Method and device for verifying low-altitude flight by means of an aircraft autopilot system, computer device and medium

Abstract

Embodiments of the present application provide a verification method and device for maintaining low altitude flight by an automatic flight system of an airplane, computer equipment and a medium, wherein the method comprises the following steps: simulating a wave surface of a sea wave according to sea conditions borne by the automatic flight system of the airplane when performing sea low altitude cruising, generating a sea wave model, and calculating statistical characteristics of the sea wave containing environmental noise through the sea wave model; determining filter coefficients and filter orders, constructing a sea wave filter through the filter coefficients and the filter orders, inputting the statistical characteristics of the sea wave containing the environmental noise into the sea wave filter, and generating filtered sea wave statistical characteristics; and inputting basic parameters, meteorological data and the filtered sea wave statistical characteristics into the automatic flight system of the airplane, and verifying whether the airplane can maintain low altitude flight through the automatic flight system of the airplane. The scheme simulates low altitude flight through the automatic flight system of the airplane, and improves the stability of sea low altitude flight.

Description

Technical Field

[0001] This invention relates to the field of aircraft autopilot technology, and in particular to a verification method, apparatus, computer equipment, and medium for maintaining low-altitude flight through an aircraft autopilot system. Background Technology

[0002] In real-world applications of transport aircraft, a unique requirement for low-altitude automatic flight control is frequently encountered. This technology primarily involves precise hold-up maneuvers within a specific radio altitude range, particularly at altitudes of approximately 100 meters above sea level, necessitating extended periods of automatic cruise control. Furthermore, this technology demands coordinated turning capabilities to ensure agility and stability in complex flight environments. To meet these requirements, the autopilot system design must incorporate corresponding control laws. These laws must not only precisely filter radio altitude signals but also effectively filter out wave interference in the low-altitude sea environment. The aim is to ensure that in the event of unforeseen circumstances, the system can respond rapidly and automatically pull the aircraft to a safe altitude, thereby guaranteeing flight safety.

[0003] To address the issue that radio altitude sensors are susceptible to wave interference during low-altitude, low-speed flight, and the relative motion between the aircraft and the waves, the observation of waves from the aircraft depends on its speed and direction. Considering the special case of flying into the waves, this study investigates the impact of waves on flight in the time domain and transforms the spectral characteristics in the frequency domain into an equivalent wave height time series. There is an urgent need for a method to combine sensor signals for wave filtering and integrate it into the altitude-holding control mode to enable the autopilot system to achieve long-term automatic low-altitude cruise flight. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a verification method for maintaining low-altitude flight through an aircraft autopilot system, to solve the technical problem that low-altitude automatic flight control cannot be achieved in the prior art. The method includes: Based on the sea conditions encountered by the aircraft's autopilot system during low-altitude cruise over the sea, the wave surface of the ocean is simulated to generate an ocean wave model. The statistical characteristics of the ocean waves, including environmental noise, are then calculated using the ocean wave model. Determine the filter coefficients and filter order, construct a wave filter using the filter coefficients and filter order, input the statistical characteristics of the waves containing environmental noise into the wave filter, and generate filtered wave statistical characteristics. The aircraft's basic parameters and meteorological data are obtained from an external system. The basic parameters, meteorological data, and filtered wave statistical characteristics are then input into the aircraft's autopilot system. The autopilot system is used to verify whether the aircraft can maintain a low altitude for flight.

[0005] This invention also provides a verification device for maintaining low-altitude flight via an aircraft autopilot system, thereby addressing the technical problem that existing technologies cannot achieve low-altitude automatic flight control. The device includes: The wave model construction module is used to simulate the wave surface of the waves based on the sea conditions encountered by the aircraft autopilot system during low-altitude cruise over the sea, generate a wave model, and calculate the statistical characteristics of the waves including environmental noise through the wave model. The wave filtering module is used to determine the filter coefficients and the filter order, construct a wave filter using the filter coefficients and the filter order, input the statistical characteristics of the waves containing environmental noise into the wave filter, and generate the filtered wave statistical characteristics. The low-altitude flight verification module is used to acquire basic parameters and meteorological data of the aircraft from an external system, and input the basic parameters, the meteorological data and the filtered sea wave statistical characteristics into the aircraft autopilot system to verify whether the aircraft can maintain a low altitude for flight. This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-mentioned verification methods for maintaining low-altitude flight through an aircraft autopilot system, thereby solving the technical problem that low-altitude automatic flight control cannot be achieved in the prior art.

