Double-acting platform differential satellite guidance performance evaluation monitoring threshold calculation method

Abstract

The invention belongs to the technical field of aviation satellite navigation, and particularly relates to a double-acting platform differential satellite guidance performance evaluation monitoring threshold calculation method, which comprises the following steps: identifying risk sources influencing performance in a double-acting platform differential satellite guidance system, including a risk source influencing a flight end and a risk source influencing a ground mobile end; setting a total integrity risk budget and a total continuity risk budget, and reserving a part of budget as an unknown risk buffer value; calculating a nominal error and a fault error, and summing the nominal error and the fault error to obtain a protection level; and taking the maximum value of the protection levels of all risk sources as the final protection level of the system. The system final protection level is used as the alarm threshold, the application combines the use scene of the double-acting platform, considers the risks of the ground mobile terminal and the flight terminal, and combines the common risk source of the ground mobile terminal and the flight terminal for distribution, so that the calculated alarm threshold is more reasonable, and frequent alarm or insufficient alarm is avoided.

Description

Technical Field

[0001] This application belongs to the technical field of aviation satellite navigation, and particularly relates to a method for calculating the performance evaluation monitoring threshold of differential satellite guidance for a dual-moving platform. Background Art

[0002] The dual-moving platform includes a flight end and a ground mobile end that provides a landing platform for the flight end. The dual-moving platform differential satellite guidance system supports the approach guidance of two mobile ends, has real-time warning capabilities, effectively improves the navigation safety of the dual-moving platform, and meets the requirements of high precision and high reliability for the guidance equipment of the dual-moving platform. The warning capability is related to the warning threshold. The traditional warning threshold is directly set by empirical values, resulting in the system alarming too frequently or not alarming at all. A quantitative method is needed to set the corresponding warning threshold. Summary of the Invention

[0003] To solve the above problems, this application provides a method for calculating the performance evaluation monitoring threshold of differential satellite guidance for a dual-moving platform, including: Step S1: Identify the risk sources that affect the performance in the dual-moving platform differential satellite guidance system, including the risk sources that affect the flight end and the risk sources that affect the ground mobile end; Step S2: Set the total integrity risk budget, the total continuity risk budget, and the reserved budget. The reserved budget is used as a buffer value for unknown risks; Step S3: Obtain the prior failure probability of each risk source respectively, calculate the proportion of the prior failure probability of each risk source in the sum of the prior failure probabilities of all risk sources, and allocate the remaining total integrity risk budget and total continuity risk budget to each risk source according to the proportion to obtain the probability value of integrity risk and the probability value of continuity risk of each risk source; Step S4: Input the probability value of continuity risk into the inverse standard normal distribution function for calculation, multiply the calculation result by the standard deviation of the nominal condition error to obtain the nominal error, divide the probability value of integrity risk by the prior failure probability of the risk source to obtain the probability that the system does not detect a failure, and substitute the probability of not detecting a failure into the inverse standard normal distribution function for calculation, multiply the calculation result by the standard deviation of the error under the condition that the risk source causes a failure to obtain the failure error; Step S5: Sum the nominal error and the failure error to obtain the protection level; Step S6: Take the maximum value of the protection levels of all risk sources as the final protection level of the system;

[0004] Step S7: Use the final protection level of the system as the warning threshold.

[0005] Preferably, the risk sources affecting the flight end include: multipath interference, electromagnetic interference, and cycle slips; the risk sources affecting the ground mobile end include: baseline deformation, electromagnetic interference, ephemeris error, abnormal ionospheric gradient, receiver failure, and multipath interference.

[0006] Preferably, identify the common risk sources among the risk sources affecting the flight end and those affecting the ground mobile end, and adjust the prior failure probability of the common risk sources. The adjustment methods include: When the two risk sources of the common risk source are completely correlated, take the maximum prior failure probability of the two risk sources as the prior failure probability of the common risk source; When the two risk sources of the common risk source are partially correlated, take the difference between the sum of the prior failure probabilities of the two risk sources and the product of the prior failure probabilities of the two risk sources as the prior failure probability of the common risk source.

[0007] Preferably, it further includes: Step S8: Test the alarm threshold. When the alarm frequency is higher than the set upper limit value or lower than the set lower limit value, jump to Step S2.

