CN110687557B - Advanced receiver autonomous integrity monitoring protection level optimization method and device - Google Patents

Advanced receiver autonomous integrity monitoring protection level optimization method and device Download PDF

Info

Publication number
CN110687557B
CN110687557B CN201910903321.5A CN201910903321A CN110687557B CN 110687557 B CN110687557 B CN 110687557B CN 201910903321 A CN201910903321 A CN 201910903321A CN 110687557 B CN110687557 B CN 110687557B
Authority
CN
China
Prior art keywords
subset
fault
detection
integrity
protection level
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201910903321.5A
Other languages
Chinese (zh)
Other versions
CN110687557A (en
Inventor
薛瑞
赵勇
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beihang University
Original Assignee
Beihang University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beihang University filed Critical Beihang University
Priority to CN201910903321.5A priority Critical patent/CN110687557B/en
Publication of CN110687557A publication Critical patent/CN110687557A/en
Application granted granted Critical
Publication of CN110687557B publication Critical patent/CN110687557B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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

Abstract

The invention provides a method and equipment for optimizing an autonomous integrity monitoring protection level of an advanced receiver. The method comprises the following steps: calculating global positioning information of a receiver and subset positioning information of a fault subset according to ISM information of a plurality of satellites; calculating the distribution of positioning estimation errors of the receiver and the distribution of detection statistics of the fault subsets according to the global positioning information and the subset positioning information; if the detection statistic is determined to pass the detection, calculating the optimized protection level according to the optimization function of the minimized integrity risk, the distribution of the positioning estimation error and the distribution of the detection statistic; and if the ARIAM is judged to be available according to the optimized protection level, outputting the positioning result of the receiver. According to the method provided by the embodiment of the invention, whether different fault subsets pass detection or not is determined under the geometric distribution of the unbalanced satellite, and the integrity target under each satellite fault hypothesis is established, so that the minimized integrity risk is taken as a target, and the integrity risk caused by the missed detection of the fault is reduced.