[0006] This invention also provides a computer-readable storage medium storing a computer program that executes any of the above-described verification methods for maintaining low-altitude flight via an aircraft autopilot system, thereby solving the technical problem that low-altitude automatic flight control cannot be achieved in the prior art.

[0007] Compared with the prior art, the beneficial effects that at least one technical solution adopted in the embodiments of this specification can achieve include at least: By simulating low-altitude flight using the aircraft's autopilot system, the stability of low-altitude flight over the sea has been improved. Attached Figure Description

[0008] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 This is a flowchart of a verification method for maintaining low-altitude flight through an aircraft autopilot system, provided by an embodiment of the present invention. Figure 2 This is a schematic diagram of the wave spectrum according to an embodiment of the present invention; Figure 3 This is a frequency response diagram of the digital elliptic filter according to an embodiment of the present invention; Figure 4 This is a structural diagram of a semi-physical simulation system according to an embodiment of the present invention; Figure 5 This is a structural block diagram of a computer device provided in an embodiment of the present invention; Figure 6 This is a structural block diagram of a verification device for maintaining low-altitude flight through an aircraft autopilot system, provided in an embodiment of the present invention. Detailed Implementation

[0010] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0011] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0012] In this embodiment of the invention, a verification method for maintaining low-altitude flight through an aircraft autopilot system is provided, such as... Figure 1 As shown, the method includes: Step S101: Based on the sea conditions encountered by the aircraft autopilot system during low-altitude cruise over the sea, simulate the wave surface of the sea waves to generate a wave model, and calculate the statistical characteristics of the sea waves including environmental noise through the wave model. Step S102: Determine the filter coefficients and filter order, construct a wave filter using the filter coefficients and filter order, input the statistical characteristics of the waves containing environmental noise into the wave filter, and generate filtered wave statistical characteristics. Step S103: Obtain the aircraft's basic parameters and meteorological data from an external system, input the basic parameters, the meteorological data, and the filtered wave statistical characteristics into the aircraft's autopilot system, and verify whether the aircraft can maintain a low altitude for flight through the aircraft's autopilot system.

[0013] In practice, the following steps are used to simulate the wave surface of the ocean waves and generate a wave model based on the sea conditions encountered by the aircraft's autopilot system during low-altitude cruise over the sea: Construct independent random sine waves, n After superimposing several independent random sinusoidal waves, the vertical displacement ζ(t) of the constituent waves at a fixed point on the sea surface is obtained, where... , t For time, a n The amplitude that makes up the wave, ω n The frequency that makes up the wave, ε n The initial phase that makes up the wave, n The number of random sine waves in the constituent wave; Construct the variance of the vertical displacement ζ(t) The first formula for calculating variance is given by, where, , S ( ω The vertical displacement ζ(t) represents the wave direction spectrum; the vertical displacement ζ(x,y,t) of the wave surface surrounding a fixed point (x,y) on the sea surface is constructed using the vertical displacement ζ(t), where, (x, y) are the coordinates of a fixed point on the sea surface. θ n The angle between the propagation direction of the wave and the wind direction is used; the variance of the vertical displacement ζ(x,y,t) is constructed using the first variance calculation formula. The second variance calculation formula is used to obtain the wave direction spectrum S(ω, y,t) of the vertical displacement ζ(x,y,t). θ ),in, Construct the wave direction spectrum relationship between the vertical displacements ζ(x,y,t) of two random component waves. According to the wave direction spectrum S ( ω The wave direction spectrum S(ω, θA wave model is constructed using the wave direction spectrum relationship; environmental noise is determined and added to the wave model.

