Flight program verification method based on integrated navigation system

Abstract

The invention discloses a flight program verification method based on an integrated navigation system, and relates to the technical field of navigation, and the method comprises the steps: simulating a first flight path of an airplane in a preset scene in a simulation system based on a flight program, and setting a plurality of obstacles in the preset scene; the simulation error is injected into a simulation system, corresponding target positions, target postures and target speeds of the aircraft at different moments are calculated through loose integrated navigation, and the target positions, the target postures and the target speeds are fused into a second flight path; calculating a first number of triggered obstacle alarms and a second number of triggered obstacle alarms in a first flight path during operation of the aircraft; and calculating a first average number and a second average number, dividing the second average number by the first average number to obtain a threshold score, and determining that the flight program is qualified when the threshold score is greater than or equal to the target threshold. By means of the technical scheme, the accuracy of verifying the flight program can be improved, and then the safety of the aircraft in the flight process can be improved.

Description

Technical Field

[0001] This invention relates to the field of navigation technology, and more specifically to a flight procedure verification method based on an integrated navigation system. Background Technology

[0002] As the aviation system has gradually matured, performance-based navigation (PBN) has brought revolutionary changes to the aviation industry. Scientific route design and high-precision flight have greatly improved airspace efficiency and ensured flight safety. Flight procedure verification is an important step in ensuring flight safety, used to verify whether the designed route is feasible in actual flight.

[0003] In related technologies, error simulation is achieved by superimposing random noise on a reference trajectory. However, when using this method to simulate and verify flight procedures, the verification results may be inaccurate, thereby reducing the safety of the aircraft during flight. Summary of the Invention

[0004] The purpose of this invention is to provide a flight procedure verification method based on an integrated navigation system to solve the technical problems existing in related technologies.

[0005] To achieve the above objectives, the present invention provides a flight procedure verification method based on an integrated navigation system, comprising:

[0006] Based on the flight program, the simulation system simulates the first flight trajectory of the aircraft in a preset scenario, which includes multiple obstacles.

[0007] Multiple different simulation errors are injected into the simulation system. For each injected simulation error, the following operations are performed in the simulation system: the target position, target attitude and target speed of the aircraft at different times are calculated by sparse combination navigation based on the simulation error. The target position, target attitude and target speed at different times are fused into a second flight trajectory. At the same time, the first number of obstacle alarms triggered by the aircraft during operation and the second number of obstacle alarms triggered on the first flight trajectory are calculated.

[0008] Calculate the first average of multiple first quantities and the second average of multiple second quantities. Divide the second average by the first average to obtain the threshold score. When the threshold score is greater than or equal to the target threshold, the flight procedure is qualified.

[0009] Optionally, the simulation errors include inertial navigation zero bias error, scaling factor error, white noise error, and clock error. The step of calculating the target position, target attitude, and target velocity of the aircraft at different times using sparse combined navigation based on the simulation errors, and fusing the target position, target attitude, and target velocity at different times into a second flight trajectory, includes:

[0010] Based on the inertial navigation zero bias error, scaling factor error, and white noise error, the inertial navigation system in the sparse combined navigation calculates the aircraft's speed, attitude, and position at the first moment, where the first moment can be any one of the different moments.

[0011] The aircraft's second position at the first moment is calculated using the global satellite navigation system in the loosely integrated navigation based on the clock error;

[0012] The velocity, attitude, first position, and second position are processed by Kalman filtering to obtain the error state at the first moment. The velocity, attitude, and first position at the first moment are then optimized based on the error state to obtain the target position, target attitude, and target velocity of the aircraft at the first moment.

[0013] The second flight trajectory is obtained by fusing the target position, target attitude, and target speed of the aircraft at different times.

[0014] Optionally, the step of calculating the aircraft's velocity, attitude, and first position at the first moment using the inertial navigation system in the slack combined navigation based on the inertial navigation zero bias error, scaling factor error, and white noise error includes:

[0015] The aircraft's acceleration and angular velocity at the first moment are obtained through the inertial navigation system. The acceleration is converted to the NED coordinate system to obtain the three-axis acceleration, and the angular velocity is converted to the NED coordinate system to obtain the three-axis angular velocity. The acceleration is obtained by adding the preset acceleration to the inertial navigation zero bias error, the scaling factor error, and the white noise error. The angular velocity is obtained by adding the preset angular velocity to the inertial navigation zero bias error, the scaling factor error, and the white noise error.

[0016] Obtain the initial three-axis velocity, initial three-axis angular velocity, and initial three-axis position of the aircraft at the initial moment;

[0017] The aircraft's velocity at the first moment is calculated using the triaxial acceleration and initial triaxial velocity. The aircraft's first position is calculated using the velocity at the first moment and the initial triaxial position. The aircraft's attitude at the first moment is calculated using the triaxial angular velocity and the initial triaxial angular velocity.