[0008] Preferably, both the nominal condition error standard deviation and the error standard deviation under the fault condition caused by the risk source need to be determined through fault injection experiments or simulations.

[0009] Preferably, the prior failure probability of the risk source is obtained through historical fault data statistics or equipment operation parameter modeling.

[0010] The advantages of this application include: This application improves the traditional protection level calculation method, dynamically allocates integrity risk and continuity risk, and preferentially processes high-probability or high-impact risk sources.

[0011] This application combines the usage scenarios of the dual-acting platform, considers the risks of both the ground mobile end and the flight end, and allocates risks in combination with the common risk sources of the ground mobile end and the flight end. Introducing dynamic risk allocation and closed-loop verification for the differential system of the dual-acting platform optimizes the real-time monitoring ability in complex environments. Description of the Drawings

[0012] Figure 1 It is an example diagram of the risk source index allocation for the flight end and the risk source for the ground mobile end in a preferred embodiment of this application. Detailed Embodiment

[0013] To make the technical solutions and their advantages of this application clearer, the following will further describe the technical solutions of this application clearly and completely in conjunction with the accompanying drawings. It can be understood that the specific embodiments described herein are only partial embodiments of this application, which are only used to explain this application rather than limit this application. It should be noted that for the convenience of description, only the parts related to this application are shown in the drawings, and other related parts can refer to the general design. Without conflict, the embodiments in this application and the technical features in the embodiments can be combined with each other to obtain new embodiments.

[0014] As Figure 1 shown, this application provides a method for calculating the monitoring threshold of the differential satellite guidance performance of a dual-acting platform, including: Step S1: Identify the risk sources that affect the performance in the differential satellite guidance system of the dual-acting platform, including the risk sources that affect the flight end and the risk sources that affect the ground mobile end; Step S2: Set the total integrity risk budget, the total continuity risk budget, and a reserved budget. The reserved budget serves as a buffer value for unknown risks; Step S3: Obtain the prior failure probability of each risk source respectively, calculate the proportion of the prior failure probability of each risk source in the sum of the prior failure probabilities of all risk sources, and allocate the remaining total integrity risk budget and total continuity risk budget to each risk source according to the proportion to obtain the probability value of the integrity risk and the probability value of the continuity risk of each risk source; Step S4: Input the probability value corresponding to the continuity risk into the inverse standard normal distribution function for calculation, multiply the calculation result by the nominal condition error standard deviation to obtain the nominal error; divide the probability value corresponding to the integrity risk by the prior failure probability of the risk source to obtain the probability that the system does not detect a failure, and substitute the probability of not detecting a failure into the inverse standard normal distribution function for calculation, and multiply the calculation result by the error standard deviation under the condition that the risk source causes a failure to obtain the failure error; among them, both the nominal condition error standard deviation and the error standard deviation under the condition that the risk source causes a failure need to be determined through fault injection experiments or simulations.

[0015] The nominal condition error standard deviation is the positioning error when the system is operating normally. Dividing the probability value corresponding to the integrity risk by the prior failure probability of the risk source to obtain the probability that the system does not detect a failure represents the continuity risk tolerance allowed by the system. After substituting the probability of not detecting a failure into the inverse standard normal distribution function and then multiplying it by the error standard deviation under the condition that the risk source causes a failure, the failure error is obtained; it converts the probability of not detecting a failure into the corresponding standard deviation multiple, reflecting the potential impact of the failure on the positioning result.

[0016] Among them, the inverse function of the standard normal distribution converts the abstract risk probability into a specific error bound. Both the nominal conditional error standard deviation and the error standard deviation under the condition that the risk source causes a fault need to be determined through fault injection experiments or simulations.

[0017] Step S5: Sum the nominal error and the fault error to obtain the protection level; that is to say, the protection level is the conservative upper limit of the positioning error of the system considering both normal operation and specific fault scenarios.

[0018] Step S6: Take the maximum value of the protection levels of all risk sources as the final protection level of the system. That is to say, the final protection level of the system is also the final global protection level, ensuring that the worst-case scenarios of all risk sources are covered.

[0019] Step S7: Use the final protection level of the system as the alarm threshold.

