CN112698371A - Navigation user autonomous integrity monitoring method based on INS assistance - Google Patents

Navigation user autonomous integrity monitoring method based on INS assistance Download PDF

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CN112698371A
CN112698371A CN202011409137.4A CN202011409137A CN112698371A CN 112698371 A CN112698371 A CN 112698371A CN 202011409137 A CN202011409137 A CN 202011409137A CN 112698371 A CN112698371 A CN 112698371A
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ins
satellites
user
pseudo
virtual
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刘小汇
吴孔阳
郭海玉
于美婷
王思鑫
姚闯
袁粤林
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National University of Defense Technology
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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
    • 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
    • G01S19/396—Determining accuracy or reliability of position or pseudorange measurements

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

Abstract

The invention provides an INS-assisted navigation user autonomous integrity monitoring method. The technical scheme is as follows: step one, constructing two virtual satellites, selecting one visible GNSS satellite, and calculating virtual pseudo-range observation values of an INS and the three satellites; secondly, calculating virtual pseudo range estimated values of the INS and the three satellites in the first step; thirdly, calculating a pseudo-range estimation value of the GNSS user and the visible GNSS satellite; fourthly, calculating the position and clock error of the user by utilizing an extended pseudorange equation set; and fifthly, carrying out integrity monitoring. The method can be used for monitoring the autonomous integrity of the navigation user only by two GNSS satellites, has strong applicability and can be better applied to signal conditions such as interference or shielding.