[0014] In practice, the following steps are used to determine the environmental noise and add it to the wave model: Sensor noise, environmental interference noise, and platform-related noise are considered as environmental noise. Statistical characteristic analysis is performed on each type of environmental noise to determine its statistical distribution and power spectral density. Based on the statistical distribution of the noise, the sensor noise, environmental interference noise, and platform-related noise are synthesized in the time domain to generate a first synthesized noise. Based on the power spectral density of the noise, the sensor noise, environmental interference noise, and platform-related noise are synthesized in the frequency domain to generate a second synthesized noise. The first synthesized noise and the second synthesized noise are added to the wave model.

[0015] In specific implementation, the statistical characteristics of ocean waves, including environmental noise, are calculated using the aforementioned wave model through the following steps: The wave direction spectrum of the wave model S ( ω Constructing the zeroth moment of the wave spectrum ,in, ; through the zeroth moment Sum-wave high gain coefficient A The effective wave height was calculated. ,in, The effective wave height As a statistical characteristic of ocean waves that include environmental noise.

[0016] In practice, the type of wave filter is determined through the following steps: The wave filter is a digital low-pass elliptic filter, and the filter transfer function of the digital low-pass elliptic filter is... ,in, and These are the filter coefficients. k Let the filter order be . X ( z ) represents the z-transform of the input signal. Y ( z ) represents the z-transform of the output signal, where z is a complex frequency variable.

[0017] In specific implementation, the following steps are used to obtain the aircraft's basic parameters and meteorological data from an external system, input the basic parameters, the meteorological data, and the filtered sea wave statistical characteristics into the aircraft's autopilot system, and verify whether the aircraft can maintain low-altitude flight through the autopilot system: The system obtains basic parameters such as throttle and flight configuration from external systems, and wind parameters from external sensors based on meteorological data. These parameters, along with the filtered wave statistics, are input into the altitude-keeping mode of the autopilot system. The autopilot system then performs mathematical and dynamic semi-physical simulations to output control surface motion. This control surface motion is input to actuators, which control the aircraft to perform low-altitude flight. External sensors feed back flight speed and attitude information, including whether low-altitude flight can be maintained, to the autopilot system.

[0018] In specific implementation, the following steps are used to input the throttle parameters, wind parameters, flight configuration, and filtered wave statistical characteristics into the altitude holding mode of the autopilot system. The autopilot system then performs mathematical simulation and dynamic semi-physical simulation to output the control surface motion: The throttle parameters, wind parameters, aircraft configuration, and filtered wave statistical characteristics are input into the aircraft's six-degree-of-freedom dynamics model and aerodynamics model. A predictive controller based on an altitude-holding modal algorithm calculates the error between the target altitude set by the pilot and the current aircraft altitude predicted by the predictive controller. The predictive controller calculates the pitch control command and throttle compensation command required to eliminate the error based on the error, the wind gradient of the wind parameters, and turbulence. The pitch control command and throttle compensation command are input into the aircraft dynamics model to solve for the aircraft's state data at the next moment. The aircraft state data is then input into the aircraft autopilot system, which outputs control surface motion including elevator deflection angle and throttle change.

[0019] The method for establishing a wave model and performing wave filtering according to an embodiment of the present invention includes the following steps: Step 1: Combining Figure 2 A wave spectrum model is established. The flight control system should be able to withstand the meteorological conditions of sea state 5 when conducting low-altitude cruise over the sea. Therefore, fully developed wind and waves need to be considered. In wave theory and application, fully developed waves are usually regarded as a stationary random process.

[0020] Furthermore, suppose the wave surface at a fixed point on the sea surface... t The vertical displacement ζ(t) at time t is composed of a superposition of many independent random sine waves. (1) In the formula, αn is the amplitude of the constituent wave, ωn is the frequency of the constituent wave, εn is the initial phase of the constituent wave, which is a random quantity uniformly distributed in the range [0, 2π], and n is the number of random sine waves in the constituent wave.

