CN112733315B - Integrity risk verification method and system - Google Patents
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Abstract
The application discloses a method and a system for verifying integrity risk. The method comprises the following steps: acquiring fault sample numbers of satellite navigation in continuous time periods, and counting a plurality of groups of correction numbers corresponding to preset fault types, a plurality of groups of correction numbers with faults and the probability of the faults of the group of correction numbers according to the fault sample numbers; selecting i groups of correction numbers from the groups of correction numbers with faults, and calculating the probability that the i groups of correction numbers simultaneously have faults, wherein the value range of i is 1-the total number of the groups of correction numbers with faults corresponding to each preset fault type; calculating the simulation sample number of the i groups of correction numbers, performing fault injection on the simulation sample number, and calculating to obtain the fault undetected rate of the i groups of correction numbers; and obtaining the probability value of integrity risk according to the probability that the i groups of correction numbers simultaneously fail and the failure undetected rate.
Description
Technical Field
The present disclosure relates generally to the field of satellite navigation technologies, and in particular, to a method and system for verifying integrity risk.
Background
Currently, the main core constellation of Global Navigation Satellite System (GNSS) includes the Global Positioning System (GPS) in the united states, the russian global navigation satellite system (GLONASS), the galileo positioning system in the european union and the beidou navigation satellite system in china. The integrity embodies the capability of providing timely and effective warning information for a user when the satellite navigation system cannot be used for navigation, plays a guiding role in promoting the overall performance of the satellite navigation system, and has important significance.
A satellite-based augmentation system (SBAS) processes satellite signals of a ground station, calculates various types of correction numbers and integrity information, and broadcasts the information to users through geostationary orbit satellites. The prior art (CN 109542084A) provides a method for simulating integrity faults of a satellite-based augmentation system, and the method is only suitable for simulating integrity faults of a civil aviation satellite-based system without verifying integrity risk indexes under the faults. And the fault type of the scheme is relatively simple, and the real fault is not analyzed and modeled in detail.
Disclosure of Invention
The specification provides a method and a system for verifying integrity risks, wherein faults are modeled and simulated based on real faults, whether the integrity risks meet requirements is verified, and the method and the system are suitable for high-precision integrity civil and commercial services.
The application discloses a method for verifying integrity risk, which comprises the following steps:
acquiring fault sample numbers of satellite navigation in continuous time periods, and counting a plurality of groups of correction numbers corresponding to preset fault types, a plurality of groups of correction numbers with faults and the probability of the faults of the group of correction numbers according to the fault sample numbers;
selecting i groups of correction numbers from the groups of correction numbers with faults, and calculating the probability that the i groups of correction numbers simultaneously have faults, wherein the value range of i is 1-the total number of the groups of correction numbers with faults corresponding to each preset fault type;
calculating the simulation sample number of the i groups of correction numbers, performing fault injection on the simulation sample number, and calculating to obtain the fault undetected rate of the i groups of correction numbers;
and obtaining the probability value of integrity risk according to the probability that the i groups of correction numbers simultaneously fail and the failure undetected rate.
In a preferred embodiment, the counting of the number of fault samples includes a plurality of sets of corrections corresponding to each preset fault type, a plurality of sets of corrections with faults, and a probability of a fault occurring in a set of corrections, and further includes:
calculating a histogram and a probability density map of the number of fault samples;
determining fault distribution according to the probability density graph;
extracting an envelope of the probability density map;
and calculating a plurality of groups of correction numbers corresponding to each preset fault type, a plurality of groups of correction numbers with faults and the probability of the faults of the group of correction numbers.
In a preferred embodiment, the histogram of the number of faulty samples represents the error of the correction number and the number of samples of the error.
In a preferred example, the probability density map of the number of faulty samples represents the error of the correction number and the occurrence probability of the error.
In a preferred example, the probability that the i groups of correction numbers simultaneously fail is:
wherein M is the total number of the plurality of groups of correction numbers corresponding to the preset fault types, P fault And the probability of the fault of the group of correction numbers corresponding to each preset fault type is obtained.
