A spaceborne lidar calibration method and system based on background noise iteration

Abstract

The present invention proposes a satellite-borne lidar calibration method and system based on background noise iteration. First, the ideal background atmospheric total attenuation backscatter coefficient is constructed, and the nighttime background noise and calibration coefficient are obtained by a robust linear fitting iteration method to realize the calibration of the satellite-borne lidar nighttime detection signal; combined with the strategy of the CALIPSO official calibration method, the daytime and nighttime calibration conversion area is set, and a simple hierarchical detection is performed to screen out the clean atmosphere calibration conversion area; the attenuation scattering ratio of the daytime and nighttime clean atmosphere calibration conversion area is calculated to obtain the calibration conversion coefficient, and the iterative calculation of the daytime calibration coefficient and background noise is completed in combination with the nighttime calibration coefficient to realize the calibration of the satellite-borne lidar daytime detection signal; the present invention realizes the daytime and nighttime calibration of the satellite-borne lidar without collecting background noise, which expands the scope of application compared with traditional methods. The present invention is suitable for on-orbit calibration of satellite-borne lidars under different detection altitude conditions, and has practicality and high accuracy.

Description

Technical Field

[0001] The present invention belongs to the field of radar technology, and in particular relates to a spaceborne laser radar calibration method and system based on background noise iteration. Background Art

[0002] Atmospheric aerosols refer to solid or liquid particles between 0.001 and 100 μm suspended in the air. They play a crucial role in atmospheric physical and chemical processes. Therefore, continuous, high-resolution horizontal and vertical observations of clouds and aerosols around the globe are necessary. Lidar, due to its short operating wavelength, can directly interact with atmospheric cloud and aerosol particles. Its high directivity, monochromaticity, and high spatial and temporal resolution make it suitable for regional and vertical atmospheric profiling, making it an effective tool for studying the vertical distribution of clouds and aerosols. Currently, the most representative spaceborne lidar is the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite launched by NASA in 2006, and its onboard CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar. CALIOP operated in orbit for approximately 17 years, demonstrating the longevity and high reliability of spaceborne lidar. However, due to performance degradation, the lidar ceased operations in August 2023. On April 16, 2022, my country successfully launched the atmospheric environment monitoring satellite DQ-1. Its onboard lidar payload, the Aerosol and Carbon dioxide Detection Lidar (ACDL), used high-spectral resolution cloud and aerosol detection technology in satellite detection for the first time, and has great potential for high-precision detection of clouds and aerosols.

[0003] The interaction between clouds and aerosols has a significant impact on global radiative forcing. To accurately quantify and assess cloud-aerosol interactions, it is first necessary to correctly calibrate cloud and aerosol detection sensors to obtain high-precision cloud and aerosol physical quantity detection data. Currently, there are a wide range of calibration methods based on spaceborne lidar, which can convert the detection electrical signals of spaceborne lidar into attenuated backscatter coefficients that are solely related to the optical properties of atmospheric components. Based on the attenuated backscatter coefficient products obtained through calibration, cloud and aerosol layer detection, layer classification, and optical parameter inversion can be carried out to obtain information on the spatial distribution, types, and content of clouds and aerosols, ultimately serving the quantitative assessment of cloud-aerosol interactions.

[0004] The calibration of spaceborne lidars is typically divided into three parts: background noise subtraction, range gain correction, and on-orbit radiometric calibration. Background noise subtraction assumes that the high-altitude detection signal is free of atmospheric molecular payload. The mean value of the high-altitude detection signal is collected as background noise, and the background noise component is subtracted from the detection signal across the entire altitude range. Range gain correction uses the lidar detection equation to perform range-square correction and system gain coefficient correction, normalizing variables unrelated to the optical properties of atmospheric components. On-orbit radiometric calibration simulates an ideal atmospheric attenuated backscatter signal based on atmospheric model data. The calibration coefficient of the detection signal is calculated using the ratio of the actual detection signal to the ideal signal, and the calibration coefficient is used for correction to obtain an accurate attenuated backscatter coefficient.

[0005] At present, there are many calibration methods for spaceborne lidar. The most representative one is the official CALIPSO day and night calibration method. This method has undergone multiple versions of iterations and is divided into two sub-methods: night calibration and day calibration.

[0006] The official CALIPSO nighttime calibration method calculates a calibration coefficient based on the atmospheric signal estimated by the atmospheric molecular scattering model to achieve the best match between the measured and estimated signals within the calibration region. The latest V4 version of the official CALIPSO nighttime calibration method first considers that the backscatter component from atmospheric components is almost absent in the detection signal at an altitude of 97-112 km. The average signal in this region is collected to subtract background noise. Secondly, due to the range attenuation of the lidar echo signal and the amplifier gain, the detection signal after subtracting the background noise signal is corrected for range gain to obtain the uncalibrated signal. The latest official V4 method assumes that the influence of clouds and aerosols in the altitude range of 34-38 km is almost negligible. Therefore, this region is used as the calibration region. The ratio of the uncalibrated signal to the attenuated backscatter signal estimated by the atmospheric molecular scattering model is calculated as the calibration coefficient and applied to the entire signal to calibrate the CALIPSO nighttime detection signal.

[0007] During the day, spaceborne lidar detection is strongly influenced by the solar background signal, resulting in a sharp drop in the signal-to-noise ratio (SNR) compared to nighttime detection. This makes nighttime calibration methods generally difficult to apply to daytime conditions. Therefore, the official CALIPSO daytime calibration method, based on the assumption that aerosol concentrations in upper clean atmospheric regions are short-term constant between day and night, applies a set of latitude-dependent scaling factors to the nighttime calibration coefficients to estimate the daytime calibration coefficients. The latest version V4 of the official CALIPSO daytime calibration method first uses the same strategy as for nighttime background noise subtraction. Secondly, a stratospheric region with low cloud and aerosol frequency is selected as a calibration conversion region. The calibration conversion coefficients are constructed using the daytime-to-night attenuation-scattering ratio within this calibration conversion region. Finally, the latitude-dependent calibration conversion coefficients are applied to the nighttime calibration coefficients for the adjacent detection scenario to obtain the daytime calibration coefficients for the daytime scenario, thereby calibrating the CALIPSO daytime detection signal.

[0008] Although the current mainstream spaceborne lidar calibration methods, such as the official CALIPSO calibration method, have been widely used in academic research and actual production, they have limitations in principle. Specifically:

[0009] In the official CALIPSO day-night calibration method, background noise collection and subtraction are based on the assumption that atmospheric components are sparse in the laser echo detection signal at very high altitudes, with virtually no atmospheric backscatter. Therefore, the mean value of the very high-altitude detection signal is used as the background noise. This requires that the detection signal be recorded at a sufficiently high altitude (for example, the background noise subtraction altitude specified in the official CALIPSO calibration method is 97-112 km). For spaceborne lidars with limited detection signal recording altitudes, this calibration method can lead to increased atmospheric molecular loading within the detection region due to the low signal recording altitude, breaking the assumption of virtually no atmospheric backscatter in the detection signal. In this case, if the mean value of the detection signal is still collected and subtracted as background noise, a portion of the atmospheric backscatter signal will be subtracted, resulting in over-subtraction of the background noise. Furthermore, since the calibration coefficients require the detection signal after background noise subtraction, over-subtraction of the background noise can lead to incorrect calibration of the spaceborne lidar. In addition, mainstream calibration methods have relatively strict requirements on the maximum signal recording altitude of satellite-borne lidar, which increases the burden on signal storage and on-orbit data transmission, and the requirements at the hardware level are relatively strict.

