Sea wave signal simulation method suitable for spaceborne photon counting laser radar

Abstract

The invention discloses a sea wave signal simulation method suitable for a satellite-borne photon counting laser radar. The sea wave signal simulation method comprises the following steps: (1) superposing wind waves generated by fast Fourier transform and surges simulated by a narrow-band Gaussian distribution model to realize sea wave modeling; (2) constructing space-time distribution of the number of photons returned by the laser emission time unit at the sea surface element; (3) time distribution of expected receiving photons is constructed in a point mode, and the number of expected noise photons is superposed; (4) calculating the number of photons reflected by the sea surface and returned by back scattering of the water body, and superposing the number of the photons to a corresponding receiving time element; (5) converting expected receiving photon distribution into detection possibility distribution, and simulating a receiving process by using a Monte Carlo method; and (6) changing the sea surface distribution along the trajectory, and repeating the steps (2)-(5) for a plurality of times to obtain sea wave point cloud signals detected by the spaceborne photon counting laser radar. The method can provide theoretical guidance for satellite-borne photon counting laser radar sea wave detection.

Description

Technical Field

[0001] This invention belongs to the field of lidar technology, and in particular relates to a method for simulating ocean wave signals suitable for spaceborne photon counting lidar. Background Technology

[0002] Currently, traditional wave detection is mainly achieved through buoys. Buoys can accurately measure parameters such as effective height, wind speed, and wave spectrum, but they cannot achieve global detection. Satellite remote sensing technology is a feasible solution for large-scale, real-time global wave parameter inversion. Satellites currently used for wave detection include microwave radiometers, scatterometers, radar altimeters, and synthetic aperture radar. Microwave radiometers were early wave detection instruments, but their data are greatly affected by environmental conditions. Scatterometers can invert sea surface wind speed and direction, but their spatial resolution is relatively low. Radar altimeters can obtain wind speed and significant wave height, but because the inversion is based on signal slope and radar cross-section, they cannot provide detailed wave spectrum information. Synthetic aperture radar can invert wave spectrum and ocean parameters such as significant wave height, wind speed, and wind direction, but its wave information is not a direct measurement of sea surface elevation, and it cannot obtain high-frequency wave spectra due to nonlinear processes.

[0003] The ICESat-2 (Ice, Cloud and land Elevation Satellite-2) carries the ATLAS (Advanced Topographic Laser Altimeter System), currently the only on-orbit spaceborne photon-counting lidar. Although ocean exploration was not part of the satellite's initial mission, its excellent response to weak signals has led to its widespread application in the marine field. ICESat-2's 0.7m along-orbit resolution provides unprecedented detail on the sea surface, enabling higher-resolution wave parameter detection.

[0004] Chinese patent document CN118376999A discloses a wave wavelength extraction method based on ICESat-2, which extracts wave signals using median filtering. Chinese patent document CN120446905A discloses a point cloud filtering method for ICESat-2 sea surface, which extracts sea surface signals based on a density algorithm. However, these methods treat the sea surface detected by ICESat-2 as the actual sea surface, failing to consider the combined interference from hardware parameters such as the Gaussian distribution of the laser, the dead time of the receiver, and environmental parameters such as water scattering. This leads to certain deviations in the actually detected wave parameters. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for simulating ocean wave signals applicable to spaceborne photon-counting lidar, which can improve the detection accuracy of ocean wave parameters of spaceborne photon-counting lidar and is of great significance for global high-resolution ocean wave observation.

[0006] A method for simulating ocean wave signals applicable to spaceborne photon counting lidar includes: (1) The wave components are divided into wind waves and swells. The wind waves are generated by fast Fourier transform and the swells are simulated by narrowband Gaussian distribution model. The two are superimposed to realize the simulation modeling of the waves. (2) The emitted laser pulse is divided into one-dimensional emission time units, and the sea surface spot is divided into two-dimensional sea surface elements. The spatiotemporal distribution of the number of photons returned at each sea surface element in each emission time unit is constructed to simulate the influence of hardware parameters of the spaceborne photon counting lidar. (3) Set the receiving time interval, divide the receiving time into discrete receiving time elements, construct the time distribution of the photons to be received with the mean sea level as the time zero point, and convert the noise from frequency to the number of the desired noise photons and uniformly superimpose them in each receiving time element. (4) Calculate the number of photons reflected from the sea surface and backscattered from the water body and the corresponding time delay, and add the number of photons reflected from the sea surface and backscattered from the water body as the expected signal photon number to the receiving time element corresponding to its time delay; (5) The time distribution of the expected received photons is converted into the probability distribution of the detection. The Monte Carlo method is used to simulate the effect of dead time during the reception process of the photon counting detector to obtain the photon point cloud detected by a single pulse. (6) Change the sea surface distribution along the trajectory according to the simulation modeling results in step (1), and repeat steps (2)-(5) several times to obtain the wave point cloud signal detected by the spaceborne photon counting lidar.

