CN114325765B - Integrity detection optimization method and computer-readable storage medium - Google Patents
Integrity detection optimization method and computer-readable storage medium Download PDFInfo
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Abstract
The invention belongs to the technical field of navigation product inspection, and particularly relates to an integrity detection optimization method and a computer-readable storage medium. The integrity detection optimization method comprises the following steps: executing validity tests on the tested product to acquire integrity information, wherein the validity tests comprise fault tests and alarm time delay tests; the integrity information is evaluated to iteratively optimize an integrity monitoring algorithm. Therefore, the method can carry out effectiveness test on the integrity monitoring module of the high-precision positioning product to determine whether the integrity monitoring can work normally or not, and carries out evaluation by two dimensions of fault test and alarm time delay test, and iteratively optimizes the integrity monitoring algorithm to provide the calculation efficiency and robustness of the integrity monitoring algorithm.
Description
Technical Field
The invention belongs to the technical field of navigation product inspection, and particularly relates to an integrity detection optimization method and a computer-readable storage medium.
Background
With the comprehensive establishment of the Beidou third-class global positioning navigation system, 4 global positioning navigation systems exist, and more than 120 satellites provide multiple-frequency and multiple-code multiple-positioning services. In the algorithm level, from Single Point Positioning (SPP) using only pseudo-range observation values, Real-Time differential Positioning (RTK) based on differential data, precision Single Point Positioning (PPP) using Precise satellite orbit and Precise satellite clock error, and Real-Time dynamic precision Single Point Positioning algorithm (PPP-RTK) using high-precision Positioning data products, which are suitable for various scenes, have been developed. The precision, the integrity, the continuity and the availability are four navigation performance indexes provided by the international civil aviation organization. In the past, academic circles and industrial circles focus on accuracy indexes, and research on integrity indexes is less. The integrity refers to the capability of timely warning a user within a specified time limit when the navigation positioning technology fails to reach the technical index preset in the scene. In the process of generating the high-precision positioning data product, the integrity monitoring module becomes a necessary module for ensuring the data quality and feeding back the confidence level of the data product to a user. Meanwhile, in the process of calculating the positioning result and the protection level of the positioning terminal, the integrity parameter generated by the integrity monitoring module is also necessary input information.
Currently, there is no test scheme for assessing the effectiveness of a real-time integrity monitoring module. The test of the integrity monitoring module mainly judges whether the integrity monitoring module detects a fault in a preset or predefined fault scene, and broadcasts alarm information in an alarm Time limit (TTA, Time to Alert) specified by a system. The difficulty is how to define the fault scene, and how to comb out the data reception, all fault types in the calculation process and the possibility of occurrence of the fault types. Meanwhile, due to the short duration and low frequency of the fault, the identification and recording of the fault often requires long time for data accumulation and analysis. How to solve the technical problems is a technical problem to be solved urgently by the technical personnel in the field.
In view of the above problems, those skilled in the art have sought solutions.
The foregoing description is provided for general background information and is not admitted to be prior art.
Disclosure of Invention
The invention solves the technical problem that in the prior art, a test scheme for evaluating the effectiveness of a real-time integrity monitoring module does not exist, so that an integrity detection optimization method is provided, the integrity monitoring module of a high-precision positioning product can be subjected to effectiveness test to determine whether integrity monitoring can normally work, two dimensions of fault test and alarm time delay test are used for evaluation, and an integrity monitoring algorithm is iteratively optimized to provide the calculation efficiency and the robustness of the integrity monitoring algorithm.
The technical problem to be solved by the invention is realized by adopting the following technical scheme:
the invention provides an integrity detection optimization method, which comprises the following steps: executing validity tests on the tested product to acquire integrity information, wherein the validity tests comprise fault tests and alarm time delay tests; the integrity information is evaluated to iteratively optimize an integrity monitoring algorithm.
Further, before the step of performing the validity test on the tested product, the method includes: acquiring standard fault information; and establishing a fault theoretical model according to the standard fault information, wherein the fault theoretical model comprises a fault type, a fault probability and a fault reason.
Further, the fault test comprises a historical fault test and a simulation fault test; the step of performing fault test on the tested product comprises the following steps: acquiring fault data of a tested product; judging whether the fault to be detected has a corresponding standard fault type or not according to the fault data and the fault theoretical model; if yes, executing historical fault test; if not, executing a simulation fault test, wherein the simulation fault test comprises a historical data manual injection fault test and a real-time manual injection fault test.
Further, the step of performing a historical failure test to obtain integrity information includes: acquiring a historical data file, a first configuration file and historical fault information, and executing a first service end integrity test; first integrity information of a first service end integrity test is obtained.
Further, the step of obtaining the historical failure information includes: acquiring a data correction truth value; and correcting the data to the true value and the tested product through an off-line data evaluation system to obtain historical fault information and second integrity information.
Further, the step of performing a manual failure test on the historical data to obtain integrity information includes: acquiring historical fault data and a second configuration file, and executing integrity test of a second server; and acquiring third integrity information of the integrity test of the second server.
Further, the step of performing a real-time manual injection fault test to obtain integrity information includes: acquiring real-time fault data and a third configuration file, and executing a third server integrity test; and acquiring fourth integrity information of the integrity test of the third server.
Further, the step of performing the alarm delay test on the product to be tested to obtain the integrity information includes: acquiring alarm time delay according to the prior integrity monitoring information time and the posterior integrity monitoring information time; and outputting fifth integrity information according to the alarm time delay.
Further, the step of evaluating the integrity information and iteratively optimizing the integrity monitoring algorithm includes: and judging whether the integrity condition is met or not according to the integrity information, and if not, performing iterative optimization according to the integrity information.
The invention also provides a computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out the steps of the integrity detection optimization method as described above.
