CN107748377B - Differential positioning method based on GNSS and positioning system thereof - Google Patents

Differential positioning method based on GNSS and positioning system thereof Download PDF

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CN107748377B
CN107748377B CN201711274713.7A CN201711274713A CN107748377B CN 107748377 B CN107748377 B CN 107748377B CN 201711274713 A CN201711274713 A CN 201711274713A CN 107748377 B CN107748377 B CN 107748377B
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CN107748377A (en
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刘浩
朱志敏
祁卫
姜黎
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Hunan Goke Microelectronics Co Ltd
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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
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/40—Correcting position, velocity or attitude
    • G01S19/41—Differential correction, e.g. DGPS [differential GPS]
    • 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
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position

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  • Computer Networks & Wireless Communication (AREA)
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Abstract

The invention provides a differential positioning method based on GNSS, comprising the following steps: s1, resolving pseudo-range observed quantity from satellite signals; s2, performing segmentation smoothing filtering to obtain the smoothed pseudorange observed quantity; s3, obtaining a pseudo range correction amount of the current time; s4, obtaining a corrected pseudo range observation quantity; s5, acquiring an initial position coordinate; and S6, outputting a positioning result by adopting Kalman filtering on the initial position coordinates. The invention also provides a differential positioning system based on the GNSS. Compared with the related art, the differential positioning method based on the GNSS and the positioning system thereof have the following beneficial effects: a proper smooth filtering constant is selected, so that the multipath error is effectively reduced; the stability of smoothing is ensured by adopting segmented smoothing filtering; correcting ionosphere troposphere errors in an external data flow mode; and by adopting Kalman filtering, pseudo-range observed quantity is effectively utilized, and positioning precision is improved.

Description

Differential positioning method based on GNSS and positioning system thereof
Technical Field
The invention relates to the technical field of communication, in particular to a differential positioning method based on GNSS and a positioning system thereof.
Background
With the development of the internet of things and the coming of sharing economy, the market has an increasing demand for positioning equipment, such as a sharing bicycle. The shared bicycle is positioned by adopting a satellite positioning terminal.
The traditional satellite positioning method adopts the following steps: according to the distance observation value from the satellite to the positioning terminal, the position of the point to be measured is calculated by utilizing the space rear distance intersection principle, but because the satellite signal is interfered by various factors in the transmission process, such as the influence of an ionosphere, a troposphere, a receiver clock error, a satellite clock error, multipath, random noise and the like, the calculated distance from the satellite to the positioning terminal has an error, so that the position output by the positioning terminal is not unified with the real position.
The errors of the ionosphere, the troposphere, the satellite clock error and the receiver clock error can be estimated by corresponding mathematical methods, but the multipath error presents certain randomness, and the magnitude of the multipath error can be estimated by an imperfect mathematical model so far.
The patent with the application number of 201710121094.1 and the patent name of 'a base station device, a terminal and a positioning method' uses window smoothing hash filtering for positioning to reduce the influence of multipath errors, uses a weighted least square method to obtain a positioning result, and each second of data is independently solved to reduce the influence caused by an observation value with a large error, but if the errors of the observation value are large at the moment, the positioning error at the moment becomes large suddenly.
Therefore, it is desirable to provide a new GNSS based differential positioning method and a positioning system thereof to solve the above technical problems.
Disclosure of Invention
The invention aims to provide a differential positioning method based on GNSS and a positioning system thereof, which adopt Kalman filtering and obviously improve the positioning precision.
In order to solve the above technical problem, the present invention provides a differential positioning method based on GNSS, comprising the following steps:
s1, receiving satellite signals transmitted by satellites through a positioning terminal, and resolving pseudo-range observed quantities from the satellite signals;
s2, performing piecewise smoothing filtering on the analyzed pseudo-range observed quantity to obtain the smoothed pseudo-range observed quantity;
s3, receiving and decoding the pseudo range difference correction quantity of the ionosphere and the troposphere coded by the external RTCM2.3 standard format to obtain the pseudo range correction quantity of the current time;
s4, obtaining a corrected pseudo-range observed quantity according to the smoothed pseudo-range observed quantity and the pseudo-range correction quantity of the current time;
s5, obtaining an initial position coordinate by using a least square method for the corrected pseudo-range observed quantity;
and S6, outputting a positioning result by adopting Kalman filtering on the initial position coordinates.