[0010] In order to solve the above problems and contradictions, it is necessary to establish a more accurate day and night calibration method and theoretical system for satellite-borne lidar. Therefore, this patent, based on the advantages of the classic CALIPSO official day and night calibration method, proposes a satellite-borne lidar calibration method and system based on background noise iteration. This method divides the satellite-borne lidar detection signal into nighttime detection signal and daytime detection signal according to the detection time. For nighttime detection signals, according to the relationship between the original detection signal and the attenuated backscatter coefficient, the ideal attenuated backscatter coefficient of the calibration area constructed based on the atmospheric scattering model is used to directly estimate the background noise and calibration coefficient using a robust linear fitting iterative method, thereby realizing the nighttime calibration of the satellite-borne lidar detection signal; for daytime detection signals, the background noise is estimated through an iterative method to ensure the accuracy of the daytime calibration results. Summary of the Invention

[0011] In order to solve the problem that the background noise collection method in the mainstream calibration method of spaceborne lidar relies on too high a signal detection height, the present invention proposes a spaceborne lidar calibration method and system based on background noise iteration.

[0012] Based on the advantages of mainstream calibration methods for spaceborne lidar, the present invention calibrates the nighttime detection signals and daytime detection signals separately according to the signal detection time. However, the traditional background noise acquisition method is no longer used. Instead, the ideal background atmospheric molecular scattering signal in the calibration area is evaluated through atmospheric model data fitting. The background noise and calibration coefficient are simultaneously estimated based on a robust linear fitting method and an iterative method, thereby optimizing the day and night calibration method. This can avoid the excessive deduction of background noise that may be caused by traditional methods and improve the calibration accuracy.

[0013] The technical solution of the method of the present invention is a space-borne lidar calibration method based on background noise iteration, comprising the following steps:

[0014] Step 1: Construct an ideal background atmospheric total attenuation backscatter coefficient. The linear relationship between the ideal background atmospheric total attenuation backscatter coefficient and the original detection signal in the detection mechanism is then iterated through robust linear fitting to obtain the two unknown quantities in the calibration: background noise and calibration coefficient. This allows for calibration of the nighttime detection signal of the spaceborne lidar.

[0015] Step 2: During daytime observations by the spaceborne lidar, the official CALIPSO daytime calibration method is used to define each calibration transition region under certain environmental conditions. A simple layer detection is performed on the attenuated backscatter coefficients obtained from the nighttime calibration and the uncalibrated daytime signal. Calibration transition regions where cloud and aerosol layers are detected are removed, while the remaining clean atmosphere calibration transition regions are retained.

[0016] Step 3: For each clean atmosphere calibration conversion region, calculate the nighttime attenuation-scattering ratio and the daytime attenuation-scattering ratio, and then calculate the calibration conversion coefficient. Apply the calibration conversion coefficient to the average calibration coefficient of the adjacent previous nighttime scene to obtain the unknown calibration coefficient for the daytime scene. Then, use the linear relationship between the total attenuation backscattering coefficient of the ideal background atmosphere and the original detection signal in the detection mechanism to solve the unknown background noise. Iteratively update the calibration coefficient and the unknown background noise to finally achieve the calibration of the daytime detection signal of the spaceborne lidar.

[0017] Preferably, in step 1, an attenuated backscattering coefficient profile under a clean atmosphere state is constructed according to the atmospheric scattering model, and the attenuated backscattering coefficient of clean atmospheric molecules is specifically calculated as follows:

[0018]

[0019] Among them, β′ m (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The clean atmospheric molecule attenuation backscattering coefficient; β m (z,k p ) represents the backscattering coefficient of atmospheric molecules; and Represent the two-way transmittance of atmospheric molecules and ozone molecules respectively; z is the altitude of the detection point, k p is the profile index number.

[0020] The attenuation-scattering ratio is defined as follows:

[0021]

[0022] Among them, R′(z, k p ) represents the altitude of the detection point is z and the profile index number is k p The attenuation scattering ratio, β′ total (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The attenuated backscattering coefficient contributed by clean atmospheric molecules and particles; β p (z,k p ) and β m (z,k p ) represent the altitude of the detection point, z, and the profile index number, k. p Backscattering coefficients of particles and atmospheric molecules; The altitude of the detection point is z and the profile index is k p The two-way transmittance of particles; z is the altitude of the detection point, in km; k p is the profile index number;

[0023] The ideal background atmospheric total attenuation backscattering coefficient profile of the calibration area is as follows:

[0024] β′ ideal (z,k p )=R′(z,k p )·β′ m (z,k p )=β(z,k p )·T 2 (z,k p )

[0025] Among them, β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; R′(z, k p ) represents the altitude of the detection point is z and the profile index number is k p The attenuation scattering ratio, β′ m (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The atmospheric molecule attenuation backscattering coefficient profile constructed by the atmospheric scattering model; β(z, k p ) and T 2 (z,k p ) represent the total backscattering coefficient and bidirectional transmittance, respectively, which are contributed by the clean atmospheric molecules and clouds and aerosol particles. The formula is as follows:

[0026] β(z,k p )=β m (z,k p )+β p (z,k p )

[0027]

[0028] Among them, β p (z,k p ) and β m (z,k p ) represent the altitude of the detection point, z, and the profile index number, k. p Backscattering coefficients of particles and atmospheric molecules; and They represent the altitude of the detection point, z, and the profile index number, k. p The two-way transmittance of atmospheric molecules, ozone molecules, cloud and aerosol particles.

[0029] The original detection signal received by the space-borne laser radar is defined as:

[0030]

[0031] Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne laser radar, respectively, and are all known quantities; C(k p ) represents the profile index number k p Scaling coefficient at ; N Back (k p ) represents the profile index number k p The background noise at is contributed by the solar background noise and dark current noise; r is the distance between the satellite-borne lidar and the detection point, in km.

[0032] Construct the relationship between the original detection signal and the ideal total attenuation backscatter coefficient, as shown in the definition of the original detection signal received by the space-borne lidar, which is a linear relationship of the form y = k x + b, where y = P (z, k p ), And k and b are the calibration coefficients C(k p ) and background noise N Back (k p );

[0033] Therefore, a calibration area can be selected, and the corresponding detection point height set is Z Cali , for a specific profile index number k p , will belong to Z Cali P(z,k p )and As input, the profile is subjected to robust linear fitting iteration based on the linear relationship defined by the original detection signal received by the laser radar, and finally the calibration coefficient C(k p ) and background noise N Back (k p ) and output it.

[0034] Based on this principle, the official CALIPSO calibration method can be avoided by collecting background noise based on extremely high-altitude detection signals, and the iterative estimation of the background noise and calibration coefficient can be completed at a lower altitude.

[0035]

[0036] Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A They represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; C(k p ) represents the profile index number k p Scaling coefficient at ; N Back (k p ) represents the profile index number k p The background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; Z Cali Represents the height set of detection points corresponding to the selected calibration area;

[0037] The robust linear fitting iteratively estimates the calibration coefficient and background noise as follows:

[0038] Step 1.1: First, perform horizontal averaging on the detection signal and the ideal total attenuation backscatter coefficient to improve the signal-to-noise ratio and obtain the average profile within a certain range of horizontal resolution.