[0021] Furthermore, it can be proven that the process ζ(t) is stationary, and its mean is: (2) The variance is: (3) In the formula, S(ω) represents the energy distribution of the ocean wave relative to the frequency distribution of the constituent waves. S(ω) is called the energy spectrum or frequency spectrum of the ocean wave, or simply the ocean wave spectrum. d is the derivative.

[0022] Furthermore, it is assumed that the vertical displacement of the wave surface in the sea area around a fixed point on the sea surface is composed of the superposition of many component waves propagating independently in different directions. (4) In the formula, x and y represent the positions of a fixed point on the sea surface, and θn represents the angle between the propagation direction of the constituent wave and the wind direction.

[0023] Furthermore, the energy distribution of each component wave relative to the wind direction is symmetrical, and the vast majority of the energy is distributed within the range of [-90°, +90°]. It can be proven that the vertical displacement ζ( The variance of ) is (5) In the formula, ω is the frequency of the constituent wave, θ is the propagation direction of the constituent wave, and S(ω,θ) is called the wave direction spectrum. The wave direction spectrum S(ω,θ) describes the frequency distribution of the energy of the constituent wave in different directions.

[0024] Furthermore, the following relationship exists between the wave direction spectra of two random component waves. (6) A linear wave spectrum model can be derived by assuming that each component wave is random and independent. The wave it represents is a stationary random process with ergodicity. The linear wave spectrum is the foundation for wave estimation and wave simulation.

[0025] Step two involves determining the statistical characteristics of the waves. Typically, the wave directional spectrum S(ω) is distributed within a defined frequency range, with its significant portion concentrated in a narrow frequency band, consistent with actual wave observations. According to stochastic process theory, the statistical characteristics of the waves, i.e., the significant wave height (i.e., the height of the 1 / 3 large wave), can be uniquely determined from the wave spectrum, which describes the frequency distribution of random wave energy.

[0026] (7) In the formula, A is the zeroth moment of the wave spectrum, and A is the wave height gain coefficient.

[0027] (8) Step 3: Establish a wave model. Since there is relative motion between the aircraft and the waves, the waves observed from the aircraft depend on the speed and direction of the aircraft. At the same time, to study the impact of waves on flight in the time domain, the spectral characteristics in the frequency domain must be transformed into an equivalent wave height time series. Based on the established wave direction spectrum, a wave model can be established. Step 4: Combining Figure 3 When designing wave filters, digital filters are generally divided into finite impulse response (FIR) filters and infinite impulse response (IIR) filters. IIR filters have better amplitude-frequency characteristics, require a lower filter order to achieve the same performance, and can effectively suppress the amplitude-frequency characteristics of noise. They also require fewer storage units and have high computational efficiency.

[0028] Furthermore, in IIR filters, elliptic filters have a narrower transition band, enabling rapid cutoff of high-frequency signals. Moreover, the passband and stopband ripple amplitudes are the same, resulting in excellent filtering performance and high tracking capabilities. The filter transfer function has the following form: (9) In the formula, and Here are the filter coefficients, and k is the filter order. X ( z ) represents the z-transform of the input signal. Y ( z ) represents the z-transform of the output signal, where z is a complex frequency variable.

[0029] Furthermore, the order and coefficients of the digital low-pass elliptic filter are designed to suppress wave interference in height sensor measurements. Step 5, Combining Figure 4 The designed wave model and wave filter were introduced into the altitude holding mode of the autopilot, and mathematical simulation and dynamic semi-physical simulation experiments were conducted to verify the correctness of the design.

[0030] In this embodiment, a computer device is provided, such as... Figure 5 As shown, it includes a memory 501, a processor 502, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-described verification methods for maintaining low-altitude flight through an aircraft autopilot system.

[0031] Specifically, the computer device can be a computer terminal, a server, or a similar computing device.