Preferably, in step S1, the pseudo-range observed value ρ is calculated by the following equation:
ρ＝c*(tu-ts)
wherein, tsFor the time of transmission of the satellite signal, tuC is the speed of light for the time when the positioning terminal receives the satellite signal.
Preferably, in step S2, the pseudorange observations are smoothed by a Hatch filtering method.
Preferably, in step S2, when the smoothing counter k is not greater than the smoothing filter constant M, the smoothed pseudorange observation amount is set to be equal to or greater than the smoothing filter constant M
Figure GDA0003142954940000021
Using a formula
Figure GDA0003142954940000022
Figure GDA0003142954940000023
Carrying out smooth filtering; smoothed pseudorange observations when the smoothing counter k is greater than the smoothing filter constant M
Figure GDA0003142954940000024
Using a formula
Figure GDA0003142954940000025
Figure GDA0003142954940000026
And performing a smoothing filtering process, wherein,
Figure GDA0003142954940000027
the smoothed pseudorange observations for the last second, Δ φ (k) is the carrier variation.
Preferably, the smoothing filter constant M is an optimal smoothing constant, and the smoothing filter constant M is obtained by adjusting the constant MtempRounded to obtain, wherein, the constant MtempCalculated by the following formula:
Figure GDA0003142954940000031
Figure GDA0003142954940000032
Figure GDA0003142954940000033
wherein q is a variable, p is a fixed constant term,
Figure GDA0003142954940000034
for the pseudo-range to observe the noise,
Figure GDA0003142954940000035
is an ionospheric error term.
Preferably, in step S3, the decoding step sequentially includes: byte scanning, byte rolling, padding, searching for sync words, and parity.
Preferably, in step S4, the modified pseudorange observation PR _ inal (i) is obtained by the following equation:
PR_final(i)＝PRC(i)+PR(i)
prc (i) is a pseudo range correction value for satellite i, and pr (i) is a smoothed pseudo range observation.
Preferably, in step S6, the kalman filtering specifically includes the following steps:
s61, updating the time of the system state vector and the state covariance matrix;
s62, predicting the observation quantity according to the updated result;
s63, calculating pseudo-range residual errors by using the corrected post-observation quantity and the predicted observation quantity;
s64, calculating a Kalman gain matrix;
and S65, updating the observation quantity of the system state vector after the time updating and updating the state covariance matrix.
The invention also provides a differential positioning system based on GNSS, comprising:
the positioning terminal is used for receiving satellite signals transmitted by satellites;
the signal analysis module is used for analyzing pseudo-range observed quantity from the received satellite signals;
the smooth filtering module is used for carrying out segmentation smooth filtering on the analyzed pseudo-range observed quantity to obtain the smoothed pseudo-range observed quantity;
the decoding module is used for receiving and decoding pseudo range difference correction values of an ionized layer and a troposphere which are externally connected and coded in an RTCM2.3 standard format, and obtaining pseudo range correction values of the current time;
the correction module is used for obtaining a corrected pseudo-range observed quantity according to the smoothed pseudo-range observed quantity and the pseudo-range correction quantity of the current time;
and the filtering module is used for performing Kalman filtering on the initial position coordinates and outputting a positioning result.
Compared with the related art, the differential positioning method based on the GNSS and the positioning system thereof have the following beneficial effects:
1. a proper smooth filtering constant is selected, so that the multipath error is effectively reduced;
2. the stability of smoothing is ensured by adopting segmented smoothing filtering;
3. correcting errors of an ionosphere and a troposphere by adopting an external data flow mode;
4. and by adopting Kalman filtering, pseudo-range observed quantity is effectively utilized, and positioning precision is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts, wherein:
FIG. 1 is a flowchart illustrating a GNSS based differential positioning method according to the present invention;
FIG. 2 is a flowchart illustrating the decoding step of the GNSS based differential positioning method of the present invention;
FIG. 3 is a diagram illustrating an RTCM2.3 decoding process in the GNSS based differential positioning method of the present invention;
FIG. 4 is a flow chart of Kalman filtering in the GNSS-based differential positioning method of the present invention;
FIG. 5 is a block diagram of a GNSS based differential positioning system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, the present invention provides a GNSS based differential positioning method, including the following steps:
s1, receiving satellite signals transmitted by satellites through a positioning terminal, and resolving pseudo-range observed quantities from the satellite signals;
the pseudorange observation ρ is represented by the formula ρ ═ c · (t)u-ts) Is calculated to obtain, wherein tsFor the time of transmission of the satellite signal, tuC is the speed of light for the time when the positioning terminal receives the satellite signal.
