CN111458736A - Short-baseline RTK positioning method based on airborne embedded platform - Google Patents

Short-baseline RTK positioning method based on airborne embedded platform Download PDF

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CN111458736A
CN111458736A CN202010293296.6A CN202010293296A CN111458736A CN 111458736 A CN111458736 A CN 111458736A CN 202010293296 A CN202010293296 A CN 202010293296A CN 111458736 A CN111458736 A CN 111458736A
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double
difference
matrix
ambiguity
airborne
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安云飞
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CETC 54 Research Institute
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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
    • G01S19/42—Determining position
    • G01S19/43—Determining position using carrier phase measurements, e.g. kinematic positioning; using long or short baseline interferometry
    • G01S19/44—Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method

Abstract

The invention discloses a short-baseline RTK positioning method based on an airborne embedded platform, which mainly comprises a base station receiver, a base station transmitting radio station, an airborne receiver and an airborne receiving radio station, wherein the influence of troposphere delay height sensitivity characteristic on RTK positioning is weakened through constructing a carrier phase double-difference equation for compensating troposphere delay, the carrier phase double-difference ambiguity fixing rate of the airborne platform in high-altitude environment is improved, and a L free of square root operation is adopted through deep research on L ambda algorithmTThe D L decomposition method enables the decomposition operation complexity of the ambiguity covariance matrix to be smaller, and is more beneficial to embedding a platform with low operation capability, the usability of the short-baseline RTK on an onboard platform is improved, and the operation complexity of L ambda is reduced.

