An Unmanned Aerial Vehicle (UAV)-borne Hyperspectral Water Quality Monitoring System and Method with Automatic Calibration

Abstract

The present invention discloses an unmanned aerial vehicle (UAV)-borne hyperspectral water quality monitoring system and method with automatic calibration, including: a UAV, an airborne hyperspectral camera, a radiation acquisition and water quality calibration analysis module, a main control module, and a UAV airfield. The UAV airfield serves as the command station and logistics supply station for the UAV. The main control module communicates with the UAV, the airborne hyperspectral camera, and the radiation acquisition and water quality calibration analysis module respectively, and is used to start and stop the operations of the three based on the instructions of the UAV airfield. At the same time, it calculates and analyzes the data collected by each module and outputs the final water quality telemetry value. The radiation acquisition and water quality calibration analysis module and the airborne hyperspectral camera are used to perform spectral acquisition according to the instructions of the main control module. The collected spectra are used to calculate the telemetry value and calibrate the telemetry value, providing data for the main control module to calculate the final water quality telemetry value. This system can realize the full-automatic calibration of water quality parameters by the UAV and can correct and calibrate to obtain a more accurate water quality monitoring result.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicles (UAVs). Specifically, it relates to a UAV-borne hyperspectral water quality monitoring system and method with automatic calibration. Background Art

[0002] Water quality monitoring plays a crucial role in water environmental protection, water pollution control, and maintaining water quality health. For a long time, widely used water quality monitoring methods include calibrating monitoring points in the water area to be measured, collecting water samples on-site and storing them, and then sending the well-preserved water samples to the laboratory for analysis. Commonly used detection methods include instrumental analysis of water quality, oxidation-reduction and electrochemistry methods, and laboratory chemical detection techniques such as heating and decomposition with oxidants. These methods can provide analysis of water quality parameters in the water area to be measured and propose corresponding solutions. Although laboratory chemical analysis can obtain relatively accurate water quality parameters, it requires a large amount of labor and time, and has strict requirements for the preservation conditions of water samples. In addition, this method is usually limited to fixed-point water sampling, making it difficult to achieve real-time monitoring of large areas and long water areas, resulting in the inability to comprehensively and specifically formulate water quality maintenance and treatment plans, and it is even more difficult to effectively predict water quality changes.

[0003] In recent years, remote sensing technology has been applied to water quality monitoring, especially UAV-based hyperspectral water quality remote sensing technology. The image data obtained through remote sensing technology can be used for real-time monitoring of water quality pollution in water areas with large measurement areas and long monitoring lengths. Hyperspectral water quality remote sensing technology utilizes the characteristics of hyperspectral remote sensing technology, such as large range, continuous observation, and multi-platform, multi-band, and multi-resolution, to periodically measure the physical and chemical properties of water to evaluate and determine the water quality status. The basis of water quality remote sensing technology lies in the spectral characteristics of water body components, and the changes in the spectral curves of these components reflect the changes in the total components of the water body. Remote sensing technology monitors water quality by capturing these spectral changes. When sunlight shines on the water surface, part of the light directly enters the atmosphere due to specular reflection, while the other part of the light refracts into the water and returns to the atmosphere after reflection, scattering, and bottom reflection. The sensors in hyperspectral remote sensing equipment capture these lights to form monitoring data. By performing regression analysis, deep learning, etc. on these spectral data, an inversion model of water quality parameters is established to invert the concentration, content, or distribution of pollutants in the water, and then to evaluate the pollution degree and water quality level of the water area.

[0004] However, hyperspectral water quality parameters are remotely affected by weather and environment, and often need to be combined with traditional sampling and detection techniques to improve accuracy. In addition, the flight control of drones also requires personnel who have received professional training and obtained a license. Therefore, there is still a large investment of manpower and time in accurately obtaining water quality parameters over a large area. In addition, the water quality parameters obtained by hyperspectral remote sensing are easily affected by various conditions such as environment, meteorology, and solar altitude, and there is a problem of large numerical fluctuations with similar trends. Accurate hyperspectral remote sensing data needs to be compared and corrected with laboratory data of sampling analysis to further improve accuracy. This undoubtedly further increases the implementation cost and difficulty of hyperspectral remote sensing, and to a certain extent limits the application of hyperspectral remote sensing in water quality monitoring. Summary of the Invention

[0005] In view of the problems in the related art, the present invention proposes an unmanned aerial vehicle (UAV)-borne hyperspectral water quality monitoring system and method with automatic calibration to overcome the above-mentioned technical problems existing in the related art.

