Greenhouse gas imaging system based on ground-air mobile platform

Abstract

The invention discloses a greenhouse gas imaging system based on a ground-air mobile platform. The greenhouse gas imaging system comprises an unmanned aerial vehicle double-holder load subsystem (1), a vehicle-mounted passive light source output subsystem (2) and a spectral analysis and processing subsystem (3), the subsystem (2) outputs an original light signal by reflecting direct sunlight on the ground, the original light signal is absorbed by greenhouse gas after passing through a target detection area to become a measurement light signal, and the measurement light signal enters the subsystem (1); the subsystem (1) and the subsystem (2) move to scan a monitoring area, receive a measurement light signal from the ground and convert the measurement light signal into spectral information, and collect a direct solar radiation light signal and convert the direct solar radiation light signal into spectral information; and the subsystem (3) receives the spectral information and performs greenhouse gas absorption cross section treatment, greenhouse gas distribution imaging and greenhouse gas emission based on the spectral information, so that imaging and detection in any direction can be freely detected without being limited by the direction of the sun.

Description

Technical Field

[0001] The present invention belongs to the technical field of the combination of optical remote sensing imaging and environmental gas monitoring and pollutant monitoring, and particularly relates to a greenhouse gas imaging system based on a ground-air mobile platform. Background Art

[0002] Global warming caused by greenhouse gases not only causes sea level rise, but also leads to an increase in extreme weather events. For greenhouse gases such as carbon dioxide and methane, efficient quantitative monitoring and imaging technologies will make scientific research, environmental supervision, and policy formulation of greenhouse gases more effective with less effort.

[0003] Currently, the monitoring methods for carbon dioxide and methane generally include satellite remote sensing, ground-based remote sensing, airborne remote sensing, vehicle-mounted remote sensing, and in-situ measurement. Among them, the spatial resolution of satellite remote sensing is too low to distinguish a certain industrial park, and it is even more powerless for imaging and emission port tracing of the park. For the quantification of greenhouse gas emissions, it is only limited to measuring on a large scale, such as different cities or regions. Although the measurement results of in-situ measurement instruments represented by mass spectrometers and chromatographs and the method of carrying gas sensors are accurate, the imaging efficiency is extremely low, and it is completely unsuitable for large-scale imaging and long-term monitoring of a relatively large park. The results of emission quantification are often restricted by its extremely small measurement range and are not representative.

[0004] Ground-based remote sensing, airborne remote sensing, and vehicle-mounted remote sensing are mainly divided into an active method using laser as a light source and a passive method using direct sunlight as a light source. The former is limited by the monochromaticity of the laser, and the types of gases that can be detected or the detection distance are very limited. The latter needs to track the sun at all times, and the detection direction is restricted. The measured results are all the mixed concentrations of greenhouse gases emitted by the park in the atmosphere, and the emission source cannot be located at a specific position, so emission quantification cannot be achieved, and the purpose of precise emission reduction cannot be achieved. On the other hand, to measure the horizontal distribution of greenhouse gases in the park, it is necessary to enter the park or above the park, which is easily detected by the park. The park manager can quickly turn off high-emission devices, resulting in measurement failure.

[0005] Therefore, there is an urgent need for a greenhouse gas imaging system with high spatio-temporal resolution for multiple components that is not restricted by the sun's azimuth and can freely detect in any direction to image multiple greenhouse gases emitted by different industrial parks, so as to further trace the emission location and quantify the emission plume, in order to hold accountable for the imaging and tracing results of greenhouse gases and achieve precise governance. Summary of the Invention

[0006] In view of the above, the object of the present invention is to provide a greenhouse gas imaging system based on a ground-air mobile platform, which can realize multi-component high spatio-temporal resolution imaging of greenhouse gases such as carbon dioxide and methane in the monitoring area without being restricted by the sun's azimuth, and can freely detect in any direction, so as to further trace the emission location and quantify the emission plume.

[0007] To achieve the above object of the invention, an embodiment provides a greenhouse gas imaging system based on a ground-air mobile platform, which is characterized by comprising: a drone dual-gimbal payload subsystem (1) as a low-altitude mobile platform, a vehicle-mounted passive light source output subsystem (2) as a ground mobile platform, and a spectral analysis and processing subsystem (3);

[0008] The vehicle-mounted passive light source output subsystem (2) outputs an original light signal on the ground by reflecting the direct sunlight, and the original light signal is absorbed by greenhouse gases after passing through the target detection area to become a measurement light signal, and then enters the drone dual-gimbal payload subsystem (1);

[0009] The drone dual-gimbal payload subsystem (1) and the vehicle-mounted passive light source output subsystem (2) move and scan the monitoring area, receive the measurement light signal from the ground and convert it into spectral information, and at the same time collect the direct sunlight signal and convert it into spectral information;

[0010] The spectral analysis and processing subsystem (3) receives the spectral information transmitted back by the drone dual-gimbal payload subsystem (1), and performs greenhouse gas absorption cross-section processing, greenhouse gas distribution imaging, and greenhouse gas emission quantification based on the spectral information.

[0011] Preferably, the vehicle-mounted passive light source output subsystem (2) includes a sun elevation angle servo motor (21), a sun elevation angle right-angle prism (22), a sun azimuth angle servo motor (23), a sun azimuth angle right-angle prism (24), a sun fixed right-angle prism (25), a drone elevation angle servo motor (26), a drone elevation angle right-angle prism (27), a drone azimuth angle servo motor (28), a drone azimuth angle right-angle prism (29), and a drone fixed right-angle prism (210);

[0012] The sun elevation angle servo motor (21) is used to control the sun elevation angle right-angle prism (22) to achieve elevation angle rotation, and the sun azimuth angle servo motor (23) is used to control the sun azimuth angle right-angle prism (24) to achieve azimuth angle rotation. The two servo motors (21) and (23) simultaneously control the two right-angle prisms (22) and (24) to track the sun in real time and refract the direct sunlight into the sun fixed right-angle prism (25) inside the vehicle;

[0013] Similarly, the elevation angle servo motor (26) of the drone-tracking device is used to control the elevation angle right-angle prism (27) of the drone-tracking device to achieve elevation angle rotation, and the azimuth angle servo motor (28) of the drone-tracking device is used to control the azimuth angle right-angle prism (29) of the drone-tracking device to achieve azimuth angle rotation. The two servo motors (26) and (28) simultaneously control the two right-angle prisms (27) and (29) to track the drone in real time. The fixed right-angle prism (210) of the drone-tracking device is used to receive the direct sunlight refracted by the fixed right-angle prism (25) of the sun, and the light is projected onto the dual gimbal payload subsystem (1) of the drone through the two direct prisms (27) and (29) of the drone-tracking device.