Description

Advanced receiver autonomous integrity monitoring protection level optimization method and device
Technical Field
The invention relates to the technical field of aviation monitoring, in particular to an advanced receiver autonomous integrity monitoring protection level optimization method and device.
Background
With the wide application of a Global Navigation Satellite System (GNSS), users have increasingly high requirements for GNSS Navigation safety and integrity, and in Performance indexes of a precision Navigation technology (RNP), the integrity is directly related to aviation safety, and the integrity refers to the capability of the System to give an alarm to the users in time when Navigation errors exceed an upper limit allowed by safe operation. The GNSS navigation signal is a modulation wave for navigation positioning broadcasted by GNSS to a user, and the signal is affected by various factors in the process of propagation to generate errors, such as satellite clock error, satellite ephemeris error, ionospheric delay, tropospheric delay, multipath, receiver noise and the like, and the errors are superposed at a user end to cause pseudo-range errors.
In the existing Advanced Receiver Autonomous Integrity Monitoring (Advanced Receiver Autonomous Integrity Monitoring, referred to as "ARAIM"), a Multiple failure Hypothesis Solution Separation (MHSS) algorithm is mainly used, satellite failure detection and failure identification are respectively provided on the basis of uniform geometric distribution of fully visible satellites, a positioning Solution of the fully visible satellites is defined in the algorithm as a global positioning Solution, a subset positioning Solution is a positioning Solution of the fully visible satellites excluding one or more satellites, the basic principle is that the fully visible satellites are used as a reference, then the distance between each subset positioning Solution and the global positioning Solution is calculated, and whether a failure exists is judged by comparing the distance with a threshold value. The algorithm considers that in the absence of a fault, the global positioning solution and all subset positioning solutions should be clustered together, whereas if a faulty satellite is present, the global positioning solution and the subset positioning solution using the faulty satellite will produce an offset, and the subset positioning solution without the faulty satellite will be closer to the true position of the aircraft.
However, in practical applications, especially when the visible number of satellites is small, the geometric distribution of the satellites is unbalanced, so that misarrangement and missing arrangement of the failed satellites are caused, dangerous misleading information is formed, and the integrity of autonomous integrity monitoring of the advanced receiver is affected.
Disclosure of Invention
The invention provides an advanced receiver autonomous integrity monitoring protection level optimization method and equipment, which are used for reducing integrity risks caused by fault omission.
In a first aspect, the present invention provides an advanced receiver autonomous integrity monitoring protection level optimization method, including:
calculating global positioning information of the receiver and subset positioning information of the fault subset according to the integrity support ISM information of the plurality of satellites;
calculating a positioning estimation error of a receiver and a detection statistic of the fault subset according to the global positioning information and the subset positioning information;
if the detection statistic is determined to pass the detection, calculating an optimized protection level according to an optimization function minimizing the integrity risk, the positioning estimation error of the receiver and the detection statistic of the fault subset;
and if the autonomous integrity monitoring ARIAM of the advanced receiver is available according to the optimized protection level, outputting the positioning result of the receiver.
In a second aspect, the present invention provides an advanced receiver autonomous integrity monitoring protection level optimization device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the method of any of the first aspects via execution of the executable instructions.
According to the method and the equipment for optimizing the autonomous integrity monitoring protection level of the advanced receiver, the global positioning information of the receiver and the subset positioning information of the fault subset are calculated according to the integrity support ISM information of a plurality of satellites; calculating a positioning estimation error of a receiver and a detection statistic of the fault subset according to the global positioning information and the subset positioning information; if the detection statistic is determined to pass the detection, calculating an optimized protection level according to an optimization function minimizing the integrity risk, the positioning estimation error of the receiver and the detection statistic of the fault subset; and if the autonomous integrity monitoring ARIAM of the advanced receiver is available according to the optimized protection level, outputting a positioning result of the receiver, and particularly under the condition of non-equilibrium satellite geometric distribution, determining whether the detection is passed or not by different fault subsets, and then establishing integrity targets under the assumption of each satellite fault to take the minimized integrity risk as a target, thereby reducing the integrity risk caused by fault omission and ensuring the aviation flight safety.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
FIG. 1 is a schematic diagram of the geometric distribution of non-equilibrium satellites provided by the present invention;
FIG. 2 is a flow chart illustrating an embodiment of a method for optimizing the protection level of the advanced receiver autonomous integrity monitoring provided by the present invention;
fig. 3 is a schematic structural diagram of an embodiment of the advanced receiver autonomous integrity monitoring protection level optimizing device provided in the present invention.
