A civil aircraft inertial satellite integrity performance testing system and method based on a semi-physical testing platform

Abstract

This invention proposes a civil aircraft inertial satellite integrity performance testing system and method based on a semi-physical testing platform, belonging to the field of aviation navigation technology. This method meets the civil aircraft standards for inertial satellite integrity performance testing by simulating flight trajectories, IMU data and error inputs, and satellite data and error inputs to test inertial satellite integrity performance. The test content mainly includes false alarm rate, fault-free accuracy performance, rare normality verification, detection / elimination verification, and integrated taxiing. This method can achieve inertial satellite integrity performance testing and verification that meets civil aircraft standards, enabling the inertial satellite integrated system to obtain airworthiness certification.

Description

Technical Field

[0001] This invention relates to the field of civil aviation navigation technology, and in particular to a civil aircraft inertial satellite integrity performance testing system and method based on a semi-physical testing platform. Background Technology

[0002] With the rapid advancements in civil aviation navigation, civil aviation organizations worldwide are promoting the development of civil aircraft navigation systems, with inertial satellite integrated navigation systems being a crucial component. Inertial navigation systems and satellite navigation systems possess inherent complementary advantages; therefore, inertial satellite integrated navigation systems can provide civil aircraft with more comprehensive performance capabilities.

[0003] The integrity of inertial satellite navigation systems has always been a major concern for the international community and is a crucial indicator for the safety of civil aircraft. Integrity refers to the ability to promptly alert users when deviations occur during flight, encompassing accuracy, continuity, and availability indicators across all flight phases. Since inertial satellite navigation systems are used in civil aircraft, they must meet airworthiness requirements, necessitating testing and verification. Summary of the Invention

[0004] The purpose of this invention is to propose a civil aircraft inertial satellite integrity performance testing system and method based on a semi-physical testing platform, which is used to test the integrity calculation capability of the inertial satellite navigation system to meet the civil aircraft standards.

[0005] The technical solution of this invention: According to a first aspect of this invention, a civil aircraft inertial satellite integrity performance testing system based on a semi-physical testing platform is proposed, applied to the testing of inertial satellite navigation systems, comprising: a flight trajectory simulation module, an IMU data and error input module, a satellite data and error input module, a false alarm rate testing module, a fault-free accuracy performance testing module, a rare normality verification module, a detection / elimination verification module, and an integrated taxiing module; the flight trajectory simulation module is used to simulate and generate the parameters required for flight according to flight requirements; the IMU data and error input module is used to reverse calculate and generate the angular increment and velocity increment output by the sensor according to the parameters required for flight, and simulate the injection of errors to obtain the angular increment and velocity increment containing errors, and convert the angular increment and velocity increment containing errors into digital signals and transmit them to the inertial satellite navigation system; the satellite data and error input module is used to simulate and generate satellite data using broadcast ephemeris according to the parameters required for flight, and simultaneously obtain the error-containing data by introducing a satellite space segment propagation error model. Poor satellite data is converted into radio frequency signals and sent to the inertial satellite navigation system (INS). The INS calculates pseudorange, pseudorange rate, GNSS / IRS combined information, and integrity parameters based on the received erroneous angular and velocity increments and the erroneous satellite data. The false alarm rate test module calculates the false alarm rate based on multiple sets of integrity parameters. The fault-free accuracy performance test module calculates the snapshot 95% horizontal accuracy and inertial satellite filtering accuracy based on multiple sets of GNSS / IRS combined information. The rare normal verification module verifies whether the fault-free rare normal HPL in the integrity parameters can correctly limit the horizontal position error based on the GNSS / IRS combined information and flight-required parameters. The detection / elimination verification module verifies the INS integrity detection / elimination algorithm after injecting a fault into the satellite data and error input module. The integrated coasting module simulates satellite failure and calculates the false alarm rate, missed alarm rate, and failure elimination probability.

[0006] In one possible embodiment, the flight requirements include initial information, flight path, and flight time. The initial information includes initial position, specifically latitude, longitude, and altitude; initial attitude, specifically heading angle, roll angle, and pitch angle; and the flight required parameters include real-time latitude, longitude, altitude, real-time attitude, and real-time time.

[0007] In one possible embodiment, the injection error includes zero bias error, scaling factor error, random walk error, non-orthogonal mounting error, Gaussian white noise error, and first-order Markov process error.

