Multi-spectral laser fluorescent radar equipment carried on basis of unmanned aerial vehicle

Abstract

The invention relates to the technical field of multispectral laser fluorescent radars, and discloses a multispectral laser fluorescent radar device carried on the basis of an unmanned aerial vehicle, a mounting plate is arranged at the top of a radar mechanism, an unmanned aerial vehicle body is arranged on the outer side of the mounting plate, and supporting legs are fixedly connected to the bottom of the unmanned aerial vehicle body. The radar mechanism comprises a transmitting and receiving module body, a space-based computer control acquisition module, a wireless transmitting and receiving module and a ground-based control computer. The transmitting and receiving module body comprises a transmitting unit, a receiving unit, a dispersion unit and a detection unit. The emission unit comprises a 405nm semiconductor laser. A 405nm semiconductor laser is adopted, high-peak power output which is up to about 4W can be obtained through narrow-pulse large-current driving and a multi-beam incoherent beam combination technology, the farthest detection distance can reach 60m in cooperation with a Schmidt Cassegrain type turn-back telescope, and remote sensing monitoring requirements of multiple scenes such as water and land can be met.

Description

Technical Field

[0001] This invention relates to the field of multispectral laser fluorescence radar technology, specifically to a multispectral laser fluorescence radar device based on a drone. Background Technology

[0002] With the increasing demand for long-distance, high-precision remote sensing monitoring in fields such as environmental monitoring and resource exploration, multispectral laser fluorescence radar technology has gained widespread attention in scenarios such as water pollution detection, terrestrial ecological monitoring, and pollutant identification due to its ability to quickly capture the fluorescence spectral characteristics of target substances. Traditional multispectral laser fluorescence radar equipment is mostly ground-based fixed or large airborne. Ground-based fixed equipment is limited by its deployment location and has a limited monitoring range, making it difficult to achieve large-scale, flexible, and mobile monitoring operations. Large airborne equipment has problems such as large size, heavy weight, complex operation, and high deployment costs, making it unsuitable for the needs of complex terrain or small-scale precise monitoring.

[0003] In water monitoring, traditional equipment struggles to respond quickly to sudden pollution events such as oil spills and algal blooms, and lacks the ability to accurately identify and quantify oil film thickness and pollutant types. Existing technologies, such as some fluorescence radar devices using a single laser or simple dispersive systems, suffer from low peak power, short detection range, and poor spectral resolution, making it difficult to distinguish fluorescence signals from substances like chlorophyll, CDOM, and different types of oil, resulting in insufficient accuracy of monitoring data. Furthermore, the signal processing algorithms of traditional equipment are relatively simple, and in complex environments such as bright sunlight, foggy or rainy weather, or water scattering, severe background noise interference makes it difficult to extract high signal-to-noise ratio fluorescence signals, further affecting the reliability of monitoring results.

[0004] In the field of pollutant identification and quantitative analysis, existing technologies mostly rely on complex calibration processes to invert oil film thickness, which are easily affected by factors such as detection distance, instrument parameters, and environmental transmittance, thus limiting the measurement range. Pollutant classification and identification often employ traditional CNN models, which have high requirements for input image size and the number of training samples. In actual monitoring, these models struggle to quickly adapt to the spectral characteristics of pollutants in different scenarios, resulting in lower identification efficiency and accuracy. Furthermore, traditional equipment has short wireless communication distances and low data transmission rates, making it difficult to achieve long-distance real-time data interaction and remote control between UAVs and ground stations, thus limiting the equipment's operating radius and application scenario expansion.

[0005] Therefore, developing a compact, lightweight, and UAV-based multispectral lidar device with long-range detection, high spectral resolution, strong anti-interference capabilities, accurate pollutant identification, and efficient quantitative analysis is crucial to solving current monitoring technology bottlenecks and meeting the needs of remote sensing monitoring in various scenarios. Summary of the Invention

[0006] The purpose of this invention is to provide a multispectral laser fluorescence radar device based on an unmanned aerial vehicle (UAV) to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a multispectral laser fluorescence radar device based on a drone, comprising a radar mechanism, a mounting plate on the top of the radar mechanism, a drone body on the outside of the mounting plate, and a support foot fixedly connected to the bottom of the drone body;

[0008] The radar system includes a transmitter / receiver module, a space-based computer control and acquisition module, a wireless transmitter / receiver module, and a ground-based control computer.