With the foregoing drawings in mind, certain embodiments of the disclosure have been shown and described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
The terms "comprising" and "having," and any variations thereof, in the description and claims of this invention and the drawings described herein are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
First, the nouns and application scenarios related to the present invention are introduced:
when the GNSS is applied to civil aviation, the GNSS must satisfy a Required Navigation Performance (RNP) index, which is mainly reflected in four parameters of integrity, continuity, accuracy, and availability. According to the International Civil Aviation Organization (ICAO) regulations, the four parameters are defined as follows:
precision (Accuracy): the difference between the user's position determined by the navigation system and the user's true position.
Integrity (Integrity): the system provides a confidence level for the navigation information, the ability of the system to alert the user within a given time when the navigation information cannot be provided due to a fault. The probability that the system cannot detect dangerous misleading information is called integrity risk.
Continuity (Continuity): the ability of the system to meet positioning accuracy and integrity requirements throughout the operational phase without interruption. The probability that the system is alerted and unable to provide navigation information throughout the operational phase is referred to as a continuity risk.
Availability (Availability): the system can satisfy the ratio of the time of positioning precision, integrity and continuity to the whole running time of the system.
ARAIM is an integrity monitoring algorithm embedded in an aircraft receiver, and belongs to the space-based augmentation technology. ARAIM is based on multi-constellation autonomous integrity monitoring and is capable of supporting vertical and horizontal navigation globally.
ARAIM treatment procedure: one or more constellations for navigation provide satellite pseudorange measurements, the ARAIM ground monitoring network transmits the observed available satellites and their performance as part of the integrity support information to the user, who then determines from the ISM information which combination of satellite failures must be detected, and then further determines the subset of failures that need to be estimated and calculates a location solution for each subset of failures, any failed satellites will be identified and eliminated.
In the process of satellite signal propagation, positioning errors are generated under the influence of various factors, and the errors mainly include troposphere errors, ephemeris clock errors, receiver noise errors, multipath errors and the like. These navigation signals that cause large deviations in positioning are referred to as satellite failures. If these faulty satellite signals are used, the positioning results will be highly biased.
The failure subset refers to the set formed by excluding one satellite or a plurality of satellites from the full-visible satellites.
The positioning solution solved by using the fully visible stars is called a global positioning solution, and the corresponding positioning solution solved by using the fault subset is called a subset positioning solution.
Whether a faulty satellite exists can be judged by comparing the distances of the subset positioning solutions and the global positioning solution. If the distances between all the subset positioning solutions and the global positioning solution are smaller than a threshold value, namely a detection threshold, the current visible satellite is considered to have no fault, and if the distances between the individual subset positioning solutions and the global solution exceed the threshold, the fault satellite is considered to exist.
The ARAIM basic algorithm is based on the assumption of balanced distribution of satellites, and in practical application, the geometric distribution of the satellites is not always balanced. For the geometric distribution of the non-equilibrium satellites, as shown in fig. 1, different satellites (numbers 1-5) have different sensitivity degrees to positioning errors and have different weights in positioning solution, so when the satellites with different weights fail, the influence of the satellites with different weights on the positioning errors is different, and in the ARAIM basic algorithm, the influence of the imbalance of the geometric distribution of the satellites on the positioning errors is ignored, so that the observation failure of the satellites with high weights causes the missing detection of the satellite failures, the integrity risk is formed, and the risk is caused to the aviation safety.
The method provided by the embodiment of the invention mainly aims at the geometric distribution of the unbalanced satellite, and based on the estimation of the missed detection probability, the integrity targets under the assumption of each satellite fault are established by adopting different detection thresholds for different fault subsets, so that the integrity risk caused by the missed detection of the fault is reduced, and the aviation flight safety is guaranteed.
Integrity support Information (ISM) is an important part of the information used by the ARAIM algorithm to calculate the vertical protection level, and is collected and broadcast by a ground reference receiver to a user, so that the ground reference receiver can provide the user with safety judgment information with extremely high reliability required by a satellite navigation system, namely performance prediction of each satellite used for navigation, and the safety judgment information comprises the following components:
1. the prior fault probability of each satellite and the prior fault probability of the constellation;
2. user Ranging Accuracy (URA);
3. user Ranging Error (URE);
4. standard deviation for integrity bnomAnd the like.
Specific parameters are shown in table 1.
TABLE 1 ISM information and user input information List
Figure BDA0002212510040000051
Figure BDA0002212510040000061
The user's input parameters are shown in table 2:
TABLE 2 user Algorithm parameter List
Parameter name Description of the invention Reference value
PHMI Total integrity budget 10-7