Description

Navigation user autonomous integrity monitoring method based on INS assistance
Technical Field
The invention relates to the technical field of satellite navigation, in particular to a method for monitoring satellite navigation signals.
Background
The autonomous integrity monitoring of the Navigation user refers to a user navigating by using a GNSS (Global Navigation satellite System) signal to judge the correctness of the received GNSS signal so as to ensure that the correct GNSS signal is used for positioning. The GNSS signals are easily affected by electromagnetic interference, shielding and multipath effects, so that the phenomena of information loss or information error and the like of a user receiver occur, a user positioning result has large deviation or cannot be positioned, and the safety of a user is possibly seriously threatened. The consequences of this can be catastrophic, such as in aviation users with high demands on life safety.
In addition, for weaponry using GNSS for navigation, the GNSS signal may be seriously interfered by targeted electromagnetic attack of enemies, so that the positioning performance of users is reduced and even completely disabled, thereby causing difficulties in command control and implementation of accurate attack on terminals, reducing the fighting capability of weaponry and causing substantial threat to enemies.
In consideration of the construction cost and convenience of the GNSS, the existing research on integrity monitoring of GNSS signals mainly focuses on user-independent integrity monitoring technology. The principle is that the accuracy detection of the GNSS signals by the user is realized by utilizing the consistency check of the redundant ranging information. The existing detection method is described in reference [1 ]. The detection algorithm needs at least 5 visible GNSS satellites, calculates a pseudo-range estimation value of a GNSS user and each visible GNSS satellite, constructs a pseudo-range observation equation set by using the pseudo-range estimation value, obtains a pseudo-range residual error by solving the equation set, calculates fault detection statistics by using the pseudo-range residual error, and determines the correctness of signals by comparing with a threshold. The method needs at least 5 visible GNSS satellites to carry out accuracy monitoring, so the method is poor in practicability under complex electromagnetic interference and shielding environments.
In recent years, with the deep development of autonomous navigation technology, it is becoming a hot point of research to improve the anti-jamming capability of the weaponry using GNSS and the reliability of navigation positioning by combining navigation technologies. In the integrated Navigation technology, an Inertial Navigation System (INS) is used as an auxiliary means for satellite Navigation, which not only can improve the positioning capability of a user under an interference condition, but also is used for monitoring the autonomous integrity of the user, and reduces the requirement of a monitoring method on the number of visible GNSS satellites. In the existing GNSS signal monitoring method based on INS assistance, see document [2], the method uses at least 3 visible GNSS satellites to calculate pseudo-range estimation values to construct a pseudo-range observation equation set, and uses a kalman filtering process to calculate pseudo-range residuals when solving the pseudo-range observation equation set to detect the correctness of navigation signals, but the method has poor model applicability, is sensitive to errors, and has large result errors and poor adaptability when the model and the user actual motion condition have deviations.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an INS-assisted navigation user autonomous integrity monitoring method, which can realize autonomous integrity monitoring under the condition that only two visible GNSS satellites exist. The method provided by the invention has strong applicability, is insensitive to the error of a calculation model, and can be used for monitoring the autonomous integrity under various signal conditions.
The technical scheme of the invention is as follows: the navigation user autonomous integrity monitoring method based on INS assistance is characterized in that when a pseudo-range observation equation set is constructed by calculating pseudo-range estimation values, two virtual satellites are constructed, one visible GNSS satellite is selected, and the virtual pseudo-range estimation values of the INS and the three satellites are calculated; and then forming an extended pseudo range observation equation set with pseudo range observation equations of at least two visible GNSS satellites.
Further, when the two virtual satellites are constructed, the user position output by the INS is perpendicular to the direction vector of each virtual satellite; the user position output by the INS and the direction vector of the visible GNSS satellite are perpendicular to a plane formed by the user position output by the INS and the two virtual satellites; and constructing two pseudo-range observation equations by using the user position information output by the INS and the positions of the two virtual satellites.
Further, when one visible GNSS satellite is selected, the satellite with the largest elevation angle in the current visible GNSS satellites is selected.
Further, the extended pseudo range observation equation set is solved by using a weighted least square method.
The invention has the technical effects that: according to the method, two virtual satellites are constructed by utilizing the user position information output by the INS, and the two virtual satellites are perpendicular to the INS position and the direction vectors of the visible GNSS satellite in pairs, so that constructed pseudo-range observation equations are not related to each other, and the complexity of solving the equations is simplified. The method only needs the position information of at least two visible GNSS satellites when calculating the user position and the error between the clock error and the true value by using the weighted least square method, does not need to use a Kalman filtering innovation detection method during calculation, only needs to use the position information of the user at the current moment, reduces the algorithm complexity and does not accumulate the error. The method can be used for monitoring the autonomous integrity of the navigation user only by two GNSS satellites, has strong applicability and can be better applied to signal conditions such as interference or shielding.
Drawings
FIG. 1 is a block diagram of a method for INS-assisted navigation user autonomy monitoring;
FIG. 2 is a diagram showing a direction vector between a user and a reference satellite or a virtual satellite;
FIG. 3 is a graph showing the comparison of the effects obtained by the experiment according to the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
The invention provides a navigation user autonomous integrity monitoring method based on INS assistance, which comprises the following steps:
step one, constructing two virtual satellites, selecting one visible GNSS satellite, and calculating virtual pseudo-range observation values of an INS and the three satellites;
the user position calculated by the GNSS and the user position output by the INS are assumed to be independent of each other, and the error between the two is ignored.
Knowing the current observation epoch tk(i.e., current time) sharingn (n is more than or equal to 2) visible GNSS satellites, and the INS works independently to obtain the current observation epoch tkIs in the coordinate X of ECEF (Earth Centered Earth Fixed coordinate system)INS＝(xI,yI,zI) And calculating to obtain the current observation epoch t according to the ephemeris information and the user position output by the INSkSatellite position with maximum elevation angle in visible GNSS satellite
Figure BDA0002818219650000031
The satellite with the largest elevation angle is called a reference satellite. In addition, other visible GNSS satellites may also be selected as the reference satellite, generally the higher the elevation angle the better.