[0008] In one possible embodiment, the satellite space segment propagation error model includes an ionospheric error model, a tropospheric error model, a satellite clock / ephemeris error model, and a receiver noise error model.

[0009] According to a second aspect of the present invention, a method for testing the integrity performance of a civil aircraft inertial satellite based on a semi-physical testing platform is proposed. The method employs the aforementioned civil aircraft inertial satellite integrity performance testing system based on a semi-physical testing platform, and specifically includes the following steps:

[0010] S1: Generates the parameters required for flight based on flight requirements;

[0011] S2: Based on the parameters required for flight, reverse calculation is performed to generate the output information of the sensor, and the injected error is simulated to obtain the angular increment and velocity increment containing the error. The angular increment and velocity increment containing the error are converted into digital signals and transmitted to the inertial satellite navigation system.

[0012] S3: Based on the parameters required for flight, satellite data is generated using broadcast ephemeris. At the same time, satellite data containing errors is obtained by introducing a satellite space segment propagation error model. The satellite data containing errors is converted into radio frequency signals and sent to the inertial satellite navigation system. The satellite data includes pseudorange, pseudorange rate, satellite position, satellite velocity, and number of visible satellites.

[0013] S4: The inertial satellite navigation system calculates GNSS / IRS combined information and integrity parameters based on the received angular and velocity increments containing errors and the satellite data containing errors.

[0014] S5: Repeat steps S1-S4 to obtain multiple sets of GNSS / IRS combination information and integrity parameters;

[0015] S6: Calculate the false alarm rate based on multiple sets of integrity parameters;

[0016] S7: Calculates 95% horizontal accuracy and inertial satellite filtering accuracy of snapshots based on multiple sets of GNSS / IRS combined information;

[0017] S8: Based on the GNSS / IRS combined information and flight-required parameters, verify whether the fault-free rare normal HPL in the integrity parameters can correctly limit the horizontal position error;

[0018] S9: Inject an integrity fault into the satellite data and error input module to verify the effectiveness of the integrity detection / elimination algorithm of the inertial satellite navigation system;

[0019] S10: Simulate the false alarm rate, missed alarm rate, and failure elimination probability under satellite interruption conditions.

[0020] In one possible embodiment, step S6 specifically includes the following steps:

[0021] S61: In step 3, at least 40 sets of satellite data with different geometries are generated;

[0022] S62: For each set of satellite data with different geometries, set the satellite velocity to 0, fly for at least 82,500 hours along a preset flight path, and count the number N times an alarm occurs in the integrity parameters. alarm The sufficiency of the false alarm rate test can be guaranteed by conducting 40×82500 hours of testing; setting a fixed satellite geometry can avoid the impact of satellite observation jumps caused by changes in satellite position, thus ensuring the integrity of the false alarm rate test.

[0023] S63: Calculate the false alarm rate according to the following formula (I). Formula (1), N all This indicates the total number of times the combined navigation is used.

[0024] In one possible embodiment, in step S7, the 95% level accuracy of the snapshot is calculated according to the following formula:

[0025]

[0026] Where, d i The instantaneous two-dimensional horizontal position error (meters) is calculated based on the real-time latitude and longitude and combined information from the parameters required for flight. Where (x1,y1) are the instantaneous latitude and longitude in the parameters required for flight, (x2,y2) are the real-time position information in the combined information; N is the total number of times of combined navigation, and HDOP is the instantaneous horizontal accuracy factor in the combined information.

[0027] In one possible embodiment, in step S7, the inertial satellite filtering accuracy is calculated using the following formula based on the inertial satellite navigation system combined filter:

[0028] Where, p 11 p 22 Let P be the covariance matrix in Kalman filtering.

[0029] In one possible embodiment, step S8 specifically includes the following steps:

[0030] S81: Calculate the horizontal position error based on the real-time latitude, longitude, and altitude information and their combination from the parameters required for flight. Where (x1,y1) represents the instantaneous latitude and longitude in the parameters required for flight, and (x2,y2) represents the real-time location information in the combined information;

[0031] S82: Compare HPL with HEL based on the integrity parameter;

[0032] S83: If HPL > HEL, the fault - free rare normal HPL (H0) can correctly limit the horizontal position error; otherwise, the fault - free rare normal HPL (H0) cannot correctly limit the horizontal position error.