[0032] In this embodiment, a computer-readable storage medium is provided, which stores a computer program that performs any of the above-described verification methods for maintaining low-altitude flight via an aircraft autopilot system.

[0033] Specifically, computer-readable storage media include both permanent and non-permanent, removable and non-removable media, which can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer-readable storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable storage media do not include transient media, such as modulated data signals and carrier waves.

[0034] Based on the same inventive concept, this invention also provides a verification device for maintaining low-altitude flight via an aircraft autopilot system, as described in the following embodiments. Since the principle of the verification device for maintaining low-altitude flight via an aircraft autopilot system is similar to that of the verification method for maintaining low-altitude flight via an aircraft autopilot system, the implementation of the verification device for maintaining low-altitude flight via an aircraft autopilot system can refer to the implementation of the verification method for maintaining low-altitude flight via an aircraft autopilot system, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0035] Figure 6 This is a structural block diagram of a verification device for maintaining low-altitude flight via an aircraft autopilot system, as described in an embodiment of the present invention. Figure 6 As shown, it includes: a wave model construction module 601, a wave filtering module 602, and a low-altitude flight verification module 603. The structure is described below.

[0036] The wave model construction module 601 is used to simulate the wave surface of the waves based on the sea conditions encountered by the aircraft autopilot system during low-altitude cruise over the sea, generate a wave model, and calculate the statistical characteristics of the waves including environmental noise through the wave model. The wave filtering module 602 is used to determine the filter coefficients and the filter order, construct a wave filter using the filter coefficients and the filter order, input the statistical characteristics of the waves containing environmental noise into the wave filter, and generate the filtered wave statistical characteristics. The low-altitude flight verification module 603 is used to acquire basic parameters and meteorological data of the aircraft from an external system, input the basic parameters, the meteorological data and the filtered sea wave statistical characteristics into the aircraft autopilot system, and verify whether the aircraft can maintain a low altitude for flight through the aircraft autopilot system.

[0037] In one embodiment, the wave model building module includes: Composition wave building units are used to construct independent random sine waves. n After superimposing several independent random sinusoidal waves, the vertical displacement ζ(t) of the constituent waves at a fixed point on the sea surface is obtained, where... , t For time, a n The amplitude that makes up the wave, ω n The frequency that makes up the wave, ε n The initial phase that makes up the wave, n The number of random sine waves in the constituent wave; The first wave direction spectrum construction unit is used to construct the variance of the vertical displacement ζ(t). The first formula for calculating variance is given by, where, , S ( ω () represents the wave direction spectrum; A vertical displacement formula construction unit is used to construct the vertical displacement ζ(x,y,t) of the wave surface surrounding a fixed point (x,y) on the sea surface using the vertical displacement ζ(t), wherein, (x, y) are the coordinates of a fixed point on the sea surface. θ n The angle between the direction of wave propagation and the wind direction; The second wave direction spectrum construction unit is used to construct the variance of the vertical displacement ζ(x,y,t) using the first variance calculation formula. The second variance calculation formula is used to obtain the wave direction spectrum S(ω, y,t) of the vertical displacement ζ(x,y,t). θ ),in, ; The relation generation unit is used to construct the wave direction spectrum relation between the vertical displacements ζ(x,y,t) of two random component waves. ; Construct wave model units for use based on the wave direction spectrum S ( ω The wave direction spectrum S(ω, θ The wave model is constructed using the wave direction spectrum relationship described above; A noise addition unit is used to determine the environmental noise and add the environmental noise to the wave model.

[0038] In one embodiment, the noise addition unit is further configured to: treat sensor noise, environmental interference noise, and platform-related noise as environmental noise; perform statistical characteristic analysis on each type of environmental noise to determine the statistical distribution and power spectral density of the noise; synthesize the sensor noise, environmental interference noise, and platform-related noise in the time domain based on the statistical distribution of the noise to generate a first synthesized noise; synthesize the sensor noise, environmental interference noise, and platform-related noise in the frequency domain based on the power spectral density of the noise to generate a second synthesized noise; and add the first synthesized noise and the second synthesized noise to the wave model.

