Method and device for evaluating actual navigation performance of integrated navigation system under DME fault

Abstract

The invention provides a method and a device for evaluating the actual navigation performance of an integrated navigation system under a DME fault, and the method comprises the steps: obtaining measurement information of an aircraft sensor, a one-step state predicted value of an integrated navigation Kalman filter and a filtering measurement matrix, and constructing a measurement residual error of the integrated navigation Kalman filter based on the information; calculating the variance of the integrated navigation Kalman filter according to the measurement residual error; constructing a fault detection function according to the measurement residual error and the variance; detecting the measurement information of the aircraft sensor based on the fault detection function, and when it is judged that the measurement information of the aircraft sensor has DME fault data, enabling the integrated navigation Kalman filter to only perform time updating and taking the one-step prediction covariance matrix as the covariance matrix of the current step for outputting; calculating the position error covariance of the horizontal right-angle system according to the covariance data corresponding to the longitude and latitude in the covariance matrix in the current step, and calculating the actual navigation performance of the integrated navigation system under the DME fault based on the position error covariance.

Description

Technical Field

[0001] This application belongs to the field of flight management technology, and specifically relates to a method and apparatus for evaluating the actual navigation performance of a combined navigation system under DME failure. Background Technology

[0002] Currently, commonly used navigation systems on aircraft include inertial navigation, distance measurement equipment (DME), and GPS navigation. A single navigation system generally cannot meet the specific requirements of an aircraft's Required Navigation Performance (RNP) in terms of accuracy, continuity, integrity, and availability. Therefore, navigation systems with different operating mechanisms are often combined. Inertial navigation is a mainstream autonomous navigation method that does not require receiving or transmitting information and can operate covertly; however, its navigation error gradually increases over time. Distance measurement equipment (DME) is the main tool of short-range ground-based radio navigation systems, offering good long-term stability but being susceptible to interference. Combining inertial navigation and DME can overcome their respective shortcomings, leveraging their strengths and compensating for their weaknesses, and is one of the commonly used methods for airborne combined navigation. When a DME fails, only inertial navigation can be used. Therefore, it is necessary to evaluate the actual navigation performance of the combined navigation system under DME failure. Accurate evaluation of actual navigation performance is crucial for ensuring aviation operational safety and the required navigation performance of the aircraft. In existing technologies, the covariance matrix of integrated navigation Kalman filter is generally derived. However, there is a problem that the measurement data may be faulty and contaminate the covariance matrix, which leads to the problem that the actual navigation performance value calculated by it cannot represent the true navigation performance of the aircraft. Summary of the Invention

[0003] The purpose of this application is to provide a method and apparatus for evaluating the actual navigation performance of a combined navigation system under DME failure, so as to solve or mitigate at least one of the problems in the background art.

[0004] On the one hand, the technical solution of this application is: a method for evaluating the actual navigation performance of a combined navigation system under DME failure, comprising:

[0005] Acquire the measurement information of the aircraft sensors, the one-step state prediction value of the integrated navigation Kalman filter, and the filtering measurement matrix. Construct the measurement residual of the integrated navigation Kalman filter based on the aircraft sensor measurement information, the one-step state prediction value of the integrated navigation Kalman filter, and the filtering measurement matrix.

[0006] The variance of the combined navigation Kalman filter is calculated based on the measurement residuals.

[0007] A fault detection function is constructed based on the measurement residuals and the variance of the combined navigation Kalman filter;

[0008] The measurement information of the aircraft sensor is detected based on the fault detection function. When it is determined that the measurement information of the aircraft sensor contains DME fault data, the integrated navigation Kalman filter is made to only perform time update and output the one-step prediction covariance matrix as the covariance matrix of the current step. When it is determined that there is no DME fault data in the measurement information of the aircraft sensor, the integrated navigation Kalman filter performs normal filtering measurement update.