[0009] Preferably, the transmitter-receiver module body includes a transmitter unit, a receiver unit, a dispersion unit, and a detector unit. The transmitter unit includes a 405nm semiconductor laser, a pulse drive circuit, and a collimated emission optical system. The pulse drive circuit adopts a narrow pulse high current drive method, and the drive current is adjustable to achieve pulse width adjustment from 5ns to 1000ns. The transmitter unit obtains high peak power laser output by incoherently combining the output beams of multiple semiconductor lasers. The collimated emission optical system consists of two K9 glass cylindrical mirrors with mutually perpendicular axes, used to compress the divergence angle of the laser beam in the x and y directions, so as to homogenize the laser energy distribution. The receiver unit adopts a Schmidt-Cassegrain telescope with a primary mirror aperture of 105mm and a focal length of 800mm, used to converge the fluorescence signal reflected by the target. The dispersion unit is a direct-view dispersion system based on dual Amici prisms. The first and third prisms are made of K9 glass, and the second prism is made of ZF7 glass. To achieve efficient dispersion of composite light, the detection unit consists of an image intensifier coupled with a CMOS camera, forming an ICCD detection system. The image intensifier is a GF2800HS type, with a spectral response covering the visible light to 950nm infrared band. The CMOS camera has a frame rate of no less than 100Hz and supports multiple acquisition modes. The space-based computer control acquisition module uses a software system developed with Python+OpenCV+PyQT, integrating a control module, data acquisition and processing module, display module, and storage module to achieve synchronous control of laser emission and camera acquisition, spectral data processing, and real-time display. The wireless transmission and reception module adopts a 2.4GHz bidirectional radio frequency communication architecture, including a router, radio frequency amplifier, and omnidirectional antenna, to achieve long-distance data transmission and remote control between the UAV and the ground station. The ground-based control computer communicates with the space-based computer through a wireless module to achieve remote control of the equipment and further processing and analysis of spectral data.

[0010] Preferably, the dispersion system for the dispersion element to perform spectral splitting is divided into grating dispersion type and prism dispersion type. The dispersion of the grating as a spectral splitting element is basically linear, while the dispersion of the prism depends on the material of the prism. The three vertices of the first prism are 66°, 55° and 59°, and the three vertices of the second prism are 55°, 55° and 70°. The height d of the prism system is 14.3 mm. According to the principle of geometric optics, the expression for the angle between the incident ray and the outgoing ray can be obtained.

[0011]

[0012] In the formula , —The refractive indices of K9 and ZF7 glass materials, respectively;

[0013] , —These are the two apex corners of the first prism;

[0014] According to Rayleigh's criterion, the smallest wavelength difference that a double Amici prism can resolve is... .

[0015]

[0016] In the formula, a represents the width of the emitted beam.

[0017] The minimum wavelength difference Dl resolved by the dual Amici prisms.

[0018]

[0019] According to Schott's formula, the refractive index n(l) of K9 glass and ZF7 glass are related to the wavelength by the following condition:

[0020]

[0021] K9 glass and ZF7 glass , , , , , It can be retrieved from the ZEMAX software glass library.

[0022] Preferably, the pulse driving circuit includes a TTL trigger signal generation circuit, a narrow pulse generation circuit, a MOSFET driving circuit, an LD driving circuit, and a matching circuit. The collimated emission optical system is optimized by ZEMAX software, and the divergence angle of the collimated beam in the meridional direction is 0.47 mrad, the divergence angle in the sagittal direction is 0.82 mrad, and the energy distribution of the laser spot at 30 m is uniform.

[0023] Preferably, the data acquisition and processing module employs a CCD longitudinal accumulation algorithm, a time integration method, a Savitzky-Golay convolution smoothing method, and a background subtraction algorithm. The background subtraction algorithm removes background noise by turning on the CMOS camera twice within one laser cycle to collect the laser signal and the pure background signal respectively and subtracting them.