Description

Short-baseline RTK positioning method based on airborne embedded platform
Technical Field
The invention belongs to the field of satellite navigation, relates to a short-baseline real-time carrier phase differential positioning algorithm and an implementation thereof on an onboard embedded platform, and particularly discloses a double-difference observation equation establishment method for compensating flow delay and an L ambda algorithm for optimizing operation complexity.
Background
According to different precision requirements, the satellite navigation positioning method comprises single-point positioning, precise single-point positioning, pseudo-range differential positioning, real-time carrier phase differential (RTK) positioning, network RTK, wide-area differential positioning and the like, wherein RTK positioning is based on the high correlation of an error item between a reference station and a flow station, and the ambiguity of carrier phase double differences is solved through an L ambda algorithm, so that centimeter-level baseline vector precision can be obtained.
According to the basic navigation principle, the pseudo-range observation equation and the carrier phase observation equation are as follows:
ρ＝r+c(tu-ts)+I+T+ρ
φ＝λ-1[r+c(tu-ts)-I+T]+N+φ
where ρ represents the pseudorange, φ represents the carrier phase, λ represents the carrier wavelength, r represents the true position between the satellite and the user, c represents the speed of light, tuIndicating the user's local clock error, tsRepresenting the satellite clock error, I the ionospheric delay, T the tropospheric delay, N the carrier-phase integer ambiguity,ρrepresents the noise of the observation of the pseudo-range,φrepresenting carrier phase observation noise. The conventional RTK positioning method obtains the following double-difference observation equation according to the user local clock difference, the satellite clock difference and the ionosphere error between the base station and the rover station and the height correlation of the flow error in the double-difference equation:
Figure BDA0002451215100000011
Figure BDA0002451215100000012
where λ represents the carrier wavelength, the indices r and u represent the reference station and rover station, respectively, the indices i and j represent the different satellite numbers,
Figure BDA0002451215100000021
a double-difference measurement of the pseudoranges is represented,
Figure BDA0002451215100000022
the double difference of the satellite distances of the stations is shown,
Figure BDA0002451215100000023
representing the double difference noise of the pseudoranges,
Figure BDA0002451215100000024
representing a double-difference observation of the carrier phase,
Figure BDA0002451215100000025
representing the double-difference ambiguity of the carrier phase,
Figure BDA0002451215100000026
representing the carrier phase double-difference noise, then solving for the carrier phase double-difference ambiguity using the L ambda algorithm
Figure BDA0002451215100000027
However, troposphere delay is sensitive to elevation, the elevation difference between an airborne platform rover and a ground reference station is generally large, and the troposphere delay does not have high correlation any more, so that the carrier phase double-difference ambiguity cannot be fixed by adopting an L ambda algorithm later, and a fixed solution cannot be obtained.
L ambda is a classical algorithm for solving double-difference ambiguity of carrier phase, which was originally proposed by professor teunessen, university of Delft, the netherlands. L ambda algorithm mainly comprises the following 3 steps:
1) and solving the floating solution of the baseline vector and the carrier phase double-difference ambiguity of the double-difference observation equation by adopting a least square method.
2) Through integer Gaussian transformation (Z transformation), the relevance of the ambiguity is reduced, and the ambiguity search space is improved.
3) Searching the transformed search space for an optimal ambiguity integer solution, and then inverse transforming (Z)T)-1The transformed spatial ambiguity is converted into an original ambiguity, and then a high-precision baseline vector can be obtained.
The decorrelated Z transform used in step 2 is the key of the L ambda algorithm, so that the search speed of ambiguity is faster, the fixed rate is higher, the invention adopts L without square root operationTThe D L decomposition method further reduces the operation complexity of Z transformation, and is more beneficial to the realization of an embedded platform.
Disclosure of Invention
The invention aims to solve the technical problem of providing a double difference equation establishing method for correcting troposphere delay and optimizing the operation complexity of an L ambda algorithm.
The technical scheme adopted by the invention is as follows:
a short-baseline RTK positioning method based on an airborne embedded platform comprises the following steps:
step 1: the airborne receiver receives observation information and reference station position information broadcasted by a ground reference station, and calculates pseudo-range double differences, carrier phase double differences and troposphere delay double differences by combining the own observation information of the airborne receiver;
step 2: constructing a double-difference observation equation for compensating troposphere delay according to the pseudo-range double difference, the carrier phase double difference and the troposphere delay double difference, and linearizing the equation;
and step 3: simultaneous linearized double-difference observation equations, neglecting the integer constraint of the carrier double-difference ambiguity, and adopting a least square method to obtain a floating solution of the base line vector X
Figure BDA0002451215100000031
Float solution of sum-carrier double-difference ambiguity Y
Figure BDA0002451215100000032
And covariance matrix Q of floating point solution:
the covariance matrix Q of the floating-point solution is:
Figure BDA0002451215100000033
wherein the content of the first and second substances,
Figure BDA0002451215100000034
and
Figure BDA0002451215100000035
are respectively as
Figure BDA0002451215100000036
And
Figure BDA0002451215100000037
the autocorrelation matrix of (a) is then determined,
Figure BDA0002451215100000038
is composed of
Figure BDA0002451215100000039
And
Figure BDA00024512151000000310
the cross-correlation matrix of (a) is,
Figure BDA00024512151000000311
is composed of
Figure BDA00024512151000000312
And
Figure BDA00024512151000000313
the cross correlation matrix of (a). Using ambiguity floating point solution and its covariance matrix
Figure BDA00024512151000000314
Integer solution for computing ambiguities
Figure BDA00024512151000000315
Figure BDA00024512151000000316
The integer constraint of the above equation must be considered and the solution of this step can be defined as
Figure BDA00024512151000000317
It is an integer least squares estimate of ambiguity;
step 4 adopting exempt square root LTD L decomposition method for double-difference ambiguity covariance matrix
Figure BDA00024512151000000318
Proceed to LTDecomposing D L to obtain L matrix and D matrix, wherein L represents lower triangular matrix and D represents diagonal matrix;
step 5, obtaining an integer domain Z transformation matrix according to the L matrix, so that the lower triangular element of the L Z matrix is minimum, and Z isT，Z，(ZT)-1All are integer matrixes, and a search space is constructed through a Z matrix as follows:
Figure BDA0002451215100000041
wherein Z is ZTY,
Figure BDA0002451215100000042
The value of χ ensures that at least two groups of integer solutions are obtained;
step 6: at x2Search in space such that
Figure BDA0002451215100000043
Minimum set of integer solutions
Figure BDA0002451215100000044
Judging the validity of the integer solution through the ratio value, converting the ambiguity after Z conversion to the original ambiguity to obtain the Y fixed solution of the carrier double-difference ambiguity
Figure BDA0002451215100000045
And 7: the fixed solution for the baseline vector X is found using the following equation:
Figure BDA0002451215100000046
wherein, the double-difference observation equation in the step (2) is as follows:
Figure BDA0002451215100000047
Figure BDA0002451215100000048
where λ represents the carrier wavelength, the indices r and u represent the reference station and rover station, respectively, the indices i and j represent the different satellite numbers,
Figure BDA0002451215100000049
a double-difference measurement of the pseudoranges is represented,
Figure BDA00024512151000000410
the double difference of the satellite distances of the stations is shown,