[0039] In one embodiment, the wave model building module further includes: The zero-order moment calculation unit is used to calculate the wave direction spectrum of the wave model. S ( ω Constructing the zeroth moment of the wave spectrum ,in, , ω The frequency that makes up the wave; The effective wave height calculation unit is used to calculate the effective wave height using the zeroth moment. Sum-wave high gain coefficient A The effective wave height was calculated. ,in, ; The statistical characteristic unit is used to determine the effective wave height. As a statistical characteristic of ocean waves that include environmental noise.

[0040] In one embodiment, the wave filtering module includes: The wave filter unit is defined as a digital low-pass elliptic filter, and the filter transfer function of the digital low-pass elliptic filter is specified. ,in, and These are the filter coefficients. k Let the filter order be . X ( z ) represents the z-transform of the input signal. Y ( z ) represents the z-transform of the output signal, where z is a complex frequency variable.

[0041] In one embodiment, the low-altitude flight verification module includes: The control surface control unit is used to obtain basic parameters such as throttle parameters and flight configuration from external systems, and wind parameters from meteorological data from external sensors. The throttle parameters, wind parameters, flight configuration, and filtered wave statistical characteristics are input into the altitude holding mode of the autopilot system. Mathematical simulation and dynamic semi-physical simulation are performed through the autopilot system to output the control surface motion. The low-altitude flight verification unit is used to input the control surface motion to the actuator, and control the aircraft to fly at low altitude through the actuator. The data feedback unit is used to feed back flight speed and flight attitude information, including whether it can maintain a low altitude, to the aircraft autopilot system via external sensors.

[0042] In one embodiment, the control surface control unit is further configured to input the throttle parameters, the wind parameters, the aircraft configuration, and the filtered wave statistical characteristics into the aircraft's six-degree-of-freedom dynamics model and aerodynamics model; a predictive controller based on an altitude-holding modal algorithm calculates the error between the target altitude set by the pilot and the current aircraft altitude predicted by the predictive controller; the predictive controller calculates the pitch control command and throttle compensation command required to eliminate the error based on the error, the wind gradient of the wind parameters, and turbulence; inputs the pitch control command and throttle compensation command into the aircraft dynamics model to solve for the aircraft state data at the next moment; inputs the aircraft state data into the aircraft autopilot system and outputs control surface motion including elevator deflection angle and throttle change.

[0043] The embodiments of the present invention achieve the following technical effects: The method described in this invention effectively solves the problem of radio altimeter signal interference caused by the dynamic movement of sea waves during long-term automatic cruise flight of an aircraft at extremely low altitudes above sea level (within the range of the radio altimeter). This method significantly improves the accuracy and robustness of altitude measurement by optimizing signal processing algorithms and introducing a multi-sensor fusion mechanism, thereby maintaining stable altitude perception of the flight control system in complex sea environments. Based on this, the aircraft can maintain its predetermined flight state more smoothly, greatly improving overall stability and safety during low-altitude flight over the sea, while significantly reducing the pilot's operational burden and workload.

[0044] Obviously, those skilled in the art should understand that the modules or steps of the above-described embodiments of the present invention can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the embodiments of the present invention are not limited to any particular hardware and software combination.