[0039] Step 1.2: For each average profile, the regression coefficient is iteratively calculated based on the robust linear fitting method of M estimation. When the regression coefficient converges, the estimated calibration coefficient C(k p ) and background noise N Back (k p ), where C(k p ) and N Back (k p ) represent the profile index number k p The calibration coefficient and background noise at ;

[0040] Step 1.3: Use a two-dimensional space-time sliding window to calibrate the coefficients C(k p ) performs sliding average;

[0041] Step 1.4: For the calibration coefficient C(k obtained after smoothing in step 1.3 p ), update the background noise N Back (k p ), the calculation formula is as follows:

[0042]

[0043] Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A They represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; C(k p ) represents the profile index number k p Scaling coefficient after smoothing; N Back (k p ) represents the profile index number k p The updated value of the background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; Z Cali Represents the height set of detection points corresponding to the selected calibration area; angle brackets indicate the heights belonging to Z Cali The average value of the calculated values ​​obtained at different heights z.

[0044] The calibration coefficient C(k p ) and background noise N Back (k p ) is applied to the detection signal of the space-borne lidar, and the background noise subtraction, range gain correction and radiation calibration process are completed at the same time, and the attenuated backscatter coefficient profile β′(z, k p ), as follows:

[0045]

[0046] Among them, β′(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The attenuated backscatter coefficient obtained after calibration at P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne laser radar, respectively, and are all known quantities; C(k p ) represents the profile index number k p Scaling coefficient after smoothing; N Back (k p ) represents the profile index number k pThe updated value of the background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km;

[0047] As an example, the step 2 sets each calibration conversion area under certain environmental factors, as follows:

[0048] Select a certain temperature and a certain height at the bottom of the stratosphere to construct multiple calibration conversion areas in the horizontal direction. Each calibration conversion area extends a certain distance in the horizontal direction along the direction of the spaceborne lidar scene.

[0049] As a preference, the calculation of the nighttime attenuation scattering ratio in step 3 is The details are as follows:

[0050]

[0051] Calculate the daytime attenuation scattering ratio as described in step 3 The details are as follows:

[0052]

[0053] Among them, β′ night (z,k p ) represents the altitude z and the profile index number k p The nighttime attenuated backscatter coefficient obtained by calibrating the spaceborne lidar at β′; m，day (z,k p ) and β′ m，night (z,k p ) represent the altitude z and the profile index k p The attenuation backscattering coefficients of atmospheric molecules during the day and night are calculated based on the atmospheric scattering model. represents the mean value of the calibration coefficients recorded for the previous night scene adjacent to the daytime scene of the spaceborne lidar; the angle brackets indicate all the profiles k within the calibration conversion region p The average value of all heights z; X day (z,k p ) represents the altitude z and the profile index number k p The daytime uncalibrated signal after background noise subtraction and gain distance correction is defined as follows:

[0054]

[0055] Among them, X day (z,k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The background noise at the location is subtracted and the gain distance corrected daytime uncalibrated signal is obtained; P day (z,kp ) represents the daytime detection of the spaceborne lidar at an altitude of z and a profile index number of k p The original detection signal at K, E(k p ) and G A represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; N Back (k p ) represents the profile index number k p The background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km;

[0056] The calibration conversion coefficient W is obtained based on the day and night attenuation scattering ratios of different calibration conversion areas. The specific calculation formula is as follows:

[0057]

[0058] Where W represents the calibration conversion factor; and Represents the average attenuation-scattering ratio of the clean atmosphere calibration conversion area at night and day corresponding to similar latitudes.

[0059] In order to obtain a stable and accurate calibration conversion coefficient W, the calibration conversion coefficients accumulated in the period before the time point corresponding to the daytime scene currently detected by the spaceborne lidar are averaged to obtain an estimated value of the calibration conversion coefficient for the scene;

[0060] Taking into account the spatial differences in the detection environment, the estimated value of W is interpolated into a latitude-related sequence. Since the detection scene of the spaceborne lidar in the polar region will pass through the same latitude multiple times and is difficult to distinguish, the estimated value of W after latitude interpolation is reported as the number of seconds since the detection of the scene began, W(t), to distinguish the different calibration conversion coefficients reported at the same latitude in the polar region; where t represents the time the spaceborne lidar has spent detecting the scene;

[0061] Multiply the time-varying and spatially varying calibration conversion coefficient W(t) by the average value of the calibration coefficients of the previous night scene adjacent to the day scene. The number of profile indexes corresponding to different times t in this scenario is k p If there is no calibration conversion area that meets the requirements or the area is not covered by the night scene, the calibration coefficients of the adjacent night scenes are used for temporal interpolation, as follows:

[0062]

[0063] Among them C day (k p) represents the profile index number k obtained by the calibration conversion factor p The daytime calibration coefficient; W(t) represents the calibration conversion coefficient obtained after latitude interpolation that changes with the detection time t; Represents the average value of the calibration coefficients of the previous nighttime scene adjacent to this daytime scene.

[0064] The background noise N is updated according to the relationship between the calibration coefficient and the background noise. Back (k p ), the specific calculation formula is as follows:

[0065]

[0066] Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A They represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; C(k p ) represents the profile index number k p Scaling coefficient after smoothing; N Back (k p ) represents the profile index number k p The updated value of the background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; Z Cali Represents the height set of detection points corresponding to the selected calibration area; angle brackets indicate the heights belonging to Z Cali The average value of the calculated values ​​obtained at different heights z.

[0067] Since the daytime calibration coefficient C day (k p ) involves the calculation of the uncalibrated signal during the day, and it is necessary to assume in advance that the background noise N Back (k p ), and then update the estimated value of the background noise according to the calculated calibration coefficient;

[0068] The calculation of calibration coefficients and background noise in daytime detection signal calibration is essentially an iterative updating process;

[0069] First, use the detection signal of the space-borne lidar and the atmospheric backscattering model to calculate the initial estimate of the background noise In order to obtain the optimal background noise, the iterative termination discriminant function δ(i) is defined. When the termination discriminant function is less than the threshold, the iteration is terminated and C is obtained. i (k p ) and Used for calculation of daytime attenuation backscatter coefficient, daytime calibration is completed; the initial estimate of the background noise The calculation formula of the iterative termination discriminant function δ(i) is as follows:

[0070]

[0071]

[0072] Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A They represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; Represents the profile index number k p The initial estimated value of the background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; Z Cali Represents the height set of detection points corresponding to the selected calibration area; angle brackets indicate the heights belonging to Z Cali The average value of the calculated values ​​obtained at different heights z; and represents the updated value of the background noise in the entire detection scene during the i-th and i-1-th iterations; δ(i) represents the iteration termination function value calculated during the i-th iteration.

[0073] The spaceborne lidar calibration method based on background noise iteration is as follows:

[0074] The night calibration module is specifically as follows:

[0075] For nighttime detection signals of spaceborne lidar, the ideal attenuation backscattering coefficient is constructed based on the atmospheric scattering model;

[0076] Perform robust linear fitting iterations on the detection signal and the ideal attenuated backscatter coefficient, and estimate the calibration coefficient and background noise at the same time.

[0077] Combining the obtained background noise with the calibration coefficient, the detection signal is used to calculate the night-time attenuated backscatter coefficient to complete the night-time calibration;

[0078] The daytime calibration module is as follows:

[0079] For the daytime detection signals of spaceborne lidar, a clean atmosphere calibration conversion region is constructed;

[0080] Based on the day-night clean atmosphere calibration conversion area, the day-night attenuation backscattering coefficients obtained from the uncalibrated daytime signal and the nighttime calibration are used to calculate the day-night attenuation scattering ratios, thereby obtaining the latitude-related calibration conversion coefficients. The daytime calibration coefficients and background noise are then iteratively calculated based on the calibration coefficients of the adjacent nighttime scenes.

[0081] The detection signal is calculated into the daytime attenuated backscatter coefficient based on the background noise and the calibration coefficient to complete the daytime calibration.