The invention also provides an integrity detection optimization method and a computer-readable storage medium. The integrity detection optimization method comprises the following steps: executing validity tests on the tested product to acquire integrity information, wherein the validity tests comprise fault tests and alarm time delay tests; the integrity information is evaluated to iteratively optimize an integrity monitoring algorithm. Therefore, the method can carry out effectiveness test on the integrity monitoring module of the high-precision positioning product to determine whether the integrity monitoring can work normally or not, and carries out evaluation by two dimensions of fault test and alarm time delay test, and iteratively optimizes the integrity monitoring algorithm to provide the calculation efficiency and robustness of the integrity monitoring algorithm. Furthermore, the integrity detection optimization method provided by an embodiment of the present invention can also perform systematic analysis and definition on the types of faults that may occur in the product under test before performing the detection. And establishing a fault theoretical model according to theoretical frequency and historical data of each fault in the whole process from generation of satellite observation to final positioning result output so as to distribute fault types and fault probability fault reasons and help to generate a simulated fault scene for testing to provide theoretical basis and preparation. In addition, in the fault test, whether the fault appears in a fault theoretical model is taken as a standard, if the historical fault is performed, the historical fault test is performed, and aiming at the problems that the real-time fault appears in short duration and is difficult to reproduce, historical product data is analyzed and compared with third-party data, a historical fault table is maintained, the function of offline processing is utilized, the fault scene is recovered for multiple times, and a monitoring algorithm is optimized; if the fault is not in the theoretical model, a simulated fault test is executed to generate an artificial simulated fault scene which is used as one of the inputs of the monitoring module, and the fault is monitored and eliminated in two different processing modes of real-time and off-line so as to test the effectiveness of the integrity monitoring module. In addition, in order to achieve the alarm time delay of the technical requirement, the time delay test of the whole link is supported, the time stamps are recorded in the whole process of data production, broadcasting and receiving, and the time delay of the fault alarm received by the user is counted and calculated so as to prove the timeliness of the fault alarm of the integrity monitoring module. Meanwhile, integrity information is evaluated, faults are injected, and a test experiment is repeated, so that the calculation efficiency and robustness of an integrity monitoring algorithm are improved, the operation of a user is reduced, the convenience of the user is improved, and the use experience of the user is improved.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present invention more clearly understood, the following preferred embodiments are specifically described in detail with reference to the accompanying drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flowchart illustrating a method for optimizing integrity check according to a first embodiment of the present invention.
Fig. 2 is a schematic diagram of a fault theory model according to a first embodiment of the present invention.
Fig. 3 is a flowchart illustrating a method for optimizing integrity check according to a second embodiment of the present invention.
Fig. 4 is a flowchart illustrating a method for optimizing integrity check according to a third embodiment of the present invention.
Fig. 5 is a flowchart illustrating an integrity detection optimization method according to a fourth embodiment of the present invention.
Fig. 6 is a flowchart illustrating an integrity detection optimization method according to a fifth embodiment of the present invention.
Fig. 7 is a schematic diagram of a data calculation and broadcasting timing sequence according to a fifth embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It is to be understood that the described embodiments are merely a few embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiments of the present invention will be described in detail with reference to the accompanying drawings.
First embodiment
Fig. 1 is a schematic flow chart of an integrity detection optimization method according to a first embodiment of the present invention; fig. 2 is a schematic diagram of a fault theory model according to a first embodiment of the present invention. For a clear description of the integrity detection optimization method provided by the first embodiment of the present invention, please refer to fig. 1 and fig. 2.
Currently, there is no test scheme for assessing the effectiveness of a real-time integrity monitoring module. The test of the integrity monitoring module mainly judges whether the integrity monitoring module detects a fault in a preset or predefined fault scene, and broadcasts alarm information in an alarm time limit (TTA) specified by a system. The difficulty is how to define a fault scene, comb out all fault types and the occurrence probability in the data receiving and calculating process, and count the time delay of the user receiving the alarm information to ensure the effectiveness of the user. Based on this, the integrity detection optimization method provided by the first embodiment of the present invention is provided, which includes the following steps:
step S1: and executing validity tests on the tested product to acquire integrity information, wherein the validity tests comprise fault tests and alarm time delay tests.
In one embodiment, the tested product referred to in the present invention is a high-precision positioning data product, i.e. a data product such as navigation software and positioning software, which are commonly available in the market. The testing method is used for simulating faults to detect the integrity monitoring module of the tested product, so that the faults can be identified timely and quickly, and the validity requirement of the integrity monitoring module is met. Specifically for testing, i.e. meeting two criteria of the integrity detection module: 1. whether the fault can be correctly identified; 2. whether the fault can be identified in time. Therefore, the fault test and the alarm time delay test are respectively corresponded. And obtaining integrity information through two tests, and evaluating the working effectiveness of the integrity monitoring module of the tested product.
In one embodiment, at step S1: before the step of performing the validity test on the tested product, the method comprises the following steps: acquiring standard fault information; and establishing a fault theoretical model according to the standard fault information, wherein the fault theoretical model comprises a standard fault type, a standard fault probability and a standard fault reason.
In one embodiment, for the fault test, it is preferable to simulate the fault of the tested product during the use process, and test whether the integrity monitoring module of the tested product can identify the corresponding fault. It will be appreciated that because faults are of short duration and low frequency, identification and recording of faults often requires a long period of data accumulation and analysis. In general, the identification and judgment of the fault depends on the post-processing comparison of third-party data, and the integrity monitoring module performance in the fault scene cannot be evaluated in real time. For fault types with extremely low occurrence probability, such as system-level faults of a satellite system, in the processes of production and integrity monitoring of high-precision positioning data products, corresponding fault scenes cannot be found out through medium-term and long-term data statistics and identification, and the difficulty is increased for testing an integrity monitoring module. In addition to correctly detecting alarms, the time delay for a user to receive an alarm message is also one of the contents of testing the validity of the integrity monitoring module. If the user cannot be guaranteed to receive the warning information within the time delay of system design, additional safety risks can be brought to the user. Therefore, a complete integrity monitoring module test scheme needs to define the fault type in advance, and consider the monitoring of all listed fault scenarios, that is, refer to the schematic diagram of the fault theoretical model shown in fig. 2.
