A method, system, device, product, and medium for eliminating platform error angle stabilization

Abstract

The present application relates to the field of error control, and provides a stable platform error angle elimination method, system, device, product and medium, including constructing a signal expression and a noise expression of a gyroscope, obtaining a power spectral density according to the signal expression and the noise expression, and obtaining a filter center frequency through the power spectral density; constructing an approximate condition, calculating a drift power spectral density and a reference speed error power spectral density according to the approximate condition and the power spectral density; establishing a reduced-order suboptimal filter through the filter center frequency, the drift power spectral density and the reference speed error power spectral density, obtaining a filter gain coefficient of the reduced-order suboptimal filter; calculating a speed error estimation value according to the filter gain coefficient, obtaining a speed estimation value through the speed error estimation value, and obtaining a correction torque according to the speed estimation value; and applying a torque to the stable platform through the correction torque, so that the error angle elimination of the stable platform can be completed.

Description

Technical Field

[0001] This invention relates to the field of error control technology, and in particular to a method, system, device, product, and medium for eliminating error angles on a stable platform. Background Technology

[0002] The Earth's gravitational field is the fundamental physical field of the Earth. It reflects the distribution of matter within the Earth and its rotational motion, and governs the movement of objects on the Earth's surface and in near-Earth space. Information on the Earth's gravitational field plays a crucial foundational role in basic disciplines of Earth science, including geophysics, geological exploration, geodesy, oceanography, and geodynamics. The platform-type relative gravimeter is one of the main instruments for acquiring information about the Earth's gravitational field. It primarily consists of a gravity sensor and a stable platform. The gravity sensor is the core sensing element of the relative gravimeter, characterized by high precision and high resolution, capable of sensing even subtle changes in the Earth's gravitational field. The stable platform provides physical support for the gravity sensor and a real-time reference benchmark for dynamic gravity measurements.

[0003] In terms of structural configuration, the stabilizing platform is composed of two horizontal universal rings. The mechanical part of the platform consists of a base, an outer frame, and an inner frame. Three gyroscopes, two horizontal accelerometers, and a gravity sensor are orthogonally mounted on the inner frame. The outer frame is a pitch ring, and the inner frame is a roll ring.

[0004] When a gravimeter measures the gravity field in a dynamic environment, the control loop of the stabilization platform controls the platform to track the local geographical level, ensuring that the input axis of the gravity sensor is aligned with the vertical gravity line, thus completing the measurement of gravity information. Taking a north-facing horizontal channel as an example, the existing platform stabilization loop uses a proportional-integral-derivative control with fixed parameters. The controller behaves as a low-pass filter with a fixed cutoff frequency in the frequency domain. When the platform encounters complex sea conditions, the stabilization platform fluctuates under the acceleration impact of the platform's motion, deviating from its horizontal position and generating an error angle. This horizontal attitude fluctuation causes the gravity sensor's sensing axis to deviate from the vertical, resulting in measurement errors. Furthermore, it causes horizontal motion acceleration to couple to the gravity output through platform tilt, ultimately leading to significant measurement errors. If the controller bandwidth is increased to improve response speed, the ability to suppress high-frequency disturbances decreases, and platform attitude fluctuations intensify. Conversely, if the bandwidth is reduced to suppress disturbances, the recovery time after the platform is subjected to motion acceleration disturbances or changes in course becomes excessively long (up to 10 minutes or more), during which time gravity data is unavailable. The more fundamental problem is that the statistical characteristics of gyroscope drift and reference velocity error are time-varying under actual sea conditions, and fixed-parameter controllers cannot be adjusted online. Therefore, it is impossible to achieve an effective adaptation of a stable platform to complex and variable sea conditions. Existing methods have failed to resolve this contradiction, severely limiting the accuracy of gravity measurements under complex and harsh sea conditions. Summary of the Invention

[0005] This invention aims to at least solve one of the technical problems existing in related technologies. To this end, this invention provides a method, system, device, product, and medium for eliminating the error angle of a stable platform, enabling rapid elimination of the error angle of a stable platform.