[0024] Preferably, the system further includes a range-gated imaging system, which consists of a gating module, a delay module, and an MCP control module. By controlling the delay between the laser pulse and the gating pulse, the system filters out medium scattering noise and background noise, thereby improving imaging quality and detection range.

[0025] Preferably, the method further includes a pollutant identification and quantitative analysis module. The quantitative analysis module uses the fluorescence-Raman intensity ratio method to invert the oil film thickness, and the identification module uses the PCANet-SVM model to achieve classification and identification of multiple pollutants.

[0026] Compared with the prior art, the present invention provides a multispectral laser fluorescence radar device based on a drone, which has the following beneficial effects:

[0027] 1. This UAV-based multispectral laser fluorescence radar device uses a 405nm semiconductor laser. Through narrow pulse high current drive and multi-beam incoherent beam combining technology, it can achieve a peak power output of up to about 4W. When paired with a Schmidt-Cassegrain telescope, the maximum detection distance can reach 60m, which can meet the long-distance remote sensing monitoring needs of multiple scenarios such as water and land.

[0028] The direct-view dispersion system based on dual Amici prisms adopts a combination design of K9 and ZF7 glass, which has excellent minimum wavelength resolution. Combined with the ICCD detection system, it can accurately capture multi-band fluorescence signals and achieve high-sensitivity detection of different substances such as chlorophyll, CDOM, and various oils.

[0029] The integrated range-gated imaging system effectively filters out medium scattering noise and background noise by controlling the delay between the laser pulse and the gating pulse. Even in complex environments such as fog, rain, and water scattering, it can obtain high-quality imaging and significantly improve the accuracy of target recognition.

[0030] 2. This UAV-based multispectral laser fluorescence radar device integrates a data acquisition and processing module with longitudinal accumulation of area CCD, time integration, Savitzky-Golay convolution smoothing, and background subtraction algorithms. The background subtraction algorithm extracts high signal-to-noise ratio fluorescence signals under bright sunlight or strong background interference by subtracting the signals acquired twice within the laser cycle. The fluorescence data has a maximum frame rate of 60fps, and the processing speed far exceeds that of traditional large-scale fluorescence radars.

[0031] An innovative fluorescence-Raman intensity ratio method is proposed, which can invert oil film thickness without complex calibration. It effectively avoids the influence of factors such as detection distance, instrument parameters, and environmental transmittance, expands the measurement range of oil film thickness, and provides accurate data support for oil spill assessment.

[0032] The PCANet-SVM classification model is used to extract and classify the features of pollutant fluorescence spectra. Compared with traditional CNN models, it is less dependent on the size of the input image and the number of training samples, and can quickly and accurately distinguish various pollutants such as corn oil, crude oil, and diesel. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort:

[0034] Figure 1 This is a front view structural diagram of the present invention;

[0035] Figure 2 This is a schematic diagram of the radar mechanism structure;

[0036] Figure 3 This is a schematic diagram of the structure of an unmanned aerial vehicle (UAV)-borne LIF radar.

[0037] Figure 4 This is a schematic diagram of the dual Amici prism beam-splitting structure;

[0038] Figure 5 This is a schematic diagram of the optical resolution structure of the dual Amici prism beam-splitting structure.

[0039] Figure 6 This is a block diagram of the structure of an unmanned aerial vehicle (UAV)-borne LIF monitoring system.

[0040] Figure 7 The process of laser pulses returning to the camera;

[0041] Figure 8 This explains the principle of range-gated imaging technology.

[0042] Figure 9 This is a schematic diagram of high-speed real-time LIF radar monitoring.

[0043] In the diagram: 1. Support leg; 2. UAV body; 3. Mounting plate; 4. Radar mechanism; 41. Space-based computer control and acquisition module; 42. Transmitter / receiver module body; 43. Wireless transmitter / receiver module; 44. Ground-based control computer. Detailed Implementation

[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0045] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0046] This invention provides the following technical solutions:

[0047] Example 1

[0048] Please see Figure 1-9 The present invention provides a technical solution: a multispectral laser fluorescence radar device based on a drone, including a radar mechanism 4, a mounting plate 3 on the top of the radar mechanism 4, a drone body 2 on the outside of the mounting plate 3, and a support foot 1 fixedly connected to the bottom of the drone body 2.