[0014] Preferably, it further includes: replacing all the right-angle prisms in the vehicle-mounted passive light source output subsystem (2) with the structure of an equivalent micro right-angle triangular prism group. Specifically, the incident surface of the right-angle prism is divided into multiple sub-incident surfaces, and the exit surface of the right-angle prism is also divided into multiple sub-exit surfaces. The sub-incident surfaces and sub-exit surfaces correspond one by one. The paths of the sub-incident surfaces and sub-exit surfaces for installing light are pushed to the reflection surface to form multiple right-angle triangular prisms, that is, the original right-angle prism is equivalent to multiple right-angle triangular prisms.

[0015] Preferably, the vehicle-mounted passive light source output subsystem (2) further includes: adding a divergence structure (212) to the exit surface of the elevation angle right-angle prism of the drone-tracking device. The structure can be composed of a diffuser with a mesh number between 2000 and 5000 or a light homogenizing sheet with a divergence angle between 5° and 15°.

[0016] Preferably, the vehicle-mounted passive light source output subsystem further includes: a set of environmental monitoring module (213), which includes a wide-angle camera and a solar radiation measuring instrument. The wide-angle camera is used to collect camera images to monitor the relative position of the sun, the approximate relative position of the drone, and the environmental occlusion situation. The solar radiation measuring instrument is used to detect the solar radiation intensity at different wavelengths of the sun, especially in the infrared band. The obtained camera images and solar radiation intensity are used on the one hand to judge the weather conditions of the day, and on the other hand, the solar radiation intensity in the infrared band obtained is used as one of the references for spectral analysis.

[0017] Preferably, the dual gimbal payload subsystem (1) of the drone includes a drone (11), a sun-tracking two-dimensional gimbal (12), a vehicle-tracking two-dimensional gimbal (13), a sun-tracking infrared spectrometer (14), and a vehicle-tracking infrared spectrometer (15);

[0018] The two-dimensional sun-tracking cloud platform (12) is placed on top of the unmanned aerial vehicle (11) and is used to track the sun and conduct the direct sunlight signal into the sun-tracking infrared spectrometer (14) through an optical fiber. The two-dimensional vehicle-tracking cloud platform (13) is placed at the bottom of the unmanned aerial vehicle (11) and is used to track the measurement optical signal output by the vehicle-mounted passive light source output subsystem (2) and conduct the measurement signal into the vehicle-tracking infrared spectrometer (15) through an optical fiber. The two infrared spectrometers (14) and (15) respectively convert the direct sunlight signal and the measurement optical signal into spectral information and transmit it back to the spectral analysis and imaging processing subsystem (3) on the ground.

[0019] Preferably, in the spectral analysis and processing subsystem (3), when processing the greenhouse gas absorption cross-section, the original greenhouse gas absorption line strength is processed into an absorption cross-section suitable for the inversion of the actual instrument concentration, so that the collected spectral information can be inversely analyzed into gas concentration. Specifically, it includes:

[0020] First, based on the pressure broadening effect of physical conditions, the broadened spectral line shape is determined in the following two ways, and the broadened spectral line shape is applied to the absorption line sequence of the original absorption cross-section to obtain the absorption cross-section after the actual gas broadening under the action of physical conditions;

[0021] Method 1: Construct the spectral line shape of the reference greenhouse gas absorption line as a Lorentz line shape f L (v), that is:

[0022]

[0023] where v and p represent the actually observed wavenumber and air pressure, v abs represents the wavenumber corresponding to a certain absorption peak of the gas, δ(p ref ) represents the pressure drift coefficient, FWHM pressure represents the pressure broadening width, which is related to the gas temperature, atmospheric pressure, gas partial pressure, self-broadening coefficient and air-broadening coefficient. The specific calculation formula is:

[0024]

[0025] where γ air and γ self respectively represent the self-broadening coefficient and air-broadening coefficient of the gas, T meas represents the gas temperature during observation, p gas and p air respectively represent the gas partial pressure and atmospheric pressure during observation, n air represents the air-broadening parameter, T ref and p ref respectively represent the standard temperature value and standard atmospheric pressure value;

[0026] Method 2: Construct the spectral line shape of the reference greenhouse gas absorption line as a Gaussian line shape f G (v), that is:

[0027]

[0028] Among them, FWHM doppler represents the Doppler broadening width, which is related to the line intensity wave number, gas temperature and gas molecular weight. The specific calculation formula is:

[0029]

[0030] Among them, M represents the molar mass of the gas, and N A , c and k are all constants;

[0031] Then, based on the effect of Doppler broadening under the instrument conditions, the absorption cross-section after convolution of the detected actual gas broadening and the spectrometer slit function will be further broadened. At this time, a spectral calibration process is added after convolution. Specifically, the convolved absorption cross-section is calibrated according to the wavelength corresponding to the CCD in the spectrometer.

[0032] Preferably, in the spectral analysis and processing subsystem (3), when processing the greenhouse gas absorption cross-section, the original greenhouse gas absorption line intensity is processed into an absorption cross-section suitable for actual instrument concentration inversion, so that the collected spectral information can be inversely analyzed into gas concentration. Specifically, it further includes:

[0033] Based on the overall shape characteristics of the reference greenhouse gas infrared absorption line intensity, draw the envelope of the actual greenhouse gas infrared absorption cross-section, so that the original absorption line sequence becomes a continuous absorption envelope characteristic curve. The specific process is: first, screen the absorption peaks based on the absorption line intensity threshold for the reference absorption line intensity data, and then perform spline interpolation or RFB interpolation on the screened absorption peaks to obtain an absorption cross-section suitable for actual instrument concentration inversion.