Two virtual satellites are constructed so that the user position output by the INS is the vector l of the direction of the virtual satellite 1 (i.e. the vector with the user as the starting point and the virtual satellite 1 as the end point)1The INS outputs a vector of the user's position and the direction of the virtual satellite 2 (i.e. the vector with the user as the starting point and the virtual satellite 2 as the ending point)/2The user position output by the INS and the direction vector l of the reference star (i.e. the vector with the user as the starting point and the reference star as the ending point)0The above vectors being perpendicular to each other two by two, i.e. /)1⊥l2，l1⊥l0，l2⊥l0See fig. 2. Let the coordinates of the two virtual satellites under ECEF be respectively
Figure BDA0002818219650000041
Respectively calculating virtual pseudo-range observed values rho of the INS and the three satellitesINS0,s(s＝1,2,3)：
Figure BDA0002818219650000042
Secondly, calculating virtual pseudo range estimated values of the INS and the three satellites in the first step;
for the current observation epoch tkAssuming that the user position estimate is
Figure BDA0002818219650000043
The estimated value may take any value. Calculating an estimated user position using the equation
Figure BDA0002818219650000044
Virtual pseudo-range estimation values of reference satellite and two virtual satellites
Figure BDA0002818219650000045
Figure BDA0002818219650000046
Thirdly, calculating a pseudo-range estimation value of the GNSS user and the visible GNSS satellite;
for the current observation epoch tkSuppose that the user's clock error estimate is
Figure BDA0002818219650000047
The estimated value may take any value. The GNSS user and n visible GNSS satellites are in the current observation epoch tkPseudo-range estimate of
Figure BDA0002818219650000048
Comprises the following steps:
Figure BDA0002818219650000049
wherein (x)i,yi,zi) And obtaining the position of the ith visible GNSS satellite according to the ephemeris information.
Fourthly, calculating the position and clock error of the user by using the extended pseudo-range equation set
Establishing an extended pseudorange equation set as follows:
Y＝HX+ε (4)
wherein:
Figure BDA0002818219650000051
Figure BDA0002818219650000052
X＝[Δx,Δy,Δz,Δδtu]T (7)
ε＝[ε1,ε2,…εi,…εn,εINS,1,…εINS,3]T (8)
in the above equation, ρiPseudorange observations (i 1, 2.., n) for the user and n visible GNSS satellites are measured using the user's GNSS receiver; in the H matrix, Hi＝[-ei,1-ei,2-ei,31](i-1, … n), wherein
Figure BDA0002818219650000053
Respectively representing the three-axis components of the direction vector from the user to the ith visible GNSS satellite in the ECEF coordinate system,
Figure BDA0002818219650000054
Figure BDA0002818219650000055
wherein
Figure BDA0002818219650000056
The three-axis component of the direction vector from the user to the reference satellite and the two virtual satellites in the ECEF coordinate system is represented, and the vector does not have a clock error item in the user position output by the INS
Figure BDA0002818219650000057
The clock difference value corresponding to the fourth component is 0; epsiloni(i ═ 1, … n) indicates that the user receiver has measured pseudorange measurement errors for the ith visible GNSS satellite, satisfying a normal distribution with zero mean,
Figure BDA0002818219650000058
Figure BDA0002818219650000059
is the range error variance of the satellite. EpsilonINS,s(s is 1,2,3) represents the virtual pseudo-range measurement error of the INS to the reference satellite and the two virtual satellites, and satisfies the normal distribution of zero mean value,
Figure BDA00028182196500000510
Figure BDA00028182196500000511
is the positioning error variance of the INS.
In the above equation set, the first three components (Δ X, Δ y, Δ z) of the vector X represent the estimated position and the true position (X) of the useru,yu,zu) The difference between the values of the two signals,
Figure BDA00028182196500000512
Δδturepresenting the value of the user's clock error estimate versus the value of the true user's clock error deltatuDifference between them
Figure BDA00028182196500000513
Iteratively solving the equation set (4) by using a weighted least square method to obtain an estimated value of the vector X
Figure BDA00028182196500000514
Figure BDA00028182196500000515
Wherein W is a weighting matrix, the diagonal element is the reciprocal of the variance of the pseudorange measurements, and since there is no correlation between the GNSS receiver ranging error and the INS virtual pseudorange error, i.e. Cov (ε)i,εj)＝0，Cov(εi,εINS,j) The direction vectors between the three virtual observations constructed by the INS are mutually perpendicular two by two, so that the virtual observation errors are considered to be uncorrelated, namely: cov (. epsilon.)INS,i,εINS,j) 0, so the off-diagonal element of the weight matrix W is 0, i.e.
Figure BDA0002818219650000061
Wherein
Figure BDA0002818219650000062
Obtained according to the INS manual.
Figure BDA0002818219650000063
Is the sum of the variances of a plurality of error sources, i.e.
Figure BDA0002818219650000064
Figure BDA0002818219650000065
For the satellite clock and the ephemeris error variance,
Figure BDA0002818219650000066
in order to correct for the variance of the ionospheric errors,
Figure BDA0002818219650000067
in order to correct the tropospheric error variance,
Figure BDA0002818219650000068
in order to be the multi-path error variance,
Figure BDA0002818219650000069
is the variance of the range error caused by the thermal noise inside the receiver. The various types of variances described above can be obtained from user manuals or empirical values.
The fifth step, carry on the integrity monitoring
And calculating to obtain a pseudo-range residual error v by using a pseudo-range residual error calculation formula:
Figure BDA00028182196500000610
and then calculating the variance normalized pseudorange residual sum of squares SSE by using a weighted least square method (namely the following formula):
SSE＝vTWv (12)
then, calculating a fault detection statistic T according to the sum of squared residuals SSE:
Figure BDA00028182196500000611
given a false alarm probability PFAThen, the fault detection threshold T is calculated using the following equationd：
Figure BDA00028182196500000612
Figure BDA0002818219650000071
Comparing the fault detection statistic T with the fault detection threshold TdIf T > TdIf so, the problem that the received GNSS signal is incorrect is indicated; otherwise, the received GNSS signal is normal.
Fig. 3 is a graph comparing the effects obtained by the experiment using the present invention and the prior art. In experiment a, 7 visible GNSS satellites are provided, and the set false alarm probability P isFA＝10-5Standard deviation of positioning error in INS
Figure BDA0002818219650000072
In this case, a fault with an amplitude of 0-100m is added to the first visible GNSS satellite, with a step size of 10 m. Using MATLAB simulation tool to calculate and use the method of the present invention and the existing weighted least squares method[1]10000 times of tests are carried out on the autonomous integrity monitoring results under different fault amplitude values by using a Monte Carlo method, the test results are shown in figure 3(a), the abscissa represents the fault amplitude value, the ordinate represents the fault detection probability, the broken line with cross signs represents the result of the existing weighted least square method, and the broken line with circles represents the faultThe result of the invention can be seen from the figure that the fault detection probability of the invention is higher than that of the existing weighted least square method under each fault amplitude. Particularly, when the fault amplitude is 50m, the fault detection probability of the invention is 93.72%, the fault detection probability of the existing weighted least square algorithm is only 48.64%, and the detection probability performance of the invention can be improved by 45%.
In the test b, 2 visible GNSS satellites are set, other simulation conditions are kept unchanged, an MATLAB simulation tool is used for calculating autonomous integrity monitoring results under the conditions of different fault amplitudes simulated by the method, a Monte Carlo method is used for 10000 times of tests, the test results are shown in fig. 3(b), the abscissa represents the fault amplitude, the ordinate represents the fault detection probability, and when the fault amplitude is 50m, the fault detection probability is 80.56%.
Reference to the literature
[1] Raim algorithm research [ J ] based on weighted least square method, photoelectric and control, 2017,24(11):7-10.
[2] Liu Hai Ying, Feng Tao, Wanghuan an inertial assisted satellite navigation system and an integrity detection method thereof [ J ] astronavigation report, 2011,32(4): 775-780.