PHMIVERT Overall integrityBudget vertical component 9.8×10-8
PHMIHOR Total integrity budget horizontal component 2×10-9
PCONST_THRES Integrity threshold from failure of unmonitored constellation 4×10-8
PSAT_THRES Integrity threshold for faults from unmonitored satellites 4×10-8
PFA Continuity budget allocated to false alarm induced interrupts 4×10-6
PFA_VERT Continuity budget allocated to vertical mode 3.9×10-6
PFA_HOR Allocating a continuity budget to a horizontal mode 9×10-8
PFA_CHI2 Continuity budget allocated to chi-square test 10-8
TOLPL Guard level calculation margin 5×10-2m
KACC Number of standard deviations used for precision calculation 1.96
KFF Number of standard deviations for no vertical position failure 5.33
PEMT Probability for calculating EMT (effective monitoring threshold) 10-5
TCHEcK Time constants between consistency checks for excluded satellites 300s
TRECOV Minimum time period for excluded satellites to recover full visible constellation set 600s
Fig. 2 is a flowchart illustrating an embodiment of an advanced receiver autonomous integrity monitoring protection level optimization method provided in the present invention. As shown in fig. 2, the method provided by this embodiment includes:
step 201, calculating global positioning information of the receiver and subset positioning information of the fault subset according to the integrity support ISM information of a plurality of satellites.
Specifically, the integrity support ISM information may include, for example, ranging error, ranging accuracy, troposphere error, multipath, and user receiver noise, and the step 101 may be implemented as follows:
calculating a pseudorange covariance matrix for integrity and a pseudorange covariance matrix for precision and continuity according to a ranging error, ranging precision, troposphere error, multipath and user receiver noise included in the ISM information;
and calculating global positioning information of the receiver and subset positioning information of the fault subset by using a weighted least square method according to the pseudo-range covariance matrix for integrity.
The global positioning information comprises a global positioning solution, and the subset positioning information comprises a subset positioning solution.
For the subset positioning solution of the fault subset, fault hypotheses are performed on all visible satellites, including single satellite fault hypotheses, multiple satellite fault hypotheses and constellation fault hypotheses, all faults which can occur are combined and arranged for each hypothesis, and then the subset positioning solution of each fault subset is solved.
Step 202, calculating a receiver positioning estimation error and a detection statistic of the fault subset according to the global positioning information and the subset positioning information.
Specifically, assume that the total number of satellites is NsatWhen the ith satellite fails, the position estimation error may be gaussian distributed following a non-zero mean.
Assume that the number of fault subsets is Nfault_modesDetection statistics for the kth fault subset
Figure BDA0002212510040000071
May be gaussian distributed following a zero mean.
Step 203, if it is determined that the detection statistic passes the detection, calculating an optimized protection level according to an optimization function minimizing the integrity risk, the positioning estimation error of the receiver and the detection statistic of the fault subset.
Further, before step 203, the following operations may be performed:
calculating a threshold of fault detection according to the distribution of the detection statistics;
determining whether the detection statistic passes the detection according to the threshold of the fault detection;
if the detection statistic fails to pass the detection, performing fault elimination until the detection statistic passes the detection;
and if the detection statistic passes the detection, calculating the optimized protection level according to an optimization function of minimizing the integrity risk and the distribution of the positioning estimation error and the detection statistic.
In this embodiment, for each fault subset, whether the detection statistic of the fault subset passes the detection is determined, and if not, the fault is eliminated until the detection statistic passes the detection.
The protection stage includes a vertical protection stage and a horizontal protection stage, and the vertical protection stage is mainly taken as an example in the embodiment of the present invention for description.
And 204, if the autonomous integrity monitoring ARIAM of the advanced receiver is judged to be available according to the optimized protection level, outputting a positioning result of the receiver.
Specifically, if the optimized vertical protection level is smaller than a preset vertical warning limit VAL, then the ariim is available; if the optimized vertical protection level is greater than the VAL, the ARIAM is unavailable.
According to the method, global positioning information of a receiver and subset positioning information of a fault subset are calculated according to the integrity support ISM information of a plurality of satellites; calculating a positioning estimation error of a receiver and a detection statistic of the fault subset according to the global positioning information and the subset positioning information; if the detection statistic is determined to pass the detection, calculating an optimized protection level according to an optimization function minimizing the integrity risk, the positioning estimation error of the receiver and the detection statistic of the fault subset; and if the autonomous integrity monitoring ARIAM of the advanced receiver is available according to the optimized protection level, outputting a positioning result of the receiver, and particularly under the condition of non-equilibrium satellite geometric distribution, determining whether the detection is passed or not by different fault subsets, and then establishing integrity targets under the assumption of each satellite fault to take the minimized integrity risk as a target, thereby reducing the integrity risk caused by fault omission and ensuring the aviation flight safety.