[0034] Preferably, in the spectral analysis and processing subsystem (3), when performing greenhouse gas distribution imaging, plan paths for the UAV dual-gimbal payload subsystem (1) and the vehicle-mounted passive light source output subsystem (2) to achieve horizontal scanning of the monitored area and perform horizontal distribution imaging of greenhouse gases; by changing the flight altitude of the UAV and combining horizontal scanning, achieve three-dimensional imaging of greenhouse gases; at the same time, it can perform inclined distribution imaging of greenhouse gases, and the inclination angle is the solar altitude angle.

[0035] Preferably, in the spectral analysis and processing subsystem (3), the quantification of greenhouse gas emissions is carried out after tracing the emission sources based on the imaging results of the greenhouse gas distribution. During the above scanning process, the optical path between the drone dual-gimbal payload subsystem (1) and the vehicle-mounted passive light source output subsystem (2) will be tangent to the emission source plume. During the movement of the drone at different altitude levels, it will be tangent to the greenhouse gas plume at different heights, and the obtained cross-section is called the horizontal cross-section. At the same time, the two-dimensional sun-tracking gimbal (12) on the top of the drone dual-gimbal payload subsystem (1) also measures the solar spectrum at all times. During the movement of the drone at different altitude levels, the optical path between the two-dimensional sun-tracking gimbal (12) and the sun will also be tangent to different positions of the emission source plume in the monitoring area, and the obtained cross-section is called the inclined cross-section. The horizontal and inclined cross-sections of the plume are approximated as circles. According to the imaging results, the concentrations of the horizontal cross-sections and inclined cross-sections at different heights are obtained, and then the emission flux of the emission source is obtained according to the emission flux calculation formula.

[0036] Compared with the prior art, the beneficial effects of the present invention at least include:

[0037] The present invention constructs a drone dual-gimbal payload subsystem (1) as a low-altitude mobile platform and a vehicle-mounted passive light source output subsystem (2) as a ground mobile platform. The vehicle-mounted passive light source output subsystem (2) uses a right-angled prism to reflect direct sunlight to provide a light source for the drone payload. One gimbal of the drone payload tracks the vehicle part of the instrument, and at the same time, the other gimbal tracks the sun in real time. The entire industrial park is scanned through the movement of the drone and the vehicle. In this way, it can be realized that there is no restriction on the sun's azimuth and any direction can be freely detected. On the basis of detecting the spectrum, based on the spectral analysis and processing subsystem (3), the processing of the greenhouse gas absorption cross-section, the imaging of the greenhouse gas distribution, and the quantification of the greenhouse gas emissions can be realized, which is convenient for tracing the emission location and quantifying the emission plume. Description of the Drawings

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0039] Figure 1 is the overall schematic diagram of the greenhouse gas imaging system based on the ground-air mobile platform provided by the embodiment;

[0040] Figure 2 is the partial schematic diagram of the optical path of the vehicle-mounted passive light source output subsystem provided by the embodiment;

[0041] Figure 3Schematic diagram of the greenhouse gas absorption cross-section processing method provided by the embodiment;

[0042] Figure 4 Schematic diagram of the greenhouse gas distribution imaging method provided by the embodiment;

[0043] Figure 5 Schematic diagram of the greenhouse gas emission quantification method provided by the embodiment. Detailed implementation manners

[0044] To make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific implementation manners described herein are only used to explain the present invention and do not limit the protection scope of the present invention.

[0045] The inventive concept of the present invention is as follows: The measurement optical path of traditional passive remote sensing instruments is from the instrument to the sun, and the monitoring azimuth is fixed. In order to enable the instrument to measure the azimuth without being restricted by the sun's azimuth and freely detect any direction, and at the same time give full play to the advantages of fast moving speed, wide detection band, high spectral resolution, and high spatio-temporal resolution of vehicle-mounted remote sensing and unmanned aerial vehicle (UAV) remote sensing, an embodiment of the present invention provides a greenhouse gas imaging system based on a ground-air mobile platform. This system consists of a vehicle-mounted part and a UAV payload part, and is equipped with a greenhouse gas absorption cross-section processing method, a greenhouse gas distribution imaging method, and a greenhouse gas emission quantification method in the system. Among them, the vehicle-mounted part converts the original vehicle-mounted remote sensing system into a vehicle-mounted passive light source output system, and uses a right-angle corner reflector to reflect the direct sunlight to provide a light source for the UAV payload. One of the pan-tilt heads of the UAV payload tracks the vehicle-mounted part of the instrument, and at the same time the other pan-tilt head tracks the sun in real time, and scans the entire industrial park through the movement of the UAV and the vehicle. The scanned spectral information is used to obtain the gas concentration according to the greenhouse gas absorption cross-section processing method provided by the present invention, and further obtain the imaging result of the scanned area according to the gas concentration and the greenhouse gas distribution imaging method. After tracing the high-concentration discharge ports, the plume of greenhouse gas emissions is quantified according to the greenhouse gas emission quantification method.

[0046] Based on the above inventive concept, the greenhouse gas imaging system based on a ground-air mobile platform provided by the embodiment is as Figure 1 shown, and includes a UAV dual-pan-tilt payload subsystem 1, a vehicle-mounted passive light source output subsystem 2, and a spectral analysis and imaging processing subsystem 3.

[0047] In the embodiment, the vehicle-mounted passive light source output subsystem 2 is used to output an original optical signal on the ground by reflecting the direct sunlight. This optical signal is absorbed by greenhouse gases after passing through the target detection area to become a measurement optical signal, and then enters the UAV dual-pan-tilt payload subsystem 1. The greenhouse gases include carbon dioxide and methane.

[0048] As Figure 2As shown in the figure, the vehicle-mounted passive light source output subsystem 2 is used to output light sources to the drone dual gimbal payload subsystem 1, and its functions include tracking the sun, tracking the drone, reflecting the sunlight path, and identifying the surrounding environment, including the sun-tracking pitch servo motor 21, the sun-tracking pitch right-angle prism 22, the sun-tracking azimuth servo motor 23, the sun-tracking azimuth right-angle prism 24, the sun-tracking fixed right-angle prism 25, the drone-tracking pitch servo motor 26, the drone-tracking pitch right-angle prism 27, the drone-tracking azimuth servo motor 28, the drone-tracking azimuth right-angle prism 29, the drone-tracking fixed right-angle prism 210, and the environmental monitoring module 213.