[0006] This invention provides a method for eliminating the error angle of a stable platform, comprising: S1: Construct the signal and noise expressions for the gyroscope, obtain the power spectral density based on the signal and noise expressions, and obtain the center frequency of the filter from the power spectral density; S2: Construct approximate conditions, and calculate the drift power spectral density and the reference velocity error power spectral density based on the approximate conditions and the power spectral density; S3: Establish a reduced-order suboptimal filter using the filter center frequency, drift power spectral density, and reference velocity error power spectral density, and obtain the filter gain coefficient of the reduced-order suboptimal filter; S4: Calculate the speed error estimate based on the filter gain coefficient, obtain the speed estimate based on the speed error estimate, and obtain the correction torque based on the speed estimate; S5: Apply torque to the stabilizing platform by correcting the torque to eliminate the error angle of the stabilizing platform.

[0007] According to the method for eliminating the error angle of a stable platform provided by the present invention, step S1 further includes: S11: Determine the reference velocity error, accelerometer noise, and gyroscope drift; construct the signal expression and noise expression of the gyroscope based on the reference velocity error, accelerometer noise, and gyroscope drift. S12: Obtain the output expression based on the signal expression and noise expression, obtain the power spectral density through the output expression, and obtain the gyroscope drift power spectral density curve and the velocity error power spectral density curve based on the power spectral density. S13: The frequency corresponding to the intersection of the gyroscope drift power spectral density curve and the velocity error power spectral density curve is taken as the center frequency of the filter.

[0008] According to a method for eliminating the error angle of a stable platform provided by the present invention, in step S2, the gyroscope drift-related frequency, the Schuler angular frequency, and the velocity error-related frequency are determined, and the approximate conditions are constructed using the gyroscope drift-related frequency, the Schuler angular frequency, and the velocity error-related frequency.

[0009] According to the method for eliminating the error angle of a stable platform provided by the present invention, step S3 further includes: S31: Determine the gyroscope operating frequency based on the center frequency of the filter, and obtain the filter observations at the gyroscope operating frequency through the drift power spectral density and the reference velocity error power spectral density. S32: Determine the state transition matrix, noise input matrix, and measurement matrix; use the filter observations, state transition matrix, noise input matrix, and measurement matrix to establish the reduced-order suboptimal filter, and obtain the filter gain coefficient of the reduced-order suboptimal filter.

[0010] According to the method for eliminating the error angle of a stable platform provided by the present invention, in step S4, the velocity error estimate is... The calculation method is as follows: Where s is the complex frequency of the Laplace transform. Let be the first filter gain coefficient at time t. Let be the gain coefficient of the second filter at time t. Let be the gain coefficient of the third filter at time t. The Schuler angular frequency, For reference speed, This is the output of the accelerometer.

[0011] According to a method for eliminating the error angle of a stable platform provided by the present invention, in step S5, the correction torque includes an eastward correction torque and a northward correction torque. The northward correction torque is used to correct the north-south error angle of the stable platform, and the eastward correction torque is used to correct the east-west error angle of the stable platform, thereby completing the elimination of the error angle of the stable platform.

[0012] The present invention also provides a stable platform error angle elimination system, comprising: Center frequency module: used to construct the signal and noise expressions of the gyroscope, obtain the power spectral density based on the signal and noise expressions, and obtain the center frequency of the filter from the power spectral density; Power spectral density module: used to construct approximate conditions, and calculate drift power spectral density and reference velocity error power spectral density based on the approximate conditions and power spectral density; Filter gain coefficient module: used to establish a reduced-order suboptimal filter using the filter center frequency, drift power spectral density and reference velocity error power spectral density, and obtain the filter gain coefficient of the reduced-order suboptimal filter; Correction torque module: used to calculate the speed error estimate based on the filter gain coefficient, obtain the speed estimate from the speed error estimate, and obtain the correction torque from the speed estimate; Error Angle Elimination Module: Used to apply torque to the stabilizing platform by correcting the torque, thereby eliminating the error angle of the stabilizing platform.

[0013] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of a stable platform error angle elimination method as described above.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a stable platform error angle elimination method as described above.

[0015] The present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, which, when executed by a computer, enable the computer to perform the steps of any of the above-described methods for eliminating the error angle of a stable platform.