[0007] In step (1), for the wind and waves part, the wind and waves spectrum (Elfouhaily spectrum) is generated by inputting the wind speed of 10m on the sea surface, and the wind and waves are generated by performing Fourier transform on the wind and waves spectrum; for the swell part, the wavelength, pulse width and effective height are input to simulate the narrow band Gaussian distribution to realize the simulation; the wind and waves and the swell are superimposed to realize the three-dimensional ocean wave modeling.

[0008] The specific process of step (2) is as follows: The energy of the emitted laser pulse follows a Gaussian distribution in the time domain, which can be expressed as: ; in, The full width at half maximum (FWHM) of the laser pulse is... The range includes the entire energy of the laser pulse; with intervals Divide this range into Then the th different time interval, The normalized energy within each emission time unit is expressed as: ; in, ; It is the initial launch time element; With intervals Dividing the light spot on the sea surface into M×M discrete surface elements, the energy received from the surface element (X,Y) without considering sea surface undulations and reflections is then... Represented as: ; in, ; The energy of the emitted pulse, The satellite's orbital altitude, It is the lowest point angle of the laser's optical axis. Transmittance of a single layer of atmosphere The quantum efficiency of the detector. For the optical efficiency of the receiver, Let the radius be the surface element of the sea. The distance from the center of the surface element to the sub-star point; The area of ​​the receiving telescope; Then the first Spatiotemporal distribution of energy returned by each emission time unit at the sea surface element (X, Y) Represented as ; Energy through Converted into photon count ,in, and These are Planck's constant and the laser frequency, respectively.

[0009] In step (3), the noise is converted from frequency to the desired noise photon number and uniformly superimposed within each receiving time cell. The specific process is as follows: The noise signal of a spaceborne photon counting lidar is uniformly distributed and can be categorized into dark noise. and solar noise Determine the simulated noise frequency ; Simulated noise frequency pass This is converted into the desired noise photon number and uniformly superimposed over each receiving time cell. This is the reception time interval.

[0010] In step (4), the sea surface reflection signal comes from specular reflection and white cap reflection; In spacetime unit The number of photons produced by the reflection of the white cap at a given location is expressed as: ; in, It is the effective reflectivity of the white cap; It is the laser incident angle; The proportion of white hats; In spacetime unit The number of photons generated by specular reflection at a given location is expressed as: ; in, The reflectivity of the sea surface, This represents the rate of change of the slope of the surface element; In spacetime unit The time delay caused by sea surface fluctuations and transmitter pulse width is expressed as: ; in, At the speed of light, It is the elevation of the sea surface element (X, Y) relative to the sea surface. It is the initial launch time unit.

[0011] In step (4), when calculating the number of photons returned by the backscattered signal from the water body, the photons are spaced at vertical distances. If the water body under the surface element is divided into several segments, then the number of photons backscattered and returned by a certain segment of water body is expressed as: ; in, For water depth, It is a given vertical interval. It is the angle of incidence when entering the water. It is the water surface transmittance. Let be the volume scattering coefficient of water. The attenuation coefficient is taken into account; the refractive index of water is considered. The time delay of the backscattered signal from the water body is expressed as: .

[0012] The specific process of step (5) is as follows: The probability P of the photons detected in each receiving time element is approximated as a Poisson distribution: ; in, This represents the number of photons contained in the received time cell. The time distribution of the desired received photons is transformed into a detection probability distribution using the above formula for the Poisson distribution; Subsequently, based on the Monte Carlo simulation method, a uniformly distributed random number is generated in the range of 0 to 1. If the number is less than P, it is considered that a photon event has occurred, and a dead time reception time element is skipped. Otherwise, it is considered that no photon event has occurred, and the next reception time element is entered. The above process is repeated until the detection process ends. The reception time of the photon event is converted into the photon elevation relative to the sea surface, thus obtaining the single-pulse photon point cloud signal.

[0013] The specific process of step (6) is as follows: Determine the spacing of the light spots between orbits based on the satellite's orbital altitude and speed. In the wave simulation model generated in step (1), the interval is moved in the direction of satellite travel. And accordingly change the detected sea surface, and then repeat steps (2) to (5) several times to obtain the entire wave point cloud signal.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention realizes the simulation of sea surface point cloud of spaceborne photon counting lidar with multi-parameter coupling of hardware and environment, accurately simulates the complex influence mechanism of the actual detection process, and can simulate the wave detection signal of spaceborne lidar under different sea conditions, noise and water environment.