[0049] Among them, the sun-tracking pitch servo motor 21 is used to control the sun-tracking pitch right-angle prism 22 to achieve pitch angle rotation, and the sun-tracking azimuth servo motor 23 is used to control the sun-tracking azimuth right-angle prism 24 to achieve azimuth angle rotation. The two servo motors 21 and 23 can control the two right-angle prisms to track the sun in real time and refract the direct sunlight into the sun-tracking fixed right-angle prism 25 inside the vehicle. Similarly, the drone-tracking pitch servo motor 26 is used to control the drone-tracking pitch right-angle prism 27 to achieve pitch angle rotation, and the drone-tracking azimuth servo motor 28 is used to control the drone-tracking azimuth right-angle prism 29 to achieve azimuth angle rotation. The two servo motors 26 and 28 can control the two right-angle prisms to track the drone in real time. The drone-tracking fixed right-angle prism 210 is used to receive the direct sunlight refracted by the sun-fixed right-angle prism 25 and project the light to the drone dual gimbal payload subsystem 1 through the two prisms of the drone-tracking. This process is the process of the vehicle-mounted passive light source output subsystem outputting passive light. The advantages of using passive light are:

[0050] 1. The spectrum of direct sunlight is continuous, and more spectral dimension information can be obtained during spectral analysis.

[0051] 2. The luminous flux of direct sunlight is very large, which is sufficient for the spectral analysis of the drone dual gimbal payload subsystem. In addition, the luminous flux of direct sunlight is much higher than that of ground-reflected light. Therefore, during spectral analysis, the influence of ground-reflected light signals can be ignored.

[0052] Furthermore, on the one hand, in order to provide a larger light flux for the dual gimbal payload subsystem 1 of the UAV, and on the other hand, to use a larger output area to increase the success rate of the dual gimbal payload subsystem 1 of the UAV in receiving light. The sizes of all the right-angled prisms 22, 24, 25, 27, 29 and 210 in the vehicle-mounted passive light source output subsystem 2 should be as large as possible, but too large a size of the right-angled prism will greatly increase the weight of the entire system. Therefore, all the right-angled prisms 22, 24, 25, 27, 29 and 210 in the system can be replaced with a structure 211 of an equivalent micro right-angled triangular prism group. The incident surface of the right-angled prism is divided into multiple sub-incident surfaces, and similarly, the exit surface of the right-angled prism is divided into multiple sub-exit surfaces, and the sub-incident surfaces and sub-exit surfaces correspond one by one. The paths for installing light on the sub-incident surfaces and sub-exit surfaces are pushed to the reflection surface to form multiple right-angled triangular prisms. That is, the original right-angled prism is equivalent to multiple right-angled triangular prisms, and the reflection effect is the same as that of the original right-angled prism.

[0053] In order to further increase the success rate of the dual gimbal payload subsystem 1 of the UAV in receiving light, a diverging structure 212 is added to the exit surface of the right-angled prism 27 for tracking the pitch angle of the UAV. The structure can be composed of a diffusing sheet with a mesh number between 2000 and 5000 or a light homogenizing sheet with a divergence angle between 5° and 15°. The specific mesh number and divergence angle depend on the actual accuracy of the vehicle-mounted passive light source output subsystem and the relative distance of the UAV.

[0054] In addition, an environmental monitoring module 213 is arranged on the vehicle-mounted passive light source output subsystem 2, including a wide-angle camera and a solar radiation measuring instrument. Among them, the wide-angle camera is mainly used to collect camera images to monitor the relative position of the sun, the approximate relative position of the UAV and the environmental occlusion situation. The solar radiation measuring instrument is used to detect the solar radiation intensity at different wavelengths of the sun, especially in the infrared band. The obtained camera images and solar radiation intensity are used on the one hand to judge the weather conditions of the day, and on the other hand, the solar radiation intensity in the infrared band obtained is used as one of the references for spectral analysis.

[0055] In the embodiment, the dual gimbal payload subsystem 1 of the UAV and the vehicle-mounted passive light source output subsystem 2 move to scan the monitoring area, receive the measured optical signal from the ground and convert it into spectral information, and at the same time collect the direct sunlight signal and convert it into spectral information. As Figure 1As shown, it includes a UAV 11, a sun-chasing two-dimensional gimbal 12, a vehicle-tracking two-dimensional gimbal 13, a sun-chasing infrared spectrometer 14, and a vehicle-chasing infrared spectrometer 15; wherein the sun-chasing two-dimensional gimbal 12 is placed on the top of the UAV 11, and is used to track the sun, and introduce the direct sunlight light signal into the sun-chasing infrared spectrometer 14 via optical fiber, and the vehicle-tracking two-dimensional gimbal 13 is placed at the bottom of the UAV 11, and is used to track the measurement light signal output by the vehicle-mounted passive light source output subsystem 2, and introduce the measurement signal into the vehicle-chasing infrared spectrometer 15 via optical fiber; the two infrared spectrometers 14 and 15 respectively convert the direct sunlight light signal and the measurement light signal into spectral information, and transmit them back to the spectral analysis and imaging processing subsystem 3 on the ground.

[0056] In the embodiment, the spectral analysis and imaging processing subsystem 3 includes a greenhouse gas absorption cross section processing method, a greenhouse gas distribution imaging method and a greenhouse gas emission quantification method. The greenhouse gas absorption cross section processing method is used to adapt the original greenhouse gas absorption cross section so that the collected spectral information can be inverted and analyzed into gas concentrations with high quality. The greenhouse gas distribution imaging method is used to plan paths for the UAV dual gimbal payload subsystem 1 and the vehicle-mounted passive light source output subsystem 2 to achieve horizontal scanning covering the inspection plant area. The greenhouse gas emission quantification method is used to calculate the emissions of carbon dioxide and methane plumes.