[0049] The radar unit 4 includes a transmitter / receiver module body 42, a space-based computer control and acquisition module 41, a wireless transmitter / receiver module 43, and a ground-based control computer 44.

[0050] Furthermore, the main body 42 of the transmitter-receiver module includes a transmitter unit, a receiver unit, a dispersion unit, and a detector unit. The transmitter unit includes a 405nm semiconductor laser, a pulse drive circuit, and a collimated emission optical system. The pulse drive circuit adopts a narrow pulse high current drive method, and the drive current is adjustable to achieve pulse width adjustment from 5ns to 1000ns. The transmitter unit obtains high peak power laser output by incoherently combining the output beams of multiple semiconductor lasers. The collimated emission optical system consists of two K9 glass cylindrical mirrors with mutually perpendicular axes, used to compress the divergence angle of the laser beam in the x and y directions, so as to homogenize the laser energy distribution. The receiver unit adopts a Schmidt-Cassegrain telescope with a primary mirror aperture of 105mm and a focal length of 800mm, used to converge the fluorescence signal reflected by the target. The dispersion unit is a direct-view dispersion system based on dual Amici prisms. The first and third prisms are made of K9 glass, and the second prism is made of ZF7 glass, achieving... The composite light exhibits high-efficiency dispersion. The detection unit consists of an image intensifier coupled with a CMOS camera to form an ICCD detection system. The image intensifier is a GF2800HS type, with a spectral response covering the visible light to 950nm infrared band. The CMOS camera has a frame rate of no less than 100Hz and supports multiple acquisition modes. The space-based computer control acquisition module 41 uses a software system developed with Python+OpenCV+PyQT, integrating a control module, a data acquisition and processing module, a display module, and a storage module to achieve synchronous control of laser emission and camera acquisition, spectral data processing, and real-time display. The wireless transmission and reception module 43 adopts a 2.4GHz bidirectional radio frequency communication architecture, including a router, radio frequency amplifier, and omnidirectional antenna, to achieve long-distance data transmission and remote control between the UAV and the ground station. The ground-based control computer 44 communicates with the space-based computer through a wireless module to achieve remote control of the equipment and further processing and analysis of spectral data.

[0051] Furthermore, dispersive systems using dispersive elements for beam splitting are divided into grating-type and prism-type systems. The dispersion of a grating as a beam splitter is essentially linear, while the dispersion of a prism depends on its material. The three vertices of the first prism are 66°, 55°, and 59°, and the three vertices of the second prism are 55°, 55°, and 70°. The height d of the prism system is 14.3 mm. Based on the principles of geometric optics, the expression for the angle between the incident and outgoing rays can be obtained.

[0052]

[0053] In the formula , —The refractive indices of K9 and ZF7 glass materials, respectively;

[0054] , —These are the two apex corners of the first prism;

[0055] According to Rayleigh's criterion, the smallest wavelength difference that a double Amici prism can resolve is... .

[0056]

[0057] In the formula, a represents the width of the emitted beam.

[0058] The minimum wavelength difference Dl resolved by the dual Amici prisms.

[0059]

[0060] According to Schott's formula, the refractive index n(l) of K9 glass and ZF7 glass are related to the wavelength by the following condition:

[0061]

[0062] K9 glass and ZF7 glass , , , , , It can be retrieved from the ZEMAX software glass library.

[0063] Furthermore, the pulse driving circuit includes a TTL trigger signal generation circuit, a narrow pulse generation circuit, a MOSFET driving circuit, an LD driving circuit, and a matching circuit. The collimated emission optical system is optimized by ZEMAX software, and the divergence angle of the collimated beam in the meridional direction is 0.47 mrad, the divergence angle in the sagittal direction is 0.82 mrad, and the energy distribution of the laser spot at 30 m is uniform.

[0064] Furthermore, the data acquisition and processing module employs a longitudinal accumulation algorithm for area-array CCDs, a time integration method, a Savitzky-Golay convolution smoothing method, and a background subtraction algorithm. The background subtraction algorithm removes background noise by turning on the CMOS camera twice within one laser cycle to acquire laser-containing signals and pure background signals respectively and subtracting them.

