A method and apparatus for real-time nonlinear calibration of a single-photon detector

Abstract

This invention relates to the field of photodetector calibration technology, and more particularly to a real-time nonlinear calibration method and apparatus for a single-photon detector. The method uses a relay circuit to enable the photodetector to simultaneously output an analog voltage signal and a photon pulse signal. Synchronous acquisition of the analog voltage signal and photon pulse signal is achieved through an analog acquisition unit and a photon counting unit. A data processing unit preprocesses the two signals and outputs a nonlinear correction factor curve. The apparatus for executing the above method is also disclosed, which can effectively achieve nonlinear correction of the photodetector under different temperature conditions, ensure the accuracy of photon counting within different dynamic response ranges, and significantly improve the overall performance of the photodetector and measuring instruments.

Description

Technical Field

[0001] This invention relates to the field of photoelectric detector calibration technology, and in particular to a real-time nonlinear calibration method and apparatus for a single-photon detector. Background Technology

[0002] Photodetectors have important applications in fields such as lidar remote sensing, optical communication, and radiation detection. Currently, common single-photon level detectors mainly include avalanche photodiodes (APDs), photomultiplier tubes (PMTs), and superconducting detectors. These devices generally exhibit nonlinear response problems in practical operation. Furthermore, the response characteristics of photodetectors are closely related to temperature conditions, and the temperature-dependent mechanisms and degrees of influence vary significantly among different types of detectors.

[0003] When the detector operates within its linear range, its output signal is directly proportional to the input light intensity. However, once the response exceeds the linear operating range, the relationship becomes non-linear, and the deviation intensifies as the output signal increases. Without real-time calibration, the measurement accuracy of the detection system will be directly affected. This is especially true in the field of lidar remote sensing, where photodetectors require a wide dynamic response range. Lidar, as an outdoor device, often faces complex and changing temperature environments. Using a fixed calibration coefficient will introduce significant measurement errors at different temperatures.

[0004] Therefore, how to achieve real-time calibration of the nonlinear response of photodetectors and maintain high-precision measurement under different temperature conditions remains a key problem that urgently needs to be solved in current photodetector calibration technology. Summary of the Invention

[0005] The purpose of this invention is to provide a real-time nonlinear calibration method and apparatus for single-photon detectors, which dynamically corrects the response deviation of the detector caused by its own nonlinearity and temperature changes, thereby ensuring the accuracy of its measurements in a wide dynamic range and variable temperature environment.

[0006] To achieve the above objectives, this invention provides a real-time nonlinear calibration method for a single-photon detector, the specific steps of which are as follows: Step S1: First, the laser emits a pulsed laser beam and simultaneously outputs a trigger synchronization signal. The receiving telescope collects the atmospheric backscattered echo signal, which is then converged, filtered, and enters the photodetector. Step S2: The optical signal is converted into an electrical signal by a photodetector, and the analog signal and the photon pulse signal are synchronously output via a relay circuit; Step S3: Under the action of the laser synchronization trigger signal, the synchronously output analog signal and photon pulse signal are uploaded to the host computer for data preprocessing; Step S4: Perform multiple difference compensation and nonlinear correction factor fitting on the preprocessed signal to obtain the correction factor; Step S5: Perform real-time nonlinear correction on the photon signal collected by the single-photon detector using a correction factor, and dynamically construct a curve relating the output photon counting rate to the correction coefficient.

[0007] Preferably, step S2 is as follows: Step S21: The photocurrent signal output by the photodetector is converted into a photovoltage signal by the transimpedance amplifier; Step S22: After the photovoltage signal passes through two parallel amplifier circuits, analog voltage echo signals are acquired and photons are counted. The amplifier circuit includes two stages of non-inverting amplifiers connected in series, with the first stage non-inverting amplifier connected to a follower; Analog voltage echo signals are acquired using an analog signal acquisition card; Photons are counted and accumulated through a photon counting unit. A processing circuit module is set between the photon counting unit and the amplifier circuit. The processing circuit module outputs a TTL photon pulse signal, which is then counted and accumulated by the photon counting unit at different distances. The processing circuit module includes a comparator and a D flip-flop. The input of the comparator is connected to the output of the amplifier circuit, and the output of the comparator is connected to the photon counting unit and the D flip-flop. The D flip-flop is connected to the photon counting unit.