S2, performing piecewise smoothing filtering on the analyzed pseudo-range observed quantity to obtain the smoothed pseudo-range observed quantity;
the multipath is that a receiver antenna of the positioning terminal receives not only a satellite direct wave signal but also a reflected wave signal, which may cause an error in calculating a pseudo-range observed quantity, the error is in the meter level, and the error is not estimable. The receiver of the positioning terminal can calculate not only the observation of the spurious data, but also the observation of the carrier wave. Although the carrier observed value has the problem of integer ambiguity, the size and the direction of the variation of the locked carrier observed value and the variation of the pseudo-range observed value are consistent, and the multipath error of the carrier observed value is only millimeter-sized and much smaller than the multipath of the pseudo-range observed value, so that the variation of the pseudo-range observed value can be corrected by using the variation of the carrier observed value, and the error caused by the multipath is reduced. Therefore, the pseudorange observed quantity is subjected to smooth filtering by adopting a Hatch filtering method.
The Hatch filtering needs a good pseudo-range initial value to effectively reduce the influence of multipath errors, otherwise, the filtered pseudo-range quality is worse. Therefore, the weight of the carrier variation is gradually increased by adopting the piecewise smooth filtering, and the divergence condition can be effectively prevented.
Smoothed pseudorange observations when the smoothing counter k is not greater than the smoothing filter constant M
Figure GDA0003142954940000051
Using a formula
Figure GDA0003142954940000052
Carrying out segmented smoothing filtering; smoothed pseudorange observations when the smoothing counter k is greater than the smoothing filter constant M
Figure GDA0003142954940000053
Using a formula
Figure GDA0003142954940000054
Figure GDA0003142954940000055
And performing piecewise smooth filtering, wherein,
Figure GDA0003142954940000056
the smoothed pseudorange observations for the last second, Δ φ (k) is the carrier variation. After carrier locking, the smoothing counter k is incremented from 1, at a frequency of 1 increment per second, until a specified value M is reached. And when the smoothing counter k is less than or equal to M or exceeds M, smoothing filtering by adopting different formulas. By adopting the piecewise function method, the stability of smoothness is ensured.
The choice of smoothing filter constant M is usually set directly to 100, but this is not an optimum oneA smoothing constant. Because the receiver of each positioning terminal has different machine characteristics, when the smoothing constant is too large, the ionosphere error is increased, and when the smoothing constant is too small, a large number of multipath errors of pseudo-range observed values are remained, so that the smoothing is meaningless. A relatively reasonable optimal smoothing constant M can be obtained according to the following formulatempTherefore, the smoothing constant is set to 100, and is not suitable for all receivers.
Therefore, the smoothing filter constant M adopted by the invention is the optimal smoothing constant, and the constant M is obtained by matchingtempRounded to obtain, wherein, the constant MtempCalculated by the following formula:
Figure GDA0003142954940000061
Figure GDA0003142954940000062
Figure GDA0003142954940000063
wherein q is a variable, p is a fixed constant term,
Figure GDA0003142954940000064
for the pseudo-range to observe the noise,
Figure GDA0003142954940000065
is an ionospheric error term.
S3, receiving and decoding the pseudo range difference correction quantity of the ionosphere and the troposphere coded by the external RTCM2.3 standard format to obtain the pseudo range correction quantity of the current time;
the existing positioning terminal adopts model estimation for ionosphere and troposphere errors. However, the estimated error value is far from the actual error value, and a large amount of correction residue is left on the error, resulting in inaccurate positioning. Therefore, the correction quantity of the ionosphere and the troposphere is read in real time by adopting an external data correction mode. The ionosphere troposphere error can be effectively reduced. Because the ionosphere and the troposphere have spatial correlation, the ionosphere troposphere error can be calculated at a base station with a known high-precision position and sent out in real time. This type of data is called RTCM (international maritime radio technical commission) 2.3 format, the transmitted data is called pseudorange differential corrections, and the amount of information is compressed accordingly for ease of transmission. In order to obtain the information in the code stream, the transmitted bytes need to be decoded.