[0016] The above-described one or more technical solutions in the embodiments of the present invention have at least one of the following technical effects: This invention provides a method, system, device, product, and medium for eliminating error angles on a stable platform. Compared to existing platform control technologies based on proportional-integral-derivative (PI-DE) control, it offers the following significant advantages: First, it balances rapid leveling and disturbance suppression. Fixed-parameter PI-DE control, due to its fixed bandwidth, cannot simultaneously meet these two requirements. This invention, through frequency domain order reduction modeling, utilizes time-varying gain to simultaneously achieve rapid platform leveling and effective suppression of error angles caused by motion and disturbances. Second, it offers high numerical stability and eliminates the risk of divergence. Because ocean gravity measurements have long durations (up to six months) and involve complex sea state changes with a wide range of filter parameter variations, high-order filters are prone to divergence. Divergence can lead to the platform capsizing and damage to the core gravity sensor. This invention, by constructing a reduced-order suboptimal filter, minimizes computational complexity, and ensures that the equation solution remains bounded, fundamentally avoiding the risk of numerical divergence.

[0017] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating a method for eliminating the error angle of a stable platform provided by the present invention.

[0020] Figure 2 This is a schematic diagram of the comparative test results of a stable platform error angle elimination method provided by the present invention.

[0021] Figure 3 This is a schematic diagram of the structure of a stable platform error angle elimination system provided by the present invention.

[0022] Figure 4 This is a schematic diagram of the structure of a stable platform error angle elimination device provided by the present invention.

[0023] Figure label: 100. Center frequency module; 200. Power spectral density module; 300. Filter gain coefficient module; 400. Correction torque module; 500. Error angle elimination module; 810. Processor; 820. Communication interface; 830. Memory; 840. Communication bus. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention. The following embodiments are used to illustrate this invention but cannot be used to limit the scope of this invention.

[0025] In the description of the embodiments of the present invention, it should be noted that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the embodiments of the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of the present invention. In addition, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0026] In the description of the embodiments of the present invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of the present invention based on the specific circumstances.

[0027] In embodiments of the present invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "on top of," and "over" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0028] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0029] The following is combined with Figures 1 to 4 Specific embodiments of the present invention are described below. Figure 1 A flowchart illustrating a method for eliminating the error angle of a stable platform provided by the present invention includes: S1: Construct the signal and noise expressions for the gyroscope, obtain the power spectral density based on the signal and noise expressions, and obtain the center frequency of the filter from the power spectral density; Furthermore, the objective of this stage is to obtain the power spectral density based on the signal and noise expressions, thereby obtaining the filter's center frequency. Specifically, step S1 further includes: S11: Determine the reference velocity error, accelerometer noise, and gyroscope drift; construct the signal expression and noise expression of the gyroscope based on the reference velocity error, accelerometer noise, and gyroscope drift. S12: Obtain the output expression based on the signal expression and noise expression, obtain the power spectral density through the output expression, and obtain the gyroscope drift power spectral density curve and velocity error power spectral density curve based on the power spectral density. S13: The frequency corresponding to the intersection of the gyroscope drift power spectral density curve and the velocity error power spectral density curve is taken as the center frequency of the filter.

[0030] The specific implementation method for the above steps in this embodiment is as follows: First, it is necessary to determine the reference velocity error of the gyroscope on the stable platform in the northward horizontal channel. and gyroscope drift It is also necessary to determine the accelerometer noise of the accelerometer on the north-facing horizontal channel. Here, the reference velocity error and accelerometer noise can be obtained using the Allan variance method. This allows us to obtain the signal and noise expressions for the stable platform: Where u is the output signal of the gyroscope, v is the output noise of the gyroscope, p is the differential operator, R represents the Earth's radius, and g is the local gravitational acceleration.