[0033] In a possible embodiment, in the step S9, it specifically includes the following steps:

[0034] S91: Inject integrity faults into the satellite data and error input module in the pseudorange domain. The integrity faults are divided into integrity step faults and integrity ramp faults.

[0035] S92: The integrity parameters are calculated by the inertial satellite navigation system. If HPL > HAL in the integrity parameters, it indicates that a fault in the satellite space segment signal is currently detected. Here, HAL is the horizontal alert limit for the current flight route phase, which is uniformly specified by the International Civil Aviation Organization.

[0036] S93: Test and verify the performance of the standard receiver autonomous integrity monitoring (RAIM). The standard RAIM algorithm built in the detection / exclusion verification module excludes the faults and calculates the HPL after the faults are excluded. RAIM ;

[0037] S94: The inertial satellite navigation system calculates the HPL after the faults are excluded. FD ;

[0038] S95: After the faults are excluded, calculate the current HEL FD , where, (x1, y1) is the instantaneous longitude and latitude in the flight - required parameters, and (x2, y2) is the real - time position information in the combined information after the faults are excluded.

[0039] S96: Compare HEL FD , HPL RAIM , HPL FD and HAL. If HEL FD < HPL FD < HPL RAIM < HAL, it indicates that the integrity fault detection and exclusion algorithm in the tested device is effective.

[0040] In a possible embodiment, in the step S10, it specifically includes the following steps:

[0041] S101: Generate satellite data with at least two different geometric structures in the step 3. In each scenario, remove enough visible satellites so that the number of visible satellites is less than 4, ensuring that the inertial satellite navigation system is in a coasting state.

[0042] S102: For each type of taxiing geometry, at least 1650 tests must be conducted to count the number of false alarms, missed alarms, and failed troubleshooting attempts.

[0043] S103: Calculate the false alarm rate, false alarm rate, and failure rejection probability; false alarm rate, False alarm rate Failure exclusion probability, Where, N fa N represents the number of alarms when there is no fault. md N represents the number of times no alarms were triggered when a fault occurred. fd N represents the number of times a fault occurs and troubleshooting fails. all This represents the total number of trials.

[0044] The beneficial technical effects of this invention are as follows: This invention proposes a civil aircraft inertial satellite integrity performance testing system based on a semi-physical testing platform, which can provide a physical platform and system architecture for integrity algorithm testing. Simultaneously, this invention proposes a complete method for testing the integrity performance of civil aircraft inertial satellites, filling the current gap in comprehensive testing methods for the integrity performance of civil aircraft inertial satellites and meeting the integrity testing requirements and airworthiness requirements for civil aircraft inertial satellites. Attached Figure Description

[0045] To more clearly illustrate the technical solutions implemented in this invention, a simple explanation of the accompanying drawings used in the description of this invention will be provided below. Obviously, the drawings described below are merely some embodiments of this invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0046] Figure 1 This is a schematic diagram of the process for testing the integrity performance of a civil aircraft inertial satellite based on a semi-physical testing platform according to the present invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] The features of various aspects of the embodiments of the present invention will now be described in detail. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that the invention can also be practiced without these specific details. The following description of the embodiments is merely intended to provide a better understanding of the invention by illustrating examples. The invention is not limited to any specific setups and methods provided below, but covers all improvements, substitutions, etc., to product structures and methods without departing from the spirit of the invention. In the various drawings and the following description, well-known structures and techniques are not shown to avoid unnecessarily obscuring the invention.

[0049] It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other, and the various embodiments can be referenced and cited in each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0050] Example 1

[0051] The method may include the following steps:

[0052] Step 1: Set initial information: initial position (33.48°, 108.5°, 80m); initial attitude (90°, 0°, 0°); flight path: Xi'an—Shanghai; flight time: 2 hours; obtain the required flight parameters, including real-time latitude and longitude, real-time attitude, and real-time time.

[0053] Step 2: Calculate the sensor output information. Based on the simulated flight trajectory, reverse calculate and generate the sensor output information and simulate the sensor error input.

[0054] Step 3: Generate the sensor output information, including the angular increment output by the three-axis gyroscope and the linear velocity increment output by the three-axis accelerometer;

[0055] Step 4: Simulate sensor error input. Deterministic errors include constant zero bias of the gyroscope and accelerometer, non-orthogonal mounting error, and scaling factor error; random errors include random walk error of the gyroscope and accelerometer, and one-section Markov process error.

