Method, apparatus, and electronic device for determining integrity risk probability

Abstract

The present application discloses a method, apparatus, and electronic device for determining the integrity risk probability, belonging to the field of satellite navigation technology. The method includes: obtaining a positioning error time series and a protection level time series of positioning information, where the positioning error time series includes positioning errors at multiple time points, and the protection level time series includes protection levels at multiple time points; performing regularization processing on the positioning error time series and the protection level time series based on a preset integrity alarm threshold to generate a first sample set, the first sample set including multiple samples, and each sample including the positioning error and the protection level at the same time point; resampling the first sample set to determine a second sample set; and calculating the integrity risk probability of the satellite based on the second sample set, where the integrity risk probability is used to represent the hazardous misleading information in the integrity assessment.

Description

Technical Field

[0001] This application relates to the field of satellite navigation technology, and particularly to a method, apparatus, and electronic device for determining the integrity risk probability. Background Art

[0002] With the rapid development of satellite navigation technology, satellite navigation systems are applied in more and more fields, including transportation, address exploration, meteorological detection, and military. Among them, integrity, as one of the requirements that satellite navigation systems must meet, refers to the ability of a satellite navigation system to provide timely and effective warnings within a specified time once a failure occurs.

[0003] However, currently, the integrity assessment of satellite navigation systems is usually achieved only through Misleading Information (MI), that is, when the Protection Level (PL) is less than the Position Error (PE), and both PL and PE are less than the Alert Limit (AL), MI is generated, making the integrity assessment incomplete, thus resulting in a low credibility of the integrity assessment of satellite navigation systems. Summary of the Invention

[0004] The purpose of the embodiments of this application is to provide a method, apparatus, and electronic device for determining the integrity risk probability, which can solve the problem of low credibility of the integrity assessment of satellite navigation systems.

[0005] In a first aspect, the embodiments of this application provide a method for determining the integrity risk probability, including:

[0006] Obtain the positioning error time series and the protection level time series of the positioning information, where the positioning error time series includes the positioning errors at multiple time points, and the protection level time series includes the protection levels at the multiple time points;

[0007] Based on a preset integrity alert threshold, perform regularization processing on the positioning error time series and the protection level time series to generate a first sample set, where the first sample set includes multiple samples, and each sample includes the positioning error and the protection level at the same time point;

[0008] Resample the first sample set to determine a second sample set;

[0009] Based on the second sample set, calculate the integrity risk probability of the satellite, and the integrity risk probability is used to characterize the dangerous misleading information in the integrity assessment.

[0010] In a second aspect, the embodiments of this application provide an apparatus for determining the integrity risk probability, including:

[0011] A time series acquisition module, configured to acquire a positioning error time series and a protection level time series of positioning information, where the positioning error time series includes positioning errors at multiple time points, and the protection level time series includes protection levels at the multiple time points;

[0012] A first sample set generation module, configured to perform regularization processing on the positioning error time series and the protection level time series based on a preset integrity alarm threshold to generate a first sample set, where the first sample set includes multiple samples, and each sample includes a positioning error and a protection level at the same time point;

[0013] A second sample set determination module, configured to resample the first sample set to determine a second sample set;

[0014] A risk probability calculation module, configured to calculate an integrity risk probability of the satellite based on the second sample set, where the integrity risk probability is used to characterize dangerous misleading information in integrity assessment.

[0015] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of the method described in the first aspect are implemented.

[0016] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0017] In a fifth aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is configured to run a program or instruction to implement the method described in the first aspect.

[0018] In the embodiments of the present application, by acquiring a positioning error time series and a protection level time series of positioning information, performing regularization processing on the positioning error time series and the protection level time series based on a preset integrity alarm threshold to generate a first sample set, resampling the first sample set to determine a second sample set, and calculating an integrity risk probability of the satellite based on the second sample set. In this way, it is possible to obtain an integrity risk probability to characterize dangerous misleading information HMI in integrity assessment, making the integrity assessment of the satellite navigation system more comprehensive, and further improving the credibility of the integrity assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a schematic flowchart of an embodiment of the integrity risk probability determination method provided by the present application;

[0020] Figure 2 is a schematic structural diagram of an embodiment of the integrity risk probability determination device provided by the present application;

[0021] Figure 3 is a schematic structural diagram of an embodiment of the electronic device provided by the present application. Detailed implementation manners

[0022] Next, the technical solutions in the embodiments of the present application will be clearly described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, rather than all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application belong to the scope of protection of the present application.