[0082] The present invention also proposes a spaceborne lidar calibration system based on background noise iteration, comprising:

[0083] The nighttime detection signal calibration module is used to construct the ideal background atmospheric total attenuation backscatter coefficient. The linear relationship between the ideal background atmospheric total attenuation backscatter coefficient and the original detection signal in the detection mechanism is then used to perform robust linear fitting iterations to obtain the two unknown quantities in the calibration: background noise and calibration coefficient, thereby achieving the calibration of the spaceborne lidar nighttime detection signal.

[0084] The clean atmosphere calibration transition region construction module is used to set each calibration transition region under certain environmental factors during daytime detection of spaceborne lidar, combining the strategy of the official CALIPSO daytime calibration method. It then performs a simple layer detection on the attenuated backscatter coefficient obtained from nighttime calibration and the uncalibrated daytime signal. Calibration transition regions that detect cloud and aerosol layers are removed, while the remaining clean atmosphere calibration transition regions are retained.

[0085] The daytime detection signal calibration module is used to calculate the nighttime attenuation and scattering ratio and the daytime attenuation and scattering ratio for each clean atmosphere calibration conversion area, and then calculate the calibration conversion coefficient. The calibration conversion coefficient is applied to the average calibration coefficient of the adjacent previous nighttime scene to obtain the unknown calibration coefficient for the daytime scene. The linear relationship between the total attenuation backscatter coefficient of the ideal background atmosphere and the original detection signal in the detection mechanism is then used to solve the unknown background noise. The calibration coefficient and the unknown background noise are iteratively updated to finally achieve the calibration of the daytime detection signal of the spaceborne lidar.

[0086] The advantages of the present invention are that it can calibrate satellite-borne lidar detection signals day and night without collecting background noise in extremely high altitude areas. Compared to mainstream methods such as the official CALIPSO calibration, the satellite-borne lidar calibration method based on background noise iteration proposed in this patent no longer relies on collecting background noise from detection signals in extremely high altitude areas. Therefore, it avoids the stringent requirements for data storage and data transmission, as well as the problem of excessive background noise subtraction when using mainstream methods when the satellite-borne lidar detection range is low, thereby improving the accuracy of calibration. These improvements enable the new method to enable satellite-borne lidar to operate effectively under detection conditions at different altitudes, expanding its scope of application. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 : A flow chart of a method according to an embodiment of the present invention;

[0088] Figure 2 : Schematic diagram of the clean air calibration conversion area construction according to an embodiment of the present invention;

[0089] Figure 3 : Flowchart of iterative calculation of daytime detection signal background noise and calibration coefficient according to an embodiment of the present invention;

[0090] Figure 4 : Graph showing calibration results of nighttime detection signals of a space-borne laser radar according to an embodiment of the present invention;

[0091] Figure 5 : Graph showing calibration results of the satellite-borne laser radar daytime detection signal according to an embodiment of the present invention. DETAILED DESCRIPTION

[0092] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0093] In specific implementation, the method proposed in the technical solution of the present invention can be automatically run by those skilled in the art using computer software technology. System devices that implement the method, such as computer-readable storage media that store the corresponding computer program of the technical solution of the present invention and computer equipment that runs the corresponding computer program, should also be within the scope of protection of the present invention.

[0094] The present invention takes China's spaceborne aerosol and cloud high spectral resolution lidar ACDL as an example, which has fixed system hardware parameters.

[0095] The following combination Figures 1 to 5The specific embodiment of the present invention is a space-borne lidar calibration method and system based on background noise iteration.

[0096] like Figure 1 As shown, a specific embodiment of the method of the present invention is a space-borne lidar calibration method based on background noise iteration, comprising the following steps:

[0097] Step 1: Construct an ideal background atmospheric total attenuation backscatter coefficient. The linear relationship between the ideal background atmospheric total attenuation backscatter coefficient and the original detection signal in the detection mechanism is then iterated through robust linear fitting to obtain the two unknown quantities in the calibration: background noise and calibration coefficient. This allows for calibration of the nighttime detection signal of the spaceborne lidar.

[0098] According to the atmospheric scattering model described in step 1, the attenuated backscattering coefficient profile under the clean atmospheric state is constructed. The specific calculation method of the attenuated backscattering coefficient of clean atmospheric molecules is:

[0099]

[0100] Among them, β′ m (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The clean atmospheric molecule attenuation backscattering coefficient; β m (z,k p ) represents the backscattering coefficient of atmospheric molecules; and Represent the two-way transmittance of atmospheric molecules and ozone molecules respectively; z is the altitude of the detection point, k p is the profile index number;

[0101] The attenuation-scattering ratio is defined as follows:

[0102]

[0103] Among them, R′(z,k p ) represents the altitude of the detection point is z and the profile index number is k p The attenuation scattering ratio, β′ total (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The attenuated backscattering coefficient contributed by clean atmospheric molecules and particles; β p (z,k p ) and β m (z,k p ) represent the altitude of the detection point, z, and the profile index number, k. p Backscattering coefficients of particles and atmospheric molecules; The altitude of the detection point is z and the profile index is k p The two-way transmittance of particles; z is the altitude of the detection point, in km; k p is the profile index number;

[0104] The ideal background atmospheric total attenuation backscattering coefficient profile of the calibration area is as follows:

[0105] β′ ideal (z,k p )=R′(z,k p )·β′ m (z,k p )=β(z,k p )·T 2 (z,k p )

[0106] where β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; R′(z, k p ) represents the altitude of the detection point is z and the profile index number is k p The attenuation scattering ratio, β′ m (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The atmospheric molecule attenuation backscattering coefficient profile constructed by the atmospheric scattering model; β(z, k p ) and T 2 (z,k p ) represent the total backscattering coefficient and bidirectional transmittance, respectively, which are contributed by the clean atmospheric molecules and clouds and aerosol particles. The formula is as follows:

[0107] β(z,k p )=β m (z,k p )+β p (z,k p )

[0108]

[0109] Among them, β p (z,k p ) and β m (z,k p ) represent the altitude of the detection point, z, and the profile index number, k. p Backscattering coefficients of particles and atmospheric molecules; and They represent the altitude of the detection point, z, and the profile index number, k. p The two-way transmittance of atmospheric molecules, ozone molecules, cloud and aerosol particles.

[0110] The original detection signal received by the laser radar is defined as:

[0111]

[0112] Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne laser radar, respectively, and are all known quantities; C(k p ) represents the profile index number k p Scaling coefficient at ; N Back (k p ) represents the profile index number k p The background noise at is contributed by the solar background noise and dark current noise; r is the distance between the satellite-borne lidar and the detection point, in km.

[0113] Construct the relationship between the original detection signal and the ideal total attenuation backscatter coefficient, as shown in the definition of the original detection signal received by the space-borne lidar, which is a linear relationship of the form y = k x + b, where y = P (z, k p ), And k and b are the calibration coefficients C(k p ) and background noise N Back (k p );

[0114] Therefore, a calibration area can be selected, and the corresponding detection point height set is z Cali = 34-38 km, for a specific profile index number k p , will belong to Z Cali P(z,k p )and As input, the profile is subjected to robust linear fitting iteration based on the linear relationship defined by the original detection signal received by the laser radar, and finally the calibration coefficient C(k p ) and background noise N Back (k p ) and output;

[0115] Based on this principle, the official CALIPSO calibration method can be avoided by collecting background noise based on extremely high-altitude detection signals, and the iterative estimation of the background noise and calibration coefficient can be completed at a lower altitude.