In a preferred example, the number of simulation samples of the i-set correction is: i is fault_i ＝1.96 2 ×(1-P req_md.i )/P req_md.i ，P req_md.i ＝P integrityrisk /P fault.i In which P is req_md.i For the desired fault undetected rate, P integrityrisk Probability value of the integrity risk that needs to be reached.
In a preferred example, the probability value of the integrity risk is:
In a preferred embodiment, the failure missing rate of the i-set correction numbers is calculated by using a Stanford graph.
In a preferred example, the fault sample number of the satellite navigation in 60-100 monitoring stations is acquired for more than 3 months.
The application also discloses a verification system of integrity risk, including:
the data modeling unit is configured to obtain the fault sample number of satellite navigation in a continuous time period, and a plurality of groups of correction numbers corresponding to preset fault types, a plurality of groups of correction numbers with faults and the probability of the faults of the group of correction numbers are counted according to the fault sample number;
a calculating unit, configured to select i groups of correction numbers from the groups of correction numbers with faults, and calculate the probability that the i groups of correction numbers have faults at the same time, wherein the value range of i is 1 to the total number of the groups of correction numbers with faults corresponding to each preset fault type;
the simulation unit is configured to calculate the simulation sample number of the i groups of correction numbers, perform fault injection on the simulation sample number, and calculate the fault missing rate of the i groups of correction numbers;
and the verification unit is configured to obtain a probability value of integrity risk according to the probability that the i groups of correction numbers simultaneously fail and the failure undetected rate.
In a preferred embodiment, the counting of the number of fault samples includes a plurality of sets of corrections corresponding to each preset fault type, a plurality of sets of corrections with faults, and a probability of a fault occurring in a set of corrections, and further includes:
calculating a histogram and a probability density map of the number of the fault samples;
determining fault distribution according to the probability density graph;
extracting an envelope of the probability density map;
and calculating a plurality of groups of correction numbers corresponding to each preset fault type, a plurality of groups of correction numbers with faults and the probability of the faults of the group of correction numbers.
In a preferred example, the probability that the i groups of correction numbers simultaneously fail is:
wherein M is the total number of the plurality of groups of correction numbers corresponding to the preset fault types, P fault And the probability of the fault of the group of correction numbers corresponding to each preset fault type.
In a preferred example, the number of simulation samples of the i-set correction is: i is fault_i ＝1.96 2 ×(1-P req_md.i )/P req_md.i ，P req_md.i ＝P integrityrisk /P fault.i In which P is req_md.i For the desired fault undetected rate, P integrityrisk Probability value of the integrity risk that needs to be reached.
In a preferred example, the probability value of the integrity risk is:
The application also discloses a verification system for integrity risk comprising:
a memory for storing computer executable instructions; and
a processor, coupled with the memory, for implementing the steps in the method as described above when executing the computer-executable instructions.
The present application also discloses a computer-readable storage medium having stored thereon computer-executable instructions which, when executed by a processor, implement the steps in the method as described above.
Compared with the prior art, the method has the following beneficial effects:
in the implementation mode of the specification, fault modeling is performed based on the number of fault samples of satellite navigation, i groups are selected from a plurality of groups of correction numbers with faults, fault simulation is performed, the probability that the i groups of correction numbers simultaneously have faults and the fault omission ratio are calculated, the product of the probability that the i groups of correction numbers simultaneously have faults and the fault omission ratio is summed to obtain the probability value of integrity risk, and the probability value of a target are verified. According to the method, modeling, simulation and analysis are carried out based on the real fault sample number, the reliability of integrity verification is higher, and the verification method is wider in application range.