In one embodiment, for the fault theory model shown in fig. 2, the establishing process may be: the method is established by obtaining standard fault information. The process of acquiring the standard fault information may be performed by collecting a large amount of fault data, or integrating fault data provided by a third party, which is not particularly limited. Further, a fault theoretical model is established, wherein the fault theoretical model comprises standard fault types, fault probabilities and fault reasons. Wherein the overall probability is 10 -5 Assigned to 5 different fault types: 1. GNSS (Global Navigation satellite System) (Sate)lite System) space segment failure: the fault occurring during the operation of the satellite is also one of the contents of the satellite health state identifier representation in the satellite ephemeris, and mainly comprises single satellite fault, multiple satellite faults, constellation fault and the like, wherein the probability is about 10 -6 . 2. GNSS ground control section trouble: the ground control station can monitor the attitude and orbit of the satellite in real time in the running process of the satellite and transmit satellite ephemeris parameters to the satellite at regular time according to a user interface protocol. The failure types of the part mainly comprise errors of satellite ephemeris parameters and satellite position errors caused by unreported satellite maneuvers, and the probability is about 10 -6 . 3. Enhancing system failure: high precision location of faults in data products provided by a data product service provider, including faults that occur during the collection of observations, calculation of data products, and dissemination of data products, with a probability of about 2 x 10 -6 . 4. Atmospheric anomalies were not corrected: local atmospheric anomalies, which are mainly caused by tropospheric anomalies and ionospheric anomalies, also cause positioning drift with a probability of about 2 × 10 -6 . 5. Receiver side exception: the type of failure within or near the receiver end, including nearby signal interference/spoofing, multipath effects in the receiving environment, tracking loop failure within the receiver, and filter failure, is approximately 4 x 10 -6 . It is understood that the above examples of the type of fault, the probability of fault, and the cause of fault are simply illustrations of the technology, not limitations of the technology, and the actual situation, for example, when a fault that does not appear in the fault theory model, appears, depends on its own properties.
In one embodiment, the fault tests include historical fault tests and simulated fault tests. At step S1: the step of performing the validity test on the tested product comprises the following steps: acquiring fault data of a tested product; judging whether the fault to be detected has a corresponding standard fault type or not according to the fault data and the fault theoretical model; if yes, executing historical fault test; if not, executing a simulation fault test, wherein the simulation fault test comprises a historical data manual injection fault test and a real-time manual injection fault test.
In one embodiment, when injecting a relevant fault into a product under test for fault testing, it is necessary to simulate the occurrence of the fault, that is, to inject fault data to simulate the fault. To ensure the occurrence of a complete recovery fault, more accurate simulation and configuration are required. And because of the existence of the fault theoretical model, whether a corresponding fault historical record exists can be completely judged from the fault theoretical model for the faults which appear before, if so, a historical fault test can be executed, and based on historical data and a plurality of third-party data products, error distribution is drawn, and the time, the type and the duration of the fault are identified. And inputting a fault scene configuration file and historical product data by using an offline processing function of the integrity monitoring module, outputting integrity monitoring information, evaluating a monitoring result, and iteratively optimizing an integrity monitoring algorithm. For the fault types which do not appear in the historical data, a simulation fault test can be executed, a fault scene configuration file is designed, and the occurrence of new faults is simulated so as to test the effectiveness of the integrity detection module. Furthermore, because the fault is a new fault, the simulation fault test can be divided into a historical data manual injection fault test and a real-time manual injection fault test, the fault data are respectively input into the offline processing function and the real-time monitoring function of the integrity monitoring module during the test, integrity monitoring information is respectively output, the monitoring result is evaluated, and the integrity monitoring algorithm is iteratively optimized. In particular, the specific implementation procedures for the historical fault test and the simulated fault test will be described in detail later, and are not expanded here for the time being.
In an embodiment, the step of performing the historical failure test to obtain the integrity information includes: acquiring a historical data file, a first configuration file and historical fault information, and executing a first service end integrity test; first integrity information of a first service end integrity test is obtained.
In one embodiment, the present embodiment is mainly directed to the detailed description of the offline monitoring test procedure in the historical fault test. It is noted that the various tests mentioned here and hereafter: the historical fault test, the simulation fault test and the like are all names of tests, and the specific execution can be carried out in a preset serviceThe end integrity detection module is implemented, so that the later integrity test of the first service end and the later integrity test of the second service end are only used for distinguishing and respectively correspond to the corresponding historical fault test, the corresponding simulation fault test and the like, and the later description is omitted. And executing a first service end integrity test of the product to be tested in the service end integrity detection module, wherein the historical data file, the first configuration file and the historical fault information are required to be acquired. Specifically, for the historical data file: downloading a historical data file generated by server software from a tested product storage server; a first configuration file: according to the difference of the tested product and the software mode, automatically generating a configuration file of the server software, so that the tested product can run according to a preset mode; the first historical fault information is information obtained by historical fault analysis, and specifically may include the following historical faults: the fault type is used for evaluating the specific time point and duration of the fault occurrence and the fault satellite (region) in the time interval; and fault error distribution data of the tested product. How to obtain the first historical fault information according to the historical fault analysis will be described in detail later, and is not expanded here. Further, for the process of executing the first service end integrity test, the tested product file at the corresponding time may be downloaded according to the historical fault event list in the historical fault information, and the first configuration file of the tested product calculation software is automatically generated. A first configuration file and a historical data product file are input in an offline processing program, and the first configuration file and the historical data product file are output as an integrity information file of a tested product, namely first integrity information. Specifically, the first integrity information includes a residual error ( res) Variance (a)sigma) Integrity identifier (a)integrity flag) And a quality identifier (QI， quality indicator) For subsequent evaluation and optimization.
In one embodiment, the step of acquiring historical failure information includes: acquiring a data correction truth value; and the data correction truth value and the tested product are processed by an off-line data evaluation system to obtain historical fault information and second integrity information.