[0045] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, various modifications and variations can be made to the embodiments of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A verification method for maintaining low-altitude flight via an aircraft autopilot system, characterized in that, include: Based on the sea conditions encountered by the aircraft's autopilot system during low-altitude cruise over the sea, the wave surface is simulated to generate a wave model. The statistical characteristics of the waves, including environmental noise, are calculated using this wave model, including: Construct independent random sine waves, n After superimposing several independent random sinusoidal waves, the vertical displacement ζ(t) of the constituent waves at a fixed point on the sea surface is obtained, where... , t For time, a n The amplitude that makes up the wave, ω n The frequency that makes up the wave, ε n The initial phase that makes up the wave, n The variance of the vertical displacement ζ(t) is constructed by the number of random sine waves in the constituent wave. The first formula for calculating variance is given by, where, , S ( ω The vertical displacement ζ(t) represents the wave direction spectrum; the vertical displacement ζ(x,y,t) of the wave surface surrounding a fixed point (x,y) on the sea surface is constructed using the vertical displacement ζ(t), where, (x, y) are the coordinates of a fixed point on the sea surface. θ n The angle between the propagation direction of the wave and the wind direction is used; the variance of the vertical displacement ζ(x,y,t) is constructed using the first variance calculation formula. The second variance calculation formula is used to obtain the wave direction spectrum S(ω, y,t) of the vertical displacement ζ(x,y,t). θ ),in, Construct the wave direction spectrum relationship between the vertical displacements ζ(x,y,t) of two random component waves. According to the wave direction spectrum S ( ω The wave direction spectrum S(ω, θ A wave model is constructed using the wave direction spectrum relationship; environmental noise is determined and added to the wave model; The wave direction spectrum of the wave model S ( ω Constructing the zeroth moment of the wave spectrum ,in, , ω The frequency that makes up the wave; Through the zeroth moment Sum-wave high gain coefficient A The effective wave height was calculated. ,in, ; The effective wave height Statistical characteristics of ocean waves that include environmental noise; Determine the filter coefficients and filter order, construct a wave filter using the filter coefficients and filter order, input the statistical characteristics of the waves containing environmental noise into the wave filter, and generate filtered wave statistical characteristics. The aircraft's basic parameters and meteorological data are obtained from an external system. The basic parameters, meteorological data, and filtered wave statistical characteristics are then input into the aircraft's autopilot system. The autopilot system is used to verify whether the aircraft can maintain a low altitude for flight.

2. The verification method for maintaining low-altitude flight via an aircraft autopilot system as described in claim 1, characterized in that, Determine the environmental noise and add it to the wave model, including: Sensor noise, environmental interference noise, and platform-related noise are considered as environmental noise. Statistical characteristic analysis was performed on each type of environmental noise to determine the statistical distribution and power spectral density of the noise. Based on the statistical distribution of the noise, the sensor noise, the environmental interference noise, and the platform-related noise are synthesized in the time domain to generate a first synthesized noise; Based on the power spectral density of the noise, the sensor noise, the environmental interference noise, and the platform-related noise are synthesized in the frequency domain to generate a second synthesized noise; The first synthesized noise and the second synthesized noise are added to the wave model.

3. The verification method for maintaining low-altitude flight via an aircraft autopilot system as described in claim 1, characterized in that, The wave filter is a digital low-pass elliptic filter, and the filter transfer function of the digital low-pass elliptic filter is... ,in, and These are the filter coefficients. k Let the filter order be . X ( z ) represents the z-transform of the input signal. Y ( z ) represents the z-transform of the output signal, where z is a complex frequency variable.

4. The verification method for maintaining low-altitude flight via an aircraft autopilot system as described in claim 1, characterized in that, The aircraft's basic parameters and meteorological data are acquired from an external system. These parameters, meteorological data, and filtered wave statistical characteristics are then input into the aircraft's autopilot system. The autopilot system is used to verify whether the aircraft can maintain low-altitude flight, including: The system obtains basic parameters such as throttle parameters and flight configuration from external systems, and wind parameters from meteorological data from external sensors. The throttle parameters, wind parameters, flight configuration, and filtered wave statistical characteristics are input into the altitude holding mode of the autopilot system. Mathematical simulation and dynamic semi-physical simulation are performed through the autopilot system to output the control surface motion. The motion of the control surfaces is input to the actuator, which controls the aircraft to fly at low altitude. External sensors feed back flight speed and flight attitude information, including whether it can maintain a low altitude, to the aircraft's autopilot system.