A large number of technical features are described in the specification, and are distributed in various technical solutions, so that the specification is too long if all possible combinations of the technical features (namely, the technical solutions) in the application are listed. In order to avoid this problem, the respective technical features disclosed in the above summary of the invention of the present specification, the respective technical features disclosed in the following embodiments and examples, and the respective technical features disclosed in the drawings may be freely combined with each other to constitute various new technical solutions (which should be regarded as having been described in the present specification) unless such a combination of the technical features is technically impossible. For example, in one example, feature a + B + C is disclosed, in another example, feature a + B + D + E is disclosed, and features C and D are equivalent technical means that serve the same purpose, technically only one feature is used, but not both, and feature E may be technically combined with feature C, then the solution of a + B + C + D should not be considered as already described because the technology is not feasible, and the solution of a + B + C + E should be considered as already described.
Drawings
Fig. 1 is a flow diagram of an integrity risk verification method in accordance with an embodiment of the present description.
Fig. 2 is a block diagram of an integrity risk verification system in accordance with an embodiment of the present description.
Detailed Description
In the following description, numerous technical details are set forth in order to provide a better understanding of the present application. However, it will be understood by those skilled in the art that the technical solutions claimed in the present application may be implemented without these technical details and with various changes and modifications based on the following embodiments.
Interpretation of terms
Integrity Risk (Integrity Risk): a probability value representing the probability of the occurrence of a fault or data error being missed during the integrity monitoring process without providing a false alarm.
Failure missing rate: the probability that the error of the correction number exceeds the warning limit but the integrity is not warned.
Fault injection: refers to a process of intentionally generating and applying a fault to a specific target system in a manual manner according to a selected fault model to accelerate the occurrence of errors and failures of the system, while collecting response information of the system to the injected fault and analyzing the recovered information to provide results.
Probability density function (probability density function): the probability of the value of the random variable falling in a certain area is the integral of the probability density function in the area.
Some of the innovation points of the invention are explained as follows:
the method comprises the steps of carrying out fault modeling based on the number of fault samples of real satellite navigation, carrying out statistics on a plurality of groups of correction numbers corresponding to preset fault types, a plurality of groups of correction numbers with faults and the probability of the fault of one group of correction numbers, selecting i groups from the plurality of groups of correction numbers with faults, wherein the value range of i is 1-the total number of the plurality of groups of correction numbers with faults, calculating the probability of the simultaneous fault occurrence of the i groups of correction numbers with the values of i and the fault omission ratio, summing the products of the simultaneous fault occurrence probability and the fault omission ratio of the i groups of correction numbers with the values of i to obtain the probability value of the integrity risk, and verifying the probability value and the probability value of a target so as to verify the integrity risk.
Embodiments of the present description will be described in further detail below with reference to the accompanying drawings.
A first embodiment of the present description relates to a method of verification of integrity risk, the flow chart of which is shown in fig. 1, the method comprising the steps of:
in step 101, the fault sample number of satellite navigation in a continuous time period is obtained, fault modeling is performed, and a plurality of sets of correction numbers corresponding to preset fault types, a plurality of sets of correction numbers with faults and the probability of the fault of the set of correction numbers are counted according to the fault sample number.
In a preferred embodiment, the counting, according to the number of the fault samples, a plurality of sets of corrections corresponding to each preset fault type, a plurality of sets of corrections with faults, and a probability of a fault occurring in a set of corrections further includes:
in step 1011, a histogram and a probability density map of the number of failure samples are calculated. In a preferred embodiment, the histogram of the number of faulty samples represents the error of the correction number and the number of samples of the error. In a preferred example, the probability density map based on the number of failure samples represents the error of the correction number and the occurrence probability of the error. In a preferred example, the number of fault samples of satellite navigation for more than 3 months is acquired based on 60 to 100 monitoring stations. In this embodiment, the fault sample number of the obtained true correction number is based on the true fault sample number to perform fault modeling.
In step 1012, a fault distribution is determined from the probability density map.
In step 1013, an envelope of the probability density map, i.e. a probability density function of the probability density map, is extracted.