[0008] Preferably, in step S3, data preprocessing includes background baseline removal and signal noise removal.

[0009] Preferably, step S4 is as follows: Step S41: By performing adaptive weighted correlation analysis and amplitude compensation on the preprocessed analog voltage accumulation sequence signal and photon pulse accumulation sequence signal, the correlation coefficient is calculated by sliding window average. The window with the highest correlation between the two signals is summed and averaged, and then divided to compensate for the multiple difference between the two signals. Step S42: The compensated signal is used to extract the correction factor through the division operation of the two signals, and a nonlinear mapping relationship between the photon counting rate and the correction coefficient is established.

[0010] Preferably, step S41 is as follows: Step S411: Calculate the local mean of the two signals. The calculation formula is as follows: ; ; in, For the first The sliding window is the local mean of the initial analog voltage accumulation sequence signal. For window length, For the first A sequence of analog voltage signal accumulations; For the first Each sliding window represents the local mean of the initial photon pulse accumulation sequence signal. For the first A sequence of photon pulse accumulation signals; Step S412: Calculate the adaptive weights based on the local means of the two signals. The calculation formula is as follows: ; ; ; in, Characterizing the first The difference in the mean values ​​of the two signals within a sliding window. This represents the total number of sampling points. For the first The difference in the mean values ​​of the two signals within a sliding window. For sensitivity adjustment parameters, A constant that is greater than zero. and The first The standard deviation of the simulated voltage accumulation sequence signal and the photon pulse accumulation sequence signal in a sliding window; and The first The standard deviation of the simulated voltage accumulation sequence signal and the photon pulse accumulation sequence signal in a sliding window; Step S413: Calculate the weighted covariance and weighted correlation coefficient of the two signals within each window; Weighted covariance The calculation formula is as follows: ; Weighted correlation coefficient The calculation formula is as follows: ; Step S414: Determine the optimal window index corresponding to the maximum weighted correlation coefficient. The expression is as follows: ; in, To traverse all A function that takes the maximum value of the independent variable; Step S415: Within the optimal window, sum and average the two signals respectively, then divide them to obtain the global amplitude compensation factor. The calculation formula is as follows: ; and Each of the following is the first The sliding window represents the local mean of the analog voltage accumulation sequence signal and the local mean of the photon pulse accumulation sequence signal. Step S416: Use Photon pulse accumulation signal Amplitude compensation is performed to match the analog voltage accumulation signal. The amplitude levels are matched to obtain the compensated signal. The compensation formula is as follows: .