[0031] Adding the signal and noise expressions together yields the gyroscope's output expression, and thus its output y. After obtaining the output expression, performing a Fourier transform and normalization on the output yields its power spectral density. : in, For the frequency related to gyroscope drift, This represents the root mean square value of the gyroscope drift. This represents the root mean square value of the gyroscope's velocity error. The above parameters can be obtained from the gyroscope's product manual or received external input parameters. The values ​​of these parameters can be determined after Fourier transform and normalization. This represents the angular frequency of the gyroscope's output signal. The Schuler angular frequency of the gyroscope. Let V be the accelerometer noise variance. In the power spectral density, The represented component indicates gyroscope drift. The representative component indicates the velocity error. This represents accelerometer noise. Since the accelerometer noise power spectral density is much lower than gyroscope drift and reference velocity error within the band of interest, the influence of accelerometer noise can be ignored. The gyroscope drift power spectral density curve is obtained through the expression for gyroscope drift, and the velocity error power spectral density curve is obtained through the expression for velocity error. Here, the gyroscope drift correlation frequency is a characteristic parameter used to describe how quickly the random drift of the gyroscope changes over time; a larger value indicates a faster change in gyroscope drift. The velocity error correlation frequency is a parameter used to describe the characteristics of the velocity measurement error of the reference velocity source changing over time.

[0032] Here, the slope of the gyroscope drift power spectral density curve is 80 dB / dec, and the slope of the velocity error power spectral density curve is 40 dB / dec. The frequency corresponding to the intersection of the gyroscope drift power spectral density curve and the velocity error power spectral density curve is taken as the filter center frequency β, and theoretically: .

[0033] S2: Construct approximate conditions, and calculate the drift power spectral density and the reference velocity error power spectral density based on the approximate conditions and the power spectral density; Furthermore, the objective of this stage is to calculate the drift power spectral density and the reference velocity error power spectral density. Specifically, in step S2, the gyroscope drift-related frequency, Schuler angular frequency, and velocity error-related frequency are determined, and the approximate conditions are constructed using these frequencies.

[0034] The specific implementation method for the above steps in this embodiment is as follows: First, it's necessary to determine the gyroscope drift-related frequency, Schuler angular frequency, and velocity error-related frequency. This allows us to construct an approximation condition: the angular frequency of the gyroscope's output signal must be much greater than the gyroscope drift-related frequency, much smaller than the velocity error-related frequency, and much greater than the Schuler angular frequency. Based on this approximation condition and the gyroscope drift and velocity error in the power spectral density, the drift power spectral density can then be calculated. and reference velocity error power spectral density : in, This is an intermediate parameter of the drift power spectrum. For reference speed intermediate parameters, we have: .

[0035] S3: Establish a reduced-order suboptimal filter using the filter center frequency, drift power spectral density, and reference velocity error power spectral density, and obtain the filter gain coefficient of the reduced-order suboptimal filter; Furthermore, the objective of this stage is to establish a reduced-order suboptimal filter, thereby obtaining the filter gain coefficient of the reduced-order suboptimal filter. Further, step S3 includes: S31: Determine the gyroscope operating frequency based on the center frequency of the filter, and obtain the filter observations at the gyroscope operating frequency through the drift power spectral density and the reference velocity error power spectral density. S32: Determine the state transition matrix, noise input matrix, and measurement matrix; use the filter observations, state transition matrix, noise input matrix, and measurement matrix to establish the reduced-order suboptimal filter, and obtain the filter gain coefficient of the reduced-order suboptimal filter.

[0036] The specific implementation method for the above steps in this embodiment is as follows; First, the gyroscope's operating frequency needs to be determined based on the filter's center frequency. This means using the filter's center frequency as the gyroscope's operating frequency, ensuring that the angular frequency of the gyroscope's output signal is equal to the filter's center frequency. Then, a configuration including the first filter's state variables is constructed. Second filter state variables and the third filter state quantity The filter state variables. Theoretically, we have: in, Unit intensity white noise, The derivative of the state variables of the first filter. The derivative of the state quantity of the second filter. The derivative of the state quantity of the third filter. It is white noise and is independent of unit intensity white noise. Let's consider the filter observations. Here, the drift power spectral density is the same as the power spectral density of the third filter state variables, and the power spectral density of the differential of the white noise is the same as the power spectral density of the reference velocity error. Since the system model of the gyroscope is known, and the gyroscope's operating frequency satisfies the approximation condition, the third filter state variables can be obtained from the drift power spectral density. Then, differentiation yields the first and second filter state variables. The differential of the white noise can be obtained from the reference velocity error power spectral density, and integration yields the white noise, thus providing the filter observations.