[0018] Optionally, the inertial navigation zero bias error is expressed by the following formula: ; in, For the first moment, For the accelerometer to have zero bias at the first moment, This represents the zero bias of the gyroscope at the first moment. This is the zero bias of the accelerometer at the initial moment. This represents the zero bias of the gyroscope at the initial moment. For the accelerometer zero-bias noise term, This is the zero-bias noise term of the gyroscope. For time infinitesimal elements;

[0019] The scaling factor error is expressed by the following formula: ; in, For the proportional factor error of the accelerometer, The vector diagonal matrix of the accelerometer. It is a triaxial acceleration. The scaling factor error coefficient along the x-axis. The error coefficient is the scaling factor along the y-axis. The scaling factor error coefficient along the z-axis. The acceleration along the x-axis, The acceleration along the y-axis, The acceleration along the z-axis, This is the scaling factor error of the gyroscope. This is the diagonal matrix of the gyroscope's vectors. For triaxial angular velocity, The scaling factor error coefficient along the x-axis. The error coefficient is the scaling factor along the y-axis. The scaling factor error coefficient along the z-axis. The x-axis angular velocity, Angular velocity along the y-axis The z-axis angular velocity;

[0020] The white noise error is expressed by the following formula: ; in, For the white noise of the accelerometer, The white noise of the gyroscope. For the accelerometer noise error along the x-axis, For the accelerometer noise error along the y-axis, For the accelerometer noise error along the z-axis, This refers to the noise error of the gyroscope along the x-axis. This refers to the noise error of the gyroscope along the y-axis. This represents the noise error of the gyroscope along the z-axis.

[0021] Optionally, the step of calculating the aircraft's second position at the first moment using the global satellite navigation system in loosely integrated navigation based on clock errors includes:

[0022] Obtain the position coordinates of the target satellites, the pseudorange between each satellite and the aircraft, and the aircraft's initial position at the first moment;

[0023] A system of sublinear equations is constructed based on the target satellite's position coordinates, pseudorange, first position, and clock error.

[0024] The nonlinear equations are solved to obtain the aircraft's second position at the first moment.

[0025] Optionally, when there are four target satellites, the nonlinear equations are expressed by the following formula: ; in, , , as well as For the satellite's coordinates, As the first position, At the speed of light, For clock error, , , as well as These are the pseudoranges of the corresponding satellites.

[0026] Optionally, the step of processing the velocity, attitude, first position, and second position using the Kalman filter method to obtain the error state at the first moment includes:

[0027] Obtain the accelerometer bias error, gyroscope bias error, measurement model matrix, and measurement noise covariance matrix in the inertial navigation system;

[0028] An initial error state is constructed based on accelerometer bias error, gyroscope bias error, velocity, attitude, first position, and second position. A state transition matrix from the second time moment to the first time moment is constructed based on velocity, attitude, first position, and Earth parameters, where the second time moment is the time moment preceding the first time moment.

[0029] Based on the state transition matrix and the initial error state, predict the prior error state estimate and the prior covariance matrix estimate for the first time step.

[0030] Calculate the Kalman gain based on the measurement model matrix, the measurement noise covariance matrix, and the prior estimate of the covariance matrix;

[0031] The error state at the first time step is calculated using Kalman gain, measurement model matrix, prior error state estimate, residual, and measurement noise covariance matrix. The residual is obtained by subtracting the second position from the first position.

[0032] Optionally, the error state is expressed by the following calculation formula: ; ; ; in, For the prior estimate at the first moment, This is a priori estimate of the covariance matrix at the first time step. Here is the state transition matrix. This is the optimal state estimate for the second time step. This is the optimal covariance matrix estimate for the second time step, where T is the transpose matrix. The process noise covariance matrix is... For residuals, For measuring the model matrix, For Kalman gain, To measure the noise covariance matrix, This represents the error state at the first moment.

[0033] Through the above technical solution, the simulation system simulates the first flight trajectory of the aircraft under a preset scenario based on the flight procedure, and sets multiple obstacles in the preset scenario to test the performance of the flight procedure. For each simulation error input into the simulation system, the target position, target attitude, and target velocity of the aircraft at different times are calculated based on the simulation error using loosely coupled navigation. The target position, target attitude, and target velocity at different times are then fused into a second flight trajectory, which can improve the accuracy of the second flight trajectory estimation. Subsequently, a threshold score for triggering obstacle warnings during aircraft operation can be calculated. When the threshold score is greater than a target threshold, the flight procedure is considered qualified, which can improve the accuracy of verifying the flight procedure and thus improve the safety of the aircraft during flight.

[0034] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0035] Figure 1 This is a schematic diagram illustrating a flight procedure verification method based on an integrated navigation system according to an exemplary embodiment of the present invention.

[0036] Figure 2 This is a schematic diagram illustrating the loosely coupled navigation solution process according to an exemplary embodiment of the present invention.

[0037] Figure 3 This is a schematic diagram illustrating the generation of clock errors according to an exemplary embodiment of the present invention.

[0038] Figure 4 This is a schematic diagram illustrating the arrangement of obstacles according to an exemplary embodiment of the present invention.