[0006] For this purpose, the specific technical solutions adopted by the present invention are as follows:

[0007] An unmanned aerial vehicle (UAV)-borne hyperspectral water quality monitoring system and method with automatic calibration, comprising: a UAV, an airborne hyperspectral camera, a radiation collection and water quality calibration analysis module, a main control module, and a UAV airport,

[0008] The airborne hyperspectral camera, the radiation collection and water quality calibration analysis module, and the main control module are all integrated on the UAV;

[0009] The UAV airport is a command station and logistics supply station for the UAV, and is used to command the flight of the UAV, execute data collection and calibration analysis tasks, provide a UAV apron, charge the UAV, download, process and transmit data, and provide logistics services for the UAV;

[0010] The main control module communicates with the UAV, the airborne hyperspectral camera, and the radiation collection and water quality calibration analysis module respectively, and is used to start and stop the operation of the three based on the instructions of the UAV airport, and at the same time calculate and analyze the data collected by each module to output the final water quality telemetry value;

[0011] The radiation collection and water quality calibration analysis module and the airborne hyperspectral camera are used to perform spectral collection according to the instructions of the main control module, and the collected spectra are used to calculate the telemetry value and calibrate the telemetry value, and provide data for the main control module to calculate the final water quality telemetry value.

[0012] Further, the radiation collection and water quality calibration analysis module includes an optical path and a flow path,

[0013] The optical path includes a cuvette, a switching mirror, a cosine corrector, a spectrometer, a first collimating lens, a second collimating lens, a third collimating lens, and a light source. The cuvette is connected to a flow path. The switching mirror and the first collimating lens are sequentially arranged on the left side of the cuvette. The first collimating lens is connected to the spectrometer through an optical fiber. The second collimating lens is located above the switching mirror. The second collimating lens is connected to the cosine corrector through an optical fiber. The third collimating lens is arranged on the right side of the cuvette. The light source is arranged on the right side of the third collimating lens. The light source, the spectrometer, and the switching mirror are all electrically connected to the main control module. The switching mirror receives the instruction of the main control module to switch the reflection angle for spectral acquisition. The spectra acquired at different reflection angles are respectively used to calculate the telemetry value and calibrate the telemetry value. The top of the cosine corrector is higher than the top of the unmanned aerial vehicle to collect sunlight;

[0014] The flow path is several pipes connected to the cuvette, and is used to provide different water samples for the cuvette according to the instruction of the main control module.

[0015] Furthermore, the light source uses a pulsed xenon lamp.

[0016] Furthermore, the spectral range of the spectrometer covers 200 - 800 nm, and the FWHH resolution is less than 2 nm.

[0017] Furthermore, the material of the cuvette is fused quartz.

[0018] Furthermore, when the radiation acquisition and water quality calibration analysis module performs spectral acquisition in water, the switching mirror rotates to the horizontal state. When the radiation acquisition and water quality calibration analysis module performs spectral acquisition under solar radiation, the switching mirror rotates to a state tilted 45° relative to the horizontal.

[0019] An unmanned aerial vehicle (UAV)-borne hyperspectral water quality monitoring method with automatic calibration is implemented using the UAV-borne hyperspectral water quality monitoring system described in any of the above. It includes the following steps:

[0020] S1: Use the radiation acquisition and water quality calibration analysis module to collect the background spectrum of pure water samples;

[0021] S2: The UAV flies to any sampling point A within the monitoring route this time. Use the radiation acquisition and water quality calibration analysis module to collect the spectrum of the water sample at sampling point A. The main control module calculates the water quality parameter P of sampling point A according to the background spectrum of the pure water sample and the spectrum of the water sample at sampling point A A ;

[0022] S3: The UAV rises linearly from sampling point A to the first height. The radiation acquisition and water quality calibration analysis module moves away from the water surface. At the same time, use the radiation acquisition and water quality calibration analysis module and the airborne hyperspectral camera to collect the module radiation spectrum S A1 and the camera radiation spectrum H A1 ;

[0023] S4: The main control module calculates the reflectance spectrum R of sampling point A based on the spectrum S at the first height A1 and the spectrum H A1 by the formula R A = S A / H A1 ; A1

[0024] S5: The main control module uses the reflectance spectrum R A to invert and obtain the hyperspectral water quality parameter P at the first height of sampling point A A ’ . Then, it calibrates using the water quality parameter P of sampling point A A to obtain and output the calibration coefficient. The calibration coefficient k = P A / P A ’ ;