Claims (5)

1. The navigation user autonomous integrity monitoring method based on INS assistance is characterized in that when a pseudo-range observation equation set is constructed by calculating pseudo-range estimation values, two virtual satellites are constructed, one visible GNSS satellite is selected, and the virtual pseudo-range estimation values of the INS and the three satellites are calculated; then forming an extended pseudo range observation equation set with pseudo range observation equations of at least two visible GNSS satellites; wherein, INS refers to inertial navigation system, GNSS refers to global satellite navigation system.
2. The method of claim 1, wherein the INS-assisted navigation user autonomous integrity monitoring is performed by constructing two virtual satellites such that the INS-output user position is perpendicular to the direction vector of each virtual satellite; the user position output by the INS and the direction vector of the visible GNSS satellite are perpendicular to a plane formed by the user position output by the INS and the two virtual satellites; and constructing two pseudo-range observation equations by using the user position information output by the INS and the positions of the two virtual satellites.
3. The method of claim 2, wherein selecting one visible GNSS satellite selects a satellite with a largest elevation angle among currently visible GNSS satellites.
4. The INS-assisted based navigation user autonomous integrity monitoring method of claim 3, wherein the extended pseudorange observation equations are solved using a weighted least squares solution.
5. An INS-assisted navigation user autonomous integrity monitoring system, characterized in that the method of one of the claims 1 to 4 performs navigation user autonomous integrity monitoring.
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Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101629997A (en) * 2009-07-24 2010-01-20 南京航空航天大学 Detection device and detection method of navigation integrity of inertia subsatellite

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101629997A (en) * 2009-07-24 2010-01-20 南京航空航天大学 Detection device and detection method of navigation integrity of inertia subsatellite

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
吴孔阳 等: ""一种基于多虚拟观测量的组合导航自主完好性监测方法", 《中国空间科学技术》, 24 September 2020 (2020-09-24), pages 1 - 8 *

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