[0056] Step 5: Generate satellite data for the simulated time using broadcast ephemeris; simultaneously, simulate satellite errors using a model.

[0057] Step 6: Satellite data includes pseudorange, pseudorange rate, satellite position, satellite velocity, and number of visible satellites;

[0058] Step 7: Satellite errors include ionospheric errors, tropospheric errors, satellite ephemeris and clock errors, and receiver errors;

[0059] Step 8: The ionospheric error model is the International Reference 2001 (IRI-2001) model;

[0060] Step 9: The tropospheric error model is a first-order Gaussian Markov process with a correlation time of 30 minutes;

[0061] Step 10: The satellite ephemeris clock error model is a first-order Gaussian Markov process with a 2-hour correlation time and σ = 2m;

[0062] Step 11, the receiver error model is as follows: σ multipath [i] = 0.13 + 0.53e (-θ[i] / 10deg) θ[i] is the elevation angle of the i-th satellite; this model is applicable to satellite elevation angles greater than 5°.

[0063] Step 12: The inertial satellite navigation system calculates the GNSS / IRS combined information and integrity parameters based on the received angular and velocity increments containing errors and the satellite data containing errors.

[0064] Step 13: Repeat steps 1-12 to obtain multiple sets of GNSS / IRS combination information and integrity parameters;

[0065] Step 14, False Alarm Rate Test: The false alarm rate in the integrity performance of the inertial satellite is tested.

[0066] Step 15: In step 13, 40 different geometries are generated, each of which simulates a total runtime of N = 82,500 hours.

[0067] Step 16: For each set of satellite data with different geometries, set the satellite velocity to 0 and fly for at least 82,500 hours in the preset flight trajectory;

[0068] Step 17: Count the total number of false alarms. The total number of alarms on all allowed geometries is 32. For each allowed geometry, there must be no more than 1 alarm.

[0069] Step 18, calculate the false alarm rate as 2.6e-9;

[0070] Step 19, Fault-free accuracy performance test, including the snapshot 95% horizontal accuracy test and inertial satellite filtering test;

[0071] Step 20, Snapshot 95% horizontal accuracy test, The precision statistic is 2drms1 = 8m;

[0072] Step 21: Compare the accuracy statistic 2drms1 with the accuracy of the corresponding route stage. 2drms1 < 16m, which meets the accuracy requirements.

[0073] Step 22, inertial satellite filter test, should be conducted according to the 2 drms² accuracy limit provided by the combined filter. Where, p 11 p 22 The covariance matrix P in Kalman filtering; 2drms² = 6m;

[0074] Step 23, 2drms2 < 16m, which meets the accuracy requirements;

[0075] Step 24, Rare Normal Verification, can be performed simultaneously with the False Alarm Rate Test to verify that the fault-free rare normal HPL(H0) correctly limits the horizontal position error.

[0076] Step 25: Calculate the horizontal position error based on the real-time latitude, longitude, and altitude information and their combination from the parameters required for flight. Among them, (x1,y1) is the instantaneous latitude, longitude, and altitude in the parameters required for flight, and (x2,y2) is the real-time position information in the combined information; thus, HEL = 7.63m is obtained;

[0077] Step 26: Compare HPL with HEL based on the integrity parameter; integrity parameter HPL = 10.5m;

[0078] Step 27, HPL>HEL, no fault, rare normal HPL(H0) can correctly limit horizontal position error;

[0079] Step 28, Detection / Rejection Verification: Test and verify the integrity fault detection algorithm and rejection algorithm;

[0080] Step 29: Inject an integrity step fault into the pseudorange domain of the satellite data and error input module;

[0081] Step 30: The integrity parameters are calculated by the inertial satellite navigation system, and HPL is calculated to be 20m. The International Civil Aviation Organization (ICAO) uniformly stipulates that HAL during the LPV-200 approach phase is 16m; if HPL > HAL in the integrity parameters, it indicates that there is a fault in the satellite space segment signal, and fault detection and troubleshooting are performed.