[0015] 2. By changing parameters, this invention can study the complex correlation effects between laser Gaussian distribution, sea surface roughness, detector dead time and solar background noise, providing a theoretical basis for promoting sea wave detection by spaceborne lidar. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the 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.

[0017] Figure 1 This is a flowchart illustrating a method for simulating ocean wave signals applicable to spaceborne photon counting lidar, as described in an embodiment of the present invention.

[0018] Figure 2 These are simulated ocean wave signals under different wind speeds and noise levels in this embodiment of the invention. Detailed Implementation

[0019] 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.

[0020] It should be noted that, unless otherwise specified, the features in the following embodiments and implementation methods can be combined with each other.

[0021] This invention uses ICESat-2 parameters as an example to simulate sea surface point clouds under wind speeds in daytime and nighttime environments.

[0022] like Figure 1 As shown, a method for simulating ocean wave signals suitable for spaceborne photon counting lidar includes the following steps: Step S1: Ocean waves are composed of superimposed waves of different wavelengths, frequencies, and directions, and can be divided into wind waves and swells. For the wind wave component, a 10 m wind speed at the sea surface is input to generate an Elfouhaily spectrum. This spectrum includes contributions from low- to high-frequency wind and waves, and is applicable to various states from young sea surfaces to fully developed sea surfaces. A Fourier transform is performed on the wind wave spectrum to generate the wind waves. Swells can be considered to have a narrow-band Gaussian distribution, with an input wavelength of 500 m and a bandwidth set to 0.005 m. -1 The effective height was set to 0.1 m. Wind waves and swells were superimposed to achieve a three-dimensional ocean wave simulation.

[0023] Step S2: Since the laser pulse has a certain pulse width, the laser energy follows a Gaussian distribution in the time domain, which can be expressed as: ; in, The full width at half maximum (FWHM) of the laser pulse is... The range contains photons of almost all energy, spaced apart. If we divide this range into N distinct time intervals, then the first interval is 0.1 ns. The normalized energy of each emission time unit is expressed as: ; in, ; It is the initial launch time unit.

[0024] The divergent properties of lasers cause their energy to follow a Gaussian distribution in space, resulting in a spot size ranging from tens to hundreds of meters in diameter upon reaching the sea surface, depending on the orbital altitude and emission angle. For ease of simulation, intervals are used... Dividing the light spot on the sea surface into M×M discrete surface elements, the energy received from a certain surface element (X,Y) without considering sea surface undulations and reflections can be expressed as: ; in, ; The energy of the ICESat-2 single pulse is 120uJ; The orbital altitude of ICESat-2 is approximately 500 km; It is the lowest point angle of the laser's optical axis, taken as 0.38°; The transmittance of a single layer of atmosphere is taken as 0.9; The quantum efficiency of the ICESat-2 detector is 0.15. The optical efficiency of the ICESat-2 receiver is 0.4. The radius of the sea surface element is 13m; The distance from the center of the surface element to the sub-star point; The area of ​​the receiving telescope is taken as 0.41m. 2 .

[0025] Then the first The spatiotemporal distribution of the energy returned by each discrete emission time unit at the sea surface element (X, Y) is represented as follows: ; Since photon-counting lidar can respond to signals at the single-photon energy level, for ease of subsequent simulation, the energy is transmitted through... Converted into photon count ,in and These are Planck's constant and the laser frequency, respectively.

[0026] Step S3: Due to the influence of dead time, there is a non-linearity between the expected number of photons and the actual number of photons in a photon-counting lidar. Simultaneously, the energy received by the photon-counting lidar in very short time intervals is very small, far less than one photon; therefore, the actual photon reception time has a certain degree of randomness. The receiving time interval is determined with the mean sea level as the zero point. =0.1ns and the time range of sea surface photon signals ( Construct the reception time distribution of the desired number of photons. The receiving time is divided into discrete time elements, and the time corresponding to each time element is the deviation relative to the mean sea level.

[0027] The noise of a spaceborne photon counting lidar is uniformly distributed and can be divided into dark noise and solar noise. Dark noise originates from the instrument itself and is 400Hz. Solar noise is related to the solar zenith angle and only occurs during the day. Taking a typical daytime noise frequency of 1MHz, the simulated noise frequency is determined, and the noise is then processed through... It is uniformly superimposed on each spatiotemporal distribution.