[0009] The horizontal rectangular system position error covariance is calculated based on the covariance data corresponding to latitude and longitude in the covariance matrix of the current step, and the actual navigation performance of the integrated navigation system under DME failure is calculated based on the position error covariance.

[0010] Furthermore, the method for constructing the measurement residuals of the integrated navigation Kalman filter based on the aircraft sensor measurement information, the one-step state prediction value of the integrated navigation Kalman filter, and the filter measurement matrix is ​​as follows:

[0011] ;

[0012] In the formula, To measure the residual, For measurement information from aircraft sensors, This is the filter measurement matrix. This represents the one-step state prediction value of the integrated navigation Kalman filter.

[0013] Furthermore, the variance of the integrated navigation Kalman filter is calculated based on the measurement residuals as follows:

[0014] ;

[0015] In the formula, The variance of the combined navigation Kalman filter, For the combined navigation Kalman filter, predict the covariance matrix in one step. To measure variance.

[0016] Furthermore, the fault detection function is:

[0017] ;

[0018] in, To obey the degree of freedom m Distribution, where m is the measurement information from the aircraft sensors. The dimension of.

[0019] Furthermore, the method for detecting aircraft sensor measurement information based on fault detection functions is as follows:

[0020]

[0021] In the formula, The detection threshold is set in advance, and the false alarm rate is used as the basis. Sure.

[0022] Furthermore, the calculation of the positional error covariance of the horizontal rectangular system includes:

[0023] The variance of the error in the x-direction is: ;

[0024] The variance of the error in the y-direction is: ;

[0025] In the formula, R, L and σ² L These represent the Earth's radius, the aircraft's latitude, and the variance of the latitudinal direction, respectively.

[0026] Furthermore, the actual navigation performance (ANP) of the integrated navigation system under DME failure is:

[0027] .

[0028] On the other hand, the technical solution provided in this application is: a device for evaluating the actual navigation performance of a combined navigation system under DME failure, comprising:

[0029] The measurement residual calculation module is used to acquire the measurement information of the aircraft sensors, the one-step state prediction value of the integrated navigation Kalman filter, and the filtering measurement matrix, and to construct the measurement residual of the integrated navigation Kalman filter based on the aircraft sensor measurement information, the one-step state prediction value of the integrated navigation Kalman filter, and the filtering measurement matrix.

[0030] The variance calculation module is used to calculate the variance of the integrated navigation Kalman filter based on the measurement residuals.

[0031] The fault detection function construction module is used to construct a fault detection function based on the measurement residual and the variance of the combined navigation Kalman filter.

[0032] The fault detection module is used to detect the measurement information of the aircraft sensors based on the fault detection function. When it is determined that the measurement information of the aircraft sensors contains DME fault data, the integrated navigation Kalman filter will only perform time updates and output the one-step prediction covariance matrix as the covariance matrix of the current step. When it is determined that there is no DME fault data in the measurement information of the aircraft sensors, the integrated navigation Kalman filter will perform filtering measurement updates normally.

[0033] The performance evaluation module is used to calculate the horizontal rectangular system position error covariance based on the covariance data corresponding to latitude and longitude in the covariance matrix of the current step, and to calculate the actual navigation performance of the integrated navigation system under DME failure based on the position error covariance.

[0034] Furthermore, the method for constructing the measurement residuals of the integrated navigation Kalman filter based on the aircraft sensor measurement information, the one-step state prediction value of the integrated navigation Kalman filter, and the filter measurement matrix is ​​as follows:

[0035] ;

[0036] In the formula, To measure the residual, For measurement information from aircraft sensors, This is the filter measurement matrix. This represents the one-step state prediction value of the integrated navigation Kalman filter.

[0037] Furthermore, the variance of the integrated navigation Kalman filter is calculated based on the measurement residuals as follows:

[0038] ;

[0039] In the formula, The variance of the combined navigation Kalman filter, For the combined navigation Kalman filter, predict the covariance matrix in one step. To measure variance.