[0057] The greenhouse gas absorption cross section processing method proposed in the present invention is used to process the greenhouse gas absorption line intensity in the existing HITRAN database into an envelope cross section suitable for actual instrument concentration inversion. At present, the method of obtaining characteristic gas concentration using observed spectral information is based on the Lambert-Beer absorption law. After obtaining the optical thickness using the reference spectrum and the measured spectrum, the least squares fitting is used to invert the oblique column concentration of the gas in combination with information such as the gas absorption cross section. The reference spectrum generally uses an observed spectrum that is relatively clean and almost does not contain the target characteristic gas. In this process, since the characteristic absorption peaks of different greenhouse gases in the infrared band are distributed far apart in the wavelength dimension, and the absorption line intensity extracted based on the HITRAN database is mainly an ideal absorption line sequence obtained by theoretical calculation, an instrument with extremely high spectral resolution is required to be applicable, and the current small airborne spectrometer cannot take into account both wide band and ultra-high spectral resolution. Taking CO 2 and CH 4 Taking these two greenhouse gases with relatively high atmospheric content as an example, the detection band required for detecting these two gases is generally at least 1590-1620nm, and the spectral resolution needs to reach the order of 0.001nm. However, the spectral resolution of a small spectrometer with 2048 CCD pixels in this band is about 0.015nm, which cannot capture the characteristic absorption lines of the gas. Therefore, in order to solve this problem, Figure 3As shown, the present invention proposes two methods for processing the greenhouse gas absorption cross-section, especially for CO 2 and CH 4 absorption cross-sections. Since the shape of the infrared absorption cross-section 31 of greenhouse gases extracted from the HITRAN database is generally in the form of a sequence of absorption lines, Figure 3 Taking a part of the absorption cross-section enlarged as an example for analysis, that is, the absorption cross-section example 32.

[0058] The first processing method is based on physical conditions and instrument conditions. Due to the effects of pressure broadening and Doppler broadening, the absorption cross-section observed after the actual gas molecules are transmitted to the instrument is not the case of line intensity or natural broadening, but shows a broadening phenomenon. Among them, the pressure broadening width FWHM pressure is mainly related to the gas temperature, atmospheric pressure, gas partial pressure, self-broadening coefficient and air-broadening coefficient, etc. See the specific formula:

[0059]

[0060] where γ air and γ self represent the self-broadening coefficient and air-broadening coefficient of the gas respectively, T meas represents the gas temperature during observation, p gas and p air represent the gas partial pressure and atmospheric pressure during observation respectively, n air represents the air-broadening parameter, T ref and p ref represent the standard temperature value and standard atmospheric pressure value respectively;

[0061] Based on this pressure broadening width FWHM pressure , the spectral line shape of the reference greenhouse gas absorption line is constructed as a Lorentz line shape f L (v), that is:

[0062]

[0063] where v and p represent the wavenumber and air pressure actually observed, and v abs represents the wavenumber corresponding to a certain absorption peak of the gas, and δ(p ref ) represents the pressure drift coefficient;

[0064] Method 2: The Doppler broadening width FWHM doppler is related to the line intensity wavenumber, gas temperature and gas molecular weight. The specific calculation formula is:

[0065]

[0066] where M represents the molar mass of the gas, and N A , c and k are all constants;

[0067] Based on the Doppler broadening width FWHM doppler , the spectral line shape of the reference greenhouse gas absorption line is constructed as a Gaussian line shape f G (v), that is:

[0068]

[0069] According to the physical conditions such as temperature, pressure, and molecular weight under the actual observation conditions, combined with the absorption line strength, broadening coefficient and other parameters provided by the HITRAN database, the broadening line shape after the superposition of pressure broadening and Doppler broadening can be obtained. Acting the superposed line shape on the absorption line sequence of the absorption cross-section example 32, the broadened absorption cross-section example 33 can be obtained. This cross-section is the actual gas absorption cross-section under this physical condition. Through an instrument with ultra-high spectral resolution, such as a Fourier transform infrared spectrometer (FTIR), the broadened line shape in the cross-section can be detected. However, in order to match a wide-band airborne small infrared spectrometer, the following steps need to be continued: The spectrum actually detected by the spectrometer is the result of the convolution of the incident spectrum and the spectrometer slit function, which causes the characteristic spectrum detected by the spectrometer to be further broadened, and the convolution result is the convolution-absorbed cross-section example 34. In order to obtain spectral information more accurately, the present invention proposes to add a spectral calibration process after convolution: Since the function of the CCD in the spectrometer is to convert the received photons into electrical signals, in order to map the pixel position of each CCD pixel to the corresponding wavelength, spectral calibration is required. Because the wavelength detected by the CCD pixel cannot exactly correspond to the absorption characteristic peak shown in the convolution-absorbed cross-section example 34, but there will be a certain offset, which will cause the position and intensity of the absorption characteristic peak collected by the spectrometer to be inconsistent with the real absorption characteristic peak, and because the characteristic absorption peaks of greenhouse gases in the infrared band are denser than those of ultraviolet characteristic gases, this inconsistency will be more significant, and even the actual spectral interval will exceed the interval between characteristic peaks. Therefore, it is necessary to calibrate the convolution-absorbed cross-section example 34 for the wavelength corresponding to the CCD, and the absorption cross-section that the CCD can actually detect finally presents as the calibrated absorption cross-section example 35. That is to say, after the above processing, the absorption line strength of the HITRAN database will adaptively change to match the physical conditions and instrument conditions, which is equivalent to removing the errors brought by the physical conditions and instrument conditions. Since the calibrated absorption cross-section example 35 takes into account the real physical conditions and instrument conditions, theoretically the accuracy and effectiveness are very high, but due to the large number of processing steps and complexity, if multiple greenhouse gases need to be processed simultaneously, the complexity is relatively high. In addition, the problem of this method is that outdoor detection will be affected by various atmospheric environmental factors and instrument vibrations, etc., and a very high root mean square error (RMS) will be generated after inversion using the processed absorption cross-section, which greatly affects the actual accuracy of detection.