In the RTCM2.3, one piece of differential information consists of (2+ n) words, each word occupies 30 bits, the first 24 bits contain information, and the last 6 bits are parity bits. The first 2 words are called headers and the last n words contain differential information, the header information being shown in table 1.
TABLE 1
Figure GDA0003142954940000071
Figure GDA0003142954940000072
Header 1 contains information:
the leading word is fixed to 01100110, which means that this is the beginning of a piece of difference information.
The data type value range is 1-63, and the information type is described.
The reference station ID indicates the number of the current base station.
Header 2 contains information:
time t at which the difference information can be obtained by correcting the Z count to an integer and multiplying the integer by a coefficient of 0.6S0。
And the serial number is used for explaining the position of the piece of differential information in a group of differential signal data.
The length of the frame, which indicates the length of the difference, can be used to position the start end of the next difference data in cooperation with the serial number.
And the base station health state indicates whether the current reference station works normally.
The last n bytes of a piece of differential information contain different types of data according to different types. By definition, the difference data for type1 is shown in Table 2.
TABLE 2 type1 Single satellite differential information
Figure GDA0003142954940000073
Figure GDA0003142954940000081
According to table 2, the differential information of one satellite occupies 40 bits. The scale factor in table 2 occupies 1bit, and when 0, the coefficients of the pseudorange correction value and the range rate correction value are 0.02m and 0.002m/s, respectively; at 1, the pseudorange correction and the range rate correction have coefficients of 0.32 and 0.032m/s, respectively. The user differential range error is used together with the health coefficient of the word head to indicate the reliability of the pseudo range correction value. The data age mainly indicates the timeliness of the satellite pseudo-range correction value, and the data age of the differential information should be consistent with the data age of the broadcast ephemeris for use. 3 satellites just occupy 5 words, and when the number of the satellites in the differential information is not a multiple of 3, the rest space is occupied alternately by 1 and 0. When using a digital transmission station, the differential data is typically delayed by several minutes or even more than ten minutes, and therefore the range rate correction value is used to correct the error caused by the delay.
Referring to fig. 2, the decoding process is divided into the following steps.
S30, byte scanning;
in order to prevent errors in transmission, for data in one byte, the RTCM2.3 only adopts 6 bits, and specifies that the most significant bit is a blank and the next most significant bit is 1. Therefore, after one byte is converted into decimal, the value range is considered as valid byte within 64-127, otherwise, the valid byte is discarded.
S31, rolling bytes;
using one valid byte, the upper 2 bits need to be discarded while the lower 6 bits are reverse ordered. For one word, 5 bytes of data are required to construct, the 5 th byte being a parity bit.
S32, taking the complement code;
when the 30 th bit of the current word is 1, the first 24 of the current word needs to be complemented. But the last 6 bits of each word are parity bits and do not need to be complemented.
S33, searching for a synchronous word;
when searching for a sync word, attention should be paid to the effect of the last byte being 1. When attempting to search for a sync word, if it fails, the 24 bits that have been complemented should be restored and then logically shifted left to replenish the new data.
S34, parity check.
And after the synchronous word is determined to be found, carrying out parity check again, and if the parity check does not pass, searching again and carrying out left shift. When the parity of each word passes, the decoding of type1 differential information can be started. The decoding process is shown in fig. 3.
S4, obtaining a corrected pseudo-range observed quantity according to the smoothed pseudo-range observed quantity and the pseudo-range correction quantity of the current time;
after decoding, a pseudorange correction amount prc (i) of the satellite i at the current time is obtained. And smoothing the pseudo range observed quantity by a carrier wave at the moment, and eliminating most of multipath errors to obtain the pseudo range observed quantity PR (i) after the satellite i is smoothed. Adding the smoothed pseudo-range observed quantity PR (i) to the current correction quantity PRC (i) through a formula PRfinal(i)Calculating to obtain a corrected pseudo-range observation PR (i) + PR (i)final(i). As can be seen from the equation, after smoothing and correction, ionospheric tropospheric and multipath errors substantially disappear.