[0040] Furthermore, the fault detection function is:

[0041] ;

[0042] in, To obey the degree of freedom m Distribution, where m is the measurement information from the aircraft sensors. The dimension of.

[0043] Furthermore, the method for detecting aircraft sensor measurement information based on fault detection functions is as follows:

[0044]

[0045] In the formula, The detection threshold is set in advance, and the false alarm rate is used as the basis. Sure.

[0046] Furthermore, the calculation of the positional error covariance of the horizontal rectangular system includes:

[0047] The variance of the error in the x-direction is: ;

[0048] The variance of the error in the y-direction is: ;

[0049] In the formula, R, L and σ² LThese represent the Earth's radius, the aircraft's latitude, and the variance of the latitudinal direction, respectively.

[0050] Furthermore, the actual navigation performance (ANP) of the integrated navigation system under DME failure is:

[0051] .

[0052] Thirdly, this application provides an airborne device, including:

[0053] One or more processors;

[0054] Memory;

[0055] One or more applications, which are stored in the memory and configured to be executed by the one or more processors, are configured to implement the method for evaluating the actual navigation performance of a combined navigation system under DME failure as described in any of the preceding claims.

[0056] Finally, this application provides a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the method for evaluating the actual navigation performance of a combined navigation system under DME failure as described in any of the preceding claims.

[0057] This application's method for evaluating the actual navigation performance of an integrated navigation system under DME (Device Measurement Equipment) failure introduces measurement data and recursively obtains one-step time update information using a Kalman filter algorithm for the integrated navigation system. The difference between the two data points is then used to construct a fault detection function, which utilizes the chi-square distribution characteristic to detect measurement failures. If a fault is detected, the actual navigation performance is calculated using the time update value, thus achieving a correct evaluation of the actual navigation performance of the integrated navigation system under DME measurement failure conditions. The algorithm structure is simple, eliminating the need to identify the specific cause of the system failure; it only requires determining the validity of a filter output in real time. This is highly practical for system-level fault detection and isolation, and ensures that flight management outputs accurate navigation performance evaluation values. Attached Figure Description

[0058] To more clearly illustrate the technical solutions provided in this application, the accompanying drawings will be briefly described below. Obviously, the drawings described below are merely some embodiments of this application.

[0059] Figure 1 This is a schematic diagram illustrating the actual navigation performance evaluation method for a combined navigation system under DME failure.

[0060] Figure 2This is a schematic diagram of a device for evaluating the actual navigation performance of a combined navigation system under DME failure. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be described in more detail below with reference to the accompanying drawings.

[0062] To address the problem that the actual navigation performance of an inertial navigation and DME integrated navigation system cannot be accurately evaluated when the DME fails, this application provides a method for evaluating the actual navigation performance of an integrated navigation system under DME failure. By changing the Kalman filter algorithm of the integrated navigation system after detecting the DME failure, only the filter time is updated to ensure that the covariance matrix is ​​not contaminated by the DME failure data, thereby correctly evaluating the actual navigation performance.

[0063] like Figure 1 As shown, this application provides a method for evaluating the actual navigation performance of a combined navigation system under DME failure, including the following process:

[0064] Step S1: Obtain the measurement information of the aircraft sensors, the one-step state prediction value of the integrated navigation Kalman filter, and the filtering measurement matrix. Construct the measurement residual of the integrated navigation Kalman filter based on the aircraft sensor measurement information, the one-step state prediction value of the integrated navigation Kalman filter, and the filtering measurement matrix.

[0065] In this application, the one-step state prediction value is based on the integrated navigation Kalman filter. Filter measurement matrix Measurement information from aircraft sensors Construction of measurement residuals for:

[0066] .

[0067] Step S2: Calculate the variance of the integrated navigation Kalman filter based on the measurement residuals.

[0068] In this application, the measurement residuals of the integrated navigation Kalman filter variance A k for:

[0069] ;

[0070] In the formula, For the combined navigation Kalman filter, predict the covariance matrix in one step. To measure variance.