[0065] Furthermore, it also includes a range-gated imaging system, which consists of a gating module, a delay module, and an MCP control module. By controlling the delay between the laser pulse and the gating pulse, it filters out medium scattering noise and background noise, thereby improving imaging quality and detection range.

[0066] Furthermore, it also includes a pollutant identification and quantitative analysis module. The quantitative analysis module uses the fluorescence-Raman intensity ratio method to invert the oil film thickness, and the identification module uses the PCANet-SVM model to achieve classification and identification of multiple pollutants.

[0067] In actual operation, when this device is used, the ground-based control computer 44 establishes a wireless communication link through a 2.4GHz bidirectional radio frequency communication architecture and connects with the space-based computer control and acquisition module 41 carried by the UAV to realize remote control command transmission and data interaction. The communication distance can reach 300m and can be extended to several kilometers through the tracking gimbal and directional antenna.

[0068] The space-based computer control and acquisition module 41 uses a software system developed with Python, OpenCV, and PyQT. After receiving ground-based control commands, it synchronously controls the working sequence of the laser emitting unit, the detection unit, and the data acquisition and processing module to ensure that all components operate in coordination.

[0069] The 405nm semiconductor laser in the emitting unit is driven by a narrow pulse and a high current under the control of the pulse driving circuit, which can achieve pulse width adjustment from 5ns to 1000ns; by incoherently combining the output beams of multiple semiconductor lasers, a high peak power laser output of about 4W is obtained.

[0070] The collimated emission optical system consists of two K9 glass cylindrical mirrors with mutually perpendicular axes. After optimization by ZEMAX software, the divergence angles of the laser beam in the x and y directions are compressed. After collimation, the divergence angle of the beam in the meridional direction is 0.47 mrad and the divergence angle in the sagittal direction is 0.82 mrad, ensuring uniform energy distribution of the laser spot at 30m and meeting the beam propagation requirements for long-distance remote sensing monitoring.

[0071] The receiving unit uses a Schmidt-Cassegrain telescope to efficiently converge the fluorescence signal reflected from the target and transmit it to the dispersion unit. The dispersion unit is a direct-view dispersion system based on two Amici prisms. The first and third prisms are made of K9 glass, and the second prism is made of ZF7 glass. The apex angles of the first prism are 66°, 55°, and 59°, and the apex angles of the second prism are 55°, 55°, and 70°. The system height is 14.3 mm. Based on the principles of geometric optics and the Rayleigh criterion, it achieves efficient dispersion and high-precision beam splitting of composite light, with excellent minimum wavelength resolution.

[0072] The detection unit consists of an ICCD detection system composed of a GF2800HS image intensifier and an MV-CS016-10UM CMOS camera. The image intensifier's spectral response covers the visible light to 950nm infrared band, and the CMOS camera has a frame rate of no less than 100Hz and a maximum of 249.1fps, enabling high-sensitivity acquisition of multi-band fluorescence signals.

[0073] An integrated range-gated imaging system filters out medium scattering noise and background noise by controlling the delay between the laser pulse and the gating pulse. Combined with a background subtraction algorithm, the CMOS camera is activated twice within one laser cycle to acquire laser-containing signals and pure background signals respectively and then subtract them. This effectively removes external light interference and camera thermal noise, improving imaging quality and detection range in complex environments.

[0074] The data acquisition and processing module integrates the longitudinal accumulation algorithm of the area array CCD, the time integration method, and the Savitzky-Golay convolution smoothing method to process the acquired spectral data in real time, extract high signal-to-noise ratio fluorescence signals, and achieve a maximum frame rate of 60fps for fluorescence data.

[0075] The pollutant identification and quantitative analysis module plays a core role: the quantitative analysis module uses the fluorescence-Raman intensity ratio method to invert oil film thickness, avoiding the influence of factors such as detection distance and instrument parameters, and providing data support for oil spill assessment; the identification module uses the PCANet-SVM model to extract and classify features from the fluorescence spectra of pollutants, and can quickly and accurately distinguish between various pollutants such as corn oil, crude oil, and diesel, with a maximum identification accuracy of 100%.