[0039] Figure 5 This is a schematic diagram illustrating the simulation process according to an exemplary embodiment of the present invention.

[0040] Figure 6 This is a schematic diagram illustrating a first flight trajectory and an obstacle according to an exemplary embodiment of the present invention.

[0041] Figure 7 This is a schematic diagram illustrating a second flight trajectory according to an exemplary embodiment of the present invention. Detailed Implementation

[0042] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, so as to provide a better understanding of the concept of the present invention, the technical problem solved, the technical features constituting the technical solution, and the technical effects brought about.

[0043] Guided by the navigation system, the aircraft flies from its starting position to its destination along a predetermined route. No physical sensor can avoid errors. The inertial measurement unit (IMU), as a core component of modern navigation systems, calculates the aircraft's attitude, speed, and position by measuring angular velocity and linear acceleration. However, limitations in its internal manufacturing processes and the influence of the operating environment inevitably lead to measurement errors. These errors accumulate over time during integration, causing the accuracy of the navigation calculations to diverge, making it impossible for the aircraft to fly along the prescribed route.

[0044] In related technologies, error simulation is achieved by superimposing random noise onto a reference trajectory, thereby verifying flight procedures. However, the inventors discovered that this method reduces the accuracy of flight procedure verification, thus decreasing the safety of the aircraft during flight missions.

[0045] In view of this, the present invention provides a flight procedure verification method based on an integrated navigation system to solve the technical problems existing in the above-mentioned related technologies.

[0046] like Figure 1 As shown, Figure 1 This is a schematic diagram illustrating a flight procedure verification method based on an integrated navigation system according to an exemplary embodiment of the present invention, with reference to... Figure 1 The method includes;

[0047] S101: Based on the flight program, the first flight trajectory of the aircraft is simulated in the simulation system under a preset scenario, wherein the preset scenario is provided with multiple obstacles;

[0048] S102: Inject multiple different simulation errors into the simulation system. For each injected simulation error, perform the following operations in the simulation system: Based on the simulation error, calculate the target position, target attitude, and target speed of the aircraft at different times using sparse combined navigation. Merge the target position, target attitude, and target speed at different times into a second flight trajectory. At the same time, calculate the first number of obstacle alarms triggered by the aircraft during operation and the second number of obstacle alarms triggered on the first flight trajectory.

[0049] S103: Calculate the first average of multiple first quantities and the second average of multiple second quantities, divide the second average by the first average to obtain the threshold score, and the flight procedure is qualified when the threshold score is greater than or equal to the target threshold.

[0050] Through the above technical solution, the simulation system simulates the first flight trajectory of the aircraft under a preset scenario based on the flight procedure, and sets multiple obstacles in the preset scenario to test the performance of the flight procedure. For each simulation error input into the simulation system, the target position, target attitude, and target velocity of the aircraft at different times are calculated based on the simulation error using loosely coupled navigation. The target position, target attitude, and target velocity at different times are then fused into a second flight trajectory, which can improve the accuracy of the second flight trajectory estimation. Subsequently, a threshold score for triggering obstacle warnings during aircraft operation can be calculated. When the threshold score is greater than a target threshold, the flight procedure is considered qualified, which can improve the accuracy of verifying the flight procedure and thus improve the safety of the aircraft during flight.

[0051] To enable those skilled in the art to better understand the flight procedure verification method based on the integrated navigation system provided by this invention, the above steps are illustrated in detail below.

[0052] For example, the preset scenario can be a mountain scene, a high-altitude scene, a plain scene, etc. The flight program can include various flight data such as the aircraft's speed, altitude, and direction during flight. The simulation error can be the inertial navigation system's zero bias error, scaling factor error, white noise error, and clock error. Among them, the inertial navigation zero bias error is the difference between the measured value output by the sensor and the true value when there is no external force or acceleration; the scaling factor error is the proportional difference between the measured value output by the accelerometer and gyroscope in the sensor and the actual value; the white noise error is a random error with specific statistical characteristics; and the clock error is the error of the global satellite navigation system at the aircraft receiver.

[0053] For example, a simulation system can be used to simulate the entire flight process of an aircraft in a preset scenario. By simulating the entire flight process according to the flight procedure within the simulation system, it can detect potential problems that may arise during flight, thereby ensuring the safety of the aircraft when performing flight missions. In this embodiment of the invention, based on the aircraft's flight procedure in the preset scenario, the simulation system can simulate the first flight trajectory of the aircraft performing the flight mission according to the flight procedure. Simultaneously, multiple obstacles need to be set in the simulation system, which can be used to evaluate the aircraft's performance during actual flight. These obstacles can be set on the first flight trajectory or deviated from it. In this embodiment of the invention, a first number of obstacles are set on the first flight trajectory, and a second number of obstacles are set in areas deviating from the first flight trajectory.