[0116]

[0117] Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A They represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; C(k p ) represents the profile index number k p Scaling coefficient at ; N Back (k p ) represents the profile index number k p The background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; Z Cali =34-38km represents the height set of detection points corresponding to the selected calibration area;

[0118] The robust linear fitting iteratively estimates the calibration coefficient and background noise as follows:

[0119] Step 1.1: First, perform horizontal averaging on the detection signal and the ideal total attenuation backscatter coefficient to improve the signal-to-noise ratio and obtain the average profile within a certain range of horizontal resolution.

[0120] The horizontal resolution of the certain range is 5 km;

[0121] Step 1.2: For each average profile, the regression coefficient is iteratively calculated based on the robust linear fitting method of M estimation. When the regression coefficient converges, the estimated calibration coefficient C(k p ) and background noise N Back (k p ), where C(k p ) and N Back (k p ) represent the profile index number k p The calibration coefficient and background noise at ;

[0122] Step 1.3: Use a certain two-dimensional space-time sliding window to calibrate the coefficients C(k p) performs sliding average;

[0123] The certain two-dimensional space-time sliding window spans 5 adjacent scenes and has 125 smooth outlines within the scene;

[0124] Step 1.4: For the calibration coefficient C(k obtained after smoothing in step 1.3 p ), iteratively update the background noise N Back (k p ), the calculation formula is as follows:

[0125]

[0126] Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A They represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; C(k p ) represents the profile index number k p Scaling coefficient after smoothing; N Back (k p ) represents the profile index number k p The updated value of the background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; Z Cali Represents the height set of detection points corresponding to the selected calibration area; angle brackets indicate the heights belonging to z Cali = The average value of the calculated values ​​obtained at different altitudes z of 34-38 km.

[0127] The calibration coefficient C(k p ) and background noise N Back (k p ) is applied to the detection signal of the space-borne lidar, and the background noise subtraction, range gain correction and radiation calibration process are completed at the same time, and the attenuated backscatter coefficient profile β′(z, k p ), as follows:

[0128]

[0129] Among them, β′(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k pThe attenuated backscatter coefficient obtained after calibration at P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne laser radar, respectively, and are all known quantities; C(k p ) represents the profile index number k p Scaling coefficient after smoothing; N Back (k p ) represents the profile index number k p The updated value of the background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km;

[0130] Step 2: During daytime observations by the spaceborne lidar, the official CALIPSO daytime calibration method is used to define each calibration transition region under certain environmental conditions. A simple layer detection is performed on the attenuated backscatter coefficients obtained from the nighttime calibration and the uncalibrated daytime signal. Calibration transition regions where cloud and aerosol layers are detected are removed, while the remaining clean atmosphere calibration transition regions are retained.

[0131] like Figure 2 As shown in step 2, each calibration conversion area under certain environmental factors is set as follows

[0132] Select a certain temperature and a certain height at the bottom of the stratosphere to construct multiple calibration conversion areas in the horizontal direction. Each calibration conversion area extends a certain distance in the horizontal direction along the direction of the spaceborne lidar scene.

[0133] The certain temperature and certain height are respectively 400K potential temperature line and 2-6km;

[0134] The certain distance is 200 km;

[0135] Step 3: For each clean atmosphere calibration conversion region, calculate the nighttime attenuation-scattering ratio and the daytime attenuation-scattering ratio, and then calculate the calibration conversion coefficient. Apply the calibration conversion coefficient to the average calibration coefficient of the adjacent previous nighttime scene to obtain the unknown calibration coefficient for the daytime scene. Then, use the linear relationship between the total attenuation backscattering coefficient of the ideal background atmosphere and the original detection signal in the detection mechanism to solve the unknown background noise. Iteratively update the calibration coefficient and the unknown background noise to finally achieve the calibration of the daytime detection signal of the spaceborne lidar.

[0136] Step 3: Calculate the nighttime attenuation scattering ratio The details are as follows:

[0137]

[0138] Calculate the daytime attenuation scattering ratio as described in step 3 The details are as follows:

[0139]

[0140] Among them, β night (z,k p ) represents the altitude z and the profile index number k p The nighttime attenuated backscatter coefficient obtained by calibrating the spaceborne lidar at β′; m，day (z,k p ) and β′ m，night (z,k p ) represent the altitude z and the profile index k p The attenuation backscattering coefficients of atmospheric molecules during the day and night are calculated based on the atmospheric scattering model. represents the mean value of the calibration coefficients recorded for the previous night scene adjacent to the daytime scene of the spaceborne lidar; the angle brackets indicate all the profiles k within the calibration conversion region p The average value of all heights z; X day (z,k p ) represents the altitude z and the profile index number k p The daytime uncalibrated signal after background noise subtraction and gain distance correction is defined as follows:

[0141]

[0142] Among them, X day (z,k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The background noise at the location is subtracted and the gain distance corrected daytime uncalibrated signal is obtained; P day (z,k p ) represents the daytime detection of the spaceborne lidar at an altitude of z and a profile index number of k p The original detection signal at K, E(k p ) and G A represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; N Back (k p ) represents the profile index number k p The background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km;

[0143] The calibration conversion coefficient W is obtained based on the day and night attenuation scattering ratios of different calibration conversion areas. The specific calculation formula is as follows:

[0144]

[0145] Where W represents the calibration conversion factor; and Represents the average attenuation-scattering ratio of the clean atmosphere calibration conversion area at night and day corresponding to similar latitudes.

[0146] In order to obtain a stable and accurate calibration conversion coefficient W, the calibration conversion coefficients accumulated in the period before the time point corresponding to the daytime scene currently detected by the spaceborne lidar are averaged to obtain an estimated value of the calibration conversion coefficient for the scene;

[0147] Taking into account the spatial differences in the detection environment, the estimated value of W is interpolated into a latitude-related sequence. Since the detection scene of the spaceborne lidar in the polar region will pass through the same latitude multiple times and is difficult to distinguish, the estimated value of W after latitude interpolation is reported as the number of seconds since the detection of the scene began, W(t), to distinguish the different calibration conversion coefficients reported at the same latitude in the polar region; where t represents the time the spaceborne lidar has spent detecting the scene;

[0148] Multiply the time-varying and spatially varying calibration conversion coefficient W(t) by the average value of the calibration coefficients of the previous night scene adjacent to the day scene. The number of profile indexes corresponding to different times t in this scenario is k p If there is no calibration conversion area that meets the requirements or the area is not covered by the night scene, the calibration coefficients of the adjacent night scenes are used for temporal interpolation, as follows:

[0149]

[0150] Among them C day (k p ) represents the profile index number k obtained by the calibration conversion factor p The daytime calibration coefficient; W(t) represents the calibration conversion coefficient obtained after latitude interpolation that changes with the detection time t; Represents the average value of the calibration coefficients of the previous nighttime scene adjacent to this daytime scene.

[0151] The background noise N is updated according to the relationship between the calibration coefficient and the background noise. Back (k p ), the specific calculation formula is as follows:

[0152]

[0153] Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A They represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; C(k p ) represents the profile index number k p Scaling coefficient after smoothing; N Back (k p ) represents the profile index number k p The updated value of the background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; Z Cali Represents the height set of detection points corresponding to the selected calibration area; angle brackets indicate the heights belonging to Z Cali The average value of the calculated values ​​obtained at different heights z.

[0154] like Figure 3 As shown, due to the daytime calibration coefficient C day (k p ) involves the calculation of the uncalibrated signal during the day, and it is necessary to assume in advance that the background noise N Back (k p ), and then update the estimated value of the background noise according to the calculated calibration coefficient;

[0155] like Figure 3 As shown in Figure 2, the calculation of calibration coefficients and background noise in daytime detection signal calibration is essentially an iterative update process.