In one embodiment of the present invention, the substrate is,the present embodiment is a specific implementation for executing the historical failure analysis step in the historical failure test. The method needs to read a tested product stored in a server through integrity offline data evaluation processing software, compare the tested product with third-party true value data, calculate an error sequence of the real-time tested product, identify a fault scene, draw error distribution and provide integrity parameters necessary for calculation of the protection level of a user side so as to execute and analyze historical fault tests. The specific implementation mode comprises the steps of obtaining a truth value file of a data product to be evaluated from a third party organization such as an IGS (International GNSS service), downloading the truth value file of the data product to be evaluated as a data correction truth value, downloading a tested product file to be evaluated generated by a server from a data product storage server, and inputting the tested product file to be evaluated into an offline data evaluation system for historical fault analysis. The truth file may include, for example: 1. the method comprises the following steps of satellite broadcast ephemeris file, z, 2, satellite precision orbit file, sp3, 3, satellite precision clock error file, clk, 4, global vertical ionosphere map, 5, station vertical troposphere estimation, 6, wide lane-narrow lane phase deviation estimation and the like. The second integrity information obtained by the offline data evaluation system includes a failure probability ( P fault ) Probability of system failure: (P sys ) Time of validity of integrity information: (T valid ) Precision factor magnification factor: (α) Nominal envelope deviation (b nom ) Mean time to failure duration: (τ) For subsequent analytical evaluation. Further, product failure probability (P fault ): probability of a user encountering a product failure during use of the product, applicable to all satellites/products of a particular GNSS system; probability of system failure: (P sys ): corresponding to each GNSS system, reflecting the probability that the same fault source affects the whole GNSS constellation; factor of precision amplification factor: (α): all satellites/products applicable to a specific GNSS system are used to conservatively estimate the envelope measurement error distribution; nominal envelope deviation (b nom ): all satellites/products applicable to a particular GNSS system, and
together, a conservative envelope of the product error property distribution is formed.
In an embodiment, the historical fault information required by the historical fault test described above can be obtained through the historical fault analysis step, where the historical fault information includes historical faults and error distributions, and the historical faults include: the fault type, the specific time point and duration of the fault and the fault satellite (region) in the evaluation time interval; and for the error distribution, drawing an error distribution diagram of the tested product based on the calculated tested product error, drawing an envelope curve and calculating relevant information such as statistic corresponding to the distribution. Therefore, integrity parameters required by historical fault test calculation are obtained after the processing of the off-line data evaluation system.
In an embodiment, in the step of performing the historical data manual failure test to obtain the integrity information, the method includes: acquiring historical fault data and a second configuration file, and executing integrity test of a second server; and acquiring third integrity information of the integrity test of the second server.
In one embodiment, the present embodiment is an embodiment in which a simulation fault test is performed on a fault that does not appear in a fault theory model by using a history file thereof. It can be understood that, for the types of faults which do not occur, corresponding fault scenarios should be designed, and configuration files should be automatically generated, so as to perform simulation tests. Furthermore, for the present embodiment, the manual fault testing is performed on the historical data with corresponding historical data files for the fault, wherein the testing process is preferably performed in an off-line processing manner because the corresponding historical data files exist. The specific execution process is that the tested product and the integrity information are generated by off-line processing through inputting historical fault data and a second configuration file, simulating a fault scene configuration file and a server side configuration file. Wherein, the historical fault data is the calendar generated by downloading the server software from the tested product storage server And a history data file, and automatically generating a fault scene configuration file according to the simulated fault type, wherein the fault scene configuration file comprises the time point and the duration of the fault, the affected area, the data parameters affected by the fault and the like. And for the second configuration file, automatically generating the configuration file of the server software according to different evaluation products and software modes. And then, according to the historical fault data and the second configuration file, executing a second server integrity test, simulating a fault scene configuration file and a server configuration file, and performing off-line processing generation on the tested product and integrity information to acquire third integrity information. Wherein the third integrity information includes a residual error: (res) Variance (a)sigma) Integrity identifier (a)integrity flag) And a quality identifier (QI) For subsequent evaluation and optimization.
In an embodiment, the step of performing the real-time manual injection fault test to obtain the integrity information includes: acquiring real-time fault data and a third configuration file, and executing a third server integrity test; and acquiring fourth integrity information of the integrity test of the third server.
In one embodiment, the present embodiment is directed to real-time manual injection fault testing for the types of faults that have not occurred. Similarly, the real-time fault data automatically generates a fault scene configuration file according to the simulated fault type, and the fault scene configuration file comprises the time point and the duration of the fault, the affected area, the data parameters affected by the fault and the like, and the fault is injected in real time; and the third configuration file is a configuration file of the server software automatically generated according to different evaluation products and software modes, and is input into the server integrity monitoring module for real-time processing. And then, the server integrity monitoring module (real-time processing) simulates a fault scene configuration file and a server configuration file by accessing the observation data, and executes a third server integrity test to perform real-time processing generation of the tested product and integrity information. The fourth integrity information obtained by final output includes residual error ( res) Variance (a)sigma) Integrity identifier (a)integrity flag) And a quality identifier (QI) For subsequent evaluation and optimization.
In an embodiment, the step of performing the alarm delay test on the product under test to obtain the integrity information includes: acquiring alarm time delay according to the prior integrity monitoring information time and the posterior integrity monitoring information time; and outputting fifth integrity information according to the alarm time delay.
In an embodiment, the present embodiment focuses on a specific implementation of an alarm delay test. It may be that immediately, in addition to the correct detection alarm, the time delay of the user receiving the alarm information is also one of the contents of testing the validity of the integrity monitoring module. If the user cannot be guaranteed to receive the warning information within the time delay of system design, additional safety risks can be brought to the user. Therefore, in the embodiment, in order to achieve the alarm time delay of the technical requirements, the time stamps are recorded in the whole process of data production, broadcasting and receiving, and the time delay of receiving the fault alarm by the user is counted and calculated so as to prove the timeliness of the fault alarm of the integrity monitoring module. The alarm time delay test focuses on the time difference between the prior integrity monitoring information and the posterior integrity monitoring information received by the user side. And counting the alarm time delays of the data service provider and the data service provider, wherein the alarm time delays of the data service provider and the data service provider are counted for a period of time, and within the time specified by the technical standard (the scheme takes 3 seconds as an example), the data service provider detects and finds a fault, broadcasts an integrity identifier of 'failing' or 'unavailable' to the user, and compares the integrity identifier with the maximum alarm time delay designed by the system to obtain fifth integrity information.