[0054] For example, when simulation errors are injected into the simulation system, different simulation errors can simulate different flight trajectories within the simulation system. A combined navigation system can be a system integrating a global satellite navigation system and an inertial navigation system. The two navigation systems calculate independently and then exchange information through error quantities. The specific calculation process is as follows... Figure 2 As shown. The second flight trajectory can be the flight trajectory that the simulation system simulates the aircraft might execute during actual flight, based on simulation errors.

[0055] In this embodiment of the invention, when the simulation system receives each simulation error, it can fuse the target position, target attitude, and target velocity corresponding to the aircraft at different times into a second flight trajectory based on the simulation error and the target position, target attitude, and target velocity calculated by loosely coupled navigation at different times. After generating the second flight trajectory, the simulation system can simulate the second flight trajectory run by the aircraft during actual flight. At the same time, it can count the first number of obstacles that generate alarms during flight, and determine the second number of obstacles that generate alarms on the first flight trajectory from among the obstacles that generate alarms. Then, it calculates the first average of the multiple first numbers, calculates the second average of the multiple second numbers, and divides the second average by the first average to obtain a threshold score. When the threshold score is greater than or equal to the target threshold, it can be considered that the flight procedure settings are qualified; otherwise, it can be considered that the flight procedure is unqualified and needs to be adjusted and re-verified.

[0056] In possible embodiments, the simulation errors include inertial navigation zero-bias error, scaling factor error, white noise error, and clock error. The step of calculating the target position, target attitude, and target velocity of the aircraft at different times using sparse combined navigation based on the simulation errors, and fusing the target position, target attitude, and target velocity at different times into a second flight trajectory, includes:

[0057] Based on the inertial navigation zero bias error, scaling factor error, and white noise error, the aircraft's speed, attitude, and first position at the first moment are calculated by the inertial navigation system in the sparse combined navigation.

[0058] The aircraft's second position at the first moment is calculated using the global satellite navigation system in the loosely integrated navigation based on the clock error;

[0059] The velocity, attitude, first position, and second position are processed by Kalman filtering to obtain the error state at the first moment. The velocity, attitude, and first position at the first moment are then optimized based on the error state to obtain the target position, target attitude, and target velocity of the aircraft at the first moment.

[0060] The second flight trajectory is obtained by fusing the target position, target attitude, and target speed of the aircraft at different times.

[0061] It should be understood that when simulating an aircraft executing a second flight trajectory in a simulation system, the aircraft's velocity, attitude, and first position at the first moment can be calculated using the inertial navigation system. The inertial navigation zero-bias error, scaling factor error, and white noise error can be used to calculate the acceleration and angle from the sensor measurements in the inertial navigation system. Subsequently, the aircraft's second position at the first moment can be calculated using the global navigation satellite system. This second position can be obtained from clock errors and the pseudorange between the satellite and the aircraft.

[0062] Then, the velocity, attitude, and first position calculated by the inertial navigation system are fused with the second position calculated by the global navigation satellite system using the Kalman filter method to obtain an error state. This error state is used to update and optimize the velocity, attitude, and first position calculated by the inertial navigation system, i.e., to correct the velocity, attitude, and first position, thus obtaining the target position, target attitude, and target velocity of the aircraft at the first moment. At each moment during the aircraft's flight, the target position, target attitude, and target velocity are calculated according to the above steps. Integrating the target position, target attitude, and target velocity from multiple moments yields the second flight trajectory.

[0063] In one possible manner, the calculation of the aircraft's velocity, attitude, and first position at the first moment using the inertial navigation system in loosely integrated navigation based on the inertial navigation zero bias error, scaling factor error, and white noise error includes:

[0064] The aircraft's acceleration and angular velocity at the first moment are obtained through the inertial navigation system. The acceleration is converted to the NED coordinate system to obtain the three-axis acceleration, and the angular velocity is converted to the NED coordinate system to obtain the three-axis angular velocity. The acceleration is obtained by adding the preset acceleration to the inertial navigation zero bias error, the scaling factor error, and the white noise error. The angular velocity is obtained by adding the preset angular velocity to the inertial navigation zero bias error, the scaling factor error, and the white noise error.

[0065] Obtain the initial three-axis velocity, initial three-axis angular velocity, and initial three-axis position of the aircraft at the initial moment;

[0066] The aircraft's velocity at the first moment is calculated using the triaxial acceleration and initial triaxial velocity. The aircraft's first position is calculated using the velocity at the first moment and the initial triaxial position. The aircraft's attitude at the first moment is calculated using the triaxial angular velocity and the initial triaxial angular velocity.

[0067] It should be understood that, in this embodiment of the invention, the aircraft's acceleration at the first moment can be obtained through an accelerometer, and the aircraft's angular velocity at the first moment can be obtained through a gyroscope. Then, the acceleration and angular velocity are converted to the NED (North East Down) coordinate system to obtain the three-axis acceleration and three-axis angular velocity. The preset acceleration can be the acceleration that the aircraft should achieve at a certain moment in the flight program, and the preset angular velocity can be the angular velocity corresponding to the aircraft at a certain moment in the flight program.