[0156] First, use the detection signal of the space-borne lidar and the atmospheric backscatter model to estimate the initial estimate of the background noise In order to obtain the optimal background noise, the iterative termination discriminant function δ(i) is defined. When the termination discriminant function is less than a certain threshold, the iteration is terminated and C is obtained. i (k p ) and Used for calculation of daytime attenuation backscatter coefficient and completion of daytime calibration;

[0157] The certain threshold is 0.001;

[0158] The initial estimate of the background noise The calculation formula of the iterative termination discriminant function δ(i) is as follows:

[0159]

[0160]

[0161] Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A They represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; Represents the profile index number k p The initial estimated value of the background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; z Cali Represents the height set of detection points corresponding to the selected calibration area; angle brackets indicate the heights belonging to Z Cali The average value of the calculated values ​​obtained at different heights z; and represents the updated value of the background noise in the entire detection scene during the i-th and i-1-th iterations; δ(i) represents the iteration termination function value calculated during the i-th iteration.

[0162] The spaceborne lidar calibration method based on background noise iteration is as follows:

[0163] The night calibration module is specifically as follows:

[0164] For nighttime detection signals of spaceborne lidar, the ideal attenuation backscattering coefficient is constructed based on the atmospheric scattering model;

[0165] Perform robust linear fitting iterations on the detection signal and the ideal attenuated backscatter coefficient, and calculate the calibration coefficient and background noise at the same time.

[0166] Combining the obtained background noise with the calibration coefficient, the detection signal is used to calculate the night-time attenuated backscatter coefficient to complete the night-time calibration;

[0167] The daytime calibration module is as follows:

[0168] For the daytime detection signals of spaceborne lidar, a clean atmosphere calibration conversion region is constructed;

[0169] Based on the day-night clean atmosphere calibration conversion area, the day-night attenuation backscattering coefficients obtained from the uncalibrated daytime signal and the nighttime calibration are used to calculate the day-night attenuation backscattering ratios, thereby obtaining the latitude-related calibration conversion coefficients. The daytime calibration coefficients and background noise are then iteratively calculated based on the nighttime scene calibration coefficients.

[0170] Combining the obtained background noise with the calibration coefficient, the detection signal is used to calculate the daytime attenuated backscatter coefficient to complete the daytime calibration.

[0171] The embodiment of the system of the present invention is a spaceborne lidar calibration system based on background noise iteration, comprising:

[0172] The nighttime detection signal calibration module is used to construct the ideal background atmospheric total attenuation backscatter coefficient. The linear relationship between the ideal background atmospheric total attenuation backscatter coefficient and the original detection signal in the detection mechanism is then used to perform robust linear fitting iterations to obtain the two unknown quantities in the calibration: background noise and calibration coefficient, thereby achieving the calibration of the spaceborne lidar nighttime detection signal.

[0173] The clean atmosphere calibration transition region construction module is used to set each calibration transition region under certain environmental factors during daytime detection of spaceborne lidar, combining the strategy of the official CALIPSO daytime calibration method. It then performs a simple layer detection on the attenuated backscatter coefficient obtained from nighttime calibration and the uncalibrated daytime signal. Calibration transition regions that detect cloud and aerosol layers are removed, while the remaining clean atmosphere calibration transition regions are retained.

[0174] The daytime detection signal calibration module is used to calculate the nighttime attenuation and scattering ratio and the daytime attenuation and scattering ratio for each clean atmosphere calibration conversion area, and then calculate the calibration conversion coefficient. The calibration conversion coefficient is applied to the average calibration coefficient of the adjacent previous nighttime scene to obtain the unknown calibration coefficient for the daytime scene. The linear relationship between the total attenuation backscatter coefficient of the ideal background atmosphere and the original detection signal in the detection mechanism is then used to solve the unknown background noise. The calibration coefficient and the unknown background noise are iteratively updated to finally achieve the calibration of the daytime detection signal of the spaceborne lidar.

[0175] According to the above steps, the day and night detection data of ACDL on July 15, 2022 are calibrated to obtain the calibrated day and night attenuated backscatter coefficients. The attenuated scattering ratios (ASR) test is often used to test the accuracy of the attenuated backscatter coefficients obtained by the calibration of spaceborne lidar. The attenuated scattering ratio test compares the attenuated backscatter coefficients obtained by calibration with the ideal atmospheric molecule attenuated backscatter coefficients derived from the atmospheric scattering model. For clean atmospheric areas, due to the absence of clouds and aerosol layers, the attenuated backscatter coefficients obtained by actual calibration should be consistent with the results derived from the model, so the ideal value of the attenuated scattering ratio should be 1. Figure 4 As shown, sub-figure (a) is a nighttime detection signal scene diagram received by the satellite sensor, with a horizontal resolution of 5km and a vertical resolution of 24m; (b) is the scene horizontal average attenuation scattering ratio profile calculated using the mainstream method, namely the official CALIPSO calibration method; (c) is the scene horizontal average attenuation scattering ratio profile calculated using the method of the present invention. Because the highest detection area of ​​the detection signal in the ACDL nighttime detection scene shown is around 40km, which is much lower than that of CALIPSO, the backscattered signal after the interaction of laser photons with atmospheric molecules is difficult to ignore. If the mainstream calibration method is used to directly use the average of the detection signal around 40km as the background noise, the background noise will be overestimated, resulting in excessive background noise subtraction. The nighttime attenuation backscattering coefficient obtained by calibration is significantly smaller or even negative at high altitudes, and the corresponding attenuation scattering ratio is also significantly smaller and abnormal. The theoretical results calculated by this invention correspond to a scene average attenuation scattering ratio that is very close to 1 in the clean atmosphere area, indicating that the attenuation backscattering coefficient obtained by calibration in the clean atmosphere area is in good agreement with the result calculated by the atmospheric scattering model, which can effectively avoid the problem of excessive subtraction caused by the background and effectively make up for the limitations of the official CALIPSO nighttime calibration algorithm. Similarly, for daytime scenes such as Figure 5As shown, (a) is a scene diagram of the daytime detection signal received by the satellite sensor, with a horizontal resolution of 5km and a vertical resolution of 24m; (b) is the scene horizontal average attenuation and scattering ratio profile calculated using the mainstream method, namely the CALIPSO official calibration method; (c) is the scene horizontal average attenuation and scattering ratio profile calculated using the new method of the present invention. The maximum detection altitude of the daytime detection ACDL is limited to about 40km. The calibration results obtained using the mainstream daytime calibration algorithm are significantly smaller above 25km, and the background noise is also over-subtracted. In contrast, the theoretical results calculated by the present invention fluctuate around 1 in the average attenuation and scattering ratio of the clean atmosphere region, indicating that the attenuation backscattering coefficient obtained by calibration in the clean atmosphere region is in good agreement with the results calculated by the atmospheric scattering model, effectively making up for the limitations of the CALIPSO daytime official calibration algorithm. Therefore, the present invention can accurately estimate the background noise and calibration coefficient of the day and night detection signals of a given satellite-borne lidar system, and effectively complete the calibration task of the satellite-borne lidar in actual engineering measurements.

[0176] It should be understood that parts not elaborated in detail in this specification belong to the prior art.

[0177] It should be understood that the above description of the embodiments is relatively detailed and cannot be regarded as limiting the scope of protection of the patent of the present invention. Under the guidance of the present invention, ordinary technicians in this field can also make substitutions or modifications without departing from the scope of protection of the claims of the present invention, which all fall within the scope of protection of the present invention. The scope of protection requested by the present invention shall be based on the attached claims.