On the basis of the foregoing embodiment, further, calculating a pseudorange covariance matrix for integrity and a pseudorange covariance matrix for precision and continuity according to a ranging error, a ranging precision, a troposphere error, a multipath and a user receiver noise included in the ISM information may specifically be implemented as follows:
calculating a pseudorange covariance matrix according to a ranging error, ranging precision, troposphere error, multipath and user receiver noise in the ISM information by using the following formula (1) and formula (2);
Figure BDA0002212510040000081
Figure BDA0002212510040000082
wherein i is 1,2satRepresents the ith satellite, NsatAs a result of the total number of satellites,
Figure BDA0002212510040000083
is the variance of the ranging error for the ith satellite,
Figure BDA0002212510040000084
is the variance of the ranging accuracy of the ith satellite,
Figure BDA0002212510040000085
is the variance of tropospheric error for the ith satellite,
Figure BDA0002212510040000086
the variance of multipath and user receiver noise for the ith satellite; cint(i, i) denotes the pseudorange covariance matrix for integrity, and Cacc(i, i) represents the pseudorange covariance matrix for accuracy and continuity;
the global positioning information includes a global positioning solution, and the global positioning information of the receiver is calculated by using a weighted least square method according to the pseudo-range covariance matrix for integrity, which may specifically be as follows:
the global positioning solution is calculated according to the weighted least squares method using the following formula (3)
Figure BDA0002212510040000096
Figure BDA0002212510040000091
Wherein G is Nsat×(3+Nconst) Geometric observation matrix of, NconstRepresenting the number of constellations, y being the pseudorange residuals, and the weighting matrix W ═ Cint -1(i,i)；
The subset positioning information includes a subset positioning solution, and the subset positioning information of the fault subset is calculated by using a weighted least square method according to the pseudo-range covariance matrix for integrity, which can be specifically realized by the following method:
calculating a subset locator solution for the kth fault subset according to equation (4) below
Figure BDA0002212510040000092
Figure BDA0002212510040000093
Wherein, k is 1fault_modes，Nfault_modesIndicates the number of fault subsets, W(k)Is the weighting matrix for the kth fault subset,wherein
Figure BDA0002212510040000094
idxkDenotes the satellite index, idx, in the kth failure subsetk＝{i1,...,it}。
The first three columns of the geometric observation matrix G are the same as G in the RAIM method, and the remaining columns correspond to the reference clock of each constellation.
Before calculating a subset positioning solution of the fault subset, determining the fault subset to be monitored by using the following formula (a) according to the satellite fault prior probability in the ISM information;
Figure BDA0002212510040000095
wherein N issat,maxIndicating the maximum number of satellites, P, that are failing at the same timesat,iRepresenting the prior probability of failure, P, of the ith satellitesat,not_monitoredIndicating the probability of at least t satellites failing simultaneously, Psat_thresAn integrity threshold indicating a failure of an unmonitored satellite.
When N is presentsat,maxIf so, all subsets of faults may be determined.
On the basis of the foregoing embodiment, further, step 202 may specifically be implemented as follows:
when the ith satellite fails, the positioning estimation error epsiloni' Gaussian distribution subject to non-zero mean, as in equation (5):
ε′i～N(ηibnom,i,(GTWG)-1) (5)
wherein the content of the first and second substances,
Figure BDA0002212510040000101
epsilon represents the measurement error, and if the measurement errors of all the satellites are normally distributed with a zero mean value, E (epsilon) is 0, x is the real position, and S is(0)A projection matrix representing the full apparent star time, bnomIs a standard deviation, ηiRepresenting the weight of the ith satellite in the positioning solution, bnom,iDenotes the standard deviation corresponding to the ith satellite, W and G have the same meaning as in equation (3);
calculating a distribution of detection statistics for a receiver, comprising:
obtaining detection statistics of the kth fault subset according to the global positioning solution and the subset positioning solution
Figure BDA0002212510040000102
Obey a zero mean gaussian distribution, as in equation (6):
Figure BDA0002212510040000103
wherein the content of the first and second substances,
Figure BDA0002212510040000104
S(k)representing the projection matrix corresponding to the kth fault subset, S(0)A projection matrix representing the full satellite time of sight, wherein, for the ith satellite,
Figure BDA0002212510040000105
the threshold T for fault detection is calculated using equation (7)k：
Figure BDA0002212510040000106
Wherein, betakRepresents H0Detection alarm rate P (| Δ x) under assumption(k)|≥Tk|H0)，H0The assumption that all the stars are visible is represented,
Figure BDA0002212510040000107
Q-1() Is the inverse function of Q.
Wherein eta isiReflecting the weight of the ith satellite in the positioning solution. Different satellites have different weights in the positioning solution, the same standard deviation bnomWhen the positioning error occurs on different observation satellites, the caused positioning error is different, the mean value is different, and the variance is the same. In the positioning domain, the probability of the positioning estimation error exceeding the limit is therefore related to the geometric distribution of the satellites, i.e. to the weight of each satellite observation in the positioning solution.
In which ξkOnly in relation to the geometric distribution of the satellite, for non-uniform geometric distribution of the satellite, different satellites correspond to different xikEach satellite has a certain influence on the detection threshold. For xikThe satellite with a smaller value is concentrated with other satellites, when the satellite fails, the detection statistic of the satellite is smaller and is insensitive to fault deviation, and the failure is difficult to detect by a detection threshold, so that missing detection is easy to cause and integrity risk is caused.