[0068] Specifically, gyroscopes and accelerometers are the core sensors in an inertial navigation system. Errors are unavoidable during design, manufacturing, packaging, and use. When there is no actual input, the sensor provides a non-zero output value, which is called the zero bias. Let the initial zero biases of the accelerometer and gyroscope be... , .

[0069] ; ;

[0070] The zero bias of the inertial navigation system (INS) drifts slowly over time. This is because slow changes in ambient temperature cause minute deformations in the support structure, altering its physical properties and leading to output deviation. Furthermore, the sensor's internal circuitry is highly sensitive to the stability of the supply voltage; slow voltage fluctuations cause gradual drift in internal voltage and current parameters, ultimately resulting in zero bias drift as well. Based on the initial zero bias superimposed with a random walk term, the zero bias error of the accelerometer and gyroscope INS at the first moment is recorded. , .

[0071] ; in, For the first moment, For the accelerometer to have zero bias at the first moment, This represents the zero bias of the gyroscope at the first moment. This is the zero bias of the accelerometer at the initial moment. This represents the zero bias of the gyroscope at the initial moment. For the accelerometer zero-bias noise term, This is the zero-bias noise term of the gyroscope. For time infinitesimal elements;

[0072] In practical applications of inertial navigation sensors, due to changes in the operating environment, the proportional relationship between the actual output value and the true input physical quantity is not precise enough. The error caused by the scaling factor is related to the input quantity. Therefore, the scaling factor error is expressed by the following formula: ; in, For the proportional factor error of the accelerometer, The vector diagonal matrix of the accelerometer. It is a triaxial acceleration. The scaling factor error coefficient along the x-axis. The error coefficient is the scaling factor along the y-axis. The scaling factor error coefficient along the z-axis. The acceleration along the x-axis, The acceleration along the y-axis, The acceleration along the z-axis, This is the scaling factor error of the gyroscope. This is the diagonal matrix of the gyroscope's vectors. For triaxial angular velocity, The scaling factor error coefficient along the x-axis. The error coefficient is the scaling factor along the y-axis. The scaling factor error coefficient along the z-axis. The x-axis angular velocity, Angular velocity along the y-axis The z-axis angular velocity.

[0073] White noise is random because the thermal motion of electrons in a conductor is random. Even without an external voltage, random current and voltage fluctuations will occur. The white noise error is expressed by the following formula: ; in, For the white noise of the accelerometer, The white noise of the gyroscope. For the accelerometer noise error along the x-axis, For the accelerometer noise error along the y-axis, For the accelerometer noise error along the z-axis, This refers to the noise error of the gyroscope along the x-axis. This refers to the noise error of the gyroscope along the y-axis. This represents the noise error of the gyroscope along the z-axis.

[0074] The aircraft's speed, initial position, and attitude at the first moment can be expressed by the following formula.

[0075] ; ; in, The speed of the aircraft at the first moment. The initial three-axis velocity, It is a triaxial acceleration. As the first position, Initial three-axis positions, As a gesture, For triaxial angular velocity, The initial triaxial angular velocities are given. The triaxial accelerations are calculated based on the coordinate transformation matrix. The acceleration measured by the sensor is converted into the triaxial angular velocity, which is obtained based on the coordinate transformation matrix. It is obtained by converting the angular velocity measured by the sensor.

[0076] When the triaxial accelerometer is stationary and parallel to the horizontal plane according to the body coordinate system, the accelerometer measures the acceleration due to gravity. The gravity vector is vertically downward and parallel to the load system. Since the axes are merged, the triaxial acceleration can be expressed by the following formula: ;

[0077] The gyroscope is positioned statically and parallel to the horizontal plane according to the machine's coordinate system, ignoring the Earth's rotational angular velocity (default is a low-precision module). Its measurement of the three-axis angular velocity can be expressed by the following formula: .

[0078] In one possible manner, the calculation of the aircraft's second position at a first moment using a global satellite navigation system in loosely integrated navigation based on clock errors includes:

[0079] Obtain the position coordinates of the target satellites, the pseudorange between each satellite and the aircraft, and the aircraft's initial position at the first moment;

[0080] A system of sublinear equations is constructed based on the target satellite's position coordinates, pseudorange, first position, and clock error.

[0081] The nonlinear equations are solved to obtain the aircraft's second position at the first moment.

[0082] It should be understood that, such as Figure 3 As shown, the clock inside the receiver of the aircraft's global navigation satellite system is far less accurate than the atomic clock on the satellite. Its frequency deviates significantly from the satellite system time, affecting subsequent pseudorange measurements and leading to inaccurate positioning. This is known as clock skew.

[0083] In embodiments of the present invention, such as Figure 2 As shown, four target satellites are selected, and their corresponding position coordinates are received through a global satellite signal receiver installed on the aircraft. The corresponding position coordinates are then processed by radio frequency signals. Then, based on the position coordinates of the four target satellites and the position coordinates of the aircraft, a system of linear equations can be constructed using the principle of trilateration. Solving the system of linear equations can yield the second position of the aircraft.