Claims

1. A spaceborne lidar calibration method based on background noise iteration, characterized in that: The following steps are involved: Step 1: Construct an ideal background atmospheric total attenuation backscatter coefficient. The linear relationship between the ideal background atmospheric total attenuation backscatter coefficient and the original detection signal in the detection mechanism is then iterated through robust linear fitting to obtain the two unknown quantities in the calibration: background noise and calibration coefficient. This allows for calibration of the nighttime detection signal of the spaceborne lidar. Step 2: During daytime observations by the spaceborne lidar, the official CALIPSO daytime calibration method is used to define each calibration transition region under certain environmental conditions. A simple layer detection is performed on the attenuated backscatter coefficients obtained from the nighttime calibration and the uncalibrated daytime signal. Calibration transition regions where cloud and aerosol layers are detected are removed, while the remaining clean atmosphere calibration transition regions are retained. Step 3: For each clean atmosphere calibration conversion area, calculate the nighttime attenuation scattering ratio and the daytime attenuation scattering ratio respectively, and then calculate the calibration conversion coefficient. Apply the calibration conversion coefficient to the average calibration coefficient of the adjacent previous nighttime scene to obtain the unknown calibration coefficient for the daytime scene. Then, use the linear relationship between the total attenuation backscattering coefficient of the ideal background atmosphere and the original detection signal in the detection mechanism to solve the unknown background noise. Iteratively update the calibration coefficient and the unknown background noise to finally achieve the calibration of the daytime detection signal of the spaceborne lidar.

2. The spaceborne lidar calibration method based on background noise iteration according to claim 1, characterized in that: According to the atmospheric scattering model described in step 1, the attenuated backscattering coefficient profile under the clean atmospheric state is constructed. The specific calculation method of the attenuated backscattering coefficient of clean atmospheric molecules is: Among them, β′ m (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The clean atmospheric molecule attenuation backscattering coefficient; β m (z,k p ) represents the backscattering coefficient of atmospheric molecules; and Represent the two-way transmittance of atmospheric molecules and ozone molecules respectively; z is the altitude of the detection point, k p is the profile index number; The attenuation-scattering ratio is defined as follows: Among them, R′(z, k p ) represents the altitude of the detection point is z and the profile index number is k p The attenuation scattering ratio, β′ total (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The attenuated backscattering coefficient contributed by clean atmospheric molecules and particles; β p (z,k p ) and β m (z,k p ) represent the altitude of the detection point, z, and the profile index number, k. p Backscattering coefficients of particles and atmospheric molecules; The altitude of the detection point is z and the profile index is k p The two-way transmittance of particles; z is the altitude of the detection point, in km; k p is the profile index number.

3. The spaceborne lidar calibration method based on background noise iteration according to claim 2, characterized in that: The ideal background atmospheric total attenuation backscattering coefficient profile of the calibration area is as follows: β′ ideal (z,k p )=R′(z,k p )·β′ m (z,k p )=β(z,k p )·T 2 (z,k p ) Among them, β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; R′(z, k p ) represents the altitude of the detection point is z and the profile index number is k p The attenuation scattering ratio, β′ m (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The atmospheric molecule attenuation backscattering coefficient profile constructed by the atmospheric scattering model; β(z, k p ) and T 2 (z,k p ) represent the total backscattering coefficient and bidirectional transmittance, respectively, which are contributed by the clean atmospheric molecules and clouds and aerosol particles. The formula is as follows: β(z,k p )=β m (z,k p )+β p (z,k p ) Among them, β p (z,k p ) and β m (z,k p ) represent the altitude of the detection point, z, and the profile index number, k. p Backscattering coefficients of particles and atmospheric molecules; and They represent the altitude of the detection point, z, and the profile index number, k. p The two-way transmittance of atmospheric molecules, ozone molecules, cloud and aerosol particles.

4. The spaceborne lidar calibration method based on background noise iteration according to claim 3, characterized in that: The original detection signal received by the space-borne laser radar is defined as: Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne laser radar, respectively, and are all known quantities; C(k p ) represents the profile index number k p Scaling coefficient at ; N Back (k p ) represents the profile index number k p The background noise at is contributed by the solar background noise and dark current noise; r is the distance between the satellite-borne lidar and the detection point, in km.

5. The spaceborne lidar calibration method based on background noise iteration according to claim 4, characterized in that: Construct the relationship between the original detection signal and the ideal total attenuation backscatter coefficient, as shown in the definition of the original detection signal received by the space-borne lidar, which is a linear relationship of the form y = k x + b, where And k and b are the calibration coefficients C(k p ) and background noise N Back (k p ); Therefore, a calibration area can be selected, and the corresponding detection point height set is Z Cali , for a specific profile index number k p , will belong to Z Cali P(z,k p )and As input, the profile is subjected to robust linear fitting iteration according to the linear relationship defined by the original detection signal received by the laser radar, and finally the calibration coefficient C(k p ) and background noise N Back (k p ) and output; Based on this principle, we can avoid the CALIPSO official calibration method that collects background noise based on extremely high-altitude sounding signals, and complete the fitting estimation of background noise and calibration coefficients at lower altitudes. Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A They represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; β ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; C(k p ) represents the profile index number k p Scaling coefficient at ; N Back (k p ) represents the profile index number k p The background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; Z Cali Represents the height set of detection points corresponding to the selected calibration area.

6. The spaceborne lidar calibration method based on background noise iteration according to claim 5, characterized in that: The robust linear fitting iteratively estimates the calibration coefficient and background noise as follows: Step 1.1: First, perform horizontal averaging on the detection signal and the ideal total attenuation backscatter coefficient to improve the signal-to-noise ratio and obtain the average profile within a certain range of horizontal resolution. Step 1.2: For each average profile, the regression coefficient is iteratively calculated based on the robust linear fitting method of M estimation. When the regression coefficient converges, the estimated calibration coefficient C(k p ) and background noise N Back (k p ), where C(k p ) and N Back (k p ) represent the profile index number k p The calibration coefficient and background noise at ; Step 1.3: Use a two-dimensional space-time sliding window to perform sliding average of the calibration coefficients C(kp) for different scenes and profiles; Step 1.4: For the calibration coefficient C(kp) obtained after smoothing in step 1.3, iteratively update the background noise N Back (k p ), the calculation formula is as follows: Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A They represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; C(k p ) represents the profile index number k p Scaling coefficient after smoothing; N Back (k p ) represents the profile index number k p The updated value of the background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; Z Cali Represents the height set of detection points corresponding to the selected calibration area; angle brackets indicate the heights belonging to Z Cali The average value of the calculated values ​​obtained at different heights z; The calibration coefficient C(k p ) and background noise N Back (k p ) is applied to the detection signal of the spaceborne lidar, and the background noise subtraction, range gain correction and radiation calibration process are completed at the same time. The attenuated backscatter coefficient profile β′(z, kp) is calculated as follows: Among them, β′(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The attenuated backscatter coefficient obtained after calibration at P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne laser radar, respectively, and are all known quantities; C(k p ) represents the profile index number k p Scaling coefficient after smoothing; N Back (k p ) represents the profile index number k p The updated value of the background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km.

7. The spaceborne lidar calibration method based on background noise iteration according to claim 6, characterized in that: Step 2 sets each calibration conversion area under certain environmental factors, as follows A certain temperature and height at the bottom of the stratosphere are selected to construct multiple calibration conversion areas along the horizontal direction. The horizontal direction of each calibration conversion area extends a certain distance along the direction of the spaceborne lidar scene.

