034
Respectively, pseudo range and carrier phase observation noise; ρ (t)s,tr) Is tsSatellite arrival at time trThe geometric distance between the receiver antennas at the time;
the formed carrier phase smoothed pseudorange is as follows:
Figure FDA0003372675690000035
in the formula, Ps,k、Ps,k-1Respectively representing carrier phase smoothing pseudo range values of epoch k and epoch k-1;
Pka pseudorange observation representing epoch k;
Lk、Lk-1respectively representing carrier phase observed values of epoch k and epoch k-1;
m is called a smoothing time constant, and the larger the value of M is, the larger P issThe smoother is.
7. The GNSS system time offset monitoring and evaluating method of claim 2, wherein the discrete error correction formula in step S03 is as follows:
Tr＝Tm-D，
wherein Tm represents the time difference value measured by the counter, D represents the discrete error of the receiver, and Tr represents the real time difference value;
if the receiver works in the mutual measurement mode, discrete errors of two receivers need to be corrected at the same time, and the correction formula is as follows:
Tr＝Tm+D1-D2，
in the formula, D1Indicating a dispersion error of the door-opening receiver, D2The dispersion error of the door-closed receiver is shown, Tm is the time difference value measured by the counter, and Tr is the real time difference value.
8. The GNSS system time offset monitoring and evaluating method of claim 1, wherein the step S03 of performing gross error rejection on the time difference measurement specifically includes:
removing gross error based on median method, and carrying out primary difference on time difference data to obtain frequency difference sequence yiWhen difference value yiSatisfies the following conditions:
|yi-m|>n·MAD
namely, determining as a coarse difference value;
in the formula: m is media (y)i)，MAD＝Median{|yi-m/0.6745, n is an adjustment factor set between 3 and 5, and Median represents the Median of a sequence.
9. The GNSS system time offset monitoring and evaluating method of claim 1, wherein in the step S03, the filtering and smoothing of the time difference measurement value specifically includes:
data smoothing based on FIR filter, i.e. using the most recent N in the pastK+1-PIndividual observation values, x being calculated by discrete time convolutionP(n) unbiased FIR filter estimate
Figure FDA0003372675690000041
Figure FDA0003372675690000042
Calculating a high-order observation quantity by using discrete difference:
Figure FDA0003372675690000051
sequentially recursion to obtain each order estimated value of the clock error model
Figure FDA0003372675690000052
10. The GNSS system time offset monitoring and evaluating method of claim 1, wherein in step S04, the comprehensive analysis and evaluation of the time difference measurement result specifically includes:
frequency accuracy:
Figure FDA0003372675690000053
frequency drift rate:
Figure FDA0003372675690000054
the Allan variance:
Figure FDA0003372675690000055
correcting Allan variance:
Figure FDA0003372675690000056
hadamard variance:
Figure FDA0003372675690000057
modified hadamard variance:
Figure FDA0003372675690000058
11. the GNSS system time offset monitoring and evaluating method according to claim 1, wherein the analyzing and forecasting of the GNSS system time difference in step S04 specifically includes:
and (3) adopting a polynomial model to perform time difference fitting, wherein the formula is as follows:
Figure FDA0003372675690000061
and continuously monitoring the time difference data of the GNSS system, solving fitting parameters of the primary model and the secondary model by a least square method, forecasting the time difference of the GNSS system for 1h and 6h, and evaluating a forecasting result.
12. The GNSS system time offset monitoring and evaluation method according to claim 1, wherein the step S04 of performing uncertainty evaluation on the fitting residuals specifically includes:
the uncertainty of the residual errors of the primary fitting model and the secondary fitting model is respectively calculated by adopting an A-type uncertainty evaluation method, and the calculation formula is as follows:
Figure FDA0003372675690000062
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