In step 1014, a plurality of sets of corrections corresponding to each preset fault type and a plurality of sets of corrections with faults corresponding to each preset fault type are obtained according to the fault distribution. For example, the total number of the plurality of sets of correction numbers corresponding to each preset fault type is M, for example, the value range of M is 3 to 10, the total number of the plurality of sets of correction numbers corresponding to each preset fault type that have faults is N, for example, the value range of N is 1 to 10. Calculating the probability of the fault of one set of correction numbers in a plurality of sets of correction numbers with faults corresponding to each preset fault type,
in this embodiment, the correction error at least includes one or more of a satellite orbit and clock error, a satellite orbit, clock error and phase deviation, a vertical ionospheric error, an oblique ionospheric error and a zenith tropospheric delay error. The preset fault types at least comprise one or more of satellite orbit and clock faults, satellite orbit, clock error and phase faults, vertical ionosphere faults, inclined ionosphere faults and zenith troposphere delay faults. In other embodiments, the correction error and the predetermined failure type may be changed according to the content of the satellite navigation calibration data, for example, the content of the satellite navigation calibration data is added with the correction parameter of the other calibration, and then the corresponding error and failure type may be added according to the added correction parameter.
In step 102, i sets of correction numbers are selected from the sets of correction numbers with faults, the probability that the i sets of correction numbers have faults simultaneously is calculated, and the value range of i is a positive integer between 1 and the total number N of the sets of correction numbers with faults corresponding to the preset fault types. In the present embodiment, the number of groups for selecting the correction numbers is determined as i, and the type of the selected correction numbers is not limited.
In a preferred example, the probability that the i sets of correction numbers fail simultaneously is:
wherein M is the total number of the plurality of groups of correction numbers corresponding to the preset fault types, P fault And the probability of the fault of the group of correction numbers corresponding to each preset fault type.
In step 103, the number of simulation samples of the i-set of corrections is calculated.
In a preferred example, the number of simulation samples of the i-set correction is:
I fault_i ＝1.96 2 ×(1-P req_md.i )/P req_md.i (2)
P req_md.i ＝P integrityrisk /P fault.i (3)
wherein, P req_md.i For the desired fault undetected rate, P integrityrisk Probability value of the integrity risk that needs to be reached.
Then, according to the simulation sample number I fault_i And performing fault injection, and calculating to obtain the fault undetected rate of the i groups of correction numbers. In a preferred embodiment, use is made ofStanford plot (Stanford plot) calculates the failure undetected rate for the i-group correction numbers. Specifically, the integrity protection level of each error is calculated according to the error component residual error corresponding to each preset fault type, the corresponding alarm threshold is set according to the quality factor of each error component, the Stanford graph is used for judging the monitoring result according to the comparison result of the integrity protection level corresponding to each error component and the corresponding alarm threshold, the number of times of missed detection of each preset fault type is determined, and the fault missed detection rate corresponding to each preset fault type is determined according to the determined number of times of missed detection. The calculation of the failure undetected rate of the i-group correction numbers according to the stanford graph is well known to those skilled in the art, and is not described herein.
In step 104, obtaining a probability value of integrity risk according to the probability that the i groups of correction numbers simultaneously fail and the failure undetected rate. Specifically, the probability that the i groups of correction numbers of all the i values simultaneously fail and the failure undetected rate are calculated, and the products of the probability that the i groups of correction numbers of all the i values simultaneously fail and the failure undetected rate are summed to obtain the probability value of the integrity risk.
In a preferred example, the probability value of the integrity risk is:
wherein N is the total number of the groups of corrected numbers with faults corresponding to the preset fault types, P fault.md.i And the fault missing rate of the i groups of correction numbers.
In this embodiment, the value range of i may be preferably a positive integer between 2 and the total number N of the sets of correction numbers with faults corresponding to the preset fault types according to requirements. In this embodiment, the probability value of the integrity risk is:
wherein N is corresponding to each preset fault typeTotal number of sets of correction numbers, P, that failed fault.md.i And the fault missing rate of the i groups of correction numbers.