[0023] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application can be implemented in an order different from those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same category, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims means at least one of the connected objects, and the character " / " generally means an "or" relationship between the associated objects before and after.

[0024] Next, in conjunction with the accompanying drawings, the integrity risk probability determination method, device, and electronic device provided by the embodiments of the present application will be described in detail through specific embodiments and their application scenarios.

[0025] Please refer to Figure 1 , which is a schematic flowchart of the integrity risk probability determination method provided by the embodiments of the present application. This integrity risk probability determination method is applied to an electronic device. As Figure 1 shown, the integrity risk probability determination method at least includes the following steps 101 to step 104.

[0026] Step 101, obtain the positioning error time series and the protection level time series of the positioning information.

[0027] Among them, the positioning error time series includes positioning errors (Position Errors, PE) at multiple time points, and the protection level time series includes protection levels (Protection Levels, PL) at multiple time points;

[0028] The above positioning information may include the positioning positions at the above multiple time points, and each positioning position may be the position of the user obtained by resolving the observation data collected by the satellite navigation system at the corresponding time point.

[0029] The time series of positioning errors for obtaining the above positioning information may be that the electronic device compares the positioning positions at each time point with the true position of the user to obtain the PE of the positioning position relative to the true position at each time point, and then obtains the above time series of positioning errors.

[0030] The time series of protection levels for obtaining the above positioning information may be to obtain the enhanced navigation message corresponding to the positioning information at each time point, and then resolve the enhanced navigation message at the time point to obtain the covariance matrix, the observation matrix, and the weighting matrix, and finally calculate the PL through the covariance matrix, the observation matrix, and the weighting matrix. Since the process of resolving the covariance matrix, the observation matrix, and the weighting matrix from the enhanced navigation message is known in the art, it will not be elaborated here.

[0031] Step 102: Regularize the time series of positioning errors and the time series of protection levels based on a preset integrity alarm threshold (Alert Limits, AL) to generate a first sample set.

[0032] The above preset AL regularizes the time series of positioning errors and the time series of protection levels, which may be to divide the PE in the time series of positioning errors by AL to obtain a normalized time series of positioning errors; and divide the PL in the time series of positioning errors by AL to obtain a normalized time series of protection levels.

[0033] Among them, the above first sample set includes multiple samples, and each sample includes the positioning error and the protection level at the same time point.

[0034] For example, assume that the above normalized time series of positioning errors is {PE1, PE2,..., PE n}, and the normalized time series of protection levels is {PL1, PL2,..., PL n}, then the above first sample set can be D = {(PL1, PE1), (PL2, PE2),..., (PL n , PE n )}, that is, the kth sample in the above first sample set is (PL k , PE k ). Among them, the above n is a positive integer, and k is a positive integer less than or equal to n.

[0035] Step 103: Resample the first sample set to determine a second sample set.

[0036] The above resampling of the first sample set to determine the second sample set may be to re-characterize the sample distribution in the first sample set according to prior knowledge, so as to screen out at least some samples in the first sample set as the second sample set.

[0037] Specifically, the above resampling of the first sample set to determine the second sample set may include: based on a preset sample length L, dividing the first sample set into M sample groups, each sample group including L samples that are continuous in time; based on a preset PE threshold, determining at least one target sample group among the M sample groups; and generating the above second sample set based on the samples in at least one target sample group.

[0038] The above determining at least one target sample group among the M samples based on a preset PE threshold may be to determine the sample groups in which the PEs of the L samples in the M sample groups are all greater than or equal to the preset PE threshold or all less than the preset PE threshold as the target sample groups.