[0084] Specifically, when there are four target satellites, the nonlinear equations are expressed by the following formula: ; in, , , as well as For the satellite's coordinates, As the first position, At the speed of light, For clock error, , , as well as These are the pseudoranges of the corresponding satellites.

[0085] In one possible manner, the process of using a Kalman filter to process the velocity, attitude, first position, and second position to obtain the error state at the first moment includes:

[0086] Obtain the accelerometer bias error, gyroscope bias error, measurement model matrix, and measurement noise covariance matrix in the inertial navigation system;

[0087] An initial error state is constructed based on accelerometer bias error, gyroscope bias error, velocity, attitude, first position, and second position. A state transition matrix from the second time moment to the first time moment is constructed based on velocity, attitude, first position, and Earth parameters, where the second time moment is the time moment preceding the first time moment.

[0088] Based on the state transition matrix and the initial error state, predict the prior error state estimate and the prior covariance matrix estimate for the first time step.

[0089] Calculate the Kalman gain based on the measurement model matrix, the measurement noise covariance matrix, and the prior estimate of the covariance matrix;

[0090] The error state at the first time step is calculated using Kalman gain, measurement model matrix, prior error state estimate, residual, and measurement noise covariance matrix. The residual is obtained by subtracting the second position from the first position.

[0091] It should be understood that the measurement model matrix can be used to describe the relationship between the measured values ​​of aircraft sensors and system state variables. The measurement noise covariance matrix is ​​used to describe the statistical characteristics of sensor measurement noise. Earth parameters may include the north and south pole radii, the equatorial radius, and the Earth's rotational angular velocity.

[0092] The initial error state can be expressed by the following formula: ; in, This is the initial error state. It is the difference between the first position and the second position. The difference between preset speeds, The difference between preset poses, This is the gyroscope bias error. This represents the accelerometer bias error. The preset velocity and preset attitude are the velocity and attitude at the corresponding moments in the flight procedure. Initialization It is a zero vector with a total dimension of 15.

[0093] Specifically, the error state is expressed by the following calculation formula: ; ; ; in, For the prior estimate at the first moment, The prior estimate of the covariance matrix at the first time step can be used to represent the uncertainty about the predicted state. Here is the state transition matrix. This is the optimal state estimate for the second time step. This is the optimal covariance matrix estimate for the second time step, where T is the transpose matrix. The process noise covariance matrix is... For residuals, For measuring the model matrix, Kalman gain is used to characterize the confidence in the measurement during fusion. To measure the noise covariance matrix, This represents the error state at the first moment.

[0094] For example, in this embodiment of the invention, after multiple simulation errors are input into the simulation system, multiple first quantities and second quantities can be obtained. That is, the number of simulation errors corresponds to the number of times the above steps need to be repeated in the simulation system to obtain multiple first quantities and second quantities. A first average quantity is calculated based on the multiple first quantities, and a second average quantity is calculated based on the multiple second quantities. The second average quantity is divided by the first average quantity to obtain a threshold score. The threshold score is compared with a target threshold. If the threshold score is greater than or equal to the target threshold, it indicates that the flight procedure is qualified.

[0095] In actual operation, 10 different simulation errors can be set. Each experiment uses the same motion state for simulation and obstacles are set. When the aircraft is less than the safe distance from the obstacle, an alarm is triggered. The obstacle alarm effect is compared between random noise error modeling and sensor error modeling under the integrated navigation algorithm.

[0096] like Figure 4 As shown, at a certain moment, the black aircraft is in the actual baseline trajectory, the blue aircraft is in the estimated position after error modeling, the red obstacle only triggers the alarm for the aircraft in the actual baseline trajectory, the black obstacle only triggers the alarm for the aircraft in the estimated position, the gray obstacle triggers the alarm for the aircraft in both the actual and estimated positions, and the green obstacle does not trigger the alarm for either the actual or estimated positions.

[0097] like Figure 5 As shown, the simulation process is as follows:

[0098] Step 1: Generate the aircraft's first flight path in a preset scenario based on the flight program. The initial position (longitude, latitude, altitude) is (40.7128, -74.0060, 1000), and the final position is (-73.6335, 35.2256, 6496.7281). Figure 6 , Figure 6In this embodiment, the 3D Flight Trajectory serves as the baseline flight trajectory, which can be the first flight trajectory. Flight Path represents the first flight trajectory, Start is the starting point of the first flight trajectory, End is the ending point of the first flight trajectory, Obstacle represents an obstacle, Longitude is longitude, Latitude is latitude, and Altitude is altitude. In the first stage, the aircraft climbs due east. In the second stage, the aircraft flies horizontally south at 85 m / s. In the third stage, the aircraft descends south. In the fourth stage, the aircraft continues to fly horizontally south at 85 m / s. Ten obstacles are placed in space for experimental evaluation, as shown in Table 1. Obstacles numbered 1-7 are located on the baseline trajectory, while obstacles numbered 8-10 deviate from the actual trajectory.