[0011] Preferably, step S42 is as follows: Step S421: Calculate the instantaneous correction factor at each moment by performing point-by-point division on the two signals. The calculation formula is as follows: ; in, For the first One instantaneous correction factor, A constant that is greater than zero; Step S422: Remove data points, the expression is as follows: The amplitude threshold filtering formula is as follows: ; in, This is the relative amplitude threshold parameter. The set of data points that meet the amplitude threshold. It is the global maximum value; The formula for eliminating local volatility is as follows: ; in, Indicates correspondence The local neighborhood, and These are the mean and standard deviation of the correction factor within the neighborhood, respectively. As the stability threshold, A set of data points that conforms to local volatility; valid data point set as follows: ; Step S423: Binate and aggregate the data within the effective data point set according to the photon counting rate; Using photon pulse accumulation signal As a measure of photon counting rate; ; in, The photon counting rate; An adaptive binning method based on data density is adopted, firstly determining the number of bins. The calculation formula is as follows: ; in, To determine the number of valid data points, the boundary is determined using the quantile method, as shown in the following expression: ; in, For the first The boundary values ​​of each bin. It is a quantile function; For the Each box contains: ; ; ; ; in, For the first A set of data points that satisfy the boundary conditions in each bin. For the first The boundary values ​​of each bin. and The first The arithmetic mean of the photon counting rate within each sub-box and the arithmetic mean of the instantaneous correction factor For the first Number of sample points in each bin For the first Standard deviation of each bin; Step S424: Considering the nonlinear characteristics of the photon counting system, the correction relationship is established using a piecewise polynomial model as follows: ; in, For nonlinear inflection point threshold, and These are the orders of the first and second piecewise polynomials, respectively. For model parameters, and These are the coefficients of the first polynomial and the coefficients of the second polynomial, respectively. For variables powers of; The model parameters are solved using the weighted least squares method as follows: ; in, For regularization terms, The regularization coefficient is . As weight, ; For a constant greater than zero, the constraints are as follows: ; Step S425: Model Validation and Uncertainty Quantification. Leave-one-out cross-validation is used to evaluate the model's generalization ability, as shown in the following expression: ; in, To account for the mean squared error of cross-validation, Indicates exclusion of the first The model after binning; Calculate the confidence interval of the prediction correction factor The expression is as follows: ; in, The number of model parameters, To predict the standard deviation, For piecewise polynomial models in The predicted value at that location, This is the critical value of the t-distribution; ; in, for The corresponding feature vector, To design the matrix, This is the weight matrix. Piecewise polynomial model The predicted value at that location.

[0012] Preferably, in step S5, the real-time acquired photon pulse accumulation signal is... Using real-time correction factor Real-time correction is performed, and the corrected photon pulse accumulated signal value is obtained. for: ; When signal characteristic drift or correction residual exceeds a set threshold is detected, a recalibration process is automatically triggered. ; in, This is the tolerance threshold. The result of the judgment to trigger recalibration For the monitoring cycle.

[0013] An apparatus for performing the above-described real-time nonlinear calibration method for a single-photon detector includes: The excitation and receiving unit is used to generate excitation signals and receive scattered echo signals. The excitation and receiving unit includes a laser that emits pulsed laser beams and a receiving telescope that collects atmospheric backscattered echo signals. A photodetector is used to convert optical signals into electrical signals; the photodetector is connected to a receiving telescope. Relay circuit, used for the synchronous output of analog signals and photon pulse signals; The analog acquisition unit is used to acquire analog voltage echo signals. The photon counting unit is used to count and accumulate photon pulses under different distance gates; Both the analog acquisition unit and the photon counting unit are connected to the relay circuit; The host computer is used for data preprocessing, performing real-time nonlinear correction on the photon signals collected by the single-photon detector, and dynamically constructing the relationship curve between the output photon counting rate and the correction coefficient; both the analog acquisition unit and the photon counting unit are connected to the host computer.

[0014] Therefore, the present invention employs the above-mentioned real-time nonlinear calibration method and apparatus for single-photon detectors, which has the following beneficial effects: (1) By real-time monitoring and compensation of the nonlinear response and temperature drift of the photodetector, the inherent error of the traditional fixed calibration coefficient in the variable temperature and variable light intensity scenario is overcome, so that the lidar can still maintain high precision and stable measurement of atmospheric parameters under complex outdoor climate conditions, fundamentally improving the environmental adaptability and data reliability of the system.

[0015] (2) By precisely correcting the nonlinear response, this invention enables the detector to maintain linear operation over a wider range of light intensity. This directly enhances the lidar system's ability to simultaneously detect targets of varying distances and intensities, avoiding information loss caused by signal nonlinear response distortion, thereby improving the integrity and accuracy of remote sensing. It is applicable to various mainstream detector types such as APD and PMT, providing flexible and universal technical support for detector selection and performance optimization in lidar and other equipment.