Step S2: the integrity information is evaluated to iteratively optimize an integrity monitoring algorithm.
In one embodiment, in step S2: the step of evaluating the integrity information to iteratively optimize the integrity monitoring algorithm comprises: and judging whether the integrity condition is met or not according to the integrity information, and if not, performing iterative optimization according to the integrity information.
In one embodiment, as described above in the various integrity information, two aspects are first included: 1. whether the detection is correct or not; 2. whether to detect in time. In particular, various information may be evaluated for iterations that do not meet validity requirementsAnd (6) optimizing. For the former, i.e. integrity information obtained by fault testing, the most important of which is the integrity identifier: (integrity flag) Integrity identifier (A)integrity flag) Is an important index for informing a user whether an orbital clock and a deviation product are available at the current moment corresponding to each satellite (an atmospheric product corresponds to each area). If after reading the file, simulate the point of failure, integrity identifier (integrity flag) If the monitoring result is 'pass' or 'undetected', an iterative integrity monitoring algorithm is optimized, and alarm information is broadcast when the fault is simulated. The system alarm information is corresponding to each GNSS system, and comprises four identifications of 'normal', 'warning' and 'unmonitored', and is embedded into a product telegraph text or a posterior integrity telegraph text. If the user decodes the message and finds that the system alarm information corresponding to a certain GNSS system is in an 'alarm' state, the GNSS system needs to be excluded from positioning. In addition, the warning state indicates that the error of the GNSS system does not cause serious consequences but has certain risks, and even the error can be changed into the warning state in a short time, so that a user can select whether to use the observation amount and the correction value of the GNSS system according to the use scene of the user. If the system alarm information is normal or unmonitored in the system-level fault simulation, optimizing an iterative integrity monitoring algorithm, broadcasting the system alarm information at the time of simulating the fault and aiming at the alarm time delay test, paying attention to whether the time delay exceeds the maximum alarm time delay, if so, adjusting the algorithm, shortening the calculation time of the posterior integrity information in the service end program, and repeatedly verifying.
The integrity detection optimization method provided by the first embodiment of the invention comprises the following steps: step S1: executing validity tests on the tested product to acquire integrity information, wherein the validity tests comprise fault tests and alarm time delay tests; step S2: the integrity information is evaluated to iteratively optimize an integrity monitoring algorithm. Therefore, the method can carry out effectiveness test on the integrity monitoring module of the high-precision positioning product to determine whether the integrity monitoring can work normally or not, and carries out evaluation by two dimensions of fault test and alarm time delay test, and iteratively optimizes the integrity monitoring algorithm to provide the calculation efficiency and robustness of the integrity monitoring algorithm. Furthermore, the integrity detection optimization method provided by an embodiment of the present invention can also perform systematic analysis and definition on the types of faults that may occur in the product under test before performing the detection. And establishing a fault theoretical model according to theoretical frequency and historical data of each fault in the whole process from generation of satellite observation to final positioning result output so as to distribute fault types and fault probability fault reasons and help to generate a simulated fault scene for testing to provide theoretical basis and preparation. In addition, in the fault test, whether the fault appears in a fault theoretical model is taken as a standard, if the historical fault is performed, the historical fault test is performed, and aiming at the problems that the real-time fault appears in short duration and is difficult to reproduce, historical product data is analyzed and compared with third-party data, a historical fault table is maintained, the function of offline processing is utilized, the fault scene is recovered for multiple times, and a monitoring algorithm is optimized; if the fault is not in the theoretical model, a simulated fault test is executed to generate an artificial simulated fault scene which is used as one of the inputs of the monitoring module, and the fault is monitored and eliminated in two different processing modes of real-time and off-line so as to test the effectiveness of the integrity monitoring module. In addition, in order to achieve the alarm time delay of the technical requirement, the time delay test of the whole link is supported, the time stamps are recorded in the whole process of data production, broadcasting and receiving, and the time delay of the fault alarm received by the user is counted and calculated so as to prove the timeliness of the fault alarm of the integrity monitoring module. Meanwhile, integrity information is evaluated, faults are injected, and a test experiment is repeated, so that the calculation efficiency and robustness of an integrity monitoring algorithm are improved, the operation of a user is reduced, the convenience of the user is improved, and the use experience of the user is improved.
Second embodiment
Fig. 3 is a flowchart illustrating an integrity detection optimization method according to a second embodiment of the present invention. For a clear description of the integrity detection optimization method provided by the second embodiment of the present invention, please refer to fig. 1 and fig. 3.
As described above, the method for testing the integrity monitoring module tests whether the module can correctly identify the fault or can identify the fault in time, and the method for testing the integrity provided by the third embodiment of the present invention mainly aims at the historical fault test set for the condition whether the module can correctly identify the fault, and specifically comprises the following steps:
step S21: and acquiring a data correction truth value, and acquiring historical fault information and second integrity information by using the data correction truth value and the tested product through an offline data evaluation system.
In one embodiment, this step is a specific implementation of the historical failure analysis step in the historical failure test. The method needs to read a tested product stored in a server through integrity offline data evaluation processing software, compare the tested product with third-party true value data, calculate an error sequence of the real-time tested product, identify a fault scene, draw error distribution and provide integrity parameters necessary for calculation of the protection level of a user side so as to execute and analyze historical fault tests. The specific implementation mode comprises the steps of obtaining a true value file of a data product to be evaluated, downloaded from a third party organization such as an IGS (integrated into system), serving as a data correction true value, downloading a tested product file to be evaluated, generated by a server side from a data product storage server, and inputting the tested product file to be evaluated into an offline data evaluation system for historical fault analysis. The second integrity information processed by the offline data evaluation system includes a probability of failure ( P fault ) Probability of system failure: (P sys ) Integrity information valid time (T valid ) Precision factor amplification factor: (α) Nominal envelope deviation (b nom ) Mean time to failure duration: (τ) For subsequent analytical evaluation. The fault diagnosis system further comprises the historical fault information required by the historical fault test, wherein the historical fault information comprises historical faults and error distribution, and the historical faults comprise: the fault type, the specific time point and duration of the fault and the fault satellite (region) in the evaluation time interval; and for the error distribution, drawing the error distribution of the tested product based on the calculated error of the tested productThe graph shows an envelope curve and calculates the relevant information such as statistics corresponding to the distribution. Therefore, integrity parameters required by historical fault test calculation are obtained after the processing of the off-line data evaluation system.