[0039] The above generating the above second sample set based on the samples in at least one target sample group may be to add all the samples in at least one target sample group to the second sample set; or, it may also be to select one target sample from the L samples in each target sample group and add it to the second sample set. Among them, the target sample may be the first sample or a sample at other preset positions, or a randomly determined sample, or a sample whose PE is closest to the preset PE threshold, and so on.

[0040] For example, in the case where the above first sample set includes 10,000 samples, assuming that the above L is 4, the electronic device divides the first sample set and can obtain 2,500 (i.e., M = 2,500) sample groups; then, the electronic device compares the PEs of the samples in each sample group with the preset PE threshold to determine the target sample groups in which the PEs of the 4 samples are all greater than or equal to the preset PE threshold or all less than the preset PE threshold. Assuming the number of target sample groups is 2,000; finally, the electronic device adds all the samples in the 2,000 target sample groups to the above second sample set, and so on.

[0041] In some embodiments, the above resampling of the first sample set to determine the second sample set includes:

[0042] Performing autocorrelation analysis on the positioning errors of the samples in the first sample set to determine the number of sample intervals with autocorrelation less than a second preset threshold;

[0043] Generating N sample subsets based on the first sample set and the number of sample intervals;

[0044] Determine at least one target sample subset among N sample subsets, where the positioning errors of all samples in the target sample subset are greater than or equal to a third preset threshold or less than the third preset threshold;

[0045] Generate a second sample set based on the first sample of each target sample subset in at least one target sample subset.

[0046] In this embodiment, by performing autocorrelation analysis on the positioning errors of the samples, the number of sample intervals is obtained. Then, N sample subsets are generated from the first sample set based on the number of sample intervals. Next, at least one target sample subset is determined among the N sample subsets. Finally, the first sample of each target sample subset is added to the second sample set, making the generated second sample set more suitable, thereby improving the accuracy of the represented Hazardously Misleading Information (HMI), and further enhancing the credibility of the integrity assessment of the satellite navigation system.

[0047] The above-mentioned autocorrelation analysis of the positioning errors of each sample in the first sample set to determine the number of sample intervals with autocorrelation less than the second preset threshold can be, when multiple numbers of sample intervals are obtained through autocorrelation analysis, comparing each number of sample intervals with the above-mentioned second preset threshold and determining any number of sample intervals less than the second preset threshold.

[0048] It should be noted that the above-mentioned electronic device can be preset with an autocorrelation analysis algorithm, and the autocorrelation analysis of the positioning errors of each sample in the first sample set is implemented through this autocorrelation analysis algorithm. Since the processing process of the autocorrelation analysis algorithm is known to those skilled in the art, it will not be elaborated here.

[0049] In addition, the above-mentioned second preset threshold can be a value set according to actual needs and is not limited here.

[0050] In this embodiment, after obtaining the above-mentioned number of sample intervals, the electronic device can generate N sample subsets based on the first sample quantity and the number of sample intervals, such that in the above-mentioned N sample subsets, the i-th sample subset includes samples with a continuous number of sample intervals in time sequence in the first sample set, and the first sample in the i-th sample subset is the i-th sample in the first sample set, N is an integer greater than 1, and i is a positive integer less than or equal to N.

[0051] For example, assume that the electronic device performs autocorrelation analysis on the PE of the samples in the first sample set D to obtain the above-mentioned number of sample intervals c. The electronic device can operate on the first sample set D according to the number of sample intervals c to obtain a set K including N sample subsets, and the set K is represented by the following formula (1).

[0052] K = {I ∈ D | I i is a set consisting of c consecutive samples starting from the i-th sample in D} (1)

[0053] As can be seen from formula (1), I i represents the i-th sample subset, and the first sample in I i is the i-th sample in D, and I i includes c samples that are consecutive in time.

[0054] After the above electronic device generates the above N sample subsets, the electronic device can compare the PE of the samples in each sample subset with a third preset threshold, determine the sample subsets in which the PE of all samples is greater than or equal to the third preset threshold as target sample subsets, and determine the sample subsets in which the PE of all samples is less than or equal to the third preset threshold as target sample subsets.