Q: the cumulative distribution function of the zero mean gaussian distribution has the following mathematical expression:
Figure BDA0002212510040000111
wherein Q-1() Is the inverse function of Q.
Further, determining whether the detection statistic passes the detection may be implemented as follows:
if | Δ x(k)|≤TkThen the statistic Δ x is detected(k)Passing the detection;
if | Δ x(k)|≥TkThen the statistic Δ x is detected(k)Failing to pass the detection, and carrying out fault elimination until the detection statistic delta x(k)And (4) passing the detection.
In particular, according to xi of the satellitekAnd adjusting the dynamic threshold of the fault subset to ensure that a smaller satellite has a corresponding smaller detection threshold, thereby reducing the missed detection rate and reducing the integrity risk.
Further, step 203 may specifically be implemented as follows:
solving the vertical protection level that minimizes the optimization function of the integrity risk as the optimized vertical protection level using the following equation (8):
Figure BDA0002212510040000112
wherein r ═ GTWG)-1，Nfault_modesIndicates the number of subsets of faults,
Figure BDA0002212510040000113
is representative of xikI.e. representing ξkIn the component of the i-th satellite,
Figure BDA0002212510040000114
representing the prior probability of the failure subset k.
The following formula (8) is used to solve the vertical protection level that minimizes the optimization function of the integrity risk, and as the optimized vertical protection level, the following method may be specifically adopted:
respectively for η in formula (9)i,
Figure BDA0002212510040000115
Derivation to find the extreme point
Figure BDA0002212510040000116
Then the extreme point is calculated
Figure BDA0002212510040000117
And substituting the formula (9) to obtain the optimized vertical protection level.
In particular, the positioning estimation error and the detection statistic are independent of each other as demonstrated by the analysis. Therefore, the integrity risk of any fault subset can represent the product of the probability of positioning error over-limit, the probability of fault detection missing detection and the prior probability of the fault subset, and is specifically represented as:
Figure BDA0002212510040000121
wherein HkHypothesis, P, representing the kth subset of faultsHMI,kIndicating the integrity risk of the kth subset of faults.
In the non-uniform satellite geometry distribution, etaiThe influence of the satellite with larger value on the positioning error is higher than that of other etaiThe sensitivity of the detection statistic to fault deviation is poor, and if the detection is performed by adopting a threshold equal to that observed by other satellites, the missed detection rate of the fault is high, and the integrity risk is increased. And the integrity risk under each satellite failure hypothesis consists of the product of the overrun probability of the positioning estimation error, the missed detection probability of the failure detection and the prior probability of the failure subset. Therefore, with the minimized integrity risk as the optimization goal, the mathematical expression is abstracted as:
Figure BDA0002212510040000122
in the case of a fault, the i-th component of the detection statistic follows a Gaussian distribution, i.e.
Figure BDA0002212510040000123
Then there is a fault HkThe probability of missed detection under the conditions is:
Figure BDA0002212510040000124
from the analysis in step 202, the positioning estimation error is obeyed
Figure BDA0002212510040000125
For convenience of calculation, let r ═ GTWG)-1From this, the overrun probability of the positioning error can be expressed as:
Figure BDA0002212510040000126
the optimization function can be further simplified to equation (9).
By solving the optimization problem of the formula (9), the danger misleading information can be dynamically distributed to each assumed fault mode, and the problem of high omission ratio of high-weight satellite observation faults under the unbalanced problem is solved. This is in fact an optimal solution problem that can be considered as one about
Figure BDA0002212510040000131
The function solves the problem of the minimum value.
Figure BDA0002212510040000132
Wherein
Figure BDA0002212510040000133
Is that
Figure BDA0002212510040000134
Respectively to
Figure BDA0002212510040000135
Derivation, i.e.
Figure BDA0002212510040000136
Then, the partial derivatives are made equal to zero, and extreme points are obtained
Figure BDA0002212510040000137
Then bring it into
Figure BDA0002212510040000138
And solving to work out the optimal VPL value.
Further, if the optimized vertical protection level is smaller than a preset vertical warning limit VAL, ARAIM is available;
if the optimized vertical protection level is greater than the VAL, the ARIAM is unavailable.
In the embodiment of the invention, the main task of fault detection is to judge whether a fault exists at present, if no fault exists, different integrity risks are distributed according to the contribution degree of each satellite to a positioning solution, and further the purpose of optimizing a protection level VPL is achieved; if a fault exists, troubleshooting is required.
Fig. 3 is a block diagram of an embodiment of the advanced receiver autonomous integrity monitoring protection level optimizing device provided in the present invention, and as shown in fig. 3, the advanced receiver autonomous integrity monitoring protection level optimizing device includes:
a processor 301, and a memory 302 for storing executable instructions of the processor 301.
Optionally, the method may further include: a communication interface 303 for enabling communication with other devices.
The above components may communicate over one or more buses.
The processor 301 is configured to execute the corresponding method in the foregoing method embodiment by executing the executable instruction, and the specific implementation process thereof may refer to the foregoing method embodiment, which is not described herein again.
The device may be, or be provided within, a receiver.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims (8)