S5, obtaining an initial position coordinate by using a least square method for the corrected pseudo-range observed quantity;
specifically, the present invention only needs to use a one-time least square method for the corrected pseudorange observed quantity.
And S6, outputting a positioning result by adopting Kalman filtering on the initial position coordinates.
Referring to FIG. 4, assume that at tkAt a time, the system state vector is
Figure GDA0003142954940000091
Covariance matrix P of statesk|kThe kalman filtering specifically includes the steps of:
s60, carrying out system state vector
Figure GDA0003142954940000092
Sum state covariance matrix Pk|kTime update of (2);
Figure GDA0003142954940000093
Figure GDA0003142954940000094
s61, predicting the observation quantity according to the updated result;
Figure GDA0003142954940000095
wherein (x)si,ysi,zsi) Is the current coordinate of satellite i, a known quantity, bk+1|kIs the updated clock difference.
S62, calculating pseudo-range residual errors by using the corrected post-observation quantity and the predicted observation quantity;
Figure GDA0003142954940000101
s63, calculating a Kalman gain matrix;
Figure GDA0003142954940000102
wherein R isk+1Is an observed quantityAnd the variance matrix is also the core of Kalman filtering.
S64, updated with time
Figure GDA0003142954940000103
Performing observation update and updating state covariance matrix Pk+1|k。
Figure GDA0003142954940000104
Pk+1|k+1＝(I-kk+1Hk+1)Pk+1|k
After update
Figure GDA0003142954940000105
And Pk+1|k+1Saved and prepared for the next moment.
In Kalman filtering, the gain matrix kmThe setting of (2) determines the quality of positioning. If k ismThe final positioning result is diverged due to the fact that the setting of (2) is not consistent with the actual setting.
According to the formula
Figure GDA0003142954940000106
It can be seen that the gain matrix kmBy the error variance matrix PmSystem observation equation HmAnd observing the noise variance matrix RmAnd (4) forming. With increasing time, PmWill gradually tend to be unbiased while the system observes equation HmDetermined by the satellite position, so that the noise variance matrix R is observedmThe determination of (a) is crucial.
The invention determines an observation noise variance matrix R from multiple aspects based on the consideration of actual environmentmAn observed noise variance matrix R is determined based on the SNR and the residual multipath errorm。
Since the signal-to-noise ratio has a greater influence on the satellite observation error, a portion of the observation noise variance of each satellite is determined based on the current signal-to-noise ratio of each satellite.
Most of multipath errors disappear after smoothing, but the influence of residual multipath errors still needs to be considered, but the influence of the residual multipath errors is smaller than the influence of the signal-to-noise ratio, so the two variances have different orders of magnitude.
Referring to fig. 5, the present invention further provides a GNSS based differential positioning system 100, including: the device comprises a positioning terminal 1, a signal analysis module 2, a smooth filtering module 3, a decoding module 4, a correction module 5 and a filtering module 6.
The positioning terminal 1 may be a mobile phone, a computer, an IPAD, or other devices, and is configured to receive satellite signals transmitted by a satellite.
The signal analysis module 2 is configured to analyze a pseudorange observation from the received satellite signal.
The smoothing filtering module 3 is configured to perform piecewise smoothing filtering on the resolved pseudo-range observed quantity to obtain the smoothed pseudo-range observed quantity.
The decoding module 4 is used for receiving and decoding the pseudo range difference correction of the ionosphere and the troposphere coded by the external RTCM2.3 standard format, and obtaining the pseudo range correction of the current time.
The correction module 5 is configured to obtain a corrected pseudo-range observed quantity according to the smoothed pseudo-range observed quantity and the pseudo-range correction quantity of the current time.
And the filtering module 6 is used for performing Kalman filtering on the initial position coordinates and outputting a positioning result.