[0028] Step S4: The sea surface reflection signal comes from two parts: specular reflection and white cap reflection. The white cap ratio is related to the wind speed at 10m above the sea surface, and this ratio is expressed as: ; In spacetime unit The number of photons produced by the reflection from the white cap portion is expressed as: ; in, It is the effective reflectivity of the white cap; It is the laser incident angle.

[0029] In spacetime unit The number of photons generated by specular reflection at a given location is expressed as: ; in, The reflectivity of the sea surface, This represents the rate of change of the slope of the surface element; In a specific spatiotemporal unit The time delay caused by sea surface fluctuations and transmitter pulse width is expressed as: ; The first term is the time delay caused by the divergence of the laser footprint, the second term is the time delay caused by the height of the sea surface element, and the third term is the time delay caused by the time-domain Gaussian distribution of the transmitter laser pulse. At the speed of light, It is the elevation of the sea surface element (X, Y) relative to the sea surface. It is the initial launch time unit.

[0030] To simulate the backscattered signal of water, at vertical distance intervals Dividing the water body under the surface element into several segments, the expected number of photons backscattered from a certain segment is expressed as: ; in, This refers to the distance from the water body interval to the water surface (i.e., the water depth). It is a given vertical interval. It is the angle of incidence when entering the water. It is the water surface transmittance. Let be the volume scattering coefficient of water. The attenuation coefficient is taken into account, considering the refractive index of water. The corresponding time delay can then be expressed as: ; Then, the expected number of photons returned from the sea surface and water body of each surface element is superimposed on the receiving time element according to its corresponding time delay.

[0031] Step S5: Since the number of photons that can be received in each receiving time cell is very small, the probability of detecting a photon in each receiving time cell can be approximated by a Poisson distribution: ; in, To determine the number of photons contained in a given receiving time cell, the desired photon distribution is transformed into a detection probability distribution using the aforementioned formula. Then, based on Monte Carlo simulation, a uniformly distributed random number is generated within the range of 0 to 1. If the number is less than P, a photon event is considered to have occurred, and a dead-time receiving time cell is skipped. Conversely, if the number is greater than P, no photon event is considered to have occurred, and the process proceeds to the next receiving time cell. This process is repeated until the detection process ends. The receiving time at which a photon event occurs is converted into photon elevation relative to the sea surface, thus obtaining the single-pulse point cloud signal.

[0032] Step S6: Determine the spacing of the light spots between orbits based on the satellite's orbital altitude and speed. In the simulated wave model generated in (1), move the interval in the direction of the satellite's travel and change the detected sea surface accordingly. Then repeat steps (2) to (5) several times to obtain the entire wave point cloud signal.

[0033] like Figure 2 The figure shows the simulated point clouds along the wave track of a spaceborne photon counting lidar under wind speeds of 5 m / s and 10 m / s at night and during the day. In the figure, (a) is the point cloud at night with a wind speed of 5 m / s; (b) is the point cloud at night with a wind speed of 10 m / s; (c) is the point cloud at daytime with a wind speed of 5 m / s; and (d) is the point cloud at daytime with a wind speed of 10 m / s.

[0034] The embodiments described above provide a detailed explanation of the technical solutions and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, additions, and equivalent substitutions made within the scope of the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for simulating ocean wave signals suitable for spaceborne photon counting lidar, characterized in that, include: (1) The wave components are divided into wind waves and swells. The wind waves are generated by fast Fourier transform and the swells are simulated by narrowband Gaussian distribution model. The two are superimposed to realize the simulation modeling of the waves. (2) Divide the emitted laser pulse into one-dimensional emission time units, divide the sea surface spot into two-dimensional sea surface elements, and construct the spatiotemporal distribution of the number of photons returned by each emission time unit at each sea surface element; (3) Set the receiving time interval, divide the receiving time into discrete receiving time elements, construct the time distribution of the photons to be received with the mean sea level as the time zero point, and convert the noise from frequency to the number of the desired noise photons and uniformly superimpose them in each receiving time element. (4) Calculate the number of photons reflected from the sea surface and backscattered from the water body and the corresponding time delay, and add the number of photons reflected from the sea surface and backscattered from the water body as the expected signal photon number to the receiving time element corresponding to its time delay; (5) The time distribution of the expected received photons is converted into the probability distribution of the detection. The Monte Carlo method is used to simulate the effect of dead time during the reception process of the photon counting detector to obtain the photon point cloud detected by a single pulse. (6) Change the sea surface distribution along the trajectory according to the simulation modeling results in step (1), and repeat steps (2)-(5) several times to obtain the wave point cloud signal detected by the spaceborne photon counting lidar.