Step S22: and acquiring a historical data file, a first configuration file and historical fault information, and executing a first service end integrity test.
In one embodiment, the offline monitoring test is then performed during the historical failure test. And executing a first service end integrity test of the product to be tested in the service end integrity detection module, wherein the historical data file, the first configuration file and the historical fault information are required to be acquired. Specifically, for the historical data file: downloading a historical data file generated by server software from a tested product storage server; a first configuration file: according to the difference of the tested product and the software mode, automatically generating a configuration file of the server software, so that the tested product can run according to a preset mode; the first historical fault information is information obtained by historical fault analysis, and specifically may include the following historical faults: fault type, specific time point and duration of fault occurrence and fault occurrence satellite (region) in the evaluation time interval; and fault error distribution data of the tested product. How to obtain the first historical fault information according to the historical fault analysis will be described in detail later, and is not expanded here. Further, for the process of executing the first service end integrity test, the tested product file at the corresponding time may be downloaded according to the historical fault event list in the historical fault information, and the first configuration file of the tested product calculation software is automatically generated. A first configuration file and a historical data product file are input in an offline processing program, and the first configuration file and the historical data product file are output as an integrity information file of a tested product, namely first integrity information. Specifically, the first integrity information includes a residual error ( res) Variance, variance (a)sigma) Integrity identifier (A)integrity flag) And a quality identifier (C:QI) For subsequent evaluation and optimization.
Step S23: first integrity information of the first service end integrity test is obtained to iteratively optimize an integrity monitoring algorithm.
In one embodiment, the integrity information obtained by the test, wherein the most important information is the integrity identifier (c:, information of the information on the information of which is information on the information of which is information about the information about integrity of which is about the information about the integrity is about the information about the most important to be about the information about the integrity of which is about the information about the integrity of which is about the most important ofintegrity flag)). If after reading the file, simulate the point of failure, integrity identifier (integrity flag) And) if the monitoring result is 'pass' or 'undetected', optimizing an iterative integrity monitoring algorithm, and broadcasting alarm information when simulating a fault.
A second embodiment of the present invention provides an integrity detection optimization method, including the steps of: step S1: acquiring a data correction truth value, and acquiring historical fault information and second integrity information by using the data correction truth value and a tested product through an offline data evaluation system; step S22: acquiring a historical data file, a first configuration file and historical fault information, and executing a first service end integrity test; step S23: first integrity information of a first service end integrity test is obtained. Therefore, the second embodiment of the present invention is directed to providing a corresponding method for optimizing integrity detection, and the technical effects that can be specifically achieved by the method for optimizing integrity detection provided by the first embodiment of the present invention have been described in detail, for which reference is made to the foregoing specifically, and therefore, the details are not repeated herein.
Third embodiment
Fig. 4 is a flowchart illustrating a method for optimizing integrity check according to a third embodiment of the present invention. For a clear description of the integrity detection optimization method provided by the second embodiment of the present invention, please refer to fig. 1 and fig. 4.
The simulation fault test in the integrity detection optimization method is performed in the second embodiment of the present invention, and is a test performed on a fault type that does not occur in the historical data, specifically, a design fault scenario configuration file, and simulates occurrence of a new fault, so as to test the validity of the integrity detection module. Furthermore, the simulation fault test can be further divided into a historical data manual injection fault test and a real-time manual injection fault test, during the test, fault data are respectively input into the off-line processing function and the real-time monitoring function of the integrity monitoring module, integrity monitoring information is respectively output, monitoring results are evaluated, and an integrity monitoring algorithm is iteratively optimized. The present embodiment preferably relates to a fault test performed by manually injecting historical data, and is a fault test performed by manually injecting historical data into a corresponding historical data file for a fault, where the test process is preferably performed in an offline processing manner because the corresponding historical data file exists.
Step S31: and acquiring historical fault data and a second configuration file, and executing integrity test of a second server.
In one embodiment, for the historical data manual injection fault test, the specific execution process is to perform offline processing generation of the tested product and the integrity information by inputting the historical fault data and the second configuration file, simulating a fault scene configuration file and a server side configuration file. The historical fault data is a historical data file generated by downloading server software from a tested product storage server, and a fault scene configuration file is automatically generated according to the simulated fault type, wherein the fault scene configuration file comprises the time point and the duration of the fault, the affected area, the data parameters affected by the fault and the like. And for the second configuration file, automatically generating the configuration file of the server software according to different evaluation products and software modes. And then, according to the historical fault data and the second configuration file, executing a second server integrity test, simulating a fault scene configuration file and a server configuration file, and performing off-line processing generation on the tested product and integrity information to acquire third integrity information. Wherein the third integrity information includes a residual error: ( res) Variance, variance (a)sigma) Integrity identifier (A)integrity flag) And a quality identifier (C:QI) For subsequent evaluation and optimization.
Step S32: and acquiring third integrity information of the integrity test of the second server so as to iteratively optimize the integrity monitoring algorithm.
In one embodiment, the integrity information obtained by the test, wherein the most important information is the integrity identifier (c:, information of the information on the information of which is information on the information of which is information about the information about integrity of which is about the information about the integrity is about the information about the most important to be about the information about the integrity of which is about the information about the integrity of which is about the most important ofintegrity flag)). If after reading the file, simulate the point of failure, integrity identifier (integrity flag) ) the monitoring result is "passAnd if the fault is detected, optimizing an iterative integrity monitoring algorithm and broadcasting alarm information when the fault is simulated.