[0099] Table 1 Obstacle Information .

[0100] Step 2: According to the flight procedure, simulation errors are sequentially injected into the simulation system. After each simulation error is injected, the slack-integrated navigation is used to calculate the target position, target attitude, and target velocity of the aircraft at different times. The target position, target attitude, and target velocity at different times are then fused into a second flight trajectory, as shown below. Figure 7 As shown, Figure 7 In the context of "3D simulation to estimate flight trajectory", the simulated estimated trajectory can be the second flight trajectory in this embodiment. "Estimated Path" is the second flight trajectory, "Flight Path" is the first flight trajectory, "Start" is the starting point of the first flight trajectory, "End" is the ending point of the first flight trajectory, and "Obstacle" is the obstacle.

[0101] Step 3: Based on the obstacles set in the first flight path, calculate the estimated minimum distance d between the trajectory and the obstacles, define a safe distance Ds (150m), and trigger an alarm if the minimum distance is less than the safe distance. Evaluate the effectiveness of the navigation error modeling algorithm based on the probability of triggering the alarm.

[0102] In the evaluation of obstacle alarm results, initial obstacles located on the actual flight path are defined. Obstacles that deviate from the actual flight path are After the pine-based combined navigation algorithm calculates the sensor measurements to generate a second flight trajectory, obstacles are detected. And trigger an alarm. The obstacles that trigger the alarm can be divided into two categories:

[0103] The detected obstacle is on the actual flight path, so the warning is valid. ;

[0104] The detected obstacle deviates from the true flight path, which is a false alarm: ;

[0105] Table 2 Modeling Trajectory's Obstacle Alarm Results .

[0106] Table 2 includes the obstacle alarm situations in 10 experiments for the loose integrated navigation error modeling. The average alarm value of the loose integrated navigation system is 6.8, the average value of correct alarms is 6.6, and the average value of false alarms is 0.2.

[0107] To further measure the performance of missed alarms and correct alarms, evaluate the metrics F1_score, F2_score, and F3_score based on the average values: ;

[0108] Table 3 Error Modeling Scores .

[0109] According to the scoring results in Table 3, when the preset threshold is 0.93, the thresholds of the combined navigation error modeling trajectory for correct alarms are all greater than the preset threshold, meeting the requirements of flight procedure verification, so the flight procedure is qualified.

[0110] Through the above technical solution, for each simulation error input into the simulation system, the sensor measurement values of the aircraft are calculated by the loose integrated navigation according to the simulation error, and the second flight trajectory is generated, which can improve the accuracy of the second flight trajectory estimation. Then, the second flight trajectory of the aircraft running in the preset scenario can be simulated in the simulation system, and at the same time, calculate the threshold score of the aircraft triggering obstacle alarms during the operation. When the threshold score is greater than the target threshold, the flight procedure is qualified, which can improve the accuracy of verifying the flight procedure and further improve the safety of the aircraft during flight.

[0111] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that; they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for flight procedure validation based on a combined navigation system, characterized in that, The method comprises the following steps: simulate a first flight trajectory of an aircraft in a simulation system based on a flight program, wherein the simulation system is set with a plurality of obstacles in a preset scene; inject a plurality of different simulation errors into the simulation system, and for each simulation error, the following operations are performed in the simulation system: calculate the target position, target attitude and target speed of the aircraft at different times according to the simulation error through loose integrated navigation, fuse the target position, target attitude and target speed of the aircraft at different times into a second flight trajectory, and calculate a first number of obstacle alarms triggered by the aircraft during operation and a second number of obstacle alarms triggered on the first flight trajectory; calculate a first average number of the plurality of first numbers and a second average number of the plurality of second numbers, divide the second average number by the first average number to obtain a threshold score, and when the threshold score is greater than or equal to a target threshold, the flight program is qualified.

2. The method of flight procedure verification based on a combined navigation system according to claim 1, characterized in that, The simulation errors include inertial navigation zero bias error, scale factor error, white noise error and clock error, and the calculation of the target position, target attitude and target speed of the aircraft at different times according to the simulation error through loose integrated navigation and the fusion of the target position, target attitude and target speed of the aircraft at different times into a second flight trajectory comprise: calculating the speed, attitude and first position of the aircraft at a first time according to the inertial navigation zero bias error, scale factor error and white noise error through the inertial navigation system in loose integrated navigation, wherein the first time is any one of the different times; calculating the second position of the aircraft at the first time according to the clock error through the global satellite navigation system in loose integrated navigation; processing the speed, attitude, first position and second position through a Kalman filtering method to obtain an error state at the first time, and optimizing the speed, attitude and first position at the first time through the error state respectively to obtain the target position, target attitude and target speed of the aircraft at the first time; fusing the target position, target attitude and target speed of the aircraft at different times to obtain the second flight trajectory.