[0070] Therefore, the present invention proposes a second processing method, that is, to draw the infrared absorption cross-section envelope 38 of greenhouse gases according to the overall shape characteristics of the infrared absorption line intensities 31 of greenhouse gases extracted from the HITRAN database, so that the original absorption line sequence becomes a continuous absorption envelope characteristic curve. Taking the absorption cross-section example 32 as the research object, there are various methods to draw the envelope line. Figure 3 One of them is shown. First, connect the tops of the absorption lines to form a broken-line absorption line intensity example 36, and then use the interpolation method to smooth the curve to obtain the curve cross-section example 37. The interpolation methods used here are mainly spline interpolation and RFB interpolation. Since the absorption line intensities in the HITRAN database include all the data of absorption peaks, and only the absorption data with high absorption line intensities play a significant role in the envelope inversion, while the remaining low absorption line intensity data have little impact on the inversion result, so the HITRAN absorption line intensity data will be screened before interpolation. For example, for CO 2 , all the absorption peaks with absorption line intensities above the absorption line intensity threshold (e.g., 10 -25 ) are screened out, and then spline interpolation is performed: Let the envelope absorption cross-section be S(λ), where λ is the wavelength, and the screened absorption line intensity data is (λ i , s i ), i = 1, …, N. Let the envelope basis function be a low-degree polynomial S i (λ). The envelope absorption cross-section S(λ) is the data fitted from all adjacent absorption line intensity data. Taking the cubic polynomial as an example, in order to ensure the continuity and second-order smoothness of S(λ) at this time, the following relational expressions are given:

[0071]

[0072] To ensure the uniqueness of the absorption cross-section S(λ), boundary conditions also need to be given. Since the absorption cross-section is a part of the entire wavelength band intercepted for envelope inversion, an additional point is selected on each side of the wavelength band to provide boundary conditions for the envelope basis function cluster. Here, let these two points be (λ 0 , s 0 ), (λ N+1 , s N+1 ), and let the boundary conditions be:

[0073]

[0074] Among them, k 0,1 represents the slope determined by the points (λ 0 , s 0 ) and (λ 1 , s 1 ), and k N-1,N represents the point (λ N-1 , sN-1 ) and the slope determined by the point (λ N , s N ). At this time, the function of the entire envelope absorption cross-section can be determined. The advantage of this scheme is that the computational amount is small and there is a certain fitting effect. If the fitting accuracy is considered, the RFB interpolation method is proposed here. Compared with spline interpolation, the Gaussian function is selected as the envelope basis function in the RFB interpolation method where ε is the instrument resolution. Then the envelope absorption cross-section where w i is the weight. After substituting the absorption peak data, we can get:

[0075]

[0076] Or expressed in matrix form as:

[0077]

[0078] Denoted as FW = S, at this time W = F -1 S, and thus the weight value can be calculated, and finally the envelope absorption cross-section can be obtained. This scheme has higher accuracy, and the basis function is more in line with the actual absorption cross-section situation. Finally, the interpolation method covers the entire absorption cross-section to obtain the infrared envelope absorption cross-section 38 of greenhouse gases.

[0079] The greenhouse gas distribution imaging method of the spectral analysis and imaging processing subsystem 3 is to image the gas concentration obtained from the greenhouse gas spectral analysis. This process needs to cooperate with the actual observation mode. The present invention proposes two observation modes, and the specific observation modes are as Figure 4 shown.

[0080] The first method is that the UAV dual-gimbal payload subsystem 1 and the vehicle-mounted passive light source output subsystem 2 are arranged at two adjacent endpoints a and b of the observation area (for example, an industrial park. Set the four consecutive endpoints of this industrial park as a, b, c, and d, and form a closed area). Then, both move forward at the same speed until the UAV dual-gimbal payload subsystem 1 reaches endpoint d from endpoint a, and the vehicle-mounted passive light source output subsystem 2 reaches endpoint c from endpoint b. The area swept by the line connecting the two during the movement is the area of the industrial park. This process is called longitudinal scanning. In the same way, arrange the two subsystems at endpoint d and endpoint a again, and make the UAV dual-gimbal payload subsystem 1 reach endpoint b from endpoint a, and the vehicle-mounted passive light source output subsystem 2 reach endpoint c from endpoint d. This process is called transverse scanning. During the observation process, the direct sunlight is reflected by the vehicle-mounted passive light source output subsystem 2 and reaches the UAV dual-gimbal payload subsystem 1. The average of the test results at the start and end of the movement can be used as one of the reference spectra. Since the gas absorption change in the optical path between the sun and the vehicle-mounted passive light source output subsystem 2 is relatively small during the test, the influence of this section of the optical path can be ignored when subtracting the reference spectrum from the measurement spectrum. The concentration obtained by spectral analysis is the concentration above the industrial park. The results of longitudinal scanning and transverse scanning are imaged in a way similar to CT scanning. In this way, the horizontal distribution above the industrial park can be imaged.

[0081] The second method is that the vehicle-mounted passive light source output subsystem 2 is arranged at endpoint b with less occlusion, and the UAV dual-gimbal payload subsystem 1 is arranged at endpoint a. Then the latter starts to move at a constant speed and reaches endpoint d and endpoint c in sequence. The area swept by the line connecting the two during the movement is the area of the industrial park. This process is called fan-shaped scanning. In the same way, arrange the vehicle-mounted passive light source output subsystem 2 at another endpoint d with less occlusion again, and the UAV dual-gimbal payload subsystem 1 is arranged at endpoint c and reaches endpoint b and endpoint a in sequence. Conduct a fan-shaped scanning at the diagonal position again. The results of two or more fan-shaped scans are also imaged in a way similar to CT scanning. In this way, the horizontal distribution above the industrial park can be imaged.

[0082] According to the imaging results, the position of high greenhouse gas emissions in the industrial park can be judged, and the exhaust port position can be determined accordingly to achieve traceability. By changing the flight altitude of the UAV and repeating the above scanning process and imaging method, multi-height layer imaging can be carried out to achieve three-dimensional imaging. Similarly, the two-dimensional sun-tracking gimbal 12 of the UAV dual-gimbal payload subsystem 1 and the corresponding infrared spectrometer 14 are also tracking the sun for measurement at the same time. The two methods of the greenhouse gas distribution imaging method can be used directly to obtain the inclined distribution imaging, and the inclined angle is the solar altitude angle.