[0025] S6: The UAV continues to ascend to the second height. Meanwhile, it uses the radiation acquisition and water quality calibration analysis module (4) and the airborne hyperspectral camera (2) to collect the spectrum S Ah and the spectrum H Ah at the second height respectively;

[0026] S7: The UAV flies to each monitoring point within the monitoring route for spectrum collection. The collection steps at each monitoring point are the same. When the UAV flies to monitoring point B, it uses the radiation acquisition and water quality calibration analysis module and the airborne hyperspectral camera to collect the spectrum S Bh and the spectrum H Bh at monitoring point B respectively;

[0027] S8: The main control module calculates the reflectance spectrum R(H A1 , S A1 ) of monitoring point B based on the module radiation spectrum S Ah and the camera radiation spectrum H Ah at the first height of sampling point A, the spectrum S Bh and the spectrum H Bh at the second height, and the spectrum S Bh and the spectrum H Bh at monitoring point B. Here, A and B are constants, which are fixed parameters determined by optics and circuits;

[0028]

[0029]

[0030] S9: The main control module uses R(H Bh , S Bh ) to invert the module radiation water quality parameter of monitoring point B and obtain the remotely sensed value P of the water quality parameter​​B ’ , then calibrate the inversion result with the calibration coefficient k to obtain the calibrated remote sensing value P of the monitoring point B B , P B = kP B ’ ;

[0031] S10: Repeat steps S7 - S9 to obtain the calibrated remote sensing values of each monitoring point and output them.

[0032] The beneficial effects of the present invention are as follows:

[0033] 1. This application can realize the full - automatic calibration of water quality parameters by the unmanned aerial vehicle and can correct and calibrate to obtain more accurate water quality monitoring results;

[0034] 2. Through the optical path and flow path design, this application can automatically calibrate the water quality parameters collected and inverted by the hyperspectral of the unmanned aerial vehicle, improving the accuracy of the hyperspectral monitoring water quality data;

[0035] 3. By making real - time corrections to the atmospheric transmission of solar radiation, this application improves the measurement accuracy of the reflectivity, and further improves the quality of the remotely sensed data of water quality parameters. Description of the Drawings

[0036] 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 use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0037] Figure 1 is a schematic structural diagram of an unmanned aerial vehicle - borne hyperspectral water quality monitoring system with automatic calibration according to Embodiment 1 of the present invention;

[0038] Figure 2 is a schematic structural diagram of the unmanned aerial vehicle of an unmanned aerial vehicle - borne hyperspectral water quality monitoring system with automatic calibration according to Embodiment 1 of the present invention;

[0039] Figure 3 is a schematic diagram of the optical path and flow path when the radiation collection and water quality calibration analysis module of an unmanned aerial vehicle - borne hyperspectral water quality monitoring system with automatic calibration according to an embodiment of the present invention performs spectral collection in water;

[0040] Figure 4 is a schematic diagram of the optical path and flow path when the radiation collection and water quality calibration analysis module of an unmanned aerial vehicle - borne hyperspectral water quality monitoring system with automatic calibration according to an embodiment of the present invention performs spectral collection under solar radiation.

[0041] In the figure:

[0042] 1. UAV; 2. airborne hyperspectral camera; 3. UAV airport; 4. radiation acquisition and water quality calibration analysis module; 41. colorimetric cell; 42. switching mirror; 43. cosine corrector; 44. spectrometer; 45. first collimating lens; 46. second collimating lens; 47. third collimating lens; 48. light source. Specific embodiments

[0043] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0044] According to an embodiment of the present invention, a UAV-borne hyperspectral water quality monitoring system and method with automatic calibration are provided.

[0045] Embodiment 1

[0046] As Figures 1-4 shown, the UAV-borne hyperspectral water quality monitoring system with automatic calibration according to an embodiment of the present invention includes a UAV 1, an airborne hyperspectral camera 2, a radiation acquisition and water quality calibration analysis module 4, a main control module, and a UAV airport 3.

[0047] The airborne hyperspectral camera 2, the radiation acquisition and water quality calibration analysis module, and the main control module are all integrated on the UAV 1.

[0048] The UAV airport 3 is a command station and logistics supply station for the UAV 1, and is used to command the UAV to fly, execute data acquisition and calibration analysis tasks, provide a UAV apron, UAV charging, data downloading, processing and transmission, and provide logistics services for the UAV.