Figure BDA00024512151000000411
representing the double difference noise of the pseudoranges,
Figure BDA00024512151000000412
representing a double-difference observation of the carrier phase,
Figure BDA00024512151000000413
representing the double-difference ambiguity of the carrier phase,
Figure BDA00024512151000000414
representing the double-difference noise of the carrier phases,
Figure BDA00024512151000000415
is the tropospheric delay double difference.
Obtaining the result after the double-difference observation equation is linearized:
Vρ＝AX-Lρ
Vφ＝AX+BY-Lφ
wherein
Figure BDA00024512151000000416
Figure BDA0002451215100000051
Figure BDA0002451215100000052
Figure BDA0002451215100000053
j is a reference star, n represents the number of double-difference ambiguities,
Figure BDA0002451215100000054
respectively representing x, y and z direction components of a unit observation vector of the n number satellite relative to the rover;
wherein L in the step (4)TThe decomposition method of D L is as follows:
Figure BDA0002451215100000055
Figure BDA0002451215100000056
from the above formula, one can obtain:
Figure BDA0002451215100000057
Figure BDA0002451215100000058
wherein u isk＝lkmdk，m＝(n,…1),w＝(n,n-1,…,m+1)。
Professor Teuniessen mentions L in related papers using the fmfac6 functionTD L, first of all
Figure BDA0002451215100000059
Decomposition of
Figure BDA0002451215100000061
Figure BDA0002451215100000062
Figure BDA0002451215100000063
Then transformed into LTD L decomposition:
Dww＝lww/lww
lwm＝lwm/lww
the square root calculation is included, and the D matrix is split and recombined, and L adopted by the inventionTThe D L decomposition method does not contain square root operation and has lower operation complexity.
Compared with the prior art, the invention has the following beneficial effects:
1) the invention provides a double-difference observation equation establishing method for compensating troposphere delay, and the fixed rate of RTK resolving under an airborne high-altitude condition is improved through troposphere delay compensation.
2) Optimization L of the inventionTThe L ambda algorithm decomposed by the D L reduces the operation complexity and shortens the time required for calculating the ambiguity fixing solution in an onboard embedded platform.
Drawings
FIG. 1 is a block diagram of an apparatus of an airborne embedded platform short-baseline RTK positioning system of the present invention;
FIG. 2 is a flowchart of a short baseline RTK positioning method of an airborne embedded platform according to the present invention.
Detailed Description
The invention adopts an RTCM protocol to transmit differential information, and specifically comprises Beidou B1 and B3 double-frequency pseudo-ranges, carrier observed quantities and reference coordinates of a reference station. The specific implementation steps are shown in fig. 2:
step 1: as shown in fig. 1, an airborne receiver receives observation information and reference station position information broadcast by a ground reference station, and calculates pseudo-range double differences, carrier phase double differences and troposphere delay double differences by combining the own observation information of the airborne receiver;
step 2: and constructing a double-difference observation equation for compensating the troposphere delay according to the pseudo-range double difference, the carrier phase double difference and the troposphere delay double difference, and linearizing the equation:
the double-difference observation equation is:
Figure BDA0002451215100000071
Figure BDA0002451215100000072
where λ represents the carrier wavelength, the indices r and u represent the reference station and rover station, respectively, the indices i and j represent the different satellite numbers,
Figure BDA0002451215100000073
a double-difference measurement of the pseudoranges is represented,
Figure BDA0002451215100000074
the double difference of the satellite distances of the stations is shown,
Figure BDA0002451215100000075
representing the double difference noise of the pseudoranges,
Figure BDA0002451215100000076
representing a double-difference observation of the carrier phase,
Figure BDA0002451215100000077
representing the double-difference ambiguity of the carrier phase,
Figure BDA0002451215100000078
representing the double-difference noise of the carrier phases,
Figure BDA0002451215100000079
is the tropospheric delay double difference;
Figure BDA00024512151000000710
can be obtained by model calculation. Since tropospheric delay has already been solved in single-point positioning operations, the above observation equation does not increase the complexity of the operations.
Linearizing the double-difference observation equation for correcting troposphere delay to obtain the following equation:
Vρ＝AX-Lρ
Vφ＝AX+BY-Lφ
wherein
Figure BDA00024512151000000711
Figure BDA00024512151000000712
Figure BDA00024512151000000713
Figure BDA00024512151000000714
j is a reference star, n represents the number of double-difference ambiguities,
Figure BDA00024512151000000715
respectively representing x, y and z direction components of a unit observation vector of the n number satellite relative to the rover;
and step 3: and (3) after simultaneous linearization, neglecting the integer constraint of the double-difference ambiguity of the carrier wave to make the double-difference observation equation be a real number, solving the real number to be regarded as a standard least square estimation problem, and obtaining a floating solution of a base line vector X and the double-difference ambiguity of the carrier wave Y and a covariance matrix Q of the floating solution by adopting a least square method. The floating solution of the baseline vector X and the carrier double-difference ambiguity Y is:
Figure BDA0002451215100000081
this solution is commonly referred to as a floating point solution. The covariance matrix Q of the floating point solution obtained in the least squares solution process is:
Figure BDA0002451215100000082
wherein the content of the first and second substances,
Figure BDA0002451215100000083
and
Figure BDA0002451215100000084
are respectively as
Figure BDA0002451215100000085
And
Figure BDA0002451215100000086
the autocorrelation matrix of (a) is then determined,
Figure BDA0002451215100000087
is composed of
Figure BDA0002451215100000088
And
Figure BDA0002451215100000089
the cross-correlation matrix of (a) is,
Figure BDA00024512151000000810
is composed of
Figure BDA00024512151000000811
And
Figure BDA00024512151000000812
the cross-correlation matrix of (a);
step 4 adopting exempt square root LTD L decomposition method for double-difference ambiguity covariance matrix
Figure BDA00024512151000000813
To carry out
Figure BDA00024512151000000814
Decomposing to obtain L matrix and D matrix, wherein L represents a lower triangular matrix, and D represents a diagonal matrix;
and 5: according to
Figure BDA00024512151000000815
Obtaining an integer domain Z transform matrix the Z matrix minimizes the triangular elements under the L Z matrix, and the Z matrixT，Z，(ZT)-1All are integer matrixes, and a search space is constructed through a Z matrix as follows:
Figure BDA00024512151000000816
wherein Z is ZTY,
Figure BDA00024512151000000817
The value of χ ensures that at least two groups of integer solutions are obtained;
step 6: at x2Search in space such that
Figure BDA00024512151000000818
Minimum set of integer solutions
Figure BDA00024512151000000819
And carrying out integer solution validity judgment through a ratio value which is
Figure BDA00024512151000000820
The ratio of the next smallest solution to the smallest solution. If the ratio value is not greater than the threshold, the ambiguity fixing is considered to fail, and the floating solution is directly output
Figure BDA0002451215100000091
If the ratio value is larger than the threshold, the ambiguity is considered to be fixed successfully, the ambiguity after Z transformation is transformed to the original ambiguity, and the fixed solution of the carrier double-difference ambiguity Y is obtained
Figure BDA0002451215100000092
Due to ZT，Z，(ZT)-1All integers do not influence the integer property of the ambiguity in the conversion process;
and 7: after determining the carrier phase double-difference ambiguity, a fixed solution of the baseline vector X can be found using the following equation:
Figure BDA0002451215100000093
although the embodiments of the present invention have been described with reference to the accompanying drawings, it will be apparent to those skilled in the art that various changes and modifications may be made without departing from the principles of the invention, and these should be construed as being included in the scope of the invention.