A third embodiment of the present invention provides an integrity detection optimization method, including the steps of: step S31: acquiring historical fault data and a second configuration file, and executing integrity test of a second server; step S32: and acquiring third integrity information of the integrity test of the second server so as to iteratively optimize the integrity monitoring algorithm. Therefore, the third embodiment of the present invention is directed to providing a corresponding method for optimizing integrity detection, and the technical effects that can be specifically achieved by the method for optimizing integrity detection provided by the first embodiment of the present invention have been described in detail, for which reference is made to the foregoing specifically, and therefore, the details are not repeated herein.
Fourth embodiment
Fig. 5 is a flowchart illustrating a method for optimizing integrity check according to a fourth embodiment of the present invention. For a clear description of the method for optimizing integrity check according to the fourth embodiment of the present invention, please refer to fig. 1 and fig. 5.
The integrity detection optimization method provided by the fourth embodiment of the present invention is directed to a real-time manual injection fault test for an unexplained fault type, and includes the following steps:
step S41: and acquiring real-time fault data and a third configuration file, and executing a third server integrity test.
In one embodiment, the real-time fault data is a fault scene configuration file automatically generated according to the simulated fault type, and the fault scene configuration file comprises the time point and the duration of the fault, the affected area, the data parameters affected by the fault and the like, and the fault is injected in real time; and the third configuration file is a configuration file of the server software automatically generated according to different evaluation products and software modes, and is input into the server integrity monitoring module for real-time processing. And then, the server integrity monitoring module (real-time processing) simulates a fault scene configuration file and a server configuration file by accessing the observation data, and executes a third server integrity test to perform real-time processing generation of the tested product and integrity information. Finally output to obtain the fourth finished product The goodness information includes residual error: (res) Variance, variance (a)sigma) Integrity identifier (A)integrity flag) And a quality identifier (C:QI) For subsequent evaluation and optimization.
Step S42: and acquiring fourth integrity information of the integrity test of the third server so as to iteratively optimize the integrity monitoring algorithm.
In one embodiment, the integrity information obtained by the test, wherein the most important information is the integrity identifier (c:, information of the information on the information of which is information on the information of which is information about the information about integrity of which is about the information about the integrity is about the information about the most important to be about the information about the integrity of which is about the information about the integrity of which is about the most important ofintegrity flag)). If after reading the file, simulate the point of failure, integrity identifier (integrity flag) And) if the monitoring result is 'pass' or 'undetected', optimizing an iterative integrity monitoring algorithm, and broadcasting alarm information when simulating a fault.
A fourth embodiment of the present invention provides an integrity detection optimization method, including the steps of: step S41: acquiring real-time fault data and a third configuration file, and executing a third server integrity test; step S42: and acquiring fourth integrity information of the integrity test of the third server so as to iteratively optimize the integrity monitoring algorithm. Therefore, the fourth embodiment of the present invention is directed to providing a corresponding method for optimizing integrity detection, and the technical effects that can be specifically achieved by the method for optimizing integrity detection provided by the first embodiment of the present invention have been described in detail, for which reference is made to the foregoing specifically, and therefore, the details are not repeated herein.
Fifth embodiment
Fig. 6 is a flowchart illustrating an integrity detection optimization method according to a fifth embodiment of the present disclosure; fig. 7 is a schematic diagram of a data calculation and dissemination sequence according to a fifth embodiment of the present invention. For a clear description of the integrity detection optimization method provided by the fifth embodiment of the present invention, please refer to fig. 1, fig. 6, and fig. 7.
The integrity detection optimization method provided by the fifth embodiment of the invention mainly aims at
Step S51: and acquiring alarm time delay according to the prior integrity monitoring information time and the posterior integrity monitoring information time.
In an embodiment, for the timing of data dissemination, reference may be made to the figureFig. 7 is a schematic diagram of a data calculation and distribution timing sequence according to a fifth embodiment of the present invention. As shown, the link, in chronological order, performs the following functions at different times in turn: t is t 0 At the moment, the high-precision positioning data product calculation module receives observation data from the station network; t is t 1 Calculating to obtain a high-precision positioning data product at any moment; t is t 2 At any moment, the high-precision positioning data product and the priori integrity monitoring information are transmitted to a data broadcasting platform together; t is t 3 At the moment, the user side receives the data product and the priori integrity monitoring information; t is t 4 At any moment, the integrity monitoring module receives the data product transmitted back by the broadcasting platform; t is t 5 Calculating posterior integrity monitoring information and transmitting the posterior integrity monitoring information to a data broadcasting platform at any moment; t is t 6 And at the moment, the user side receives posterior integrity monitoring information.
In an embodiment, the present embodiment focuses on a specific implementation of an alarm delay test. It may be that immediately, in addition to the correct detection alarm, the time delay of the user receiving the alarm information is also one of the contents of testing the validity of the integrity monitoring module. If the user cannot be guaranteed to receive the warning information within the time delay of system design, additional safety risks can be brought to the user. Therefore, in the embodiment, in order to achieve the alarm time delay of the technical requirements, the time stamps are recorded in the whole process of data production, broadcasting and receiving, and the time delay of receiving the fault alarm by the user is counted and calculated so as to prove the timeliness of the fault alarm of the integrity monitoring module. Wherein the alarm delay test focuses on t in FIG. 7 6 —t 3 The time difference between the time when the user side receives the prior integrity monitoring information and the time when the user side receives the posterior integrity monitoring information is also referred to as the time difference. Wherein the a priori integrity monitoring information, i.e. the a priori integrity detection flag is received (Pre-Check): the prior detection result for representing the broadcast product comprises four identifications of 'normal', 'unavailable', 'unmonitored' and 'information abnormal'. If the user receives the prior detection identifier of a certain product as 'unavailable', products corresponding to satellites, signals or regions are removed in the positioning calculation; if the integrity prior detection received by the user is identified as "unmonitored," the user may, depending on the current application scenario, Automatically judging whether to use the product; and the posterior integrity monitoring information comprises a posterior integrity detection mark (A)Post-Check): the posterior detection result of the broadcast product is represented, a closed loop is realized, the four identifications of 'normal', 'unavailable' and 'information abnormal' are included, and the using logic is the same as that of the integrity prior detection identification.