[0037] Subsequently, a reduced-order suboptimal filter is established based on the Kalman filter, with its center frequency being the filter's center frequency. The state transition matrix F, noise input matrix G, and measurement matrix H are respectively: The state variables of the first, second, and third filters are estimated using a reduced-order suboptimal filter. Based on the relationship satisfied by the filter gain coefficients, the gain coefficient of the first filter at time t can be obtained. Second filter gain coefficient and the third filter gain coefficient The filter gain coefficients satisfy the following relationship: in, This is an estimate of the first filter state quantity output by the reduced-order suboptimal filter. This is an estimate of the second filter state quantity output by the reduced-order suboptimal filter. This is an estimate of the third filter state quantity output by the reduced-order suboptimal filter. The derivative of the estimated state quantity of the first filter. The derivative of the estimated state quantity of the second filter. It is the derivative of the estimated state quantity of the third filter.

[0038] S4: Calculate the speed error estimate based on the filter gain coefficient, obtain the speed estimate based on the speed error estimate, and obtain the correction torque based on the speed estimate; Furthermore, the objective of this stage is to calculate the speed error estimate, thereby obtaining the correction torque. Specifically, in step S4, the speed error estimate... The calculation method is as follows: Where s is the complex frequency of the Laplace transform. Let be the first filter gain coefficient at time t. Let be the gain coefficient of the second filter at time t. Let be the gain coefficient of the third filter at time t. The Schuler angular frequency, For reference speed, This is the output of the accelerometer.

[0039] The specific implementation method for the above steps in this embodiment is as follows; Once the filter gain coefficients are obtained, the velocity error estimate can be calculated. : Where s is the Laplace transform complex frequency determined based on the gyroscope's operating frequency. For reference speed, This is the accelerometer output. Since the reference velocity error, accelerometer noise, and gyroscope drift in step S1 are all located in the north-north horizontal direction, the velocity error estimate here is also in the north-north horizontal direction.

[0040] Then, the northbound speed estimate is obtained by estimating the speed error. : Finally, the northward correction torque is obtained based on the speed estimate. : in, The torque coefficient is used to stabilize the platform. The corrected torque obtained here is the northward corrected torque. The reference velocity error, accelerometer noise, and gyroscope drift in step S1 are replaced with the reference velocity error, accelerometer noise, and gyroscope drift in the eastward horizontal direction. Other parameters are also replaced with the corresponding data in the eastward horizontal direction. Steps S1 to S4 are then executed to obtain the eastward corrected torque. This yields the corrected torque that includes both the northward and eastward corrected torques.

[0041] S5: Apply torque to the stabilizing platform by correcting the torque to eliminate the error angle of the stabilizing platform.

[0042] Furthermore, the objective of this stage is to apply torque to the stabilizing platform to eliminate its error angle. Specifically, in step S5, the correction torque includes an eastward correction torque and a northward correction torque. The northward correction torque is used to correct the north-south error angle of the stabilizing platform, and the eastward correction torque is used to correct the east-west error angle of the stabilizing platform, thereby eliminating the error angle of the stabilizing platform.

[0043] The specific implementation method for the above steps in this embodiment is as follows: After obtaining the eastward correction torque and the northward correction torque, the northward correction torque is applied to the due north direction of the stabilizing platform through a correction motor and other mechanisms to correct the north-south error angle, and the eastward correction torque is applied to the due east direction of the stabilizing platform to correct the east-west error angle. This completes the elimination of the error angle of the stabilizing platform.

[0044] Here, the effectiveness of a method for eliminating the error angle of a stable platform is also verified. To measure the effect of eliminating the error angle of the stable platform, a gravity meter using the stable platform is used to measure gravity. When the stable platform produces an error angle, the gravity measurement result will show a gravity anomaly. The result of the gravity anomaly is as follows: Figure 2 As shown, the first gravity anomaly curve is the gravity anomaly curve obtained by eliminating the error angle using this method, and the second gravity anomaly curve is the gravity anomaly curve obtained by eliminating the error angle using proportional-integral-derivative control. The vertical axis represents the value of the gravity anomaly in mGal, and the horizontal axis represents latitude. It can be seen that the first gravity anomaly curve is smoother and the noise is significantly reduced. The peak-to-peak noise value of the first gravity anomaly curve is 0.3 mGal, while that of the second gravity anomaly curve is 0.9 mGal. This indicates that the proposed method is more effective at eliminating the error angle.