[0016] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0017] Figure 1This is a flowchart of a real-time nonlinear calibration method for a single-photon detector; Figure 2 This is a block diagram illustrating the design principle of the relay circuit section of the device; Figure 3 It is a real-time output of the correction factor curve at a temperature of +15℃ (±1℃); Figure 4 It is a real-time output correction factor curve at a temperature of -10℃ (±1℃); Figure 5 This is a comparison of photon pulse signal sequences before and after nonlinear correction at a temperature of +15℃ (±1℃). Figure 6 This is a comparison of photon pulse signal sequences before and after nonlinear correction at a temperature of -10℃ (±1℃). Figure 7 This is a comparison chart of the original photon signal sequence after correction with fixed and dynamic correction coefficients; Figure 8 This is an error analysis diagram between fixed correction coefficients and dynamic correction coefficients. Detailed Implementation

[0018] In the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product is in use. They are used only for the convenience of describing the 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 invention. In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," and "connect" 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; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0019] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0020] like Figure 1 As shown, a real-time nonlinear calibration method for a single-photon detector includes the following steps: Step S1: First, the laser emits a pulsed laser beam and simultaneously outputs a trigger synchronization signal. The receiving telescope collects the atmospheric backscattered echo signal, which is then converged, filtered, and enters the photodetector.

[0021] Step S2: The optical signal is converted into an electrical signal by a photodetector, and the analog signal and photon pulse signal are synchronously output via a relay circuit. The relay circuit is as follows: Figure 2 As shown.

[0022] Step S21: The photocurrent signal output by the photodetector is converted into a photovoltage signal by the transimpedance amplifier; Step S22: After the photovoltage signal passes through two parallel amplifier circuits, analog voltage echo signals are acquired and photons are counted. The amplifier circuit consists of two stages of non-inverting amplifiers connected in series, with the first stage non-inverting amplifier connected to a follower; analog voltage echo signals are acquired through an analog signal acquisition card.

[0023] Photons are counted and accumulated through a photon counting unit. A processing circuit module is set between the photon counting unit and the amplifier circuit. The processing circuit module outputs a TTL photon pulse signal, which is then counted and accumulated by the photon counting unit at different distances. The processing circuit module includes a comparator and a D flip-flop. The input of the comparator is connected to the output of the amplifier circuit, and the output of the comparator is connected to the photon counting unit and the D flip-flop. The D flip-flop is connected to the photon counting unit.

[0024] Step S3: Under the action of the laser synchronization trigger signal, the synchronously output analog signal and photon pulse signal are uploaded to the host computer for data preprocessing; the processing includes background baseline removal and signal noise removal.

[0025] Step S4: Perform multiple difference compensation and nonlinear correction factor fitting on the preprocessed signal to obtain the correction factor.

[0026] Step S41: Adaptive weighted correlation analysis and amplitude compensation are performed on the preprocessed analog voltage accumulation sequence signal and the photon pulse accumulation sequence signal. The correlation coefficient is calculated by sliding window averaging. The window size is set to 50. The window with the highest correlation between the two signals is summed and averaged, and then divided to compensate for the multiple difference between the two signals.

[0027] The preprocessed analog voltage signal accumulation sequence is represented as follows: ,in N is the total number of sampling points. The photon pulse accumulation sequence signal is represented as: (Each value is the cumulative photon count or equivalent intensity within the distance gate), and... Synchronous sampling. Sliding window size. The sliding window index is represented as .

[0028] Step S411: Calculate the local mean of the two signals. The calculation formula is as follows: ; ; in, For the first The sliding window is the local mean of the initial analog voltage accumulation sequence signal. For window length, For the first A sequence of analog voltage signal accumulations; For the first Each sliding window represents the local mean of the initial photon pulse accumulation sequence signal. For the first A sequence of photon pulse accumulation signals; Step S412: Calculate adaptive weights based on the local means of the two signals to improve the robustness of the correlation analysis. Higher weights are assigned to signal ranges with stable amplitudes and smooth fluctuations. The adaptive weight calculation formula is as follows: ; ; ; in, Characterizing the first The difference in the mean values ​​of the two signals within a sliding window. This represents the total number of sampling points. For the first The difference in the mean values ​​of the two signals within a sliding window. For sensitivity adjustment parameters, It is a constant greater than zero (a very small constant used to prevent the denominator from being zero). and The first A sliding window is used to simulate the standard deviation of the voltage accumulation sequence signal and the photon pulse accumulation sequence signal, which is used to characterize the fluctuation of the signal. and The first A sliding window simulates the standard deviation of the voltage accumulation sequence signal and the photon pulse accumulation sequence signal. When the difference in the means of the two signals is small ( Small and with gentle fluctuations ( , Hour, A larger value indicates that the data in that window is of higher quality and should be given more weight in subsequent correlation assessments.