In one embodiment, all the steps may be performed in the cloud server, and in another embodiment, all the steps may be performed in the terminal positioning module. In other embodiments, the above steps may be distributed to the cloud server and the terminal positioning module to be executed respectively according to requirements or implementation conditions.
A second embodiment of the present specification relates to a system for integrity risk verification, a block diagram of which is shown in fig. 2, and specifically includes:
the data modeling unit 10 is configured to obtain the number of fault samples of satellite navigation in a continuous time period, and count a plurality of groups of correction numbers corresponding to preset fault types, a plurality of groups of correction numbers with faults and the probability of the faults of the group of correction numbers according to the number of the fault samples;
a calculating unit 20 configured to select i groups of correction numbers from the groups of correction numbers with faults, and calculate the probability that the i groups of correction numbers have faults at the same time, wherein the value range of i is 1 to the total number of the groups of correction numbers with faults corresponding to each preset fault type;
the simulation unit 30 is configured to calculate the number of simulation samples of the i groups of correction numbers, perform fault injection on the number of simulation samples, and calculate the fault undetected rate of the i groups of correction numbers;
and the verification unit 40 is configured to obtain a probability value of integrity risk according to the probability that the i groups of correction numbers simultaneously fail and the failure undetected rate.
In a preferred embodiment, the counting, according to the number of the fault samples, a plurality of sets of corrections corresponding to each preset fault type, a plurality of sets of corrections with faults, and a probability of a fault occurring in a set of corrections further includes:
calculating a histogram and a probability density map of the number of the fault samples;
determining fault distribution according to the probability density graph;
extracting an envelope of the probability density map;
and calculating a plurality of groups of correction numbers corresponding to each preset fault type, a plurality of groups of correction numbers with faults and the probability of the faults of the group of correction numbers.
In a preferred embodiment, the histogram of the number of faulty samples represents the error of the correction number and the number of samples of the error.
In a preferred example, the probability density map of the number of faulty samples represents the error of the correction number and the occurrence probability of the error.
In a preferred example, the probability that the i sets of correction numbers fail simultaneously is:
wherein M is the total number of the plurality of groups of correction numbers corresponding to the preset fault types, P fault And the probability of the fault of the group of correction numbers corresponding to each preset fault type is obtained.
In a preferred example, the number of simulation samples of the i-set correction is: i is fault_i ＝1.96 2 ×(1-P req_md.i )/P req_md.i ，P req_md.i ＝P integrtyrisk /P fault.i In which P is req_md.i For the desired fault undetected rate, P integrtyrisk Probability value of the integrity risk that needs to be reached.
In a preferred example, the probability value of the integrity risk is:
In a preferred embodiment, the failure missing rate of the i-set correction numbers is calculated by using a Stanford graph.
In a preferred example, the fault sample number of the satellite navigation in 60 monitoring stations is acquired for more than 3 months.
The first embodiment is a method embodiment corresponding to the present embodiment, and the technical details in the first embodiment may be applied to the present embodiment, and the technical details in the present embodiment may also be applied to the first embodiment.
It should be noted that, as will be understood by those skilled in the art, the implementation functions of the units shown in the embodiment of the integrity risk verification system described above can be understood by referring to the related description of the integrity risk verification method described above. The functions of the units shown in the embodiments of the integrity risk verification system described above may be implemented by a program (executable instructions) running on a processor, or by specific logic circuits. The above integrity risk verification system in the embodiments of the present disclosure may also be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solutions of the embodiments of the present specification may be essentially or partially implemented in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present specification. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a magnetic disk, or an optical disk. Thus, embodiments of the present description are not limited to any specific combination of hardware and software.