[0083] The method for quantifying greenhouse gas emissions of the spectral analysis and imaging processing subsystem 3 is carried out after tracing the emission source according to the greenhouse gas distribution imaging method. As Figure 5 shown, during the above scanning process, the optical path between the UAV dual gimbal payload subsystem 1 and the vehicle-mounted passive light source output subsystem 2 will be tangent to the emission source plume. During the movement of the UAV at different altitude layers, it will be tangent to the greenhouse gas plume at different altitudes, and the tangent plane is Figure 5 represented as three hollow ellipses in Figure 5 , which is called the horizontal tangent plane; at the same time, the two-dimensional gimbal 12 at the top of the UAV dual gimbal payload subsystem 1 is also measuring the solar spectrum at all times. During the movement of the UAV at different altitude layers, the optical path between the two-dimensional gimbal 12 at the top and the sun will also be tangent to different positions of the emission source plume in the industrial park, and the tangent plane is

[0084] represented as three solid ellipses in

[0085] , which is called the inclined tangent plane. The plume tangent plane is approximated as a circle, and the size of the tangent plane can be obtained according to the imaging result. Specifically, by combining the map information and the imaging result, the position of the emission port (plume) can be mapped onto the map. According to the position information output by the UAV during the movement, the distance between the UAV and the plume at each spectral acquisition can be obtained; according to the imaging result, a gas concentration threshold is set, and the area exceeding this threshold is considered a high-emission area and identified as the emission port, and the size and concentration of the plume tangent plane at this altitude are calculated based on the area exceeding the threshold. In this way, the horizontal tangent plane concentration and inclined tangent plane concentration at different altitudes are obtained. According to the emission flux calculation formula, the emission flux of this emission port can be obtained.

[0084] The greenhouse gas imaging system based on the ground-air mobile platform provided by the present invention can simultaneously image multiple greenhouse gases and calculate the emission flux, and relevant factories and relevant departments can carry out precise monitoring and efficient prevention and control based on the calculation results.

[0085] The above specific embodiments have elaborated in detail the technical solutions and beneficial effects of the present invention. It should be understood that the above is only the most preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, supplements, equivalent replacements, etc. made within the scope of the principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A greenhouse gas imaging system based on a ground-to-air mobile platform, characterized in that: include: The UAV dual gimbal payload subsystem (1) as a low-altitude mobile platform, the vehicle-mounted passive light source output subsystem (2) as a ground mobile platform, and the spectrum analysis and processing subsystem (3); The vehicle-mounted passive light source output subsystem (2) outputs an original light signal on the ground by reflecting direct sunlight. After passing through the target detection area, the original light signal is absorbed by greenhouse gases and becomes a measurement light signal, and enters the UAV dual gimbal payload subsystem (1); The UAV dual gimbal payload subsystem (1) and the vehicle-mounted passive light source output subsystem (2) move to scan the monitoring area, receive the measurement light signal from the ground and convert it into spectral information, and also collect the direct sunlight light signal and convert it into spectral information; The spectral analysis and processing subsystem (3) receives spectral information transmitted back by the UAV dual gimbal payload subsystem (1), and performs greenhouse gas absorption cross-section processing, greenhouse gas distribution imaging, and greenhouse gas emission quantification based on the spectral information.

2. The greenhouse gas imaging system based on the ground-to-air mobile platform according to claim 1 is characterized in that: The vehicle-mounted passive light source output subsystem (2) comprises a sun pitch angle servo motor (21), a sun-chasing pitch angle right-angle prism (22), a sun-chasing azimuth angle servo motor (23), a sun-chasing azimuth angle right-angle prism (24), a sun-chasing fixed right-angle prism (25), a drone-chasing pitch angle servo motor (26), a drone-chasing pitch angle right-angle prism (27), a drone-chasing azimuth angle servo motor (28), a drone-chasing azimuth angle right-angle prism (29), and a drone-chasing fixed right-angle prism (210); The sun-tracking pitch angle servo motor (21) is used to control the sun-tracking pitch angle right-angle prism (22) to realize pitch angle rotation, and the sun-tracking azimuth angle servo motor (23) is used to control the sun-tracking azimuth angle right-angle prism (24) to realize azimuth angle rotation. The two servo motors (21) and (23) simultaneously control the two right-angle prisms (22) and (24) to track the sun in real time, and refract the direct sunlight into the sun-tracking fixed right-angle prism (25) in the vehicle; Similarly, the pitch angle servo motor (26) of the chasing drone is used to control the pitch angle right-angle prism (27) of the chasing drone to realize pitch angle rotation, and the azimuth angle servo motor (28) of the chasing drone is used to control the azimuth angle right-angle prism (29) of the chasing drone to realize azimuth angle rotation. The two servo motors (26) and (28) simultaneously control the two right-angle prisms (27) and (29) to track the drone in real time. The fixed right-angle prism (210) of the chasing drone is used to receive the direct sunlight reflected by the fixed right-angle prism (25) of the sun, and emit the light to the drone dual gimbal load subsystem (1) through the two direct prisms (27) and (29) of the chasing drone.

3. The greenhouse gas imaging system based on the ground-to-air mobile platform according to claim 2 is characterized in that: The method further comprises: replacing all right-angle prisms in the vehicle-mounted passive light source output subsystem (2) with the structure of an equivalent micro right-angle triangular prism group, specifically dividing the incident surface of the right-angle prism into a plurality of sub-incident surfaces, and similarly dividing the exit surface of the right-angle prism into a plurality of sub-exit surfaces, wherein the sub-incident surfaces correspond to the sub-exit surfaces one by one, and pushing the paths of the light rays installed on the sub-incident surfaces and the sub-exit surfaces to the reflecting surface to form a plurality of right-angle triangular prisms, that is, converting the original right-angle prism into a plurality of right-angle triangular prisms.

4. The greenhouse gas imaging system based on a ground-to-air mobile platform according to claim 2, characterized in that: The vehicle-mounted passive light source output subsystem (2) further comprises: adding a divergent structure (212) to the output surface of the right-angle prism of the pitch angle of the chasing drone, wherein the structure may be composed of a scattering sheet with a mesh size of 2000 to 5000 or a uniform light sheet with a divergence angle of 5° to 15°.