[0055] The above third preset threshold can be a value set according to actual needs and is not limited here.

[0056] The above generating the second sample set based on the first sample of each target sample subset in at least one target sample subset can be adding the first sample of each target sample subset to the second sample set.

[0057] For example, after the electronic device obtains the above set K, the electronic device can compare each sample e in each sample subset I in the set K with a threshold Thr (i.e., the third preset threshold). If all samples in I satisfy e(PE) < Thr or e(PE) ≥ Thr, then add the first sample in I to the sample set D * (i.e., the second sample set).

[0058] Step 104: Calculate the integrity risk probability of the satellite based on the second sample set.

[0059] Among them, the integrity risk probability is used to characterize the hazardous misleading information HMI in integrity assessment.

[0060] The above calculating the integrity risk probability of the satellite based on the second sample set may include: fitting the above second sample set to obtain a fitting function; determining the difference between 1 and the fitting function as the integrity risk probability of the above satellite.

[0061] In some embodiments, the above calculating the integrity risk probability of the satellite based on the second sample set includes:

[0062] Fitting the first screened samples in the second sample set to obtain a fitting function;

[0063] The integrity risk probability is calculated based on the ratio of the second screened samples in the second sample set to the number of samples in the second sample set; wherein, the first screened samples in the second sample set satisfy: the positioning error is greater than or equal to a first preset threshold, and the protection level is less than or equal to the integrity warning threshold; the second screened samples in the second sample set satisfy: the positioning error is greater than or equal to the integrity warning threshold, and the protection level is less than or equal to the integrity warning threshold.

[0064] In this embodiment, by fitting the first screened samples in the second sample set, a fitting function is obtained, and based on the fitting function and the ratio of the second screened samples in the second sample set to the number of samples in the second sample set, the integrity risk probability is calculated, making the calculated integrity risk probability more accurate, thereby further enhancing the credibility of the integrity assessment of the satellite navigation system.

[0065] The above-mentioned first screened samples may satisfy: the positioning error is greater than or equal to a first preset threshold μ, and the protection level is less than or equal to the integrity warning threshold. Specifically, it may be that the first screened samples satisfy: the positioning error is greater than or equal to the first preset threshold μ, the protection level is less than or equal to the integrity warning threshold, and the positioning error is greater than or equal to the integrity warning threshold.

[0066] The above-mentioned second screened samples may satisfy: the positioning error is greater than or equal to the integrity warning threshold, and the protection level is less than or equal to the integrity warning threshold.

[0067] The above-mentioned fitting of the first screened samples in the second sample set to obtain a fitting function may be to input the priority in the first screened samples into the initial fitting function, solve for the constants in the initial fitting function, and generate the above-mentioned fitting function, which can be represented by the following formula (2).

[0068]

[0069] In the above formula (2), ξ and δ are constants respectively, and x represents the protection level of the sample.

[0070] The above-mentioned calculation of the integrity risk probability based on the fitting function and the ratio of the second screened samples in the second sample set to the number of samples in the second sample set may be to directly determine the above-mentioned integrity risk probability by multiplying the above-mentioned fitting function by the above-mentioned ratio.

[0071] In some embodiments, the step of calculating the integrity risk probability based on the fitting function and the ratio of the second screened samples in the second sample set to the number of samples in the second sample set is calculated based on the following formula (3).

[0072]

[0073] In the above formula (3), P HMI represents the integrity risk probability;

[0074] |D1| represents the number of the second screening samples;

[0075] |D * | represents the number of samples in the second sample set;

[0076] G ξ,δ (y) represents the fitting function, and ξ and δ are respectively constants of the fitting function, and x represents the protection level of the sample;

[0077] y represents the difference between the protection level of the sample and the first preset threshold, that is, y = PL - μ.

[0078] In this embodiment, by using the difference between the protection level and the first preset threshold as the input of the fitting function, the calculated integrity risk probability is more accurate, thereby improving the accuracy of the represented dangerous misleading information, and further improving the credibility of the integrity assessment of the satellite navigation system.