3. The method of flight procedure verification based on a combined navigation system according to claim 2, characterized in that, The calculation of the speed, attitude and first position of the aircraft at the first time according to the inertial navigation zero bias error, scale factor error and white noise error through the inertial navigation system in loose integrated navigation comprises: obtaining the acceleration and angular velocity of the aircraft at the first time through the inertial navigation system, converting the acceleration to the NED coordinate system to obtain three-axis acceleration, and converting the angular velocity to the NED coordinate system to obtain three-axis angular velocity, wherein the acceleration is obtained by adding a preset acceleration to the inertial navigation zero bias error, scale factor error and white noise error, and the angular velocity is obtained by adding a preset angular velocity to the inertial navigation zero bias error, scale factor error and white noise error; obtaining the initial three-axis speed, initial three-axis angular velocity and initial three-axis position of the aircraft at the initial time; The speed of the airplane at the first time is calculated by the three-axis acceleration and the initial three-axis speed, the first position of the airplane is calculated by the speed of the airplane at the first time and the initial three-axis position, and the attitude of the airplane at the first time is calculated by the three-axis angular speed and the initial three-axis angular speed.

4. The method of flight procedure verification based on a combined navigation system according to claim 3, characterized in that, The inertial navigation zero offset error is expressed by the following calculation formula: ； wherein, is a first time, is a zero offset of the accelerometer at the first time, is a zero offset of the gyroscope at the first time, is a zero offset of the accelerometer at the initial time, is a zero offset of the gyroscope at the initial time, is an accelerometer zero offset noise term, is a gyroscope zero offset noise term, is a time infinitesimal; The scale factor error is expressed by the following calculation formula: ； wherein, is a scale factor error of the accelerometer, is a vector diagonal matrix of the accelerometer, is a three-axis acceleration, is a scale factor error coefficient along the x-axis, is a scale factor error coefficient along the y-axis, is a scale factor error coefficient along the z-axis, is an acceleration along the x-axis, is an acceleration along the y-axis, is an acceleration along the z-axis, is a scale factor error of the gyroscope, is a vector diagonal matrix of the gyroscope, is a three-axis angular velocity, is a scale factor error coefficient along the x-axis, is a scale factor error coefficient along the y-axis, is a scale factor error coefficient along the z-axis, is an angular velocity along the x-axis, is an angular velocity along the y-axis, is an angular velocity along the z-axis; The white noise error is expressed by the following calculation formula: ； wherein, is the white noise of the accelerometer, is the white noise of the gyroscope, is the noise error of the accelerometer along the x-axis, is the noise error of the accelerometer along the y-axis, is the noise error of the accelerometer along the z-axis, is the noise error of the gyroscope along the x-axis, is the noise error of the gyroscope along the y-axis, is the noise error of the gyroscope along the z-axis.

5. The method of flight procedure verification based on a combined navigation system according to claim 2, characterized in that, The second position of the airplane at the first time is calculated according to the clock error by solving the global satellite navigation system in loose combination navigation, comprising: The position coordinates of the target satellites at the first time, the pseudo-range between each satellite and the airplane and the first position of the airplane are acquired; The partial linear equation set is constructed according to the position coordinates of the target satellites, the pseudo-range, the first position and the clock error; The non-linear equation set is solved to obtain the second position of the airplane at the first time.

6. The method of flight procedure verification based on a combined navigation system according to claim 5, characterized in that, When the target satellites are four, the non-linear equation set is expressed by the following calculation formula: ； wherein , , and are coordinates of the satellites, is the first position, is the speed of light, is the clock error, , , and are the pseudo ranges to the corresponding satellites, respectively.

7. The method of flight procedure verification based on a combined navigation system according to claim 2, characterized in that, The speed, the attitude, the first position and the second position are processed by the Kalman filtering method to obtain the error state at the first time, comprising: The accelerometer bias error, the gyroscope bias error, the measurement model matrix and the measurement noise covariance matrix in the inertial navigation system are acquired; The initial error state is constructed based on the accelerometer bias error, the gyroscope bias error, the speed, the attitude, the first position and the second position, and the state transition matrix from the second time to the first time is constructed according to the speed, the attitude, the first position and the earth parameters, wherein the second time is the time before the first time; The prior error state estimation and the covariance matrix prior estimation at the first time are predicted according to the state transition matrix and the initial error state; The Kalman gain is calculated according to the measurement model matrix, the measurement noise covariance matrix and the covariance matrix prior estimation; The error state at the first time is calculated by the Kalman gain, the measurement model matrix, the prior error state estimation, the residual error and the measurement noise covariance matrix, wherein the residual error is obtained by subtracting the first position from the second position.

8. The method of flight procedure verification based on a combined navigation system according to claim 7, characterized in that, The error state is expressed by the following calculation formula: ； ； ； wherein, is a prior estimate of the first time instant, is a prior estimate of the covariance matrix of the first time instant, is a state transition matrix, is an optimal state estimate of the second time instant, is an optimal estimate of the covariance matrix of the second time instant, T is a transpose matrix, is a process noise covariance matrix, is a residual, is a measurement model matrix, is a Kalman gain, is a measurement noise covariance matrix, is an error state of the first time instant.

Images