[0071] Step S3, based on the measurement residuals in step S1 And the variance in step S2 is used to construct the fault detection function.

[0072] In this application, the fault detection function is: ;

[0073] in, To obey the degree of freedom m Distribution, where m is the measurement information from the aircraft sensors. The dimension of.

[0074] Step S4: Detect the measurement information of the aircraft sensors based on the fault detection function. When it is determined that the measurement information of the aircraft sensors contains DME fault data, the integrated navigation Kalman filter will only perform time updates and output the one-step prediction covariance matrix as the covariance matrix of this step. When it is determined that there is no DME fault data in the measurement information of the aircraft sensors, the integrated navigation Kalman filter will perform normal filtering measurement updates.

[0075] In this application, the process of detecting aircraft sensor measurement information based on the fault detection function is as follows:

[0076]

[0077] In the formula, The detection threshold is set in advance, and the false alarm rate is used as the basis. Sure.

[0078] When the aircraft sensor measurement information is determined to contain DME fault data, the integrated navigation Kalman filter utilizes... as well as Only time updates are performed, and its output is a one-step prediction covariance matrix. The covariance matrix of the current step : ;

[0079] When it is determined that there is no DME fault data in the aircraft sensor measurement information, use as well as Normal filter measurement updates are performed.

[0080] Step S5, based on the current step covariance matrix in step S4 The covariance data corresponding to the latitude and longitude within the system are used to calculate the horizontal rectangular system position error covariance. Based on this position error covariance, the actual navigation performance of the integrated navigation system under DME failure is calculated.

[0081] In this application, the variance of the x-direction error is: ;

[0082] The variance of the error in the y-direction is: ;

[0083] In the formula, R, L and σ² L These represent the Earth's radius, the aircraft's latitude, and the variance of the latitudinal direction, respectively.

[0084] In this application, the Actual Navigation Performance (ANP) of the integrated navigation system under DME failure is:

[0085] .

[0086] This application's method for evaluating the actual navigation performance of an integrated navigation system under DME (Device Measurement Equipment) failure introduces measurement data and recursively obtains one-step time update information using a Kalman filter algorithm for the integrated navigation system. The difference between the two data points is then used to construct a fault detection function, which utilizes the chi-square distribution characteristic to detect measurement failures. If a fault is detected, the actual navigation performance is calculated using the time update value, thus achieving a correct evaluation of the actual navigation performance of the integrated navigation system under DME measurement failure conditions. The algorithm structure is simple, eliminating the need to identify the specific cause of the system failure; it only requires determining the validity of a filter output in real time. This is highly practical for system-level fault detection and isolation, and ensures that flight management outputs accurate navigation performance evaluation values.

[0087] Based on the above, such as Figure 2 As shown, this application also provides a device for evaluating the actual navigation performance of a combined navigation system under DME failure, the device 100 comprising:

[0088] The measurement residual calculation module 101 is used to acquire the measurement information of the aircraft sensor, the one-step state prediction value of the integrated navigation Kalman filter and the filtering measurement matrix, and to construct the measurement residual of the integrated navigation Kalman filter based on the aircraft sensor measurement information, the one-step state prediction value of the integrated navigation Kalman filter and the filtering measurement matrix.

[0089] The variance calculation module 102 is used to calculate the variance of the combined navigation Kalman filter based on the measurement residuals.

[0090] The fault detection function construction module 103 is used to construct a fault detection function based on the measurement residual and the variance of the combined navigation Kalman filter;

[0091] The fault detection module 104 is used to detect the measurement information of the aircraft sensor based on the fault detection function. When it is determined that the measurement information of the aircraft sensor contains DME fault data, the integrated navigation Kalman filter is made to only perform time update and output the one-step prediction covariance matrix as the covariance matrix of the current step. When it is determined that there is no DME fault data in the measurement information of the aircraft sensor, the integrated navigation Kalman filter performs normal filtering measurement update.