[0079] The above first preset threshold can be a value preset according to actual needs, and it can be a fixed value in the electronic device.

[0080] In some embodiments, before the ratio of the second screening samples of the second sample set to the number of samples in the second sample set based on the fitting function, the following steps are further included:

[0081] Obtain multiple candidate thresholds;

[0082] Determine at least one candidate threshold among the multiple candidate thresholds that satisfies the expected linear condition and the estimation parameter condition, where the expected linear condition is that the candidate threshold makes the corresponding σ present a linear relationship; the estimation parameter condition is that the candidate threshold makes the corresponding ζ present an equal relationship;

[0083] Determine the first preset threshold among the at least one candidate threshold.

[0084] In this embodiment, by determining the candidate threshold that satisfies the expected linear condition and the estimation parameter condition among the multiple candidate thresholds as the above first preset threshold, the first preset threshold is more appropriate, further improving the accuracy of the integrity risk probability, thereby improving the accuracy of the represented dangerous misleading information, and further improving the credibility of the integrity assessment of the satellite navigation system.

[0085] Determining the first preset threshold among at least one candidate threshold may be randomly selecting one candidate threshold among at least one candidate threshold as the first preset threshold, or alternatively, selecting the smallest or largest candidate threshold as the first preset threshold, and so on.

[0086] In some ways, after calculating the integrity risk probability of the satellite, the electronic device may further calculate the hazardous misleading information based on the integrity risk probability.

[0087] For example, the hazardous misleading information can be calculated through the following formula (4):

[0088] (HMI) prisk = 1 - exp(-P HMI ·36000) (4)

[0089] In the above formula (4), (HMI) prisk represents the hazardous misleading information.

[0090] In the embodiments of the present application, by obtaining the positioning error time series and the protection level time series of the positioning information, regularizing the positioning error time series and the protection level time series based on a preset integrity alarm threshold to generate a first sample set, resampling the first sample set to determine a second sample set, and calculating the integrity risk probability of the satellite based on the second sample set. In this way, it is possible to obtain the integrity risk probability to characterize the hazardous misleading information HMI in the integrity assessment, making the integrity assessment of the satellite navigation system more comprehensive, and further improving the credibility of the integrity assessment.

[0091] It should be noted that for the integrity risk probability determination method provided in the embodiments of the present application, the execution subject may be a device for determining the integrity risk probability, or a control module in the device for determining the integrity risk probability that is used to execute the integrity risk probability determination method. In the embodiments of the present application, taking the device for determining the integrity risk probability as an example to execute the integrity risk probability determination method, the device for determining the integrity risk probability provided in the embodiments of the present application is described.

[0092] Please refer to Figure 2 , which is a schematic structural diagram of the device for determining the integrity risk probability provided in the embodiments of the present application. As Figure 2 shown, the device 200 for determining the integrity risk probability includes:

[0093] A time series acquisition module 201, configured to acquire the positioning error time series and the protection level time series of the positioning information, where the positioning error time series includes positioning errors at multiple time points, and the protection level time series includes protection levels at multiple time points;

[0094] The first sample set generation module 202 is configured to perform regularization processing on the positioning error time series and the protection level time series based on a preset integrity alarm threshold to generate a first sample set. The first sample set includes multiple samples, and each sample includes the positioning error and the protection level at the same time point.

[0095] The second sample set determination module 203 is configured to resample the first sample set to determine a second sample set.

[0096] The risk probability calculation module 204 is configured to calculate the integrity risk probability of the satellite based on the second sample set. The integrity risk probability is used to characterize the dangerous misleading information in the integrity assessment.

[0097] In some embodiments, the risk probability calculation module 204 includes:

[0098] The fitting unit is configured to fit the first screened samples in the second sample set to obtain a fitting function.

[0099] The calculation unit is configured to calculate the integrity risk probability based on the fitting function and the ratio of the number of the second screened samples in the second sample set to the number of samples in the second sample set.