[0049] The main control module communicates with the UAV 1, the airborne hyperspectral camera 2, and the radiation acquisition and water quality calibration analysis module 4 respectively, and is used to start and stop the operation of the three based on the instructions of the UAV airport 3, and at the same time calculate and analyze the data collected by each module and output the final water quality telemetry value.

[0050] The radiation acquisition and water quality calibration analysis module 4 and the airborne hyperspectral camera 2 are used to perform spectral acquisition according to the instructions of the main control module. The collected spectra are used to calculate the telemetry value and calibrate the telemetry value, and provide data for the main control module to calculate the final water quality telemetry value.

[0051] It should be noted that the main control module includes necessary control circuits and a data processing computer. The data processing computer can be integrated with the airborne hyperspectral camera 2, or installed on the fuselage of the unmanned aerial vehicle 1 together with the radiation collection and water quality calibration analysis module 4. The airborne hyperspectral camera 2 is connected to the unmanned aerial vehicle 1 through a gimbal and a gimbal bracket. Wires are arranged in the gimbal to enable the airborne hyperspectral camera 2 to obtain power from the unmanned aerial vehicle 1 and communicate with the unmanned aerial vehicle. The radiation collection and water quality calibration analysis module 4 can be installed on the top of the unmanned aerial vehicle or integrated into the fuselage of the unmanned aerial vehicle, depending on the structural design of the unmanned aerial vehicle.

[0052] The unmanned aerial vehicle airport 3 is powered on and connected to the network. The user can achieve the inspection of the unmanned aerial vehicle 1 by presetting the flight path and the task points in the flight path. During the task process, the unmanned aerial vehicle airport 3 can command the unmanned aerial vehicle 1 to fly, execute data collection and calibration tasks, provide a landing pad for the unmanned aerial vehicle, charge the unmanned aerial vehicle, and download, process and transmit data.

[0053] Among them, the radiation collection and water quality calibration analysis module 4 includes an optical path and a flow path.

[0054] The optical path includes a cuvette 41, a switching mirror 42, a cosine corrector 43, a spectrometer 44, a first collimating lens 45, a second collimating lens 46, a third collimating lens 47 and a light source 48. The light source 48 uses a pulsed xenon lamp. The spectral range of the spectrometer 44 covers 200 - 800 nm, and the FWHH resolution is less than 2 nm. The cuvette 41 is made of fused quartz. The cuvette 41 is connected to the flow path. The switching mirror 42 and the first collimating lens 45 are sequentially arranged on the left side of the cuvette 41. The first collimating lens 45 is connected to the spectrometer 44 through an optical fiber. The second collimating lens 46 is located above the switching mirror 42. The second collimating lens 46 is connected to the cosine corrector 43 through an optical fiber. The third collimating lens 47 is arranged on the right side of the cuvette 41. The light source 48 is arranged on the right side of the third collimating lens 47. The light source 48, the spectrometer 44 and the switching mirror 42 are all electrically connected to the main control module. The switching mirror 42 receives the instruction of the main control module to switch the reflection angle for spectral collection. The spectra collected at different reflection angles are respectively used to calculate the telemetry value and calibrate the telemetry value. The top of the cosine corrector 43 is higher than the top of the unmanned aerial vehicle 1 to collect sunlight.

[0055] The flow path is several pipes connected to the cuvette 41, which are used to provide different water samples for the cuvette 41 according to the instruction of the main control module. The flow path part includes a three-way switching valve controlled by an electric circuit, pipelines, and a sampling pump connected to the cuvette and the pipelines. In addition, necessary control and drive circuits are provided to realize the control such as the switching of the optical path and the flow path.

[0056] The radiation collection and water quality calibration analysis module 4 needs to perform spectral collection both in the process of calculating the telemetry value and calibrating the telemetry value, and needs to perform spectral collection in water and under solar radiation respectively, asFigure 3 As shown, when collecting spectrum in water, the switch reflector 42 is rotated to a horizontal state, as shown in FIG. Figure 4 As shown, when the radiation collection and water quality calibration analysis module 4 performs spectrum collection under solar radiation, the switching reflector 42 rotates to a state of 45° relative horizontal inclination. In addition, in order to cooperate with the realization of spectrum collection in water, pure water, cleaning liquid, containers and pipelines need to be set up in the airport. When the drone 1 is recovered to the airport, the sampling tube of the drone 1 is in a retracted state. The main control board of the radiation collection and water quality calibration analysis module 4 communicates with the airport, and then allows the airport to control which container the sampling tube is connected to.