Compared with the related art, the differential positioning method based on the GNSS and the positioning system thereof have the following beneficial effects:
1. a proper smooth filtering constant is selected, so that the multipath error is effectively reduced;
2. the stability of smoothing is ensured by adopting segmented smoothing filtering;
3. correcting ionosphere troposphere errors in an external data flow mode;
4. and by adopting Kalman filtering, pseudo-range observed quantity is effectively utilized, and positioning precision is improved.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (7)

1. A differential positioning method based on GNSS is characterized by comprising the following steps:
s1, receiving satellite signals transmitted by satellites through a positioning terminal, and resolving pseudo-range observed quantities from the satellite signals;
s2, carrying out segmentation smoothing filtering on the analyzed pseudo range observed quantity to obtain the smoothed pseudo range observed quantity, and when a smoothing counter k is not more than a smoothing filtering constant M, carrying out smoothing filtering on the smoothed pseudo range observed quantity
Figure FDA0003142954930000011
Using a formula
Figure FDA0003142954930000012
Carrying out smooth filtering; smoothed pseudorange observations when the smoothing counter k is greater than the smoothing filter constant M
Figure FDA0003142954930000013
Using a formula
Figure FDA0003142954930000014
And performing a smoothing filtering process, wherein,
Figure FDA0003142954930000015
for the smoothed pseudorange observations of the last second, Δ φ (k) is the carrier variation, and the smoothing filter constant M is the optimal smoothing constant, obtained by applying a constant M totempRounded to obtain, wherein, the constant MtempCalculated by the following formula:
Figure FDA0003142954930000016
Figure FDA0003142954930000017
Figure FDA0003142954930000018
wherein q is a variable, p is a fixed constant term,
Figure FDA0003142954930000019
for the pseudo-range to observe the noise,
Figure FDA00031429549300000110
is an ionospheric error term;
s3, receiving and decoding the pseudo range difference correction quantity of the ionosphere and the troposphere coded by the external RTCM2.3 standard format to obtain the pseudo range correction quantity of the current time;
s4, obtaining a corrected pseudo-range observed quantity according to the smoothed pseudo-range observed quantity and the pseudo-range correction quantity of the current time;
s5, obtaining an initial position coordinate by using a least square method for the corrected pseudo-range observed quantity;
and S6, outputting a positioning result by adopting Kalman filtering on the initial position coordinates.
2. The GNSS based differential positioning method according to claim 1, wherein in step S1, the pseudo-range observation amount p is calculated by the following formula:
ρ＝c*(tu-ts)
wherein, tsFor the time of transmission of the satellite signal, tuC is the speed of light for the time when the positioning terminal receives the satellite signal.
3. The GNSS based differential positioning method according to claim 1, wherein in step S2, the pseudorange observations are smoothed by a Hatch filtering method.
4. The GNSS based differential positioning method of claim 1, wherein in step S3, the decoding step sequentially comprises: byte scanning, byte rolling, padding, searching for sync words, and parity.
5. The GNSS based differential positioning method according to claim 1, wherein in step S4, the modified pseudorange observations PR _ final (i) are obtained by the following formula:
PR_final(i)＝PRC(i)+PR(i)
prc (i) is a pseudo range correction value for satellite i, and pr (i) is a smoothed pseudo range observation.
6. The GNSS based differential positioning method according to claim 1, wherein in step S6, the kalman filtering specifically includes the steps of:
s61, updating the time of the system state vector and the state covariance matrix;
s62, predicting the observation quantity according to the updated result;
s63, calculating pseudo-range residual errors by using the corrected post-observation quantity and the predicted observation quantity;
s64, calculating a Kalman gain matrix;
and S65, updating the observation quantity of the system state vector after the time updating and updating the state covariance matrix.
7. A GNSS based differential positioning system, wherein the differential positioning method according to any one of claim 1 to claim 6 is employed, the differential positioning system further comprising:
the positioning terminal is used for receiving satellite signals transmitted by satellites;
the signal analysis module is used for analyzing pseudo-range observed quantity from the received satellite signals;
the smooth filtering module is used for carrying out segmentation smooth filtering on the analyzed pseudo-range observed quantity to obtain the smoothed pseudo-range observed quantity;
the decoding module is used for receiving and decoding pseudo range difference correction values of an ionized layer and a troposphere which are externally connected and coded in an RTCM2.3 standard format, and obtaining pseudo range correction values of the current time;
the correction module is used for obtaining a corrected pseudo-range observed quantity according to the smoothed pseudo-range observed quantity and the pseudo-range correction quantity of the current time, and obtaining an initial position coordinate by using a least square method for the corrected pseudo-range observed quantity;
and the filtering module is used for performing Kalman filtering on the initial position coordinates and outputting a positioning result.
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