Accordingly, the present specification embodiments also provide a computer-readable storage medium having stored therein computer-executable instructions that, when executed by a processor, implement the method embodiments of the present specification. Computer-readable storage media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. Information may be computer readable instructions, data structures, units of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable storage medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
In addition, the present specification further provides a system for verifying integrity risk, which includes a memory for storing computer executable instructions and a processor; the processor is configured to implement the steps of the method embodiments described above when executing the computer-executable instructions in the memory.
In one embodiment, the computer-executable instructions may be for:
acquiring fault sample numbers of satellite navigation in continuous time periods, and counting a plurality of groups of correction numbers corresponding to preset fault types, a plurality of groups of correction numbers with faults and the probability of the faults of the group of correction numbers according to the fault sample numbers;
selecting i groups of correction numbers from the groups of correction numbers with faults, and calculating the probability that the i groups of correction numbers simultaneously have faults, wherein the value range of i is 1-the total number of the groups of correction numbers with faults corresponding to each preset fault type;
calculating the simulation sample number of the i groups of correction numbers, performing fault injection on the simulation sample number, and calculating to obtain the fault undetected rate of the i groups of correction numbers;
and obtaining the probability value of integrity risk according to the probability that the i groups of correction numbers simultaneously fail and the failure undetected rate. .
In one embodiment, the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), or the like. The aforementioned memory may be a read-only memory (ROM), a Random Access Memory (RAM), a Flash memory (Flash), a hard disk, or a solid state disk. The steps of the method disclosed in the embodiments of the present invention may be directly implemented by a hardware processor, or implemented by a combination of hardware and software elements in a processor. In one embodiment, the integrity risk verification system further comprises a bus and a communication interface. The processor, memory and communication interface are all interconnected by a bus. The communication interface may be a wireless communication interface or a wired communication interface for enabling the processor to communicate with other systems.
It should be noted that, in the present patent application, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the use of the verb "comprise a" to define an element does not exclude the presence of another, same element in a process, method, article, or apparatus that comprises the element. In the present patent application, if it is mentioned that a certain action is executed according to a certain element, it means that the action is executed according to at least the element, and two cases are included: performing the action based only on the element, and performing the action based on the element and other elements. The expression of a plurality of, a plurality of and the like includes 2, 2 and more than 2, more than 2 and more than 2.
All documents mentioned in this specification are to be considered as being integrally included in the disclosure of this specification so as to be able to be a basis for modifications as necessary. It should be understood that the above description is only for the preferred embodiment of the present disclosure, and is not intended to limit the scope of the present disclosure. Any modification, equivalent replacement, improvement or the like made within the spirit and principle of one or more embodiments of the present disclosure should be included in the protection scope of one or more embodiments of the present disclosure.
In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Claims (10)
1. A method of integrity risk verification, comprising:
acquiring fault sample numbers of satellite navigation in continuous time periods, and counting a plurality of groups of correction numbers corresponding to preset fault types, a plurality of groups of correction numbers with faults and the probability of the faults of the group of correction numbers according to the fault sample numbers;
selecting i groups of correction numbers from the groups of correction numbers with faults, and calculating the probability of the i groups of correction numbers with faults at the same time, wherein the value range of i is 1-the total number of the groups of correction numbers with faults corresponding to each preset fault type, and the probability of the i groups of correction numbers with faults at the same time is as follows:
wherein M is the total number of the plurality of groups of correction numbers corresponding to the preset fault types, P fault A group of changes corresponding to each preset fault typeProbability of a positive number failing;
calculating the simulation sample number of the i groups of correction numbers, performing fault injection on the simulation sample number, and calculating the fault undetected rate of the i groups of correction numbers, wherein the simulation sample number of the i groups of correction numbers is as follows: i is fault_i ＝1.96 2 ×(1-P req_md.i )/P req_md.i ，P req_md.i ＝P integrityrisk /P fault.i In which P is req_md.i For a desired fault undetected rate, P integrityrisk A probability value for the integrity risk that needs to be achieved;
obtaining a probability value of integrity risk according to the probability that the i group correction numbers simultaneously fail and the failure undetected rate, wherein the probability value of the integrity risk is as follows:
wherein N is the total number of the groups of corrected numbers with faults corresponding to the preset fault types, P fault.md.i And the fault missing rate of the i groups of correction numbers.