[0092] The performance evaluation module 105 is used to calculate the horizontal rectangular system position error covariance based on the covariance data corresponding to latitude and longitude in the covariance matrix of the current step, and to calculate the actual navigation performance of the integrated navigation system under DME failure based on the position error covariance.

[0093] The processing procedures of each module of the combined navigation system actual navigation performance evaluation device of this application can refer to the above-mentioned method of combined navigation system actual navigation performance evaluation device under DME failure, and will not be repeated here.

[0094] In addition, this application also provides an airborne device, which includes:

[0095] One or more processors;

[0096] Memory;

[0097] One or more applications, which are stored in the memory and configured to be executed by the one or more processors, are configured to implement the method for evaluating the actual navigation performance of a combined navigation system under DME failure as described in any of the preceding claims.

[0098] Finally, this application also provides a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the method for evaluating the actual navigation performance of a combined navigation system under DME failure as described in any of the above claims.

[0099] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for evaluating the actual navigation performance of a combined navigation system under DME failure, characterized in that, include: Acquire the measurement information of the aircraft sensors, the one-step state prediction value of the integrated navigation Kalman filter, and the filtering measurement matrix. Construct the measurement residual of the integrated navigation Kalman filter based on the aircraft sensor measurement information, the one-step state prediction value of the integrated navigation Kalman filter, and the filtering measurement matrix. The variance of the combined navigation Kalman filter is calculated based on the measurement residuals. A fault detection function is constructed based on the measurement residuals and the variance of the combined navigation Kalman filter; The measurement information of the aircraft sensor is detected based on the fault detection function. When it is determined that the measurement information of the aircraft sensor contains DME fault data, the integrated navigation Kalman filter is made to only perform time update and output the one-step prediction covariance matrix as the covariance matrix of the current step. When it is determined that there is no DME fault data in the measurement information of the aircraft sensor, the integrated navigation Kalman filter performs normal filtering measurement update. The horizontal rectangular system position error covariance is calculated based on the covariance data corresponding to latitude and longitude in the covariance matrix of the current step, and the actual navigation performance of the integrated navigation system under DME failure is calculated based on the position error covariance.

2. The method for evaluating the actual navigation performance of a combined navigation system under DME failure as described in claim 1, characterized in that, The method for constructing the measurement residuals of the integrated navigation Kalman filter based on the aircraft sensor measurement information, the one-step state prediction value of the integrated navigation Kalman filter, and the filter measurement matrix is ​​as follows: ； In the formula, To measure the residual, For measurement information from aircraft sensors, This is the filter measurement matrix. This represents the one-step state prediction value of the integrated navigation Kalman filter.

3. The method for evaluating the actual navigation performance of a combined navigation system under DME failure as described in claim 2, characterized in that, The variance of the combined navigation Kalman filter is calculated based on the measured residuals as follows: ； In the formula, The variance of the combined navigation Kalman filter, For the combined navigation Kalman filter, predict the covariance matrix in one step. To measure variance.

4. The method for evaluating the actual navigation performance of a combined navigation system under DME failure as described in claim 3, characterized in that, The fault detection function is: ； in, To obey the degree of freedom m Distribution, where m is the measurement information from the aircraft sensors. The dimension of.

5. The method for evaluating the actual navigation performance of a combined navigation system under DME failure as described in claim 4, characterized in that, The method for detecting aircraft sensor measurement information based on fault detection functions is as follows: In the formula, The detection threshold is set in advance, and the false alarm rate is used as the basis. Sure.

6. The method for evaluating the actual navigation performance of a combined navigation system under DME failure as described in claim 5, characterized in that, The calculation of the positional error covariance of the horizontal rectangular system includes: The variance of the error in the x-direction is: ; The variance of the error in the y-direction is: ; In the formula, R, L and σ² L These represent the Earth's radius, the aircraft's latitude, and the variance of the latitudinal direction, respectively.