[0029] Step S413: Calculate the weighted covariance and weighted correlation coefficient of the two signals within each window; Weighted covariance The calculation formula is as follows: ; Weighted correlation coefficient The calculation formula is as follows: ; Step S414: Determine the optimal window index corresponding to the maximum weighted correlation coefficient. The expression is as follows: ; in, To traverse all A function that takes the maximum value of the independent variable; Step S415: Within the optimal window, sum and average the two signals respectively, then divide them to obtain the global amplitude compensation factor. The calculation formula is as follows: ; and Each of the following is the first The sliding window represents the local mean of the analog voltage accumulation sequence signal and the local mean of the photon pulse accumulation sequence signal.

[0030] Step S416: Use Photon pulse accumulation signal Amplitude compensation is performed to match the analog voltage accumulation signal. The amplitude levels are matched to obtain the compensated signal. The compensation formula is as follows: .

[0031] Step S42: The compensated signal is used to extract the correction factor through the division operation of the two signals, and a nonlinear mapping relationship between the photon counting rate and the correction coefficient is established.

[0032] Step S421: Calculate the instantaneous correction factor at each moment by performing point-by-point division on the two signals, such as... Figure 3 As shown, the calculation formula is as follows: ; in, For the first One instantaneous correction factor, A constant greater than zero (a very small constant, used to prevent the denominator from being zero), correction factor. It reflects the proportional relationship between the analog voltage signal and the photon signal at a specific photon counting intensity.

[0033] Step S422: Remove data points. To improve the reliability of the correction factor calculation, a dual screening mechanism based on signal quality is introduced, as shown in the following expression: Amplitude threshold filtering is used to remove data points with excessively low signal-to-noise ratios. The formula is as follows: ; in, The relative amplitude threshold parameter ( ), The set of data points that meet the amplitude threshold. It is the global maximum value; Based on local volatility, unstable data points are eliminated using the following formula: ; in, Indicates correspondence The local neighborhood, and These are the mean and standard deviation of the correction factor within the neighborhood, respectively. As the stability threshold, A set of data points that conforms to local volatility; valid data point set as follows: ; Step S423: Binate and aggregate the data within the effective data point set according to the photon counting rate; Using photon pulse accumulation signal As a measure of photon counting rate; ; in, The photon counting rate; An adaptive binning method based on data density is adopted, firstly determining the number of bins. The calculation formula is as follows: ; in, To determine the effective number of data points, the quantile method is used to define the boundaries, ensuring that each bin contains approximately the same number of data points. The expression is as follows: ; in, For the first The boundary values ​​of each bin. It is a quantile function; For the Each box contains: ; ; ; ; in, For the first A set of data points that satisfy the boundary conditions in each bin. For the first The boundary values ​​of each bin. and The first The arithmetic mean of the photon counting rate within each sub-box and the arithmetic mean of the instantaneous correction factor For the first Number of sample points in each bin For the first Standard deviation of each bin; Step S424: Considering the nonlinear characteristics of the photon counting system, the correction relationship is established using a piecewise polynomial model as follows: ; in, For nonlinear inflection point threshold, and These are the orders of the first and second piecewise polynomials, respectively. For model parameters, and These are the coefficients of the first polynomial and the coefficients of the second polynomial, respectively. For variables powers of; The model parameters are solved using the weighted least squares method as follows: ; in, This is a regularization term to prevent overfitting. The regularization coefficient is . As weight, ; This is a constant greater than zero (a very small constant to prevent the denominator from being zero). This is to ensure that the piecewise function... The continuity at a given point is subject to the following constraints: ; Step S425: Model Validation and Uncertainty Quantification. Leave-one-out cross-validation is used to evaluate the model's generalization ability, as shown in the following expression: ; in, To account for the mean squared error of cross-validation, Indicates exclusion of the first The model after binning; Calculate the confidence interval of the prediction correction factor The expression is as follows: ; in, The number of model parameters, To predict the standard deviation, For piecewise polynomial models in The predicted value at that location, This is the critical value of the t-distribution; ; in, for The corresponding feature vector, To design the matrix, This is the weight matrix. Piecewise polynomial model The predicted value at that location.