1. An advanced receiver autonomous integrity monitoring protection level optimization method is characterized by comprising the following steps:
calculating global positioning information of the receiver and subset positioning information of the fault subset according to the integrity support ISM information of the plurality of satellites;
calculating a positioning estimation error of a receiver and a detection statistic of the fault subset according to the global positioning information and the subset positioning information;
if the detection statistic is determined to pass the detection, calculating an optimized protection level according to an optimization function minimizing the integrity risk, the positioning estimation error of the receiver and the detection statistic of the fault subset;
if the ARIAM is available according to the optimized protection level, the positioning result of the advanced receiver is output;
calculating global positioning information of the receiver and subset positioning information of the fault subset according to the integrity support ISM information of the plurality of satellites, comprising:
calculating a pseudorange covariance matrix for integrity and a pseudorange covariance matrix for precision and continuity according to a ranging error, ranging precision, troposphere error, multipath and user receiver noise included in the ISM information;
calculating global positioning information of the receiver and subset positioning information of the fault subset by using a weighted least square method according to the pseudo-range covariance matrix for integrity;
the calculating a pseudorange covariance matrix for integrity and a pseudorange covariance matrix for accuracy and continuity according to a ranging error, a ranging accuracy, a tropospheric error, a multipath and user receiver noise included in the ISM information includes:
calculating a pseudorange covariance matrix according to a ranging error, ranging precision, troposphere error, multipath and user receiver noise in the ISM information by using the following formula (1) and formula (2);
Figure FDA0003200189380000011
Figure FDA0003200189380000012
wherein i is 1,2satRepresents the ith satellite, NsatAs a result of the total number of satellites,
Figure FDA0003200189380000013
is the variance of the ranging error for the ith satellite,
Figure FDA0003200189380000014
is the variance of the ranging accuracy of the ith satellite,
Figure FDA0003200189380000015
is the variance of tropospheric error for the ith satellite,
Figure FDA0003200189380000016
the variance of multipath and user receiver noise for the ith satellite; cint(i, i) denotes the pseudorange covariance matrix for integrity, and Cacc(i, i) represents the pseudorange covariance matrix for accuracy and continuity;
the global positioning information comprises a global positioning solution, and the global positioning information of the receiver is calculated by using a weighted least square method according to the pseudo-range covariance matrix for integrity, wherein the global positioning information comprises the following steps:
the global positioning solution is calculated according to the weighted least squares method using the following formula (3)
Figure FDA0003200189380000027
Figure FDA0003200189380000021
Wherein G is Nsat×(3+Nconst) Geometric observation matrix of, NconstRepresenting the number of constellations, y being the pseudorange residuals, and the weighting matrix W ═ Cint -1(i,i)；
The subset positioning information comprises a subset positioning solution, and the subset positioning information of the fault subset is calculated by using a weighted least square method according to the pseudo-range covariance matrix for integrity, and comprises the following steps:
calculating a subset locator solution for the kth fault subset according to equation (4) below
Figure FDA0003200189380000022
Figure FDA0003200189380000023
Wherein, k is 1fault_modes，Nfault_modesIndicates the number of fault subsets, W(k)A weighting matrix for the kth fault subset, wherein
Figure FDA0003200189380000024
idxkDenotes the satellite index, idx, in the kth failure subsetk＝{i1,...,it}。
2. The method of claim 1, wherein computing a receiver's position estimation error and detection statistics for the faulty subset based on the global positioning information and the subset positioning information comprises:
when the ith satellite fails, the positioning estimation error epsiloni' Gaussian distribution subject to non-zero mean, as in equation (5):
ε′i～N(ηibnom,i,(GTWG)-1) (5)
wherein the content of the first and second substances,
Figure FDA0003200189380000025
ε denotes the measurement error, x is the true position, S(0)A projection matrix representing the full visible star time,bnomis a standard deviation, ηiRepresenting the weight of the ith satellite in the positioning solution, bnom,iDenotes the standard deviation corresponding to the ith satellite, W and G have the same meaning as in equation (3);
obtaining detection statistics of the kth fault subset according to the global positioning solution and the subset positioning solution
Figure FDA0003200189380000026
Obey a zero mean gaussian distribution, as in equation (6):
Figure FDA0003200189380000031
wherein the content of the first and second substances,
Figure FDA0003200189380000032
S(k)representing the projection matrix corresponding to the kth fault subset, S(0)A projection matrix representing the full satellite time of sight, wherein, for the ith satellite,
Figure FDA0003200189380000033
3. the method of claim 2, further comprising:
calculating a threshold of fault detection according to the distribution of the detection statistics;
determining whether the detection statistic passes the detection according to the threshold of the fault detection;
if the detection statistic fails to pass the detection, performing fault elimination until the detection statistic passes the detection;
and if the detection statistic passes the detection, calculating the optimized protection level according to an optimization function of minimizing the integrity risk and the distribution of the positioning estimation error and the detection statistic.
4. The method of claim 3, wherein computing a threshold for fault detection based on the distribution of the detection statistics comprises
The threshold T for fault detection is calculated using equation (7)k：
Figure FDA0003200189380000034
Wherein, betakRepresents H0Detection alarm rate P (| Δ x) under assumption(k)|≥Tk|H0)，H0The assumption that all the stars are visible is represented,
Figure FDA0003200189380000035
Q-1() Is the inverse function of Q.
5. The method of claim 3, wherein the protection stage comprises: a vertical protection level, calculating an optimized protection level, comprising:
solving the vertical protection level that minimizes the optimization function of the integrity risk as the optimized vertical protection level using the following equation (8):
Figure FDA0003200189380000036
wherein r ═ GTWG)-1，Nfault_modesIndicates the number of subsets of faults,
Figure FDA0003200189380000041
is representative of xikI.e. representing ξkIn the component of the i-th satellite,
Figure FDA0003200189380000042
representing the prior probability of the failure subset k.
6. The method of claim 5, wherein solving the vertical protection level that minimizes the optimization function of the integrity risk using the following equation (8) as the optimized vertical protection level comprises:
respectively to the formula (9)
Figure FDA0003200189380000043
Derivation to find the extreme point
Figure FDA0003200189380000044
Then the extreme point is calculated
Figure FDA0003200189380000045
And substituting the formula (9) to obtain the optimized vertical protection level.
7. The method of claim 5, wherein prior to outputting the receiver positioning result, further comprising:
if the optimized vertical protection level is smaller than a preset vertical warning limit VAL, ARAIM is available;
if the optimized vertical protection level is greater than the VAL, the ARIAM is unavailable.
8. An advanced receiver autonomous integrity monitoring protection level optimization device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the method of any of claims 1-7 via execution of the executable instructions.
CN201910903321.5A 2019-09-24 2019-09-24 Advanced receiver autonomous integrity monitoring protection level optimization method and device Active CN110687557B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910903321.5A CN110687557B (en) 2019-09-24 2019-09-24 Advanced receiver autonomous integrity monitoring protection level optimization method and device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910903321.5A CN110687557B (en) 2019-09-24 2019-09-24 Advanced receiver autonomous integrity monitoring protection level optimization method and device