[0100] Among them, the first screened samples in the second sample set may satisfy: the positioning error is greater than or equal to a first preset threshold, and the protection level is less than or equal to the integrity alarm threshold; the second screened samples in the second sample set may satisfy: the positioning error is greater than or equal to the integrity alarm threshold, and the protection level is less than or equal to the integrity alarm threshold.

[0101] In some embodiments, the calculation unit calculates based on the following formula:

[0102]

[0103] Among them, P HMI represents the integrity risk probability;

[0104] |D1| represents the number of the second screened samples;

[0105] |D * | represents the number of samples in the second sample set;

[0106] G ξ,δ (y) represents the fitting function, and ξ and δ are respectively constants of the fitting function, x represents the protection level of the sample;

[0107] y represents the difference between the protection level of the sample and the first preset threshold.

[0108] In some embodiments, the risk probability calculation module 204 further includes:

[0109] A threshold acquisition unit, configured to acquire a plurality of candidate thresholds;

[0110] A first determination unit, configured to determine at least one candidate threshold among the plurality of candidate thresholds that satisfies an expected linear condition and an estimation parameter condition, where the expected linear condition is that the candidate threshold makes the corresponding σ present a linear relationship; the estimation parameter condition is that the candidate threshold makes the corresponding ζ present an equal relationship;

[0111] A second determination unit, configured to determine a first preset threshold among the at least one candidate threshold.

[0112] In some embodiments, the second sample set determination module 203 includes:

[0113] An autocorrelation analysis unit, configured to perform an autocorrelation analysis on the positioning errors of the samples in the first sample set, and determine the number of sample intervals with an autocorrelation less than a second preset threshold;

[0114] A sample subset generation unit, configured to generate N sample subsets based on the first sample set and the number of sample intervals, where, among the N sample subsets, the i-th sample subset includes the samples with the number of sample intervals that are temporally consecutive in the first sample set, and the first sample in the i-th sample subset is the i-th sample in the first sample set, N is an integer greater than 1, and i is a positive integer less than or equal to N;

[0115] A sample subset determination unit, configured to determine at least one target sample subset among the N sample subsets, where all the samples in the target sample subset have a positioning error greater than or equal to a third preset threshold or less than the third preset threshold;

[0116] A second sample set generation unit, configured to generate a second sample set based on the first samples of each target sample subset in the at least one target sample subset.

[0117] The integrity risk probability determination device provided by the embodiments of the present application can implement Figure 1 each process implemented by the method embodiments and achieve the same beneficial effects. To avoid repetition, details are not described here again.

[0118] Please refer to Figure 3 which is a schematic hardware structure diagram of an electronic device provided by the embodiments of the present application.

[0119] The electronic device may include a processor 301 and a memory 302 storing computer program instructions.

[0120] Specifically, the above-mentioned processor 301 may include a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or may be configured as one or more integrated circuits for implementing the embodiments of the present application.

[0121] The memory 302 may include a mass storage for data or instructions. By way of example and not limitation, the memory 302 may include a Hard Disk Drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. In some embodiments, the memory 302 may include removable or non-removable (or fixed) media, or the memory 302 is a non-volatile solid-state memory. In some embodiments, the memory 302 may be inside or outside the battery device.

[0122] In some embodiments, the memory 302 may be a Read Only Memory (ROM). In one example, the ROM may be a mask-programmed ROM, a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), an Electrically Alterable ROM (EAROM), or a flash memory, or a combination of two or more of these.

[0123] The memory 302 may include a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk storage media device, an optical storage media device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the integrity risk probability determination method according to the present application.

[0124] The processor 301 reads and executes the computer program instructions stored in the memory 302 to implement Figure 1 the method in the illustrated embodiments and achieve Figure 1 the corresponding technical effects achieved by the method / steps executed in the illustrated examples. For the sake of brevity, the description is not repeated here.

[0125] In some embodiments, the electronic device may further include a communication interface 303 and a bus 304. Among them, as Figure 3As shown, a processor 301, a memory 302, and a communication interface 303 are connected via a bus 304 to complete communication with each other.

[0126] The communication interface 303 is mainly used to implement communication between various modules, devices, units, and / or devices in the embodiments of the present application.