2. The method for verifying the integrity risk as claimed in claim 1, wherein the failure sample number counts a plurality of sets of corrections corresponding to each preset failure type, a plurality of sets of corrections that have failed, and a probability that a set of corrections has failed, further comprising:
calculating a histogram and a probability density map of the number of the fault samples;
determining fault distribution according to the probability density graph;
extracting an envelope of the probability density map;
and calculating a plurality of groups of correction numbers corresponding to each preset fault type, a plurality of groups of correction numbers with faults and the probability of the faults of the group of correction numbers.
3. Method for verifying the integrity risk as claimed in claim 2, characterized in that the histogram of the number of failed samples represents the error of the correction number and the number of samples of this error.
4. Method for verifying the integrity risk as claimed in claim 2, characterized in that the probability density map of the number of faulty samples represents the error of the correction number and the probability of occurrence of this error.
5. The integrity risk verification method of claim 1, wherein the failure undetected rate of the i-set of corrections is calculated using a stanford graph.
6. The method for verifying the integrity risk of claim 1 wherein the number of faulty samples from 60 to 100 satellite navigations within a monitoring station is obtained over 3 months.
7. A system for verifying integrity risk, comprising:
the data modeling unit is configured to obtain the fault sample number of satellite navigation in a continuous time period, and a plurality of groups of correction numbers corresponding to preset fault types, a plurality of groups of correction numbers with faults and the probability of the faults of the group of correction numbers are counted according to the fault sample number;
a calculating unit, configured to select i groups of correction numbers from the groups of correction numbers with faults, and calculate the probability that the i groups of correction numbers have faults at the same time, where a value range of i is 1 to the total number of the groups of correction numbers with faults corresponding to each preset fault type, where the probability that the i groups of correction numbers have faults at the same time is:
wherein M is the total number of the plurality of groups of correction numbers corresponding to the preset fault types, P fault The probability of the fault of a group of correction numbers corresponding to each preset fault type is obtained;
a simulation unit configured to calculate the simulation sample number of the i-group correction number, perform fault injection on the simulation sample number, and calculate the fault undetected rate of the i-group correction number, wherein the i-group correction number is obtainedThe number of simulation samples of the i sets of correction numbers is as follows: I.C. A fault_i ＝1.96 2 ×(1-P req_md.i )/P req_md.i ，P req_md.i ＝P integrityrisk /P fault.i In which P is req_md.i For the desired fault undetected rate, P integrityrisk A probability value for the integrity risk that needs to be achieved;
the verification unit is configured to obtain a probability value of the integrity risk according to the probability that the i-group correction number fails simultaneously and the failure undetected rate, wherein the probability value of the integrity risk is as follows:
wherein N is the total number of the groups of corrected numbers with faults corresponding to the preset fault types, P fault.md.i And the fault missing rate of the i groups of correction numbers.
8. The system for verifying the integrity risk of a vehicle according to claim 7, wherein the statistics of the sets of corrections corresponding to the predetermined failure types, the sets of corrections that have failed, and the probability of failure of the set of corrections according to the number of failure samples further comprises:
calculating a histogram and a probability density map of the number of the fault samples;
determining fault distribution according to the probability density graph;
extracting an envelope of the probability density map;
and calculating a plurality of groups of correction numbers corresponding to each preset fault type, a plurality of groups of correction numbers with faults and the probability of the faults of the group of correction numbers.
9. A verification system of integrity risk, comprising:
a memory for storing computer executable instructions; and
a processor, coupled with the memory, for implementing the steps in the method of any of claims 1-6 when executing the computer-executable instructions.
10. A computer-readable storage medium having stored thereon computer-executable instructions which, when executed by a processor, implement the steps of the method of any one of claims 1 to 6.
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