[0045] The following describes a stable platform error angle elimination device provided by the present invention. The stable platform error angle elimination device described below and the stable platform error angle elimination method described above can be referred to in correspondence.

[0046] Figure 3 An example is a schematic diagram of a stable platform error angle elimination system, as shown below. Figure 3 As shown, a stable platform error angle elimination method as described above includes: Center frequency module: used to construct the signal and noise expressions of the gyroscope, obtain the power spectral density based on the signal and noise expressions, and obtain the center frequency of the filter from the power spectral density; Power spectral density module: used to construct approximate conditions, and calculate drift power spectral density and reference velocity error power spectral density based on the approximate conditions and power spectral density; Filter gain coefficient module: used to establish a reduced-order suboptimal filter using the filter center frequency, drift power spectral density and reference velocity error power spectral density, and obtain the filter gain coefficient of the reduced-order suboptimal filter; Correction torque module: used to calculate the speed error estimate based on the filter gain coefficient, obtain the speed estimate from the speed error estimate, and obtain the correction torque from the speed estimate; Error Angle Elimination Module: Used to apply torque to the stabilizing platform by correcting the torque, thereby eliminating the error angle of the stabilizing platform.

[0047] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 can call a computer program in the memory 830 to execute a stable platform error angle elimination method, which includes: S1: Construct the signal and noise expressions for the gyroscope, obtain the power spectral density based on the signal and noise expressions, and obtain the center frequency of the filter from the power spectral density; S2: Construct approximate conditions, and calculate the drift power spectral density and the reference velocity error power spectral density based on the approximate conditions and the power spectral density; S3: Establish a reduced-order suboptimal filter using the filter center frequency, drift power spectral density, and reference velocity error power spectral density, and obtain the filter gain coefficient of the reduced-order suboptimal filter; S4: Calculate the speed error estimate based on the filter gain coefficient, obtain the speed estimate based on the speed error estimate, and obtain the correction torque based on the speed estimate; S5: Apply torque to the stabilizing platform by correcting the torque to eliminate the error angle of the stabilizing platform.

[0048] Furthermore, when the computer program in the aforementioned memory 830 can be implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0049] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein when the program instructions are executed by a computer, the computer is able to execute a stable platform error angle elimination method provided by the above methods, the method comprising: S1: Construct the signal and noise expressions for the gyroscope, obtain the power spectral density based on the signal and noise expressions, and obtain the center frequency of the filter from the power spectral density; S2: Construct approximate conditions, and calculate the drift power spectral density and the reference velocity error power spectral density based on the approximate conditions and the power spectral density; S3: Establish a reduced-order suboptimal filter using the filter center frequency, drift power spectral density, and reference velocity error power spectral density, and obtain the filter gain coefficient of the reduced-order suboptimal filter; S4: Calculate the speed error estimate based on the filter gain coefficient, obtain the speed estimate based on the speed error estimate, and obtain the correction torque based on the speed estimate; S5: Apply torque to the stabilizing platform by correcting the torque to eliminate the error angle of the stabilizing platform.

[0050] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the aforementioned methods for eliminating a stable platform error angle, the method comprising: S1: Construct the signal and noise expressions for the gyroscope, obtain the power spectral density based on the signal and noise expressions, and obtain the center frequency of the filter from the power spectral density; S2: Construct approximate conditions, and calculate the drift power spectral density and the reference velocity error power spectral density based on the approximate conditions and the power spectral density; S3: Establish a reduced-order suboptimal filter using the filter center frequency, drift power spectral density, and reference velocity error power spectral density, and obtain the filter gain coefficient of the reduced-order suboptimal filter; S4: Calculate the speed error estimate based on the filter gain coefficient, obtain the speed estimate based on the speed error estimate, and obtain the correction torque based on the speed estimate; S5: Apply torque to the stabilizing platform by correcting the torque to eliminate the error angle of the stabilizing platform.