[0127] The bus 304 includes hardware, software, or both, and couples the components of the online data flow metering device to each other. By way of example and not limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses or a combination of two or more of these. In a suitable case, the bus 304 may include one or more buses. Although the embodiments of the present application describe and illustrate a specific bus, the present application contemplates any suitable bus or interconnect.

[0128] The electronic device can execute the integrity risk probability determination method in the embodiments of the present application, thereby implementing the integrity risk probability determination method and its device described in combination with Figure 1 and Figure 2 the integrity risk probability determination method and its device described.

[0129] The embodiments of the present application further provide a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, it implements each process of the above-mentioned integrity risk probability determination method embodiment and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0130] Wherein, the processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer-readable storage medium, such as a computer Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disc, etc.

[0131] Another embodiment of the present application further provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is configured to run programs or instructions to implement each process of the above-described embodiment of the integrity risk probability determination method and can achieve the same technical effects. To avoid repetition, details are not described herein again.

[0132] It should be understood that the chip mentioned in the embodiments of the present application may also be referred to as a system-on-chip, system chip, chip system, or system-on-chip, etc.

[0133] It should be noted that in this article, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device including a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including such element. In addition, it should be pointed out that the methods and devices in the embodiments of the present application are not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in a reverse order according to the functions involved. For example, the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0134] Through the description of the above embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present application.

[0135] The embodiments of the present application have been described above with reference to the accompanying drawings. However, the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms without departing from the purpose of the present application and the scope protected by the claims, and all of them fall within the protection scope of the present application.

Claims

1. A method for determining the integrity risk probability, characterized in that, Including: Obtaining a positioning error time series and a protection level time series for positioning information, where the positioning error time series includes positioning errors at multiple time points, and the protection level time series includes protection levels at the multiple time points; Regularizing the positioning error time series and the protection level time series based on a preset integrity alarm threshold to generate a first sample set, where the first sample set includes multiple samples, and each sample includes a positioning error and a protection level at the same time point; Resampling the first sample set to determine a second sample set; Calculating an integrity risk probability of a satellite based on the second sample set, where the integrity risk probability is used to characterize a Hazardous Misleading Information (HMI) in integrity assessment; The calculating the integrity risk probability of the satellite based on the second sample set includes: Fitting a first screening sample in the second sample set to obtain a fitting function; Calculating an integrity risk probability based on the fitting function and a ratio of a second screening sample in the second sample set to the number of samples in the second sample set; Wherein, the first screening sample in the second sample set satisfies: the positioning error is greater than or equal to a first preset threshold, and the protection level is less than or equal to the integrity alarm threshold; The second screening sample in the second sample set satisfies: the positioning error is greater than or equal to the integrity alarm threshold, and the protection level is less than or equal to the integrity alarm threshold.

2. The method according to claim 1, characterized in that, The step of calculating the integrity risk probability based on the fitting function and the ratio of the second screening sample in the second sample set to the number of samples in the second sample set is calculated based on the following formula: Among them, P HMI represents the integrity risk probability; |D1| represents the number of second screening samples; |D * | represents the number of samples in the second sample set; G ξ,δ (y) represents the fitting function, and ξ and δ are the constants of the fitting function respectively, and x represents the protection level of the sample; y represents the difference between the protection level of a sample and the first preset threshold.

3. The method according to claim 2, characterized in that, Before the calculating the integrity risk probability based on the fitting function and the ratio of the second screening sample in the second sample set to the number of samples in the second sample set, it further includes: Obtaining a plurality of candidate thresholds; Determining at least one candidate threshold among the plurality of candidate thresholds that satisfies an expected linear condition and an estimation parameter condition, where the expected linear condition is that the candidate threshold makes the corresponding σ present a linear relationship; the estimation parameter condition is that the candidate threshold makes the corresponding ζ equal; Determining the first preset threshold among the at least one candidate threshold.