5. The verification method for maintaining low-altitude flight via an aircraft autopilot system as described in claim 4, characterized in that, The throttle parameters, wind parameters, flight configuration, and filtered wave statistical characteristics are input into the altitude holding mode of the autopilot system. Mathematical and dynamic semi-physical simulations are performed by the autopilot system to output control surface motion quantities, including: The throttle parameters, wind parameters, aircraft configuration, and filtered wave statistical characteristics are input into the aircraft's six-degree-of-freedom dynamics model and aerodynamics model. A predictive controller based on an altitude-keeping modal algorithm calculates the error between the target altitude set by the pilot and the current altitude of the aircraft predicted by the predictive controller. The predictive controller calculates the pitch control command and throttle compensation command required to eliminate the error based on the error, the wind gradient of the wind parameters, and turbulence. The pitch control command and the throttle compensation command are input into the aircraft dynamics model to calculate the aircraft state data at the next moment. The aircraft state data is then input into the aircraft autopilot system, which outputs control surface motion including elevator deflection angle and throttle change.

6. A verification device for maintaining low-altitude flight via an aircraft autopilot system, characterized in that, include: The wave model construction module is used to simulate the wave surface of the waves based on the sea conditions encountered by the aircraft autopilot system during low-altitude cruise over the sea, generate a wave model, and calculate the statistical characteristics of the waves including environmental noise through the wave model. The wave model building module includes: Composition wave building units are used to construct independent random sine waves. n After superimposing several independent random sinusoidal waves, the vertical displacement ζ(t) of the constituent waves at a fixed point on the sea surface is obtained, where... , t For time, a n The amplitude that makes up the wave, ω n The frequency that makes up the wave, ε n The initial phase that makes up the wave, n The number of random sine waves in the constituent wave; The first wave direction spectrum construction unit is used to construct the variance of the vertical displacement ζ(t). The first formula for calculating variance is given by, where, , S ( ω () represents the wave direction spectrum; A vertical displacement formula construction unit is used to construct the vertical displacement ζ(x,y,t) of the wave surface surrounding a fixed point (x,y) on the sea surface using the vertical displacement ζ(t), wherein, (x, y) are the coordinates of a fixed point on the sea surface. θ n The angle between the direction of wave propagation and the wind direction; The second wave direction spectrum construction unit is used to construct the variance of the vertical displacement ζ(x,y,t) using the first variance calculation formula. The second variance calculation formula is used to obtain the wave direction spectrum S(ω, y,t) of the vertical displacement ζ(x,y,t). θ ),in, ; The relation generation unit is used to construct the wave direction spectrum relation between the vertical displacements ζ(x,y,t) of two random component waves. ; Construct wave model units for use based on the wave direction spectrum S ( ω The wave direction spectrum S(ω, θ The wave model is constructed using the wave direction spectrum relationship described above; A noise addition unit is used to determine the environmental noise and add the environmental noise to the wave model; The zero-order moment calculation unit is used to calculate the wave direction spectrum of the wave model. S ( ω Constructing the zeroth moment of the wave spectrum ,in, , ω The frequency that makes up the wave; The effective wave height calculation unit is used to calculate the effective wave height using the zeroth moment. Sum-wave high gain coefficient A The effective wave height was calculated. ,in, ; The statistical characteristic unit is used to determine the effective wave height. Statistical characteristics of ocean waves that include environmental noise; The wave filtering module is used to determine the filter coefficients and the filter order, construct a wave filter using the filter coefficients and the filter order, input the statistical characteristics of the waves containing environmental noise into the wave filter, and generate the filtered wave statistical characteristics. The low-altitude flight verification module is used to acquire basic parameters and meteorological data of the aircraft from an external system, and input the basic parameters, the meteorological data and the filtered sea wave statistical characteristics into the aircraft autopilot system to verify whether the aircraft can maintain a low altitude for flight.

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the verification method for maintaining low-altitude flight via an aircraft autopilot system as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that performs the verification method of maintaining low-altitude flight via an aircraft autopilot system as described in any one of claims 1 to 5.

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