[0057] The entire system can automatically inspect the target water area without human intervention. And its automatic calibration capability can obtain water quality parameter analysis values at the beginning of each mission to calibrate the telemetry values, without the need for personnel to go to the site for calibration operations or perform subsequent data processing, so as to ensure data quality. After the inspection, the system automatically processes the data, uploads the data, and automatically cleans the water quality analysis module. Therefore, fully automated and reliable water quality parameter remote sensing operations can be achieved. In addition to regular maintenance, battery inspection, and pure water replenishment, there is no other work in order.

[0058] Hyperspectral remote sensing of water quality is based on the change in light reflectivity caused by changes in components in the water body. The change in reflectivity is essentially still caused by the absorption of light by specific molecules in the water. In this process, the reflectivity spectrum curve is used to measure specific components, and to achieve a quantitative level, it is necessary to obtain the reflectivity curve more accurately. In addition, even if a more accurate reflectivity curve is obtained, it is still difficult to obtain accurate water quality parameters. Because the components in the water are not the only factors that affect the reflectivity curve, other factors include the intensity of solar radiation, solar altitude angle, water depth, water turbidity and other meteorological conditions. Based on this complex actual situation, the present invention designs a set of optical paths and flow paths to achieve real-time reflectivity detection and water quality parameter analysis and calibration. Since the water quality parameters inverted by the hyperspectral method have a good correlation with the water quality parameters obtained by the transmission analysis method, the calibration can be completed by polynomial fitting and other methods.

[0059] Specifically, Figure 3As shown in the figure, when performing spectral acquisition in water, the main control module controls the switching mirror 42 to rotate to the horizontal state in the figure. The polychromatic light emitted by the xenon lamp of the light source 48 is collimated into parallel light by the third collimating lens 47 and incident on the cuvette 41. The material of the cuvette 41 is preferably fused quartz to achieve high transmittance in the ultraviolet band. The light beam passes through the cuvette 41 and enters the lens of the spectrometer 44, where it is converged and received by the optical fiber and transmitted to the spectrometer 44 for acquisition. The working process is as follows: The three-way valve is switched to the pure water path, and the sampling pump is started to work for a period of time so that the cuvette 41 is filled with pure water. The pulsed xenon lamp is triggered to flash, and at the same time, the spectrometer 44 is triggered to acquire the spectrum. At this time, the background spectrum of pure water is obtained. Then the three-way valve is switched to the sample water / washing liquid path. If the drone 1 is collecting above the water body, then this path is connected to the sample water body. The sampling pump is started to work for a period of time so that the cuvette 41 is filled with pure water. The xenon lamp is triggered to flash, and at the same time, the spectrometer 44 is triggered to acquire the spectrum. At this time, the sample water spectrum is obtained, and then the absorbance spectrum of the sample water is obtained. Then, the water quality parameters are calculated according to the absorbance spectrum of the sample water and the pre-built model.

[0060] Specifically, as Figure 4 shown in the figure, when performing spectral acquisition under solar radiation, the switching mirror 42 rotates to the inclined 45° state in the figure. At this time, the xenon lamp no longer works synchronously with the spectrometer 44, and the optical path of the cuvette 41 is blocked. The solar radiation passes through the cosine corrector 43 and is transmitted by the optical fiber. After being collimated by the second collimating lens 46, it is reflected by the switching mirror 42, then converged by the first collimating lens 45 and transmitted by the optical fiber, and finally received by the spectrometer 44.

[0061] Embodiment 2

[0062] A drone-borne hyperspectral water quality monitoring method with automatic calibration is implemented using the drone-borne hyperspectral water quality monitoring system of Embodiment 1, and includes the following steps:

[0063] S1: Use the radiation acquisition and water quality calibration analysis module 4 to acquire the background spectrum of pure water samples;

[0064] S2: The drone 1 flies to any sampling point A within the monitoring route this time. Use the radiation acquisition and water quality calibration analysis module 4 to acquire the spectrum of the water sample at sampling point A. The main control module calculates the water quality parameter P of sampling point A according to the background spectrum of the pure water sample and the spectrum of the water sample at sampling point A A ;

[0065] S3: The drone 1 rises linearly from sampling point A to the first height, which is about 10 meters. The radiation acquisition and water quality calibration analysis module 4 is far from the water surface. At the same time, use the radiation acquisition and water quality calibration analysis module 4 and the airborne hyperspectral camera 2 to acquire the module radiation spectrum S A1 and the camera radiation spectrum H of sampling point A at the first heightA1 ;