Publications (2)

Publication Number Publication Date
CN110687557A CN110687557A (en) 2020-01-14
CN110687557B true CN110687557B (en) 2021-11-16

Family

ID=69109997

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910903321.5A Active CN110687557B (en) 2019-09-24 2019-09-24 Advanced receiver autonomous integrity monitoring protection level optimization method and device

Country Status (1)

Country Link
CN (1) CN110687557B (en)

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111708054B (en) * 2020-06-16 2023-06-30 沈阳航空航天大学 ARAIM vertical protection level optimization method based on particle swarm optimization algorithm
US11555930B2 (en) 2020-06-24 2023-01-17 Honeywell Aerospace Sas Split vertical advanced receiver autonomous integrity monitoring
CN114636431B (en) * 2021-11-12 2024-04-30 北京航空航天大学 Navigation integrity monitoring method for intelligent operation system in complex environment
WO2023097595A1 (en) 2021-12-02 2023-06-08 北京航空航天大学 Method and system for positioning and integrity monitoring of apnt service
CN114235007B (en) * 2021-12-02 2023-09-29 北京航空航天大学 Positioning and integrity monitoring method and system for APNT service
CN115291253B (en) * 2022-08-02 2023-12-05 东北大学 Vehicle positioning integrity monitoring method and system based on residual error detection
CN116794700B (en) * 2023-08-24 2023-12-12 浙江中裕通信技术有限公司 Satellite fault detection method for shipborne Beidou all-in-one machine

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103592656A (en) * 2013-10-17 2014-02-19 航天恒星科技有限公司 Self-integrity monitoring method suitable for satellite-borne navigation receiver
CN104267410A (en) * 2014-10-10 2015-01-07 北京航空航天大学 Method and device for excluding multiple faults in airborne integrity monitoring
RU2644450C1 (en) * 2017-03-24 2018-02-12 Акционерное общество "Российская корпорация ракетно-космического приборостроения и информационных систем" (АО "Российские космические системы") Method of high-precision navigational sightings integrity definition in real time
CN109061683A (en) * 2018-06-29 2018-12-21 北京航空航天大学 A kind of H-ARAIM system of optimum level protected level

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7667644B2 (en) * 2007-10-09 2010-02-23 Honeywell International Inc. GPS receiver RAIM with slaved precision clock

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103592656A (en) * 2013-10-17 2014-02-19 航天恒星科技有限公司 Self-integrity monitoring method suitable for satellite-borne navigation receiver
CN104267410A (en) * 2014-10-10 2015-01-07 北京航空航天大学 Method and device for excluding multiple faults in airborne integrity monitoring
RU2644450C1 (en) * 2017-03-24 2018-02-12 Акционерное общество "Российская корпорация ракетно-космического приборостроения и информационных систем" (АО "Российские космические системы") Method of high-precision navigational sightings integrity definition in real time
CN109061683A (en) * 2018-06-29 2018-12-21 北京航空航天大学 A kind of H-ARAIM system of optimum level protected level

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
GNSS自主完好性检测算法研究;宋恺;《中国优秀硕士学位论文全文数据库 信息科技辑》;20180315;摘要，正文第51页第1-2段，第52页第5.2.2节，第52-53页第5.2.3节，第56-57页第5.3.1节，第57-59页第5.3.2节及图5.1 *

Also Published As

Publication number Publication date
CN110687557A (en) 2020-01-14

Similar Documents

Publication Publication Date Title
CN110687557B (en) Advanced receiver autonomous integrity monitoring protection level optimization method and device
RU2559842C2 (en) Method and apparatus for detecting and eliminating multiple failures of gnss system satellites
Blanch et al. Baseline advanced RAIM user algorithm and possible improvements
EP2887097B1 (en) Architectures for high Navigation Satellite System integrity multi-constellation solution separation
Blanch et al. Advanced RAIM user algorithm description: Integrity support message processing, fault detection, exclusion, and protection level calculation
RU2672676C2 (en) Navigation and integrity monitoring
US9146322B2 (en) Hybrid system and device for calculating a position and for monitoring its integrity
RU2668077C1 (en) Reserved piloting device with sensors for a rotary-wing aircraft
Lee et al. Summary of RTCA SC‐159 GPS integrity working group activities
CN109061683B (en) H-ARAIM system for optimizing horizontal protection level
CN105008956A (en) State detecting method, correction value processing device, positioning system, and state detecting program
CN110007317A (en) A kind of senior receiver autonomous integrity monitoring method for selecting star to optimize
US9651669B2 (en) Method for detecting anomaly satellite in multi-reference stations environment and apparatus using detecting method
RU2634693C2 (en) Validity control method and combination/consolidation device with multiple processing modules
Pesonen A framework for Bayesian receiver autonomous integrity monitoring in urban navigation
Jiang et al. Code carrier divergence monitoring for dual-frequency GBAS
Rakipi et al. Integrity monitoring in navigation systems: Fault detection and exclusion RAIM algorithm implementation
Li et al. Integrity and continuity allocation for the RAIM with multiple constellations
CN110879407A (en) Satellite navigation observation quantity innovation detection method based on integrity risk model
Bakhache et al. Reliable detection of faults in measurement systems
Kropp et al. Optimized MHSS ARAIM user algorithms: Assumptions, protection level calculation and availability analysis
CN115561782B (en) Satellite fault detection method in integrated navigation based on odd-even vector projection
Tmazirte et al. Fast multi fault detection & exclusion approach for GNSS integrity monitoring
CN114047526B (en) Ionized layer anomaly monitoring method and device based on dual-frequency dual-constellation GBAS
Ma et al. Progress of global ARAIM availability of BDS-2/BDS-3 with TGD and ISB

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant