Narrowband disturbance suppression method and system for adaptive optical system

Abstract

The invention discloses a narrowband disturbance suppression method and system suitable for a self-adaptive optical system, and the method comprises the steps: carrying out the modeling based on each effective narrowband disturbance, obtaining each narrowband disturbance model, carrying out the parameter identification of each narrowband disturbance model, obtaining the narrowband disturbance model parameter value of each narrowband disturbance model, and obtaining the narrowband disturbance model parameter value of each narrowband disturbance model; and according to the number of the effective narrowband disturbances and each narrowband disturbance model parameter value, calculating to obtain narrowband disturbance control parameters, according to the narrowband disturbance control parameters, constructing a linear quadratic Gaussian optimal controller, suppressing each narrowband disturbance through the linear quadratic Gaussian optimal controller, and when it is judged that there is narrowband disturbance in the system, determining that the narrowband disturbance exists in the system. The narrowband disturbance suppression module can quickly and effectively correct narrowband disturbance existing in the system, so that the influence of the narrowband disturbance is eliminated, the disturbance suppression performance of the adaptive optical system is improved, and the imaging quality of the optical system is improved.

Description

Technical Field

[0001] The present application belongs to the field of stability control, and in particular to a method and system for suppressing narrowband disturbances in an adaptive optical system. Background Art

[0002] Adaptive optics (AO) is a modern optical technology that detects and corrects dynamic optical distortion wavefronts in real time, thereby suppressing disturbance effects and improving the imaging quality of optical systems. The disturbances that cause phase distortion of light wavefronts include not only low-frequency broadband disturbances introduced by atmospheric turbulence, but also complex random narrowband disturbances introduced by various disturbance sources such as structural resonance or vibration devices of the system platform. These narrowband disturbances have diverse sources, complex frequency components, and some have time-varying characteristics, which have become an important factor affecting the imaging quality of optical systems.

[0003] The classical control method based on proportional-integral (PI) is widely used in adaptive optical systems because of its simple control law, independence from the system model, and good suppression effect on low-frequency turbulence disturbances. However, due to the limitations of its control law, the classical PI control cannot effectively suppress narrow-band disturbances in the system, and may even amplify them, greatly affecting the stability of the system. Summary of the invention

[0004] In order to overcome the defects of the prior art, the purpose of the present application is to provide a narrowband disturbance suppression method and system for an adaptive optical system, which can solve at least one of the above problems.

[0005] The first aspect of the present application provides a narrowband disturbance suppression method for an adaptive optical system, comprising the following steps: Acquire a disturbance signal, measure and process the disturbance signal to obtain open-loop slope data of the adaptive optical system; perform wavefront restoration on the open-loop slope data of the adaptive optical system to obtain wavefront distortion phase information; obtain the number of effective narrowband disturbances from the wavefront distortion phase information; perform modeling based on each effective narrowband disturbance to obtain each narrowband disturbance model; perform parameter identification on each narrowband disturbance model to obtain the narrowband disturbance model parameter value of each narrowband disturbance model; calculate the narrowband disturbance control parameters according to the number of effective narrowband disturbances and each narrowband disturbance model parameter value; construct a linear quadratic Gaussian optimal controller according to the narrowband disturbance control parameters, and suppress each narrowband disturbance through the linear quadratic Gaussian optimal controller.

[0006] In some implementations, the performing parameter identification on the narrowband disturbance model to obtain each narrowband disturbance model parameter value specifically includes: The standard particle swarm optimization algorithm is used to identify the narrowband perturbation model parameters to obtain each narrowband perturbation model parameter, where the narrowband perturbation model parameters include the vibration frequency of each narrowband perturbation f , damping coefficient , and the driving source variance σ 2 .

[0007] In some implementations, the narrowband disturbance control parameter is calculated according to the number of narrowband disturbances and the parameter value of each narrowband disturbance model, specifically including: According to the number of narrowband disturbances, the matrix dimension of the control parameters of the linear quadratic Gaussian optimal controller is determined; According to the matrix dimension and the vibration frequency of each narrowband perturbation f , damping coefficient and driving source variance σ 2 The model parameter values ​​are used to calculate the narrowband disturbance control parameters.

[0008] In some embodiments, the narrowband perturbation model is a second-order autoregressive model, and the specific model formula is:

[0009] in, is the disturbance signal, is the model error, , is the perturbation model coefficient, and the perturbation model system consists of the vibration frequency f , damping coefficient , vibration angular frequency w 0 and the driving source variance σ 2 The expression formula is as follows, where is the sampling period:

[0010] In some implementations, acquiring the number of effective narrowband disturbances from the wavefront distortion phase information includes: Estimate the power spectrum density of the disturbance signal to obtain the disturbance spectrum information, and convert the disturbance time domain signal into the disturbance frequency domain signal; Search the maximum and minimum values ​​in the disturbance power spectrum density curve to obtain all amplitude maxima and all amplitude minima; It is determined whether each maximum value obtained by the search is valid. If the ratio of the maximum value to its adjacent minimum value is greater than a first preset multiple, it is determined that there is a valid narrowband disturbance at the maximum value, so as to obtain the number of valid narrowband disturbances from the wavefront distortion phase information.

[0011] In some implementations, after obtaining the number of effective narrowband disturbances from the wavefront distortion phase information, the method further includes: Obtaining the number of effective narrowband disturbances, and judging whether narrowband disturbances exist according to the number of effective narrowband disturbances; When the number of effective narrowband disturbances is greater than 0, it is determined that narrowband disturbances exist in the disturbance signal; When the number of effective narrowband disturbances is 0, it is determined that there is no narrowband disturbance in the disturbance signal.

[0012] In some embodiments, if the ratio of the peak maximum value to its adjacent minimum value is greater than a first preset multiple, determining that there is an effective narrowband disturbance at the maximum value includes: If the ratio of the maximum value to its adjacent minimum value is greater than a first preset multiple, obtaining a disturbance spectrum signal of a corresponding frequency band between adjacent minimum values ​​of the maximum value obtained after searching; Performing linear interpolation on the obtained disturbance spectrum signal to obtain an interpolation value corresponding to the disturbance spectrum amplitude; The ratio of the disturbance spectrum amplitude to its corresponding interpolation value is calculated, and when the ratio is greater than a second preset multiple, it is determined that the peak maximum value is a valid narrowband disturbance.

[0013] In some embodiments, the transfer function used by the linear quadratic Gaussian optimal controller is expressed as:

[0014] Among them, the matrix M is the wavefront corrector response matrix N P The generalized inverse of P =[1,0,1,0,…], matrix I is the identity matrix, H ∞ is the Kalman filter gain matrix, C is the system measurement state coefficient matrix, D is the wavefront detector response matrix, A is the model parameter matrix, z is a complex variable, representing the frequency characteristics of the system.

[0015] In some embodiments, after the step of calculating the control parameters according to the model and constructing a linear quadratic Gaussian optimal controller to suppress narrowband disturbances, the method further includes: The wavefront distortion caused by non-narrowband disturbance is corrected by PI control method.

[0016] The second aspect of the present application also provides a narrowband disturbance identification and suppression system communication system for an adaptive optical system, including a processing module, a restoration module, an acquisition module, a modeling module, an identification module, a calculation module and a suppression module.

[0017] The processing module is used to obtain the disturbance signal, measure and process the disturbance signal to obtain the open-loop slope data of the adaptive optical system; the restoration module is used to perform wavefront restoration on the open-loop slope data of the adaptive optical system to obtain the wavefront distortion phase information; the acquisition module is used to obtain the number of effective narrowband disturbances from the wavefront distortion phase information; the modeling module is used to perform modeling based on each effective narrowband disturbance to obtain each narrowband disturbance model; the identification module is used to perform parameter identification on each narrowband disturbance model to obtain the narrowband disturbance model parameter value of each narrowband disturbance model; the calculation module is used to calculate the narrowband disturbance control parameters according to the number of effective narrowband disturbances and each narrowband disturbance model parameter value; the suppression module is used to construct a linear quadratic Gaussian optimal controller according to the narrowband disturbance control parameters, and suppress each narrowband disturbance through the linear quadratic Gaussian optimal controller.

[0018] Therefore, the present application has at least the following beneficial effects: when it is determined that narrowband disturbances exist in the system, the narrowband disturbance suppression module can quickly and effectively correct the narrowband disturbances existing in the system, thereby eliminating the influence of the narrowband disturbances, improving the disturbance suppression performance of the adaptive optical system, and further improving the imaging quality of the optical system.

[0019] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of a narrowband disturbance suppression method provided in an embodiment of the present application; Figure 2 is a schematic diagram of a narrowband disturbance suppression system provided in an embodiment of the present application; Figure 3 is a schematic diagram of a disturbance signal provided in an embodiment of the present application; Figure 4 A schematic diagram of an effective narrowband disturbance identification process provided in an embodiment of the present application; Figure 5 A schematic diagram of narrowband disturbance identification results provided in an embodiment of the present application; Figure 6 A time domain comparison diagram of disturbance suppression and pure PI correction provided in an embodiment of the present application; Figure 7 A frequency domain comparison diagram of disturbance suppression and pure PI correction provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] The following description provides specific application scenarios and requirements of this specification, with the purpose of enabling those skilled in the art to make and use the contents of this specification. Various local modifications to the disclosed embodiments will be apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of this specification. Therefore, this specification is not limited to the embodiments shown, but to the widest scope consistent with the claims.

[0022] The terms used herein are for the purpose of describing specific example embodiments only and are not intended to be limiting. For example, as used herein, the singular forms "a", "an", and "the" may also include the plural forms unless the context clearly indicates otherwise. The terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. However, it should also be understood that the drawings are for illustration and description purposes only and are not intended to limit the scope of this specification.

[0023] It should be noted that the embodiments of the present invention and the features in the embodiments may be combined with each other if there is no conflict in structure or function.

[0024] The present application is described in detail below through specific embodiments.

[0025] Based on the above, refer to Figure 1 to Figure 7 :The embodiment of the present application provides a narrowband disturbance suppression method for an adaptive optical system, comprising the following steps: S100, obtaining a disturbance signal, measuring and processing the disturbance signal to obtain open-loop slope data of the adaptive optical system; specifically, the disturbance signal can be measured by a wavefront sensor in the adaptive optical system, and processed to obtain open-loop slope data of the adaptive optical system or corrected residual disturbance slope data.

[0026] S200, performing wavefront restoration on the open-loop slope data of the adaptive optical system to obtain wavefront distortion phase information; wherein, the wavefront restoration method is not limited, as long as the wavefront distortion phase can be obtained, for example, the wavefront distortion phase represented by the Zernike mode coefficients well known to those skilled in the art.

[0027] S300, obtaining the number of effective narrowband disturbances from the wavefront distortion phase information; specifically, since the narrowband disturbance has the characteristics of narrow spectrum and high energy, the peak energy of the effective narrowband disturbance should be much larger than the adjacent minimum value and much larger than the noise energy; in addition, the effective narrowband disturbance should have an impact on the energy distribution of the measurement disturbance and be the main disturbance component of the measurement disturbance except for the broadband turbulence. Therefore, this characteristic can be used as a basis for judging the fast and effective narrowband disturbance.

[0028] S400, modeling each effective narrowband disturbance to obtain each narrowband disturbance model; S500, performing parameter identification on each narrowband disturbance model to obtain narrowband disturbance model parameter values ​​of each narrowband disturbance model; S600, calculating and obtaining narrowband disturbance control parameters according to the number of effective narrowband disturbances and each narrowband disturbance model parameter value; S700: construct a linear quadratic Gaussian optimal controller according to the narrowband disturbance control parameters, and suppress each narrowband disturbance by the linear quadratic Gaussian optimal controller.

[0029] In some implementations, performing parameter identification on the narrowband disturbance model to obtain each narrowband disturbance model parameter value specifically includes: The standard particle swarm optimization algorithm is used to identify the narrowband perturbation model parameters to obtain each narrowband perturbation model parameter, where the narrowband perturbation model parameters include the vibration frequency of each narrowband perturbation f , damping coefficient , and the driving source variance σ 2 The standard particle swarm optimization algorithm first establishes a beam jitter model; secondly, collects the beam jitter timing signal; thirdly, determines the identification error criterion function; then, uses the particle swarm algorithm to perform a global random search on the beam jitter model parameters, and then obtains the optimal parameters of the model, thereby realizing intelligent optimization of the model parameters. It should be noted that this application is not an improvement on the model parameter identification algorithm, and will not be repeated here.

[0030] In some implementations, the narrowband disturbance control parameter is calculated according to the number of narrowband disturbances and the parameter value of each narrowband disturbance model, specifically including: According to the number of narrowband disturbances, the matrix dimension of the control parameters of the quadratic Gaussian optimal controller is determined; According to the matrix dimension and the vibration frequency of each narrowband perturbation f , damping coefficient and driving source variance σ 2 The narrowband disturbance control parameters are calculated based on the model parameter values ​​of the narrowband disturbances obtained by parameter identification. The control parameters are calculated based on the model parameters of each narrowband disturbance obtained by parameter identification; wherein the narrowband disturbance control parameters include: the model parameter matrix A , model error covariance matrix Σ V , measurement noise variance , and the Kalman filter gain matrix H ∞ , calculated as follows: Since linear quadratic Gaussian control is a control method based on a state space model, the state space model of narrowband disturbances in the adaptive optical system can be expressed as:

[0031] Among them, the model error matrix V It is represented by the driving source signal corresponding to each narrow-band disturbance component, The matrix dimension is determined by the number of narrowband perturbations. For example, if the number of perturbations is N, the matrix dimension is 2N×1. Model error covariance matrix Σ V The variance σ of each narrowband disturbance driving source obtained by the identification step is 2 Calculated.

[0032] matrix A is the model parameter matrix representing the narrowband perturbation, with a size of 2N×2N. The vibration frequencies of each narrowband perturbation obtained by identification are f and the damping coefficient Calculated.

[0033] The specific form is as follows: Model parameter matrix , Model error covariance matrix .

[0034] Measurement noise variance: According to the relationship between the unilateral power spectrum density of the white noise signal and its variance, the variance of the measurement noise can be estimated as ,in To estimate the power spectral density of the measurement noise, is the system sampling frequency, wherein the estimation method of the measurement noise power spectral density is not limited, for example, the Welch method well known to those skilled in the art is used.

[0035] Kalman filter gain matrix H ∞ The calculation formula is:

[0036] in ,matrix C = D [0, 1, 0, 1, …] 2N is the system measurement state coefficient matrix, D is the wavefront detector response matrix.

[0037] In some embodiments, when it is determined that there is a narrowband disturbance in the signal, the narrowband disturbance is suppressed by a narrowband disturbance suppression module. According to the narrowband disturbance characteristics, the narrowband disturbance is usually modeled as a second-order autoregressive model. The specific model formula is:

[0038] in, is the disturbance signal, is the model error, , is the perturbation model coefficient, , The disturbance characteristic parameters with physical significance can be used, and the disturbance model system consists of the vibration frequency f , damping coefficient , vibration angular frequency w 0 and driving source variance σ 2 The expression formula is as follows, where is the sampling period:

[0039] In some implementations, obtaining the number of effective narrowband disturbances from wavefront distortion phase information includes the following steps: Estimate the power spectral density of the disturbance signal to obtain the disturbance spectrum information, and convert the disturbance time domain signal into a disturbance frequency domain signal; specifically, estimate the power spectral density of the measured disturbance signal, convert the disturbance time domain signal into a frequency domain signal, and obtain the spectrum representation of the disturbance signal, wherein the power spectral density estimation method of the signal can be used in a manner well known to those skilled in the art, and is not limited here The maximum and minimum values ​​in the disturbance power spectrum density curve are searched to obtain all amplitude maxima and all amplitude minima; wherein the method for searching the maximum and minimum values ​​is not limited, for example, a line search method well known to those skilled in the art is used.

[0040] It is determined whether each maximum value obtained by the search is valid. If the ratio of the maximum value to its adjacent minimum value is greater than a first preset multiple, it is determined that there is a valid narrowband disturbance at the maximum value, so as to obtain the number of valid narrowband disturbances from the wavefront distortion phase information.

[0041] Specifically, the amplitude maximum and minimum in the disturbance power spectrum density curve are searched, and when the maximum peak value is set to be α times greater than the smaller value of its two adjacent minimum values, where α is generally set to be no less than 5, it can be quickly determined that the maximum value is the corresponding narrowband disturbance peak.

[0042] In some implementations, the number of effective narrowband disturbances is obtained from the wavefront distortion phase information, and then the following steps are further included: The number of effective narrowband disturbances is obtained, and whether there is narrowband disturbance is determined according to the number of effective narrowband disturbances; wherein, when the number of effective narrowband disturbances is greater than 0, it is determined that there is narrowband disturbance in the disturbance signal, and the number of effective narrowband disturbances is the number of narrowband disturbances, the number of narrowband disturbances is obtained, and each narrowband disturbance model is obtained based on modeling of each narrowband disturbance; when the number of effective narrowband disturbances is 0, it is determined that there is no narrowband disturbance in the disturbance signal, and the wavefront corrector is directly controlled by the PI control method to correct the wavefront distortion caused by the disturbance. Therefore, a new control loop is formed by introducing narrowband disturbance judgment and narrowband disturbance suppression in the adaptive optical control system to facilitate the suppression of narrowband disturbances.

[0043] Furthermore, since the estimated power spectrum density curve is rough and has many burrs, the maximum disturbance peak obtained by quick judgment is not completely accurate, and further judgment of the effective narrowband disturbance is required. If the ratio of the amplitude maximum value to its adjacent minimum value is greater than the first preset multiple, it is determined that there is an effective narrowband disturbance at the maximum value, including: If the ratio of the maximum value to its adjacent minimum value is greater than a first preset multiple, obtaining a disturbance spectrum signal of a corresponding frequency band between adjacent minimum values ​​of the maximum value obtained after searching; Performing linear interpolation on the obtained disturbance spectrum signal to obtain an interpolation value corresponding to the disturbance spectrum amplitude; The ratio of the disturbance spectrum amplitude to its corresponding interpolation value is calculated. When the ratio is greater than the second preset multiple, it is determined that there is an effective narrowband disturbance at the peak maximum value. The second preset multiple should generally be no less than 2, and the frequency range between the frequency values ​​corresponding to the two adjacent minimum values ​​is the frequency range where the narrowband disturbance exists.

[0044] Therefore, the composite narrowband disturbances with overlapping narrowband disturbance amplitudes due to very close vibration frequencies can be further distinguished, and the number of narrowband disturbances and the frequency range corresponding to the narrowband disturbances can be obtained more accurately.

[0045] In some implementations, a linear quadratic Gaussian optimal controller is constructed according to the determined narrowband disturbance control parameters to suppress the narrowband disturbance. Specifically, the transfer function of the linear quadratic Gaussian controller is expressed as:

[0046] Among them, the matrix M is the wavefront corrector response matrix N P The generalized inverse of ,matrix P =[1,0,1,0,…], matrix I is the identity matrix, H ∞is the Kalman filter gain matrix, C is the system measurement state coefficient matrix, D is the wavefront detector response matrix, z is a complex variable, representing the frequency characteristics of the system.

[0047] In some embodiments, when it is determined that there is no narrowband disturbance in the system, the wavefront corrector is directly controlled by the PI control method to correct the wavefront distortion caused by the disturbance; when there is a narrowband disturbance in the system, the narrowband disturbance is first effectively suppressed by narrowband disturbance suppression, and then the wavefront corrector is controlled by the PI control method to correct the wavefront distortion caused by non-narrowband disturbance.

[0048] Therefore, the present application proposes a narrowband disturbance suppression method suitable for an adaptive optical system, by introducing narrowband disturbance judgment and narrowband disturbance suppression into an adaptive optical control system to form a new control loop, wherein the narrowband disturbance judgment quickly determines whether there is a narrowband disturbance in the system by separating the narrowband disturbance spectrum information, and when it is determined that there is a narrowband disturbance in the system, the narrowband disturbance suppression module designs a disturbance controller control parameter to quickly and effectively correct the narrowband disturbance in the system, thereby eliminating the influence of the narrowband disturbance, improving the disturbance suppression performance of the adaptive optical system, and further improving the imaging quality of the optical system.

[0049] In addition, when there is a narrowband disturbance that varies with time in the system, the time-varying narrowband disturbance can be effectively suppressed by updating the narrowband disturbance judgment module and the narrowband disturbance suppression module.

[0050] The second aspect of the present application also provides a narrowband disturbance suppression system for an adaptive optical system, see Figure 2 , including a processing module 100 , a restoration module 110 , an acquisition module 120 , a modeling module 130 , an identification module 140 , a calculation module 150 and a suppression module 160 .

[0051] Among them, the processing module 100 is used to obtain the disturbance signal, measure and process the disturbance signal to obtain the open-loop slope data of the adaptive optical system; the restoration module 110 is used to perform wavefront restoration on the open-loop slope data of the adaptive optical system to obtain the wavefront distortion phase information; the acquisition module 120 is used to obtain the number of effective narrowband disturbances from the wavefront distortion phase information; the modeling module 130 is used to perform modeling based on each effective narrowband disturbance to obtain each narrowband disturbance model; the identification module 140 is used to perform parameter identification on each narrowband disturbance model to obtain the narrowband disturbance model parameter value of each narrowband disturbance model; the calculation module 150 is used to calculate the narrowband disturbance control parameters according to the number of effective narrowband disturbances and each narrowband disturbance model parameter value; the suppression module 160 is used to construct a linear quadratic Gaussian optimal controller according to the narrowband disturbance control parameters, and suppress each narrowband disturbance through the linear quadratic Gaussian optimal controller.

[0052] Exemplarily, in a specific embodiment, the open-loop slope data of the adaptive optical system is measured by a wavefront sensor in the adaptive optical system, wherein the sampling frequency may be set to 3400 Hz; Then, the distorted wavefront is restored by the Zernike mode restoration method, and the wavefront distortion phase represented by the Zernike mode coefficient is obtained; Then, a narrowband disturbance judgment module is used to quickly judge whether there is narrowband disturbance in the measured disturbance signal. The narrowband disturbance judgment module includes the following steps: First, the Welch method is used to estimate the power spectrum density of the measured disturbance signal, such as Figure 3 As shown, the disturbance time domain signal is converted into a frequency domain signal to obtain a spectrum representation of the disturbance signal; Then, the line search method is used to search for the amplitude maximum and minimum in the disturbance spectrum signal, and it is set that when the maximum value is greater than 5 times the smaller value of its two adjacent minimum values, the maximum value can be quickly judged as the corresponding narrowband disturbance peak.

[0053] Then, the effective narrowband disturbance is judged, and the corresponding spectrum of the quickly judged narrowband disturbance is linearly interpolated. It is set that when the power spectrum amplitude of the narrowband disturbance is greater than twice the corresponding linear interpolation, it is judged as an effective narrowband disturbance, and the frequency range between the corresponding frequency values ​​of its two adjacent minimum values ​​is the frequency segment where the narrowband disturbance exists.

[0054] Hence, see Figure 5 , the red part is the effective narrowband perturbation separated after narrowband perturbation judgment, where the number of narrowband perturbations N is 2.

[0055] Due to the existence of narrowband disturbances, it is necessary to suppress the narrowband disturbances through a narrowband disturbance suppression module, wherein the narrowband disturbance suppression method is designed based on the linear quadratic Gaussian optimal control theory, and the narrowband disturbance suppression module includes the following steps: Narrowband disturbance modeling, according to the characteristics of narrowband disturbance, narrowband disturbance is usually modeled as a second-order autoregressive model, specifically:

[0056] in is the disturbance signal, is the model error, , is the disturbance model coefficient, and the physical disturbance characteristic parameter, namely the vibration frequency, can be used f , damping coefficient , vibration angular frequency w 0 and the driving source variance σ 2 The specific expression formula is as follows:

[0057] in is the sampling period.

[0058] Then, the standard particle swarm optimization algorithm is used to identify the narrowband perturbation model parameters to obtain the model parameter values ​​corresponding to each narrowband perturbation. The obtained model parameters include the vibration frequency of each narrowband perturbation. f , damping coefficient , and the driving source variance σ 2 .

[0059] Then, the control parameter matrix dimension of the optimal controller is determined according to the number of narrowband disturbances 2 and the model parameter values ​​of each narrowband disturbance obtained by identification are used to calculate the control parameters; the narrowband disturbance control parameters include the model parameter matrix A , model error covariance matrix Σ V , measurement noise variance , and the Kalman filter gain matrix H ∞ , the calculation process is as follows: Since linear quadratic Gaussian control is a control method based on a state space model, the state space model of narrowband disturbances in the adaptive optical system can be expressed as:

[0060] Among them, the model error matrix V It is represented by the driving source signal corresponding to each narrow-band disturbance component, The matrix size is 4×1, the model error covariance matrix ΣV The variance σ of each narrowband disturbance driving source can be obtained by identification 2 Calculated; Matrix A is the model parameter matrix representing the narrowband perturbation, with a size of 4×4. The vibration frequencies of each narrowband perturbation obtained by identification are f and the damping coefficient The calculation results are as follows: Model parameter matrix

[0061] Model error covariance matrix

[0062] Measurement noise variance: According to the relationship between the unilateral power spectrum density of the white noise signal and its variance, the variance of the measurement noise can be estimated as ,in To estimate the power spectral density of the measurement noise, is the system sampling frequency.

[0063] When the frequency is higher than a certain value, the disturbance signal will be buried in the noise. At this time, the measurement noise becomes the dominant signal. In this embodiment, the noise frequency is set to fw=fs / 3 , and assume that when the frequency is greater than f When the signal contains only noise signal. Therefore, the estimation of noise power spectrum density, that is, the frequency range ( f>fw ) is the average of the power spectral density within .

[0064] Kalman filter gain matrix H ∞ :

[0065] in , matrix C = D [0, 1, 0, 1] is the system measurement state coefficient matrix, D is the wavefront detector response matrix. In this embodiment, it is assumed that the wavefront detector has a linear response, that is, the wavefront detector response matrix D is 1.

[0066] According to the calculated narrow-band disturbance control parameters, a linear quadratic Gaussian optimal controller is constructed. The transfer function of the linear quadratic Gaussian controller is expressed as:

[0067] Among them, the matrix P =[1,0,1,0], matrix M is the wavefront corrector response matrix N P The generalized inverse of Right now ,matrix I is the unit matrix. This embodiment assumes that the wavefront corrector has a linear response, that is, the wavefront corrector response matrix is N P is 1.

[0068] Thereby, the narrowband disturbance is suppressed. After the narrowband disturbance is effectively suppressed by the narrowband disturbance suppression module, the wavefront corrector is controlled by the PI control method to correct the wavefront distortion caused by the non-narrowband disturbance.

[0069] See also Figure 6 , Figure 6 This is a time domain comparison diagram of the method of this application before and after suppressing narrowband disturbances and before and after suppressing narrowband disturbance signals only through PI control, where the PI control gain parameter is the optimal gain. Figure 6 It can be seen that, through the method proposed in this application, the residual RMS value after the overall disturbance correction is 0.5545urad, of which 72.22% of the disturbance is effectively suppressed, while the residual RMS value after the overall disturbance correction of PI control alone is 1.0085urad, of which only 49.48% of the disturbance is effectively suppressed, and the disturbance suppression effect is improved by about 1.46 times.

[0070] See also Figure 7 , Figure 7 This is a frequency domain comparison diagram of the method used in this case before and after suppressing narrowband disturbances and before and after suppressing narrowband disturbance signals only through PI control. Figure 7 It can be seen that the disturbance identification and suppression method proposed in this application has obvious suppression effect on the two narrowband disturbances, among which the amplitude of the narrowband disturbance with a vibration center frequency of 299Hz is reduced from 1.73e-3dB before correction to 7.54e-5dB after correction, and the amplitude of the narrowband disturbance with a vibration center frequency of 520Hz is reduced from 1.87e-3dB before correction to 1.92e-5dB after correction. The vibration amplitudes of the two narrowband disturbances are both reduced by about two orders of magnitude. However, only PI control has no suppression effect on the narrowband disturbances existing in the system, and even amplifies the frequency spectra of the two narrowband disturbances.

[0071] The above is a description of a specific embodiment of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require a specific order or a continuous order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0072] In addition, certain terms in this specification have been used to describe embodiments of this specification. For example, "one embodiment", "an embodiment" and / or "some embodiments" mean that a particular feature, structure or characteristic described in conjunction with the embodiment may be included in at least one embodiment of this specification. Therefore, it can be emphasized and should be understood that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various parts of this specification do not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics may be appropriately combined in one or more embodiments of this specification.

[0073] Finally, it should be understood that the embodiments of the application disclosed herein are explanations of the principles of the embodiments of this specification. Other modified embodiments are also within the scope of this specification. Therefore, the embodiments disclosed in this specification are only used as examples and not as limitations. Those skilled in the art can adopt alternative configurations according to the embodiments in this specification to implement the application in this specification. The embodiments of this specification are not limited to the embodiments accurately described in the application.

Claims

1. A narrowband disturbance suppression method for an adaptive optical system, characterized in that: include: Acquire a disturbance signal, and measure and process the disturbance signal to obtain open-loop slope data of the adaptive optical system; Perform wavefront restoration on the open-loop slope data of the adaptive optical system to obtain the wavefront distortion phase information; Obtain the number of effective narrowband disturbances from the wavefront distortion phase information; Modeling is performed based on each effective narrow-band disturbance to obtain each narrow-band disturbance model; Performing parameter identification on each narrowband perturbation model to obtain narrowband perturbation model parameter values ​​of each narrowband perturbation model; According to the number of effective narrowband disturbances and the parameter value of each narrowband disturbance model, the narrowband disturbance control parameter is calculated; A linear quadratic Gaussian optimal controller is constructed according to the narrow-band disturbance control parameters, and each narrow-band disturbance is suppressed by the linear quadratic Gaussian optimal controller.

2. According to the narrowband disturbance suppression method for an adaptive optical system according to claim 1, the step of performing parameter identification on the narrowband disturbance model to obtain each narrowband disturbance model parameter value specifically comprises: The standard particle swarm optimization algorithm is used to identify the narrowband perturbation model parameters to obtain each narrowband perturbation model parameter, where the narrowband perturbation model parameters include the vibration frequency of each narrowband perturbation f , damping coefficient , and the driving source variance σ 2 .

3. The narrowband disturbance suppression method for an adaptive optical system according to claim 2, characterized in that: The narrowband disturbance control parameter is calculated according to the number of effective narrowband disturbances and the parameter value of each narrowband disturbance model, specifically including: According to the number of effective narrowband disturbances, the matrix dimension of the control parameters of the linear quadratic Gaussian optimal controller is determined; According to the matrix dimension and the vibration frequency of each narrowband perturbation f , damping coefficient and driving source variance σ 2 The model parameter values ​​are used to calculate the narrowband disturbance control parameters.

4. The narrowband disturbance suppression method for an adaptive optical system according to claim 1, characterized in that: The feature is that The narrowband perturbation model is a second-order autoregressive model, and the specific model formula is: in, is the disturbance signal, is the model error, , is the perturbation model coefficient, and the perturbation model system consists of the vibration frequency f , damping coefficient , vibration angular frequency w 0 and driving source variance σ 2 The expression formula is as follows, where is the sampling period:

5. The narrowband disturbance suppression method for an adaptive optical system according to claim 1, characterized in that: The step of obtaining the number of effective narrowband disturbances from the wavefront distortion phase information comprises: Estimate the power spectrum density of the disturbance signal to obtain the disturbance spectrum information, and convert the disturbance time domain signal into the disturbance frequency domain signal; Search the maximum and minimum values ​​in the disturbance power spectrum density curve to obtain all amplitude maxima and all amplitude minima; It is determined whether each maximum value obtained by the search is valid. If the ratio of the maximum value to its adjacent minimum value is greater than a first preset multiple, it is determined that there is a valid narrowband disturbance at the maximum value, so as to obtain the number of valid narrowband disturbances from the wavefront distortion phase information.

6. The narrowband disturbance suppression method for an adaptive optical system according to claim 5, characterized in that: After obtaining the number of effective narrowband disturbances from the wavefront distortion phase information, it also includes: Obtaining the number of effective narrowband disturbances, and judging whether narrowband disturbances exist according to the number of effective narrowband disturbances; When the number of effective narrowband disturbances is greater than 0, it is determined that narrowband disturbances exist in the disturbance signal; When the number of effective narrowband disturbances is 0, it is determined that there is no narrowband disturbance in the disturbance signal.

7. The narrowband disturbance suppression method for an adaptive optical system according to claim 5, characterized in that: If the ratio of the maximum value to its adjacent minimum value is greater than a first preset multiple, determining that there is an effective narrowband disturbance at the maximum value includes: If the ratio of the maximum value to its adjacent minimum value is greater than a first preset multiple, obtaining a disturbance spectrum signal of a corresponding frequency band between adjacent minimum values ​​of the maximum value obtained after searching; Performing linear interpolation on the obtained disturbance spectrum signal to obtain an interpolation value corresponding to the disturbance spectrum amplitude; The ratio of the disturbance spectrum amplitude to its corresponding interpolation value is calculated, and when the ratio is greater than a second preset multiple, it is determined that the peak maximum value is a valid narrowband disturbance.

8. The narrowband disturbance suppression method for an adaptive optical system according to claim 3, characterized in that: The transfer function adopted by the linear quadratic Gaussian optimal controller is expressed as: Among them, the matrix M is the wavefront corrector response matrix N P The generalized inverse of P =[1,0,1,0,…], matrix I is the identity matrix, H ∞ is the Kalman filter gain matrix, C is the system measurement state coefficient matrix, D is the wavefront detector response matrix, A is the model parameter matrix, z is a complex variable, representing the frequency characteristics of the system.

9. The narrowband disturbance suppression method for an adaptive optical system according to claim 4, characterized in that: After the step of calculating the control parameters according to the model and constructing a linear quadratic Gaussian optimal controller to suppress narrowband disturbances, the method further includes: The wavefront distortion caused by non-narrowband disturbance is corrected by PI control method.

10. A narrowband disturbance suppression system for an adaptive optical system, characterized in that: A processing module is used to obtain a disturbance signal, measure and process the disturbance signal to obtain open-loop slope data of the adaptive optical system; A restoration module is used to perform wavefront restoration on the open-loop slope data of the adaptive optical system to obtain wavefront distortion phase information; An acquisition module, used for acquiring the number of effective narrowband disturbances from wavefront distortion phase information; A modeling module, used for modeling each effective narrow-band disturbance to obtain each narrow-band disturbance model; An identification module, used for performing parameter identification on each narrowband disturbance model to obtain narrowband disturbance model parameter values ​​of each narrowband disturbance model; A calculation module, used for calculating the narrowband disturbance control parameter according to the number of effective narrowband disturbances and the parameter value of each narrowband disturbance model; The suppression module is used to construct a linear quadratic Gaussian optimal controller according to the narrow-band disturbance control parameters, and suppress each narrow-band disturbance through the linear quadratic Gaussian optimal controller.

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