[0020] Step S8: Test the alarm threshold. When the alarm frequency is higher than the set upper limit value or lower than the set lower limit value, jump to Step S2.

[0021] In some alternative embodiments, the risk sources affecting the flight end include: multipath interference, electromagnetic interference, and cycle slips; the risk sources affecting the ground mobile end include: baseline deformation, electromagnetic interference, ephemeris error, ionospheric gradient anomaly, receiver failure, and multipath interference.

[0022] Identifying the risk sources affecting the performance of the dual-acting platform differential satellite guidance system specifically includes: Risk sources in the space segment include: 1) Satellite ephemeris fault: Incorrect ephemeris or unannounced satellite maneuvers can cause the satellite ephemeris not to truly represent the satellite's orbital position; 2) Low satellite signal power: Excessively low signal power can cause the satellite signal received by the receiver to lose lock or be unable to track; 3) Inter-frequency bias: Due to the use of the dual-frequency differential mode, the clock bias is inconsistent between different frequency points, introducing inter-frequency bias.

[0023] Risk sources in the atmospheric segment include: 1) Tropospheric storms: Tropospheric storms will introduce anomalies in space signals, usually occurring in thunderstorm weather, introducing large changes in the observed quantity error. The magnitude of the introduced tropospheric delay gradient can reach 10 mm / km; 2) Ionospheric gradient anomaly: Solar activity causes ionospheric electron storms. Under severe ionospheric anomaly conditions, the ionospheric second-order terms between the code and the carrier, and between different frequencies, will introduce non-linear relationships. The introduced ionospheric delay gradient can reach 400 mm / km; 3) Ionospheric scintillation: Ionospheric scintillation events often occur in high-latitude regions or near the magnetic equator, which will cause abnormal ionospheric refraction, reduce the signal-to-noise ratio, and sometimes lead to rapid recombination, resulting in a sharp decrease in ionospheric delay; 4) Data transmission spoofing: The communication link used for data transmission may be attacked and subjected to spoofing interference.

[0024] The risk sources generated at the flight end and the ground end include: 1) Baseline deformation: Due to the deformation of the antenna support structure, the movement of the reference receiver antenna introduces a position error relative to the final contact point; 2) Electromagnetic signal interference: Due to the interference signal generated by the electromagnetic radiation source, the signal integrity is reduced; 3) Power supply interruption: The interruption of the power supply of the data transmission device will cause the navigation service to be interrupted; 4) Antenna calibration deviation: The switching of satellite signals between different antennas, corrosion of the antenna or damage to the array elements will introduce antenna calibration errors; 5) Receiver failure: Failure of the receiver antenna, low-noise amplifier or other modules will cause an increase in the measurement error of the receiver; 6) Multipath: In the case of severe multipath, the reflected signal will cause distortion of the correlation peak of the direct signal, introducing deviation; 7) Cycle slip: Occlusion of the satellite signal, movement of the receiver or too low satellite signal-to-noise ratio will cause the signal to lose lock, and then cause an integer jump in the carrier phase observation value.

[0025] Since the integrity monitoring fault tree model in the dual-moving platform scenario has multiple risk sources from the space segment, the atmosphere segment, and the signal layer, data layer, and information layer at the flight end / ground end. In the architecture design of the dual-moving platform differential satellite guidance system, hardware device technology can be used to mitigate the threat of some risks, including too low signal power, power supply interruption, data transmission spoofing, etc. Similarly, software algorithms such as the wide-narrow lane carrier phase differential two-step relative navigation algorithm can be used to eliminate almost all observation biases except for antenna calibration errors. In summary, most of the risk sources of the dual-moving platform differential satellite guidance can be eliminated through system architecture, hardware design, and navigation algorithm design, but there are still some risk sources that cannot be eliminated and must be monitored in real time, including ephemeris faults, ionospheric storms, reference receiver faults, cycle slips, baseline deformations, and electromagnetic signal interference, etc. The differences in false alarm and missed detection allocation due to different prior failure rates of each risk source need to be fully considered to achieve optimal allocation, so as to achieve real-time evaluation and monitoring.