[0082] Step 31: Test and verify the performance of the standard RAIM algorithm by troubleshooting the fault and calculating the HPL after troubleshooting. RAIM =15m;

[0083] Step 32: The inertial satellite navigation system calculates the HPL after the fault has been cleared. FD =9.8m;

[0084] Step 33: After troubleshooting, calculate the current HEL. FD , Among them, (x1, y1) is the instant longitude, latitude and altitude in the parameters required for flight, and (x2, y2) is the real-time position information in the combined information after troubleshooting; HEL FD = 5.6m;

[0085] Step 34, compare HEL FD , HPL RAIM , HPL FD and HAL. If HEL FD < HPL FD < HPL RAIM < HAL, it indicates that the integrity fault detection and troubleshooting algorithm in the tested device is effective;

[0086] Step 35, integrated coasting test, test and verify the false alarm rate, missed alarm rate and failure troubleshooting probability during GNSS interruption;<00002​​​​​​​​​​​​​​​​​​​​

Claims

1. A civil aircraft inertial satellite integrity performance testing system based on a semi-physical testing platform, applied to the testing of inertial satellite navigation systems, characterized in that, include: The system includes a flight trajectory simulation module, an IMU data and error input module, a satellite data and error input module, a false alarm rate testing module, a fault-free accuracy performance testing module, a rare normal verification module, a detection / elimination verification module, and an integrated taxiing module. The flight trajectory simulation module simulates and generates the required flight parameters based on flight requirements. The IMU data and error input module reverse-engineers the required flight parameters to generate the angular and velocity increments output by the sensors, and simulates the injection of errors to obtain angular and velocity increments containing the errors. These angular and velocity increments containing the errors are then converted into digital signals and transmitted to the inertial sensor. The satellite navigation system includes a satellite data and error input module. This module simulates and generates satellite data using broadcast ephemeris parameters based on flight requirements. Simultaneously, it introduces a satellite space segment propagation error model to obtain error-laden satellite data, which is then converted into radio frequency signals and transmitted to the inertial satellite navigation system. The inertial satellite navigation system calculates pseudorange, pseudorange rate, GNSS / IRS combined information, and integrity parameters based on the received error-laden angular and velocity increments and the error-laden satellite data. The false alarm rate testing module is used to statistically calculate the false alarm rate based on multiple sets of integrity parameters. The fault-free accuracy... The testing module is used to calculate the 95% horizontal accuracy and inertial satellite filtering accuracy of the snapshot based on multiple sets of GNSS / IRS combined information; the rare normal verification module is used to verify whether the fault-free rare normal HPL in the integrity parameters can correctly limit the horizontal position error based on the GNSS / IRS combined information and flight-required parameters; the detection / elimination verification module is used to verify the integrity detection / elimination algorithm of the inertial satellite navigation system after injecting a fault into the satellite data and error input module; the integrated coasting module is used to simulate the satellite failure state and calculate the false alarm rate, missed alarm rate, and failure elimination probability. The flight requirements include initial information, flight path, and flight time. The initial information includes initial position, specifically latitude, longitude, and altitude; initial attitude, specifically heading angle, roll angle, and pitch angle; the required flight parameters include instantaneous latitude, longitude, altitude, instantaneous attitude, and instantaneous time; the injected errors include zero bias error, scaling factor error, random walk error, non-orthogonal installation error, Gaussian white noise error, and first-order Markov process error; the satellite space segment propagation error model includes ionospheric error model, tropospheric error model, satellite clock / ephemeris error model, and receiver noise error model.