Claims (3)

1. A short-baseline RTK positioning method based on an airborne embedded platform is characterized by comprising the following steps:
step 1: the airborne receiver receives observation information and reference station position information broadcasted by a ground reference station, and calculates pseudo-range double differences, carrier phase double differences and troposphere delay double differences by combining the own observation information of the airborne receiver;
step 2: constructing a double-difference observation equation for compensating troposphere delay according to the pseudo-range double difference, the carrier phase double difference and the troposphere delay double difference, and linearizing the equation;
and step 3: simultaneous linearized double-difference observation equations, neglecting the integer constraint of the carrier double-difference ambiguity, and adopting a least square method to obtain a floating solution of the base line vector X
Figure FDA0002451215090000011
Float solution of sum-carrier double-difference ambiguity Y
Figure FDA0002451215090000012
And a covariance matrix Q of the floating point solution;
the covariance matrix Q of the floating-point solution is:
Figure FDA0002451215090000013
wherein the content of the first and second substances,
Figure FDA0002451215090000014
and
Figure FDA0002451215090000015
are respectively as
Figure FDA0002451215090000016
And
Figure FDA0002451215090000017
the autocorrelation matrix of (a) is then determined,
Figure FDA0002451215090000018
is composed of
Figure FDA0002451215090000019
And
Figure FDA00024512150900000110
the cross-correlation matrix of (a) is,
Figure FDA00024512150900000111
is composed of
Figure FDA00024512150900000112
And
Figure FDA00024512150900000113
the cross-correlation matrix of (a);
step 4 adopting exempt square root LTD L decomposition method for double-difference ambiguity covariance matrix
Figure FDA00024512150900000114
Proceed to LTDecomposing D L to obtain L matrix and D matrix, wherein L represents lower triangular matrix and D represents diagonal matrix;
step 5, obtaining an integer domain Z transformation matrix according to the L matrix, so that the lower triangular element of the L Z matrix is minimum, and Z isT，Z，(ZT)-1All are integer matrixes, and a search space is constructed through a Z matrix as follows:
Figure FDA00024512150900000115
wherein Z is ZTY,
Figure FDA00024512150900000116
The value of χ ensures that at least two groups of integer solutions are obtained;
step 6: at x2Search in space such that
Figure FDA00024512150900000117
Minimum set of integer solutions
Figure FDA00024512150900000118
Judging the validity of the integer solution through the ratio value, converting the ambiguity after Z conversion to the original ambiguity to obtain the fixed solution of the carrier double-difference ambiguity Y
Figure FDA0002451215090000021
And 7: the fixed solution for the baseline vector X is found using the following equation:
Figure FDA0002451215090000022
2. the short-baseline RTK positioning method based on the airborne embedded platform as claimed in claim 1, wherein the double-difference observation equation in step (2) is:
Figure FDA0002451215090000023
Figure FDA0002451215090000024
where λ represents the carrier wavelength, the indices r and u represent the reference station and rover station, respectively, the indices i and j represent the different satellite numbers,
Figure FDA0002451215090000025
a double-difference measurement of the pseudoranges is represented,
Figure FDA0002451215090000026
the double difference of the satellite distances of the stations is shown,
Figure FDA0002451215090000027
representing the double difference noise of the pseudoranges,
Figure FDA0002451215090000028
representing a double-difference observation of the carrier phase,
Figure FDA0002451215090000029
representing the double-difference ambiguity of the carrier phase,
Figure FDA00024512150900000210
representing the double-difference noise of the carrier phases,
Figure FDA00024512150900000211
is the tropospheric delay double difference;
obtaining the result after the double-difference observation equation is linearized:
Vρ＝AX-Lρ
Vφ＝AX+BY-Lφ
wherein
Figure FDA00024512150900000212
Figure FDA00024512150900000213
Figure FDA00024512150900000214
Figure FDA0002451215090000031
j is a reference star, n represents the number of double-difference ambiguities,
Figure FDA0002451215090000032
respectively representing the x, y, z direction components of the unit observation vector of satellite n relative to the rover.
3. The short baseline RTK positioning method based on the embedded platform of claim 1, wherein L in step (4)TThe decomposition method of D L is as follows:
Figure FDA0002451215090000033
Figure FDA0002451215090000034
from the above formula, one can obtain:
Figure FDA0002451215090000035
Figure FDA0002451215090000036
wherein u isk＝lkmdk，m＝(n,…1),w＝(n,n-1,…,m+1)。
CN202010293296.6A 2020-04-15 2020-04-15 Short-baseline RTK positioning method based on airborne embedded platform Pending CN111458736A (en)