7. The method for evaluating the actual navigation performance of a combined navigation system under DME failure as described in claim 6, characterized in that, The actual navigation performance (ANP) of the integrated navigation system under DME failure is: 。 8. A device for evaluating the actual navigation performance of a combined navigation system under DME failure, characterized in that, include: The measurement residual calculation module is used to acquire the measurement information of the aircraft sensors, the one-step state prediction value of the integrated navigation Kalman filter, and the filtering measurement matrix, and to construct the measurement residual of the integrated navigation Kalman filter based on the aircraft sensor measurement information, the one-step state prediction value of the integrated navigation Kalman filter, and the filtering measurement matrix. The variance calculation module is used to calculate the variance of the integrated navigation Kalman filter based on the measurement residuals. The fault detection function construction module is used to construct a fault detection function based on the measurement residual and the variance of the combined navigation Kalman filter. The fault detection module is used to detect the measurement information of the aircraft sensors based on the fault detection function. When it is determined that the measurement information of the aircraft sensors has DME fault data, the integrated navigation Kalman filter will only perform time updates and output the one-step prediction covariance matrix as the covariance matrix of the current step. When it is determined that there is no DME fault data in the measurement information of the aircraft sensors, the integrated navigation Kalman filter will perform normal filtering measurement update. The performance evaluation module is used to calculate the horizontal rectangular system position error covariance based on the covariance data corresponding to latitude and longitude in the covariance matrix of the current step, and to calculate the actual navigation performance of the integrated navigation system under DME failure based on the position error covariance.

9. The device for evaluating the actual navigation performance of a combined navigation system under DME failure as described in claim 8, characterized in that, The method for constructing the measurement residuals of the integrated navigation Kalman filter based on the aircraft sensor measurement information, the one-step state prediction value of the integrated navigation Kalman filter, and the filter measurement matrix is ​​as follows: ； In the formula, To measure the residual, For measurement information from aircraft sensors, This is the filter measurement matrix. This represents the one-step state prediction value of the integrated navigation Kalman filter.

10. The device for evaluating the actual navigation performance of a combined navigation system under DME failure as described in claim 9, characterized in that, The variance of the combined navigation Kalman filter is calculated based on the measured residuals as follows: ； In the formula, The variance of the combined navigation Kalman filter, For the combined navigation Kalman filter, predict the covariance matrix in one step. To measure variance.

11. The device for evaluating the actual navigation performance of a combined navigation system under DME failure as described in claim 10, characterized in that, The fault detection function is: ； in, To obey the degree of freedom m Distribution, where m is the measurement information from the aircraft sensors. The dimension of.

12. The device for evaluating the actual navigation performance of a combined navigation system under DME failure as described in claim 11, characterized in that, The method for detecting aircraft sensor measurement information based on fault detection functions is as follows: In the formula, The detection threshold is set in advance, and the false alarm rate is used as the basis. Sure.

13. The device for evaluating the actual navigation performance of a combined navigation system under DME failure as described in claim 12, characterized in that, The calculation of the positional error covariance of the horizontal rectangular system includes: The variance of the error in the x-direction is: ; The variance of the error in the y-direction is: ; In the formula, R, L and σ² L These represent the Earth's radius, the aircraft's latitude, and the variance of the latitudinal direction, respectively.

14. The device for evaluating the actual navigation performance of a combined navigation system under DME failure as described in claim 13, characterized in that, The actual navigation performance (ANP) of the integrated navigation system under DME failure is: 。 15. An airborne device, characterized in that, include: One or more processors; Memory; One or more applications, which are stored in the memory and configured to be executed by the one or more processors, are configured to implement the method for evaluating the actual navigation performance of a combined navigation system under DME failure as described in any one of claims 1 to 7.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the method for evaluating the actual navigation performance of a combined navigation system under DME failure as described in any one of claims 1 to 7.

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