[0066] S4: The main control module calculates the reflectance spectrum R of sampling point A according to the spectrum S at the first height A1 and the spectrum H A1 ; R A = S A / H A1 ; A1 ;

[0067] S5: The main control module uses the reflectance spectrum R A to perform inversion to obtain the hyperspectral water quality parameter P at the first height of sampling point A A ’ , and then calibrates it with the water quality parameter P of sampling point A A to obtain and output the calibration coefficient. The calibration coefficient k = P A / P A ’ ;

[0068] S6: UAV 1 continues to rise to the second height, which is about 100 meters. At the same time, the radiation acquisition and water quality calibration analysis module 4 and the airborne hyperspectral camera 2 are used to collect the spectrum S at the second height Ah and the spectrum H Ah ;

[0069] S7: UAV 1 flies to each monitoring point within the monitoring route for spectrum collection. The collection steps at each monitoring point are the same. When UAV 1 flies to monitoring point B, the radiation acquisition and water quality calibration analysis module 4 and the airborne hyperspectral camera 2 are used to collect the spectrum S of monitoring point B Bh and the spectrum H Bh ;

[0070] S8: The main control module calculates the reflectance spectrum R of monitoring point B according to the module radiation spectrum S at the first height of sampling point A A1 and the camera radiation spectrum H A1 , the spectrum S at the second height Ah and the spectrum H Ah as well as the spectrum S of monitoring point B Bh and the spectrum H Bh ; R(H Bh , S Bh ),

[0071]

[0072] , where A and B are constants, which are fixed parameters determined by optics and circuits;

[0073] S9: The main control module uses R(H Bh , S Bh)Invert the module radiation water quality parameters at monitoring point B to obtain the remotely sensed value P of the water quality parameters B ’ , and then calibrate the inversion result with the calibration coefficient k to obtain the calibrated remotely sensed value P at monitoring point B B , P B = kP B ’ ;

[0074] S10: Repeat steps S7 - S9 to obtain the calibrated remotely sensed values of each monitoring point and output them

[0075] It should be noted that the hyperspectral remote sensing inversion of water quality parameters is mainly obtained by analyzing the water body reflectance. Therefore, the accurate acquisition of water body reflectance is the premise and key for the correct inversion of water quality parameters. Since the unmanned aerial vehicle hyperspectral remote sensing is in an open environment, the states of the hyperspectral camera, light source (the sun), and target sample (flowing water body) cannot remain static. Therefore, it is not feasible to obtain absolutely accurate reflectance, and only the main systematic errors can be eliminated as much as possible

[0076] The most commonly used method is to use a standard reflectance panel, which is generally made of metal or Teflon materials to form a diffuse reflection surface with a known reflectance. By collecting the spectra of the standard reflectance panel and the sample and comparing the two, a relatively accurate reflectance spectrum of the sample can be obtained. This method is simple and effective, and the accuracy is also very high. The measurement conditions of the sample and the standard reflectance panel are almost exactly the same, and the only variable is the reflectance of the sample itself. Solar radiation, atmospheric transmission, and environmental changes are all taken into account. However, this method also has obvious disadvantages - lack of timeliness. The sun, as a changing and moving light source, its altitude angle and cloud cover rate are constantly changing. Sometimes, within a few minutes, the effective radiation reaching the sample surface by the sun can change drastically. In actual monitoring, the task may often last for half an hour, and it is impossible to measure the standard reflectance panel throughout the entire time. Therefore, the reflectance collected during the task is actually fluctuating continuously with the change of solar radiation. In addition, the carrying and deployment of the reflectance panel need to be completed manually, which is not conducive to automated operation

[0077] Another solution is to use solar radiation to measure solar radiation in real time. In the early stage, a standard reflectance plate or a standard light source is still used to calibrate the hyperspectral camera and solar radiation, so that the measurement of radiation intensity has relative consistency. In this way, the real-time reflectance spectrum can be obtained through the data of solar radiation and the hyperspectral camera. This solution solves the problem that the standard reflectance plate cannot provide data in real time. However, the accuracy of using solar radiation to correct the reflectance is limited. The main reason is that the installation position of solar radiation is on top of the drone, about 100 meters above the ground. Therefore, the light intensity here does not fully represent the light intensity on the water surface. Air transmission is not considered.