In one embodiment, t is counted over a period of time 6 —t 3 Within the time specified by the technical standard (the scheme takes 3 seconds as an example), the data service provider should detect the found fault and broadcast the integrity identifier of "failed" or "unavailable" to the user, and compare the integrity identifier with the maximum alarm time delay designed by the system to obtain the fifth integrity information.
Step S52: and outputting fifth integrity information according to the alarm time delay so as to iteratively optimize the integrity monitoring algorithm.
In an embodiment, for the alarm delay test, it is noted whether the delay in the fifth integrity information exceeds the maximum alarm delay, if so, the optimization algorithm is adjusted, the calculation time of the posterior integrity information in the server program is shortened, and the verification is repeated.
A fifth embodiment of the present invention provides an integrity detection optimization method, including the steps of: step S51: acquiring alarm time delay according to the prior integrity monitoring information time and the posterior integrity monitoring information time; step S52: and outputting fifth integrity information according to the alarm time delay so as to iteratively optimize the integrity monitoring algorithm. Therefore, the fifth embodiment of the present invention is directed to providing a corresponding method for optimizing integrity detection, and the technical effects that can be specifically achieved by the method for optimizing integrity detection provided by the first embodiment of the present invention are described in detail, for which reference is made to the foregoing specifically, and therefore, the details are not repeated herein.
Sixth embodiment
The sixth embodiment of the present invention also provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the integrity detection optimization method as described in the first, second, third, fourth, or fifth embodiment.
In an implementation, the computer-readable storage medium provided in this embodiment may be a volatile memory or a nonvolatile memory, and may also include both volatile and nonvolatile memories. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical disk, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Enhanced Synchronous Dynamic Random Access Memory (Enhanced DRAM), Synchronous Dynamic Random Access Memory (SLDRAM), Direct Memory (DRmb Access), and Random Access Memory (DRAM). The computer-readable storage media described in the embodiments of the invention are intended to comprise, without being limited to, these and any other suitable types of memory.
In an embodiment, the computer readable storage medium provided by the embodiment may include any entity or device capable of carrying computer program code, a recording medium, such as ROM, RAM, magnetic disk, optical disk, flash memory, and the like.
The technical effects that can be achieved by the computer program stored in the computer-readable storage medium provided by the sixth embodiment of the present invention when the computer program is executed by the processor are already described in detail in the foregoing, and specifically, refer to the foregoing, and are not described herein again.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
It should be noted that, in this document, 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 recitation of an element by the phrase "comprising an … …" does not exclude the presence of additional like elements in the process, method, article, or apparatus that comprises the element, and further, where similarly-named elements, features, or elements in different embodiments of the disclosure may have the same meaning, or may have different meanings, that particular meaning should be determined by their interpretation in the embodiment or further by context with the embodiment. As used herein, the meaning of "a plurality" or "a plurality" is two or more unless otherwise specified.
It should be understood that, although the steps in the flowcharts in the embodiments of the present application are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless otherwise indicated herein. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, in different orders, and may be performed alternately or at least partially with respect to other steps or sub-steps of other steps.
It will be understood by those skilled in the art that all or part of the steps of implementing the above method embodiments may be implemented by hardware associated with program instructions, and the program may be stored in a computer readable storage medium, and when executed, performs the steps including the above method embodiments. The foregoing storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (7)
1. A method for optimizing integrity detection is characterized by comprising the following steps:
acquiring standard fault information;
establishing a fault theoretical model according to the standard fault information, wherein the fault theoretical model comprises a fault type, a fault probability and a fault reason;
executing validity tests on a tested product to acquire integrity information, wherein the validity tests comprise fault tests and alarm time delay tests, and the fault tests comprise historical fault tests and simulated fault tests;
evaluating the integrity information to iteratively optimize an integrity monitoring algorithm;
the step of performing a validity test on the tested product to obtain integrity information includes:
acquiring fault data of the tested product;
judging whether the fault to be detected in the fault data has a corresponding standard fault type or not according to the fault data and the fault theoretical model;
If yes, executing the historical fault test;
if not, executing the simulation fault test, wherein the simulation fault test comprises a historical data manual injection fault test and a real-time manual injection fault test;
wherein the step of evaluating the integrity information to iteratively optimize an integrity monitoring algorithm comprises:
and judging whether the integrity condition is met or not according to the integrity information, and if not, performing iterative optimization according to the integrity information.
2. The integrity detection optimization method of claim 1, the step of performing the historical failure test comprising:
acquiring a historical data file, a first configuration file and historical fault information, and executing a first service end integrity test;
first integrity information of the first service end integrity test is obtained.
3. The integrity detection optimization method of claim 2, wherein the step of obtaining historical failure information comprises:
acquiring a data correction truth value;
and acquiring the historical fault information and second integrity information by using the data correction truth value and the tested product through an offline data evaluation system.
4. The integrity detection optimization method of claim 1, the step of performing the historical data manual injection fault test comprising:
Acquiring historical fault data and a second configuration file, and executing integrity test of a second server;
and acquiring third integrity information of the integrity test of the second server.
5. The integrity detection optimization method of claim 1, the step of performing the real-time manual injection fault test comprising:
acquiring real-time fault data and a third configuration file, and executing a third server integrity test;
and acquiring fourth integrity information of the integrity test of the third server.
6. The integrity detection optimization method of claim 1, wherein the step of performing the alarm delay test on the product under test to obtain integrity information comprises:
acquiring alarm time delay according to the prior integrity monitoring information time and the posterior integrity monitoring information time;
and outputting fifth integrity information according to the alarm time delay.
7. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the steps of the integrity detection optimization method of any one of claims 1 to 6.
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