[0026] In some alternative embodiments, the method for adjusting the prior failure probability of common risk sources: When the two risk sources of the common risk source are completely correlated, take the maximum prior failure probability of the two risk sources as the prior failure probability of the common risk source; When the two risk sources of the common risk source are partially correlated, take the difference between the sum of the prior failure probabilities of the two risk sources and the product of the prior failure probabilities of the two risk sources as the prior failure probability of the common risk source.

[0027] The advantages of this application include: This application optimizes the traditional protection level calculation method, dynamically allocates integrity risks and continuity risks, and preferentially processes high-probability or high-impact risk sources.

[0028] This application combines the usage scenarios of a dual-acting platform, considers the risks in both the ground mobile terminal and the flight terminal, and allocates risks by combining the common risk sources of the ground mobile terminal and the flight terminal. For the differential system of the dual-acting platform, dynamic risk allocation and closed-loop verification are introduced to optimize the real-time monitoring ability in complex environments.

[0029] As described above, the above are only specific embodiments of this application, but the protection scope of this application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed in this application should be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A dual-motion platform differential satellite guidance performance evaluation monitoring threshold calculation method, characterized in that: include: Step S1: Identify risk sources that affect performance in the dual-motion platform differential satellite guidance system, including risk sources that affect the flight end and risk sources that affect the ground mobile end; Step S2: Set the total integrity risk budget, the total continuity risk budget and the reserved budget, and the reserved budget is used as a buffer value for unknown risks; Step S3: respectively obtain the priori failure probability of each risk source, calculate the ratio of the priori failure probability of each risk source to the sum of the priori failure probabilities of all risk sources, distribute the remaining total integrity risk budget and total continuity risk budget to each risk source according to the ratio, and obtain the probability value of the integrity risk and the probability value of the continuity risk of each risk source; Step S4: input the probability value of continuity risk into the inverse function of standard normal distribution for calculation, and multiply the calculation result by the standard deviation of the error under nominal conditions to obtain the nominal error; divide the probability value of integrity risk by the priori failure probability of the risk source to obtain the probability of the system not detecting a fault, and substitute the probability of not detecting a fault into the inverse function of standard normal distribution for calculation, and multiply the calculation result by the standard deviation of the error under the condition of the risk source causing a fault to obtain the fault error; Step S5: sum the nominal error and the fault error to obtain a protection level; Step S6: taking the maximum value of the protection levels of all risk sources as the final protection level of the system; Step S7: taking the final protection level of the system as the alarm threshold.

2. The dual-motion platform differential satellite guidance performance evaluation monitoring threshold calculation method according to claim 1, characterized in that: The risk sources that affect the flight end include: multipath interference, electromagnetic interference and cycle slips; the risk sources that affect the ground mobile end include: baseline deformation, electromagnetic interference, ephemeris error, ionospheric gradient anomaly, receiver failure and multipath interference.

3. The dual-motion platform differential satellite guidance performance evaluation monitoring threshold calculation method as claimed in claim 2, characterized in that: Find out the common risk sources of the risk sources affecting the flight end and the risk sources affecting the ground mobile end, and adjust the priori failure probability of the common risk sources. The adjustment methods include: When the two risk sources of a common risk source are completely correlated, the largest prior failure probability of the two risk sources is taken as the prior failure probability of the common risk source; When two risk sources of a common risk source are partially correlated, the difference between the sum of the prior failure probabilities of the two risk sources and the product of the prior failure probabilities of the two risk sources is taken as the prior failure probability of the common risk source.

4. The dual-motion platform differential satellite guidance performance evaluation monitoring threshold calculation method as claimed in claim 1, characterized in that: The method also includes: Step S8: testing the alarm threshold, and when the alarm frequency is higher than the set frequency upper limit or lower than the set frequency lower limit, jumping to Step S2.

5. The dual-motion platform differential satellite guidance performance evaluation monitoring threshold calculation method as claimed in claim 1, characterized in that: The standard deviation of the error under nominal conditions and the standard deviation of the error under the condition of failure caused by the risk source are determined through fault injection experiments or simulations.

6. The dual-motion platform differential satellite guidance performance evaluation monitoring threshold calculation method according to claim 1, characterized in that: The a priori failure probability of the risk source is obtained through the historical failure data statistics method or the equipment operation parameter modeling method.

Images