[0051] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0052] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0053] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for eliminating the error angle of a stable platform, characterized in that, include: S1: Construct the signal and noise expressions for the gyroscope, obtain the power spectral density based on the signal and noise expressions, and obtain the center frequency of the filter from the power spectral density; S2: Construct approximate conditions, and calculate the drift power spectral density and the reference velocity error power spectral density based on the approximate conditions and the power spectral density; Specifically, the gyroscope drift-related frequency, Schuler angular frequency, and velocity error-related frequency are determined, and the approximate conditions are constructed using the gyroscope drift-related frequency, Schuler angular frequency, and velocity error-related frequency. S3: Establish a reduced-order suboptimal filter using the filter center frequency, drift power spectral density, and reference velocity error power spectral density, and obtain the filter gain coefficient of the reduced-order suboptimal filter; S4: Calculate the speed error estimate based on the filter gain coefficient, obtain the speed estimate based on the speed error estimate, and obtain the correction torque based on the speed estimate; S5: Apply torque to the stabilizing platform by correcting the torque to eliminate the error angle of the stabilizing platform.

2. The method for eliminating the error angle of a stable platform according to claim 1, characterized in that, Step S1 further includes: S11: Determine the reference velocity error, accelerometer noise, and gyroscope drift; construct the signal expression and noise expression of the gyroscope based on the reference velocity error, accelerometer noise, and gyroscope drift. S12: Obtain the output expression based on the signal expression and noise expression, obtain the power spectral density through the output expression, and obtain the gyroscope drift power spectral density curve and velocity error power spectral density curve based on the power spectral density. S13: The frequency corresponding to the intersection of the gyroscope drift power spectral density curve and the velocity error power spectral density curve is taken as the center frequency of the filter.

3. The method for eliminating the error angle of a stable platform according to claim 1, characterized in that, Step S3 further includes: S31: Determine the gyroscope operating frequency based on the center frequency of the filter, and obtain the filter observations at the gyroscope operating frequency through the drift power spectral density and the reference velocity error power spectral density. S32: Determine the state transition matrix, noise input matrix, and measurement matrix; use the filter observations, state transition matrix, noise input matrix, and measurement matrix to establish the reduced-order suboptimal filter, and obtain the filter gain coefficient of the reduced-order suboptimal filter.

4. The method for eliminating the error angle of a stable platform according to claim 1, characterized in that, In step S4, the speed error estimate The calculation method is as follows: Where s is the complex frequency of the Laplace transform. Let be the first filter gain coefficient at time t. Let be the gain coefficient of the second filter at time t. Let be the gain coefficient of the third filter at time t. The Schuler angular frequency, For reference speed, This is the output of the accelerometer.

5. The method for eliminating the error angle of a stable platform according to claim 1, characterized in that, In step S5, the correction torque includes an eastward correction torque and a northward correction torque. The northward correction torque is used to correct the north-south error angle of the stable platform, and the eastward correction torque is used to correct the east-west error angle of the stable platform, thereby completing the elimination of the error angle of the stable platform.

6. A stable platform error angle elimination system, used to perform a stable platform error angle elimination method as described in any one of claims 1 to 5, characterized in that, include: Center frequency module: used to construct the signal and noise expressions of the gyroscope, obtain the power spectral density based on the signal and noise expressions, and obtain the center frequency of the filter from the power spectral density; Power spectral density module: used to construct approximate conditions, and calculate drift power spectral density and reference velocity error power spectral density based on the approximate conditions and power spectral density; Specifically, the gyroscope drift-related frequency, Schuler angular frequency, and velocity error-related frequency are determined, and the approximate conditions are constructed using the gyroscope drift-related frequency, Schuler angular frequency, and velocity error-related frequency. Filter gain coefficient module: used to establish a reduced-order suboptimal filter using the filter center frequency, drift power spectral density and reference velocity error power spectral density, and obtain the filter gain coefficient of the reduced-order suboptimal filter; Correction torque module: used to calculate the speed error estimate based on the filter gain coefficient, obtain the speed estimate from the speed error estimate, and obtain the correction torque from the speed estimate; Error Angle Elimination Module: Used to apply torque to the stabilizing platform by correcting the torque, thereby eliminating the error angle of the stabilizing platform.

7. An electronic 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 a stable platform error angle elimination method as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements a stable platform error angle elimination method as described in any one of claims 1 to 5.

9. A computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, characterized in that, When the program instructions are executed by the computer, the computer is able to perform a stable platform error angle elimination method as described in any one of claims 1 to 5.

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