[0076] The space-based computer control acquisition module 41 transmits the processed spectral data, pollutant identification results, and quantitative analysis data to the ground-based control computer 44 in real time via the wireless transmission and reception module 43. The ground-based control computer 44 further processes and analyzes the received data, displays real-time spectral images, pollutant types and content information through the software interface, and stores relevant data to provide a basis for subsequent monitoring and analysis, thereby realizing comprehensive and high-precision remote sensing monitoring of the target area.

[0077] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A multispectral laser-fluorescent radar device based on a UAV, comprising a radar mechanism (4), characterized in that: The radar mechanism (4) is provided with a mounting plate (3) on the top, and the UAV body (2) is provided on the outside of the mounting plate (3). The UAV body (2) is fixedly connected to the bottom of the UAV body (2). The radar mechanism (4) includes a transmitter and receiver module body (42), a space-based computer control and acquisition module (41), a wireless transmitter and receiver module (43), and a ground-based control computer (44).

2. The multispectral lidar-fluorescent radar device based on an unmanned aerial vehicle (UAV) according to claim 1, characterized in that: The main body (42) of the transmitting and receiving module includes a transmitting unit, a receiving unit, a dispersion unit and a detection unit; the transmitting unit includes a 405nm semiconductor laser, a pulse driving circuit and a collimated emission optical system; the receiving unit adopts a Schmidt-Cassegrain telescope; the dispersion unit is a direct-view dispersion system based on dual Amici prisms; the first and third prisms are made of K9 glass and the second prism is made of ZF7 glass; the detection unit consists of an image intensifier and a CMOS camera coupled to form an ICCD detection system; the space-based computer control and acquisition module (41) adopts a software system developed using Python+OpenCV+PyQT, integrating a control module, a data acquisition and processing module, a display module and a storage module; the wireless transmitting and receiving module (43) adopts a 2.4GHz bidirectional radio frequency communication architecture, including a router, a radio frequency amplifier and an omnidirectional antenna; the ground-based control computer (44) communicates with the space-based computer through a wireless module.

3. The multispectral lidar-fluorescent radar device based on an unmanned aerial vehicle (UAV) according to claim 1, characterized in that: The designed system has three apex angles of 66°, 55°, and 59° for the first prism and 55°, 55°, and 70° for the second prism. The height d of the prism system is 14.3 mm. According to the principles of geometric optics, the expression for the angle between the incident ray and the outgoing ray can be obtained. In the formula , —The refractive indices of K9 and ZF7 glass materials, respectively; , —These are the two apex corners of the first prism. According to Rayleigh's criterion, the smallest wavelength difference that a double Amici prism can resolve is... . In the formula, a represents the width of the emitted beam. The minimum wavelength difference Dl resolved by the dual Amici prisms. According to Schott's formula, the refractive index n(l) of K9 glass and ZF7 glass are related to the wavelength by the following condition: K9 glass and ZF7 glass , , , , , It can be retrieved from the ZEMAX software glass library.

4. The multispectral lidar-fluorescent radar device based on an unmanned aerial vehicle (UAV) according to claim 1, characterized in that: The pulse driving circuit includes a TTL trigger signal generation circuit, a narrow pulse generation circuit, a MOSFET driving circuit, an LD driving circuit, and a matching circuit. The collimated emission optical system is optimized by ZEMAX software, and the divergence angle of the collimated beam in the meridional direction is 0.47 mrad, and the divergence angle in the sagittal direction is 0.82 mrad.

5. The multispectral lidar-fluorescent radar device based on an unmanned aerial vehicle (UAV) according to claim 1, characterized in that: The data acquisition and processing module employs a longitudinal accumulation algorithm for area CCDs, a time integration method, a Savitzky-Golay convolution smoothing method, and a background subtraction algorithm.

6. The multispectral lidar-fluorescent radar device based on an unmanned aerial vehicle (UAV) according to claim 1, characterized in that: It also includes a range-gated imaging system, which consists of a gating module, a delay module, and an MCP control module.

7. A multispectral lidar-fluorescent radar device based on an unmanned aerial vehicle (UAV) according to claim 1, characterized in that: It also includes a pollutant identification and quantitative analysis module. The quantitative analysis module uses the fluorescence-Raman intensity ratio method to invert the oil film thickness, and the identification module uses the PCANet-SVM model.

Images