[0078] The above-mentioned effects of solar radiation and atmospheric transmission on reflectance not only make the inversion results of water quality parameters inaccurate, but also require more data processing and correction work in the later stage to improve the accuracy of the data. In order to achieve fully automatic operation of hyperspectral water quality monitoring, the present invention not only gives the design of the hardware, but also gives the work and calculation method for improving the accuracy of reflectance.

[0079] The wavelength band of 400-1000nm used in hyperspectral remote sensing of water quality is an atmospheric window, but there are still absorptions of water and carbon dioxide. In addition, particulate matter and aerosols in the air will also scatter sunlight. Since the drone carrying the hyperspectral camera generally operates at an altitude of about 100 meters, the reflected light of the water body collected by the hyperspectral camera under the same solar radiation is affected by atmospheric absorption and scattering. This is particularly significant in areas with severe air pollution or fog. The reflectance of the water body obtained in this way has a large error, which causes an error in the inversion of water quality parameters.

[0080] Based on the above, the present invention proposes that before leaving the factory, the solar radiation and the hyperspectral camera need to be calibrated using the same light source to obtain the following relationship: I s =AI hs +B, where I s is the spectrum collected by the solar radiation, I hs is the spectrum collected by the hyperspectral camera, and A and B are constants. Since I s and I hs can both be measured simultaneously in the experiment, A and B can both be calculated. A and B are fixed parameters determined by optics and circuits.

[0081] Therefore, before each flight mission is executed, the system first performs an automatic calibration, and the calibration method is as described in the above steps S3-S8.

[0082] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An airborne hyperspectral water quality monitoring system with automatic calibration, characterized in that Including: An unmanned aerial vehicle (1), an airborne hyperspectral camera (2), a radiation acquisition and water quality calibration analysis module (4), a main control module, and an unmanned aerial vehicle airport (3). The airborne hyperspectral camera (2), the radiation acquisition and water quality calibration analysis module, and the main control module are all integrated on the unmanned aerial vehicle (1). The unmanned aerial vehicle airport (3) is the command station and logistics supply station for the unmanned aerial vehicle (1), and is used to command the flight of the unmanned aerial vehicle, execute data acquisition and calibration analysis tasks, provide a landing pad for the unmanned aerial vehicle, charge the unmanned aerial vehicle, download, process and transmit data, and provide logistics services for the unmanned aerial vehicle. The main control module communicates with the unmanned aerial vehicle (1), the airborne hyperspectral camera (2), and the radiation acquisition and water quality calibration analysis module (4) respectively, and is used to start and stop the work of the three based on the instructions of the unmanned aerial vehicle airport (3), and at the same time calculate and analyze the data collected by each module to output the final water quality telemetry value. The radiation acquisition and water quality calibration analysis module (4) includes an optical path and a flow path to realize the detection of real-time reflectance and the analysis and calibration of water quality parameters; the radiation acquisition and water quality calibration analysis module (4) and the airborne hyperspectral camera (2) are used to perform spectral acquisition according to the instructions of the main control module, and the collected spectra are used to calculate the telemetry value and calibrate the telemetry value, providing data for the main control module to calculate the final water quality telemetry value. The radiation acquisition and water quality calibration analysis module (4) is used to collect the background spectrum of pure water samples before flight and the spectrum of water samples at the sampling points during flight, for calculating the water quality parameters of the water samples at the sampling points. At the same time, the radiation acquisition and water quality calibration analysis module (4) and the hyperspectral camera (2) are used to collect spectral data at two heights from the sampling point during flight, for calculating the calibration coefficient in combination with the water quality parameters at the sampling point, and the calibration coefficient is used to correct the telemetry value at the sampling point.

2. The airborne hyperspectral water quality monitoring system with automatic calibration according to claim 1, characterized in that, The optical path includes a colorimetric cell (41), a switching mirror (42), a cosine corrector (43), a spectrometer (44), a first collimating lens (45), a second collimating lens (46), a third collimating lens (47), and a light source (48). The colorimetric cell (41) is connected to the flow path. The switching mirror (42) and the first collimating lens (45) are sequentially arranged on the left side of the colorimetric cell (41). The first collimating lens (45) is connected to the spectrometer (44) through an optical fiber. The second collimating lens (46) is located above the switching mirror (42), and the second collimating lens (46) is connected to the cosine corrector (43) through an optical fiber. The third collimating lens (47) is arranged on the right side of the colorimetric cell (41), and the light source (48) is arranged on the right side of the third collimating lens (47). The light source (48), the spectrometer (44), and the switching mirror (42) are all electrically connected to the main control module. The switching mirror (42) receives the instructions of the main control module to switch the reflection angle for spectral acquisition. The spectra collected at different reflection angles are respectively used to calculate the telemetry value and calibrate the telemetry value. The top of the cosine corrector (43) is higher than the top of the unmanned aerial vehicle (1) to collect sunlight. The flow path is several pipes connecting the colorimetric cell (41), and is used to provide different water samples for the colorimetric cell (41) according to the instructions of the main control module.