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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050151683A1 (en) * 2004-01-13 2005-07-14 Sharpe Richard T. Method for combined use of a local rtk system and a regional, wide-area, or global carrier-phase positioning system
CN102636800A (en) * 2012-04-28 2012-08-15 北京航空航天大学 Decorrelation method of global navigation satellite system (GNSS) integer ambiguity based on finishing pretreatment
CN105005060A (en) * 2015-07-20 2015-10-28 武汉大学 Parallel LLL high-dimensional ambiguity decorrelation algorithm
CN106646564A (en) * 2016-10-31 2017-05-10 电子科技大学 Navigation enhancing method based on low track satellite
CN106772474A (en) * 2016-12-14 2017-05-31 航天恒星科技有限公司 A kind of method and device for determining integer ambiguity
CN107957586A (en) * 2017-11-21 2018-04-24 东华理工大学 Correlation technique drops in a kind of fuzziness decomposed based on lower triangle Cholesky

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050151683A1 (en) * 2004-01-13 2005-07-14 Sharpe Richard T. Method for combined use of a local rtk system and a regional, wide-area, or global carrier-phase positioning system
CN102636800A (en) * 2012-04-28 2012-08-15 北京航空航天大学 Decorrelation method of global navigation satellite system (GNSS) integer ambiguity based on finishing pretreatment
CN105005060A (en) * 2015-07-20 2015-10-28 武汉大学 Parallel LLL high-dimensional ambiguity decorrelation algorithm
CN106646564A (en) * 2016-10-31 2017-05-10 电子科技大学 Navigation enhancing method based on low track satellite
CN106772474A (en) * 2016-12-14 2017-05-31 航天恒星科技有限公司 A kind of method and device for determining integer ambiguity
CN107957586A (en) * 2017-11-21 2018-04-24 东华理工大学 Correlation technique drops in a kind of fuzziness decomposed based on lower triangle Cholesky

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