4. The method according to claim 1, characterized in that, The resampling the first sample set to determine a second sample set includes: Performing autocorrelation analysis on the positioning errors of each sample in the first sample set to determine the number of sample intervals with autocorrelation less than a second preset threshold; Generating N sample subsets based on the first sample set and the number of sample intervals, where in the N sample subsets, the i-th sample subset includes samples with a continuous number of sample intervals in time series in the first sample set, and the first sample in the i-th sample subset is the i-th sample in the first sample set, N is an integer greater than 1, and i is a positive integer less than or equal to N; Determine at least one target sample subset among the N sample subsets, where the positioning errors of all samples in the target sample subset are greater than or equal to a third preset threshold or less than the third preset threshold; Generate a second sample set based on the first sample of each of the at least one target sample subset.

5. An apparatus for determining the integrity risk probability, characterized in that, Including: A time series acquisition module, configured to acquire a positioning error time series and a protection level time series of the positioning information. The positioning error time series includes positioning errors at multiple time points, and the protection level time series includes the protection levels at the multiple time points; A first sample set generation module, configured to perform regularization processing on the positioning error time series and the protection level time series based on a preset integrity alarm threshold to generate a first sample set. The first sample set includes multiple samples, and each sample includes a positioning error and a protection level at the same time point; A second sample set determination module, configured to resample the first sample set to determine a second sample set; A risk probability calculation module, configured to calculate an integrity risk probability of the satellite based on the second sample set. The integrity risk probability is used to represent dangerous misleading information in integrity evaluation; The risk probability calculation module includes: A fitting unit, configured to fit the first screened samples in the second sample set to obtain a fitting function; A calculation unit, configured to calculate an integrity risk probability based on the fitting function and the ratio of the second screened samples in the second sample set to the number of samples in the second sample set, where the first screened samples in the second sample set satisfy: the positioning error is greater than or equal to a first preset threshold, and the protection level is less than or equal to the integrity alarm threshold; The second screened samples in the second sample set satisfy: the positioning error is greater than or equal to the integrity alarm threshold, and the protection level is less than or equal to the integrity alarm threshold.

6. The device according to claim 5, wherein, The calculation unit calculates based on the following formula: Among them, P HMI represents the integrity risk probability; |D1| represents the number of second screened samples; |D * | represents the number of samples in the second sample set; G ξ,δ (y) represents the fitting function, and ξ and δ are the constants of the fitting function respectively, and x represents the protection level of the sample; y represents the difference between the protection level of the sample and the first preset threshold.

7. The device according to claim 6, wherein, The risk probability calculation module further includes: A threshold acquisition unit, configured to acquire a plurality of candidate thresholds; A first determination unit, configured to determine at least one candidate threshold among the plurality of candidate thresholds that satisfies an expected linear condition and an estimation parameter condition. The expected linear condition is that the candidate threshold makes the corresponding σ present a linear relationship; the estimation parameter condition is that the candidate threshold makes the corresponding ζ equal; A second determination unit, configured to determine the first preset threshold among the at least one candidate threshold.

8. The device according to claim 5, wherein, The second sample set determination module includes: An autocorrelation analysis unit, configured to perform autocorrelation analysis on the positioning errors of the samples in the first sample set to determine the number of sample intervals with autocorrelation less than a second preset threshold; A sample subset generation unit, configured to generate N sample subsets based on the first sample set and the number of sample intervals, where, among the N sample subsets, the i-th sample subset includes the number of samples in the first sample set that are continuous in time sequence, and the first sample in the i-th sample subset is the i-th sample in the first sample set, N is an integer greater than 1, and i is a positive integer less than or equal to N; A sample subset determination unit, configured to determine at least one target sample subset among the N sample subsets, where the positioning errors of all samples in the target sample subset are greater than or equal to a third preset threshold or less than the third preset threshold; A second sample set generation unit, configured to generate a second sample set based on the first samples of the target sample subsets in the at least one target sample subset.

9. An electronic device, wherein, It includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of the integrity risk probability determination method according to any one of claims 1-4 are implemented.

10. A readable storage medium, wherein, A program or instruction is stored on the readable storage medium. When the program or instruction is executed by a processor, the steps of the integrity risk probability determination method according to any one of claims 1-4 are implemented.

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