3. The airborne hyperspectral water quality monitoring system with automatic calibration according to claim 2, characterized in that, The light source (48) uses a pulsed xenon lamp.

4. The airborne hyperspectral water quality monitoring system with automatic calibration according to claim 2 or 3, characterized in that The spectral range of the spectrometer (44) covers 200 - 800 nm, and the FWHH resolution is less than 2 nm.

5. The airborne hyperspectral water quality monitoring system with automatic calibration according to claim 2 or 3, characterized in that, The cuvette (41) is made of fused quartz.

6. The airborne hyperspectral water quality monitoring system with automatic calibration according to claim 2 or 3, characterized in that, When the radiation acquisition and water quality calibration analysis module (4) performs spectral acquisition in water, the switching mirror (42) rotates to the horizontal state. When the radiation acquisition and water quality calibration analysis module (4) performs spectral acquisition under solar radiation, the switching mirror (42) rotates to a state inclined 45° relative to the horizontal.

7. A method for monitoring water quality using an airborne hyperspectral sensor with automatic calibration, which is implemented by using the airborne hyperspectral water quality monitoring system with automatic calibration according to any one of claims 1-6, characterized in that It includes the following steps: S1: Use the radiation acquisition and water quality calibration analysis module (4) to collect the background spectrum of pure water samples. S2: The drone (1) flies to any sampling point A within the current monitoring route, and the radiation collection and water quality calibration analysis module (4) collects the spectrum of the water sample at sampling point A. The main control module calculates the water quality parameter P of sampling point A based on the background spectrum of the pure water sample and the spectrum of the water sample at sampling point A A ; S3: The drone (1) ascends linearly to the first altitude along the sampling point A, the radiation acquisition and water quality calibration analysis module (4) moves away from the water surface, and meanwhile, the radiation acquisition and water quality calibration analysis module (4) and the airborne hyperspectral camera (2) are respectively used to acquire the module radiation spectrum S of the sampling point A at the first altitude A1 and the camera radiation spectrum H A1 ; S4: The main control module calculates the reflectance spectrum R of the sampling point A according to the spectrum S at the first height A1 and the spectrum H A1 A where R A = H A1 / S A1 ;​ S5: The main control module uses the reflectance spectrum R A to perform inversion to obtain the hyperspectral water quality parameter P at the first height of sampling point A A ’ , and then uses the water quality parameter P of sampling point A A for calibration, obtains and outputs the calibration coefficient, and the calibration coefficient k = P A / P A ’ ; S6: The drone (1) continues to ascend to the second altitude, and meanwhile, the radiation acquisition and water quality calibration analysis module (4) and the airborne hyperspectral camera (2) are used to respectively collect the spectrum S Ah and the spectrum H Ah ; S7: The drone (1) flies to each monitoring point within the current monitoring route for spectral acquisition. The acquisition steps at each monitoring point are the same. When the drone (1) flies to monitoring point B, the radiation acquisition and water quality calibration analysis module (4) and the airborne hyperspectral camera (2) are used to acquire the spectrum S Bh and the spectrum H Bh ; S8: The main control module calculates the reflectance spectrum R(H A1 , S A1 ) of monitoring point B based on the module radiation spectrum S of the first height at sampling point A Ah and the camera radiation spectrum H Ah , the spectrum S of the second height Bh and the spectrum H Bh , as well as the spectrum S of monitoring point B Bh and the spectrum H Bh ; R(H Bh , S Bh ) = (AH Bh H A1 S Ah + BH A1 S Ah ) / S Bh S A1 H Ah , where A and B are constants, which are fixed parameters determined by optics and circuits; S9: The main control module uses R(H Bh , S Bh ) to invert the module radiation water quality parameters at monitoring point B, and obtain the telemetered water quality parameter value P B ’ . Then, use the calibration coefficient k to calibrate the inversion result to obtain the calibrated telemetered value P B at monitoring point B, P B = kP B ’ ; S10: Repeat steps S7 - S9 to obtain the calibrated telemetry values at each monitoring point and output them.

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