8. The spaceborne lidar calibration method based on background noise iteration according to claim 7, characterized in that: Step 3: Calculate the nighttime attenuation scattering ratio The details are as follows: Calculate the daytime attenuation scattering ratio as described in step 3 The details are as follows: Among them, β night (z,k p ) represents the altitude z and the profile index number k p The nighttime attenuated backscatter coefficient obtained by calibrating the spaceborne lidar at β′; m，day (z,k p ) and β′ m，night (z,k p ) represent the altitude z and the profile index k p The attenuation backscattering coefficients of atmospheric molecules during the day and night are calculated based on the atmospheric scattering model. represents the mean value of the calibration coefficients recorded for the previous night scene adjacent to the daytime scene of the spaceborne lidar; the angle brackets indicate the mean value at all heights z of all profiles kp within the calibration conversion region; X day (z,k p ) represents the altitude z and the profile index number k p The daytime uncalibrated signal after background noise subtraction and gain distance correction is defined as follows: Among them, X day (z,k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The background noise at the location is subtracted and the gain distance corrected daytime uncalibrated signal is obtained; P day (z,k p ) represents the daytime detection of the spaceborne lidar at an altitude of z and a profile index number of k p The original detection signal at K, E(k p ) and G A represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; N Back (k p ) represents the profile index number k p The background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; The calibration conversion coefficient W is obtained based on the day and night attenuation scattering ratios of different calibration conversion areas. The specific calculation formula is as follows: Where W represents the calibration conversion factor; and Represents the average attenuation-scattering ratio of the clean atmosphere calibration conversion area at night and day corresponding to similar latitudes; In order to obtain a stable and accurate calibration conversion coefficient W, the calibration conversion coefficients accumulated in the period before the time point corresponding to the daytime scene currently detected by the spaceborne lidar are averaged to obtain an estimated value of the calibration conversion coefficient for the scene; Taking into account the spatial differences in the detection environment, the estimated value of W is interpolated into a latitude-related sequence. Since the detection scene of the spaceborne lidar in the polar region will pass through the same latitude multiple times and is difficult to distinguish, the estimated value of W after latitude interpolation is reported as the number of seconds since the detection of the scene began, W(t), to distinguish the different calibration conversion coefficients reported at the same latitude in the polar region; where t represents the time the spaceborne lidar has spent detecting the scene; Multiply the time-varying and spatially varying calibration conversion coefficient W(t) by the average value of the calibration coefficients of the previous night scene adjacent to the day scene. The number of profile indexes corresponding to different times t in this scenario is k p If there is no calibration conversion area that meets the requirements or the area is not covered by the night scene, the calibration coefficients of the adjacent night scenes are used for temporal interpolation, as follows: Among them C day (k p ) represents the profile index number k obtained by the calibration conversion factor p The daytime calibration coefficient; W(t) represents the calibration conversion coefficient obtained after latitude interpolation that changes with the detection time t; Represents the average value of the calibration coefficients of the previous nighttime scene adjacent to this daytime scene.

9. The spaceborne lidar calibration method based on background noise iteration according to claim 8, characterized in that: The background noise N is updated according to the relationship between the calibration coefficient and the background noise. Back (k p ), the specific calculation formula is as follows; Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A They represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; C(k p ) represents the profile index number k p Scaling coefficient after smoothing; N Back (k p ) represents the profile index number k p The updated value of the background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; Z Cali Represents the height set of detection points corresponding to the selected calibration area; angle brackets indicate the heights belonging to Z Cali The average value of the calculated values ​​obtained at different heights z; Since the daytime calibration coefficient C day (k p ) involves the calculation of the uncalibrated signal during the day, and it is necessary to assume in advance that the background noise N Back (k p ), and then update the estimated value of the background noise according to the calculated calibration coefficient; The calculation of calibration coefficients and background noise in daytime detection signal calibration is essentially an iterative updating process; First, use the detection signal of the space-borne lidar and the atmospheric backscattering model to calculate the initial estimate of the background noise In order to obtain the optimal background noise, the iterative termination discriminant function δ(i) is defined. When the termination discriminant function is less than the threshold, the iteration is terminated and C is obtained. i (k p ) and Used for calculation of daytime attenuation backscatter coefficient, daytime calibration is completed; the initial estimate of the background noise The calculation formula of the iterative termination discriminant function δ(i) is as follows: Among them, P(z, k p ) represents the spaceborne lidar at an altitude of z and a profile index of k p The original detection signal at K, E(k p ) and G A They represent the system constant, laser pulse energy and amplifier gain coefficient of the spaceborne lidar, respectively, and are all known quantities; β′ ideal (z,k p ) represents the altitude of the detection point is z and the profile index number is k p The ideal background atmosphere total attenuation backscattering coefficient; Represents the profile index number k p The initial estimate of the background noise at ; r is the distance between the satellite-borne lidar and the detection point, in km; Z Cali Represents the height set of detection points corresponding to the selected calibration area; angle brackets indicate the heights belonging to Z Cali The average value of the calculated values ​​obtained at different heights z; and represents the updated value of the background noise in the entire detection scene during the i-th and i-1-th iterations; δ(i) represents the iteration termination function value calculated during the i-th iteration; The night calibration module is specifically as follows: For nighttime detection signals of spaceborne lidar, the ideal attenuation backscattering coefficient is constructed based on the atmospheric scattering model; A robust linear fitting iteration is performed on the detection signal and the ideal attenuated backscatter coefficient to estimate the calibration coefficient and background noise. Combining the obtained background noise with the calibration coefficient, the detection signal is used to calculate the night-time attenuated backscatter coefficient to complete the night-time calibration; The daytime calibration module is as follows: For the daytime detection signals of spaceborne lidar, a clean atmosphere calibration conversion region is constructed; Based on the day-night clean atmosphere calibration conversion area, the day-night attenuation backscattering coefficients obtained from the uncalibrated daytime signal and the nighttime calibration are used to calculate the day-night attenuation scattering ratios, thereby obtaining the latitude-related calibration conversion coefficients. The daytime calibration coefficients and background noise are then iteratively calculated based on the calibration coefficients of the adjacent nighttime scenes. The detection signal is calculated into the daytime attenuated backscatter coefficient based on the background noise and the calibration coefficient to complete the daytime calibration.

10. A spaceborne lidar calibration system based on background noise iteration, characterized in that: include: The nighttime detection signal calibration module is used to construct the ideal background atmospheric total attenuation backscatter coefficient. The linear relationship between the ideal background atmospheric total attenuation backscatter coefficient and the original detection signal in the detection mechanism is then used to perform robust linear fitting iterations to obtain the two unknown quantities in the calibration: background noise and calibration coefficient, thereby achieving the calibration of the spaceborne lidar nighttime detection signal. The clean atmosphere calibration transition region construction module is used to set each calibration transition region under certain environmental factors during daytime detection of spaceborne lidar, combining the strategy of the official CALIPSO daytime calibration method. It then performs a simple layer detection on the attenuated backscatter coefficient obtained from nighttime calibration and the uncalibrated daytime signal. Calibration transition regions that detect cloud and aerosol layers are removed, while the remaining clean atmosphere calibration transition regions are retained. The daytime detection signal calibration module is used to calculate the nighttime attenuation and scattering ratio and the daytime attenuation and scattering ratio for each clean atmosphere calibration conversion area, and then calculate the calibration conversion coefficient. The calibration conversion coefficient is applied to the average calibration coefficient of the adjacent previous nighttime scene to obtain the unknown calibration coefficient in the daytime scene. The linear relationship between the total attenuation backscattering coefficient of the ideal background atmosphere and the original detection signal in the detection mechanism is then used to solve the unknown background noise. The calibration coefficient and the unknown background noise are iteratively updated to finally realize the calibration of the daytime detection signal of the spaceborne lidar.

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