[0034] Step S5: Perform real-time nonlinear correction on the photon signal acquired by the single-photon detector using a correction factor, and dynamically construct a curve relating the output photon counting rate to the correction coefficient. This solves the nonlinear response problem of the single-photon detector over a wide dynamic range and improves the accuracy of the measuring instrument.

[0035] Accumulate the real-time acquired photon pulse signal Using real-time correction factor Real-time correction is performed, and the corrected photon pulse accumulated signal value is obtained. for: ; When signal characteristic drift or correction residual exceeds a set threshold is detected, a recalibration process is automatically triggered. ; in, The tolerance threshold is set between 0 and 0.05. The result of the judgment to trigger recalibration For the monitoring cycle.

[0036] An apparatus for performing the above-described real-time nonlinear calibration method for a single-photon detector includes: The excitation and receiving unit is used to generate excitation signals and receive scattered echo signals. The excitation and receiving unit includes a laser that emits pulsed laser beams and a receiving telescope that collects atmospheric backscattered echo signals. A photodetector is used to convert optical signals into electrical signals; the photodetector is connected to a receiving telescope. Relay circuit, used for the synchronous output of analog signals and photon pulse signals; The analog acquisition unit is used to acquire analog voltage echo signals. The photon counting unit is used to count and accumulate photon pulses under different distance gates; Both the analog acquisition unit and the photon counting unit are connected to the relay circuit; The host computer is used for data preprocessing, performing real-time nonlinear correction on the photon signals collected by the single-photon detector, and dynamically constructing the relationship curve between the output photon counting rate and the correction coefficient; both the analog acquisition unit and the photon counting unit are connected to the host computer.

[0037] To verify the effectiveness of the correction method in this embodiment, a comparative test was conducted before and after correction, as well as a comparative test with fixed parameters and the method of this embodiment. The test results are as follows: Figure 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7 as well as Figure 8 As shown, Figures 3-6 The text describes the change in the correction factor at different temperatures. Figure 7 The correction effects of traditional fixed correction coefficients and the proposed dynamic correction coefficients on the original photon count were compared. The results show that at high photon counting rates, the correction differences between the two methods are significant. Traditional fixed correction methods struggle to compensate for detector nonlinear errors introduced by environmental factors such as temperature fluctuations, while the proposed dynamic correction method effectively suppresses such system deviations and improves correction accuracy. Figure 8 The error of the fixed correction coefficient method was analyzed. The results show that using a fixed correction coefficient results in significant deviations in the high photon counting rate range, with a maximum error of approximately 50,000 photons. In contrast, the dynamic correction method proposed in this embodiment effectively eliminates this error, significantly improving the measurement accuracy of photon counting and ensuring the instrument's detection accuracy and reliability. This device and method can achieve real-time nonlinear calibration of single-photon detectors, making the detector's output signal at high counting rates closer to the true value, effectively ensuring detection accuracy and data reliability.

[0038] 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 preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A real-time nonlinear calibration method for a single-photon detector, characterized in that, The specific steps are as follows: Step S1: First, the laser emits a pulsed laser beam and simultaneously outputs a trigger synchronization signal. The receiving telescope collects the atmospheric backscattered echo signal, which is then converged, filtered, and enters the photodetector. Step S2: The optical signal is converted into an electrical signal by a photodetector, and the analog signal and the photon pulse signal are synchronously output via a relay circuit; Step S3: Under the action of the laser synchronization trigger signal, the synchronously output analog signal and photon pulse signal are uploaded to the host computer for data preprocessing; Step S4: Perform multiple difference compensation and nonlinear correction factor fitting on the preprocessed signal to obtain the correction factor; Step S5: Perform real-time nonlinear correction on the photon signal collected by the single-photon detector using a correction factor, and dynamically construct a curve relating the output photon counting rate to the correction coefficient.

2. The real-time nonlinear calibration method for a single-photon detector according to claim 1, characterized in that, Step S2 is as follows: Step S21: The photocurrent signal output by the photodetector is converted into a photovoltage signal by the transimpedance amplifier; Step S22: After the photovoltage signal passes through two parallel amplifier circuits, analog voltage echo signals are acquired and photons are counted. The amplifier circuit includes two stages of non-inverting amplifiers connected in series, with the first stage non-inverting amplifier connected to a follower; Analog voltage echo signals are acquired using an analog signal acquisition card; Photons are counted and accumulated through a photon counting unit. A processing circuit module is set between the photon counting unit and the amplifier circuit. The processing circuit module outputs a TTL photon pulse signal, which is then counted and accumulated by the photon counting unit at different distances. The processing circuit module includes a comparator and a D flip-flop. The input of the comparator is connected to the output of the amplifier circuit, and the output of the comparator is connected to the photon counting unit and the D flip-flop. The D flip-flop is connected to the photon counting unit.

3. The real-time nonlinear calibration method for a single-photon detector according to claim 2, characterized in that, In step S3, data preprocessing includes background baseline removal and signal noise removal.

4. The real-time nonlinear calibration method for a single-photon detector according to claim 3, characterized in that, Step S4 is as follows: Step S41: By performing adaptive weighted correlation analysis and amplitude compensation on the preprocessed analog voltage accumulation sequence signal and photon pulse accumulation sequence signal, the correlation coefficient is calculated by sliding window average. The window with the highest correlation between the two signals is summed and averaged, and then divided to compensate for the multiple difference between the two signals. Step S42: The compensated signal is used to extract the correction factor through the division operation of the two signals, and a nonlinear mapping relationship between the photon counting rate and the correction coefficient is established.

5. The real-time nonlinear calibration method for a single-photon detector according to claim 4, characterized in that, Step S41 is as follows: Step S411: Calculate the local mean of the two signals. The calculation formula is as follows: ； ； in, For the first The sliding window is the local mean of the initial analog voltage accumulation sequence signal. For window length, For the first A sequence of analog voltage signal accumulations; For the first Each sliding window represents the local mean of the initial photon pulse accumulation sequence signal. For the first A sequence of photon pulse accumulation signals; Step S412: Calculate the adaptive weights based on the local means of the two signals. The calculation formula is as follows: ； ； ； in, Characterizing the first The difference in the mean values ​​of the two signals within a sliding window. This represents the total number of sampling points. For the first The difference in the mean values ​​of the two signals within a sliding window. For sensitivity adjustment parameters, A constant that is greater than zero. and The first The standard deviation of the simulated voltage accumulation sequence signal and the photon pulse accumulation sequence signal in a sliding window; and The first The standard deviation of the simulated voltage accumulation sequence signal and the photon pulse accumulation sequence signal in a sliding window; Step S413: Calculate the weighted covariance and weighted correlation coefficient of the two signals within each window; Weighted covariance The calculation formula is as follows: ； Weighted correlation coefficient The calculation formula is as follows: ； Step S414: Determine the optimal window index corresponding to the maximum weighted correlation coefficient. The expression is as follows: ； in, To traverse all A function that takes the maximum value of the independent variable; Step S415: Within the optimal window, sum and average the two signals respectively, then divide them to obtain the global amplitude compensation factor. The calculation formula is as follows: ； and Each of the following is the first The sliding window represents the local mean of the analog voltage accumulation sequence signal and the local mean of the photon pulse accumulation sequence signal. Step S416: Use Photon pulse accumulation signal Amplitude compensation is performed to match the analog voltage accumulation signal. The amplitude levels are matched to obtain the compensated signal. The compensation formula is as follows: 。 6. The real-time nonlinear calibration method for a single-photon detector according to claim 5, characterized in that, Step S42 is as follows: Step S421: Calculate the instantaneous correction factor at each moment by performing point-by-point division on the two signals. The calculation formula is as follows: ； in, For the first One instantaneous correction factor, A constant that is greater than zero; Step S422: Remove data points, the expression is as follows: The amplitude threshold filtering formula is as follows: ； in, This is the relative amplitude threshold parameter. The set of data points that meet the amplitude threshold. It is the global maximum value; The formula for eliminating local volatility is as follows: ； in, Indicates correspondence The local neighborhood, and These are the mean and standard deviation of the correction factor within the neighborhood, respectively. As the stability threshold, A set of data points that conforms to local volatility; valid data point set as follows: ； Step S423: Binate and aggregate the data within the effective data point set according to the photon counting rate; Using photon pulse accumulation signal As a measure of photon counting rate; ； in, Photon counting rate; An adaptive binning method based on data density is adopted, firstly determining the number of bins. The calculation formula is as follows: ； in, To determine the number of valid data points, the boundary is determined using the quantile method, as shown in the following expression: ； in, For the first The boundary values ​​of each bin. It is a quantile function; For the Each box contains: ； ； ； ； in, For the first A set of data points that satisfy the boundary conditions in each bin. For the first The boundary values ​​of each bin. and The first The arithmetic mean of the photon counting rate within each sub-box and the arithmetic mean of the instantaneous correction factor For the first Number of sample points in each bin For the first Standard deviation of each bin; Step S424: Considering the nonlinear characteristics of the photon counting system, the correction relationship is established using a piecewise polynomial model as follows: ； in, For nonlinear inflection point threshold, and These are the orders of the first and second piecewise polynomials, respectively. For model parameters, and These are the coefficients of the first polynomial and the coefficients of the second polynomial, respectively. For variables powers of; The model parameters are solved using the weighted least squares method as follows: ； in, For regularization terms, The regularization coefficient is . As weight, ; For a constant greater than zero, the constraints are as follows: ； Step S425: Model Validation and Uncertainty Quantification. Leave-one-out cross-validation is used to evaluate the model's generalization ability, as shown in the following expression: ； in, To account for the mean squared error of cross-validation, Indicates exclusion of the first The model after binning; Calculate the confidence interval of the prediction correction factor The expression is as follows: ； in, The number of model parameters. To predict the standard deviation, For piecewise polynomial models in The predicted value at that location, This is the critical value of the t-distribution; ； in, for The corresponding feature vector, To design the matrix, This is the weight matrix. Piecewise polynomial model The predicted value at that location.

7. The real-time nonlinear calibration method for a single-photon detector according to claim 6, characterized in that, In step S5, the real-time acquired photon pulse accumulation signal is... Using real-time correction factor Real-time correction is performed, and the corrected photon pulse accumulated signal value is obtained. for: ； When signal characteristic drift or correction residual exceeds a set threshold is detected, a recalibration process is automatically triggered. ； in, This is the tolerance threshold. The result of the judgment to trigger recalibration For the monitoring cycle.

8. An apparatus for performing the real-time nonlinear calibration method for a single-photon detector as described in claim 7, characterized in that, include: The excitation and receiving unit is used to generate excitation signals and receive scattered echo signals. The excitation and receiving unit includes a laser that emits pulsed laser beams and a receiving telescope that collects atmospheric backscattered echo signals. Photodetectors are used to convert optical signals into electrical signals; The photodetector is connected to the receiving telescope; Relay circuit, used for the synchronous output of analog signals and photon pulse signals; The analog acquisition unit is used to acquire analog voltage echo signals. The photon counting unit is used to count and accumulate photon pulses under different distance gates; Both the analog acquisition unit and the photon counting unit are connected to the relay circuit; The host computer is used for data preprocessing, performing real-time nonlinear correction on the photon signals collected by the single-photon detector, and dynamically constructing the relationship curve between the output photon counting rate and the correction coefficient; both the analog acquisition unit and the photon counting unit are connected to the host computer.

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