5. The greenhouse gas imaging system based on a ground-to-air mobile platform according to claim 2, characterized in that: The vehicle-mounted passive light source output subsystem also includes: an environment monitoring module (213), which includes a wide-angle camera and a solar radiation meter. The wide-angle camera is used to collect camera images to monitor the relative position of the sun, the approximate relative position of the drone and the environmental shielding situation. The solar radiation meter is used to detect the solar radiation intensity at different wavelengths of the sun, especially in the infrared band. The obtained camera images and solar radiation intensity are used to judge the weather conditions of the day on the one hand, and the obtained infrared band solar radiation intensity is used as one of the references for spectral analysis on the other hand.

6. The greenhouse gas imaging system based on a ground-to-air mobile platform according to claim 1, characterized in that: The unmanned aerial vehicle dual-gimbal payload subsystem (1) comprises an unmanned aerial vehicle (11), a sun-chasing two-dimensional gimbal (12), a vehicle-chasing two-dimensional gimbal (13), a sun-chasing infrared spectrometer (14), and a vehicle-chasing infrared spectrometer (15); The sun-tracking two-dimensional gimbal (12) is placed on the top of the drone (11) to track the sun and to introduce the direct sunlight signal into the sun-tracking infrared spectrometer (14) via optical fiber. The vehicle-tracking two-dimensional gimbal (13) is placed on the bottom of the drone (11) to track the measurement light signal output by the vehicle-mounted passive light source output subsystem (2) and to introduce the measurement signal into the vehicle-tracking infrared spectrometer (15) via optical fiber. The two infrared spectrometers (14) and (15) convert the direct sunlight signal and the measurement light signal into spectral information respectively, and transmit the information back to the spectral analysis and imaging processing subsystem (3) on the ground.

7. The greenhouse gas imaging system based on a ground-to-air mobile platform according to claim 1, characterized in that: In the spectral analysis and processing subsystem (3), when performing greenhouse gas absorption cross section processing, the original greenhouse gas absorption line intensity is processed into an absorption cross section suitable for actual instrument concentration inversion, so that the collected spectral information can be inverted and analyzed into gas concentration, specifically including: First, based on the pressure broadening effect of physical conditions, the broadened spectral line shape is determined by the following two methods, and the broadened spectral line shape is applied to the absorption line sequence of the original absorption cross section to obtain the absorption cross section after actual gas broadening under physical conditions; Method 1: Construct the spectral line shape of the benchmark greenhouse gas absorption line as the Lorentz line shape f L (v) namely: Where v and p represent the actual observed wave number and pressure, v abs Indicates the wave number corresponding to a gas absorption peak, δ(p ref ) represents the pressure drift coefficient, FWHM pressure It represents the pressure broadening width, which is related to the gas temperature, atmospheric pressure and gas partial pressure, self-broadening coefficient and air broadening coefficient. The specific calculation formula is: where γ air and γ self They represent the self-broadening coefficient of gas and the air broadening coefficient, T meas represents the gas temperature at the time of observation, p gas and p air Respectively represent the gas partial pressure and atmospheric pressure during observation, n air represents the air broadening parameter, T ref and p ref Respectively represent standard temperature value and standard atmospheric pressure value; Method 2: Construct the spectral line shape of the reference greenhouse gas absorption line into a Gaussian line shape f G (v) namely: Among them, FWHM doppler It represents the Doppler broadening width, which is related to the line intensity wave number, gas temperature and gas molecular weight. The specific calculation formula is: Where M represents the molar mass of the gas, N A , c and k are all constants; Then, based on the Doppler broadening effect of the instrument conditions, the absorption cross section obtained by convolving the actual gas broadened absorption cross section with the spectrometer slit function will be further broadened. At this time, a spectral calibration process is added after the convolution, and the convolved absorption cross section is specifically calibrated according to the wavelength corresponding to the CCD in the spectrometer.

8. The greenhouse gas imaging system based on a ground-to-air mobile platform according to claim 1, characterized in that: In the spectral analysis and processing subsystem (3), when performing greenhouse gas absorption cross section processing, the original greenhouse gas absorption line intensity is processed into an absorption cross section suitable for actual instrument concentration inversion, so that the collected spectral information can be inverted and analyzed into gas concentration, which specifically includes: Based on the overall shape characteristics of the infrared absorption line strength of the benchmark greenhouse gas, the actual greenhouse gas infrared absorption cross-section envelope is drawn, so that the original absorption line sequence is transformed into a continuous absorption envelope characteristic curve. The specific process is: first, the benchmark absorption line strength data is screened for absorption peaks based on the absorption line strength threshold, and then the screened absorption peaks are spline interpolated or RFB interpolated to obtain the absorption cross section suitable for actual instrument concentration inversion.

9. The greenhouse gas imaging system based on a ground-to-air mobile platform according to claim 1, characterized in that: In the spectral analysis and processing subsystem (3), when greenhouse gas distribution imaging is performed, a path is planned for the UAV dual gimbal load subsystem (1) and the vehicle-mounted passive light source output subsystem (2), so as to achieve horizontal scanning covering the monitoring area and perform horizontal distribution imaging of greenhouse gases; by changing the flight altitude of the UAV and combining horizontal scanning, stereoscopic imaging of greenhouse gases is achieved; and at the same time, inclined distribution imaging of greenhouse gases can be performed, with the inclination angle being the altitude angle of the sun.

10. The greenhouse gas imaging system based on a ground-to-air mobile platform according to claim 9, characterized in that: In the spectral analysis and processing subsystem (3), greenhouse gas emission quantification is performed after the emission source is traced according to the greenhouse gas distribution imaging results. During the above scanning process, the optical path between the UAV dual gimbal payload subsystem (1) and the vehicle-mounted passive light source output subsystem (2) will be tangent to the emission source plume. The movement of the UAV at different altitudes will be tangent to the greenhouse gas plume at different altitudes. The obtained section is called a horizontal section. At the same time, the sun-tracking two-dimensional gimbal (12) on the top of the UAV dual gimbal payload subsystem (1) is also measuring the solar spectrum at all times. During the movement of the UAV at different altitudes, the optical path between the sun-tracking two-dimensional gimbal (12) and the sun will also be tangent to different positions of the emission source plume in the monitoring area. The obtained section is called an inclined section. The horizontal section and the inclined section of the plume are approximated into a circle. The horizontal section concentration and the inclined section concentration at different altitudes are obtained according to the imaging results, and then the emission flux of the emission source is obtained according to the emission flux calculation formula.

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