2. A method for testing the integrity performance of civil aircraft inertial satellites based on a semi-physical testing platform, employing the civil aircraft inertial satellite integrity performance testing system based on a semi-physical testing platform as described in claim 1, characterized in that... Specifically, the steps include the following: S1: Generates the parameters required for flight based on flight requirements; S2: Based on the parameters required for flight, reverse calculation is performed to generate the output information of the sensor, and the injected error is simulated to obtain the angular increment and velocity increment containing the error. The angular increment and velocity increment containing the error are converted into digital signals and transmitted to the inertial satellite navigation system. S3: Based on the parameters required for flight, satellite data is generated using broadcast ephemeris. At the same time, satellite data containing errors is obtained by introducing a satellite space segment propagation error model. The satellite data containing errors is converted into radio frequency signals and sent to the inertial satellite navigation system. The satellite data includes pseudorange, pseudorange rate, satellite position, satellite velocity, and number of visible satellites. S4: The inertial satellite navigation system calculates GNSS / IRS combined information and integrity parameters based on the received angular and velocity increments containing errors and the satellite data containing errors. S5: Repeat steps S1-S4 to obtain multiple sets of GNSS / IRS combination information and integrity parameters; S6: Calculate the false alarm rate based on multiple sets of integrity parameters; S7: Calculates 95% horizontal accuracy and inertial satellite filtering accuracy of snapshots based on multiple sets of GNSS / IRS combined information; S8: Based on the GNSS / IRS combined information and flight-required parameters, verify whether the fault-free rare normal HPL in the integrity parameters can correctly limit the horizontal position error; Step S8 specifically includes the following steps: S81: Calculate the horizontal position error based on the real-time latitude, longitude, and altitude information and their combination from the parameters required for flight. ,in, For the instant latitude and longitude of the parameters required for flight, This refers to real-time location information within the combined information; S82: Based on the integrity parameters ,and Compare; S83: If If the fault-free rare normal HPL (H0) is true, then the horizontal position error can be correctly limited; otherwise, the fault-free rare normal HPL (H0) cannot be correctly limited. S9: Inject an integrity fault into the satellite data and error input module to verify the effectiveness of the integrity detection / elimination algorithm of the inertial satellite navigation system; Step S9 specifically includes the following steps: S91: Inject integrity faults into the pseudorange domain of the satellite data and error input module. Integrity faults are divided into integrity step faults and integrity ramp faults. S92: The integrity parameters are calculated by the inertial satellite navigation system. If the integrity parameters include... This indicates that a fault has been detected in the current satellite space segment signal; among which, The horizontal warning limits for the current flight route phase are uniformly stipulated by the International Civil Aviation Organization. S93: Test and verify the standard receiver's autonomous integrity monitoring (RAIM) performance. The standard RAIM algorithm built into the detection / removal verification module removes faults and calculates the results after fault removal. ; S94: After the fault is eliminated, the inertial satellite navigation system calculates the solution. ; S95: After troubleshooting, calculate the current... , ,in, For the instant latitude and longitude of the parameters required for flight, This is to include real-time location information in the combined information after troubleshooting; S96: Comparison , , and ,like < < < This indicates that the integrity fault detection and elimination algorithm in the tested equipment is effective; S10: Simulate the false alarm rate, missed alarm rate, and failure elimination probability under satellite interruption conditions.

3. The method for testing the integrity performance of civil aircraft inertial satellites based on a semi-physical testing platform according to claim 2, characterized in that, Step S6 specifically includes the following steps: S61: In step 3, at least 40 sets of satellite data with different geometries are generated; S62: For each set of satellite data with different geometries, set the satellite velocity to 0, fly for at least 82,500 hours along a preset flight path, and count the number of alarms that occur in the integrity parameters. ; S63: Calculate the false alarm rate according to the following formula (I). Formula (1) This indicates the total number of times the combined navigation was performed.

4. The method for testing the integrity performance of civil aircraft inertial satellites based on a semi-physical testing platform according to claim 2, characterized in that, In step S7, the 95% horizontal accuracy of the snapshot is calculated according to the following formula: in, The instantaneous two-dimensional horizontal position error (meters) is given. The number of sampling points. This is the instantaneous horizontal precision factor.

5. The method for testing the integrity performance of civil aircraft inertial satellites based on a semi-physical testing platform according to claim 2, characterized in that, In step S7, the inertial satellite filtering accuracy is calculated using the following formula based on the inertial satellite navigation system combined filter: ,in, , Covariance matrix in Kalman filtering Formation.

6. The method for testing the integrity performance of civil aircraft inertial satellites based on a semi-physical testing platform according to claim 2, characterized in that, Step S10 specifically includes the following steps: S101: In step 3, generate satellite data with at least two different geometries. In each scenario, remove enough visible satellites so that the number of visible satellites is less than 4, to ensure that the inertial satellite navigation system is in a gliding state. S102: For each type of taxiing geometry, at least 1650 tests must be conducted to count the number of false alarms, missed alarms, and failed troubleshooting attempts. S103: Calculate the false alarm rate, false alarm rate, and failure rejection probability; false alarm rate, ; false alarm rate Failure exclusion probability, ;in, This represents the number of alarms that occurred when there were no faults. This represents the number of times no alarms were triggered when a fault occurred. This represents the number of times a fault occurred and troubleshooting failed. This represents the total number of trials.

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