2. The method for simulating ocean wave signals for spaceborne photon counting lidar according to claim 1, characterized in that, In step (1), for the wind and wave part, the wind and wave spectrum is generated by inputting the wind speed of 10m on the sea surface, and the wind and wave spectrum is transformed by Fourier transform to generate wind and waves; for the swell part, the wavelength, pulse width and effective height are input to simulate the narrow band Gaussian distribution to realize the simulation; the wind and waves and the swell are superimposed to realize the three-dimensional ocean wave modeling.

3. The method for simulating ocean wave signals for spaceborne photon counting lidar according to claim 1, characterized in that, The specific process of step (2) is as follows: The energy of the emitted laser pulse follows a Gaussian distribution in the time domain, which can be expressed as: ； in, The full width at half maximum (FWHM) of the laser pulse is... The range includes the entire energy of the laser pulse; with intervals Divide this range into Then the th different time interval, Normalized energy within each launch time unit Represented as: ； in, ; It is the initial launch time element; With intervals Dividing the light spot on the sea surface into M×M discrete surface elements, the energy received from the surface element (X,Y) without considering sea surface undulations and reflections is then... Represented as: ； in, ; The energy of the emitted pulse, The satellite's orbital altitude, It is the lowest point angle of the laser's optical axis. Transmittance of a single layer of atmosphere The quantum efficiency of the detector. For the optical efficiency of the receiver, Let the radius be the surface element of the sea. The distance from the center of the surface element to the sub-star point; The area of ​​the receiving telescope; Then the first Spatiotemporal distribution of energy returned by each emission time unit at the sea surface element (X, Y) Represented as: ； Energy through Converted into photon count ,in, and These are Planck's constant and the laser frequency, respectively.

4. The method for simulating ocean wave signals for spaceborne photon counting lidar according to claim 1, characterized in that, In step (3), the noise is converted from frequency to the desired noise photon number and uniformly superimposed within each receiving time cell. The specific process is as follows: The noise signal of a spaceborne photon counting lidar is uniformly distributed and can be categorized into dark noise. and solar noise Determine the simulated noise frequency ; Simulated noise frequency pass This is converted into the desired noise photon number and uniformly superimposed over each receiving time cell. This is the reception time interval.

5. The method for simulating ocean wave signals for spaceborne photon counting lidar according to claim 3, characterized in that, In step (4), the sea surface reflection signal comes from specular reflection and white cap reflection; In spacetime unit The number of photons produced by the reflection of the white cap at a given location is expressed as: ； in, It is the effective reflectivity of the white cap; It is the laser incident angle; The proportion of white hats; In spacetime unit The number of photons generated by specular reflection at a given location is expressed as: ； in, The reflectivity of the sea surface, This represents the rate of change of the slope of the surface element; In spacetime unit The time delay caused by sea surface fluctuations and transmitter pulse width is expressed as: ； in, At the speed of light, It is the elevation of the sea surface element (X, Y) relative to the sea surface. It is the initial launch time unit.

6. The method for simulating ocean wave signals for spaceborne photon counting lidar according to claim 5, characterized in that, In step (4), when calculating the number of photons returned by the backscattered signal from the water body, the photons are spaced at vertical distances. If the water body under the surface element is divided into several segments, then the number of photons backscattered and returned by a certain segment of water body is expressed as: ； in, For water depth, It is a given vertical interval. It is the angle of incidence when entering the water. It is the water surface transmittance. Let be the volume scattering coefficient of water. The attenuation coefficient is taken into account; the refractive index of water is considered. The time delay of the backscattered signal from the water body is expressed as: 。 7. The method for simulating ocean wave signals for spaceborne photon counting lidar according to claim 1, characterized in that, The specific process of step (5) is as follows: The probability P of the photons detected in each receiving time element is approximated as a Poisson distribution: ； in, This represents the number of photons contained in the received time cell. The time distribution of the desired received photons is transformed into a detection probability distribution using the above formula for the Poisson distribution; Subsequently, based on the Monte Carlo simulation method, a uniformly distributed random number is generated in the range of 0 to 1. If the number is less than P, it is considered that a photon event has occurred, and a dead time reception time element is skipped. Otherwise, it is considered that no photon event has occurred, and the next reception time element is entered. The above process is repeated until the detection process ends. The reception time of the photon event is converted into the photon elevation relative to the sea surface, thus obtaining the single-pulse photon point cloud signal.

8. The method for simulating ocean wave signals for spaceborne photon counting lidar according to claim 1, characterized in that, The specific process of step (6) is as follows: Determine the spacing of the light spots between orbits based on the satellite's orbital altitude and speed. In the wave simulation model generated in step (1), the interval is moved in the direction of satellite travel. And accordingly change the detected sea surface, and then repeat steps (2) to (5) several times to obtain the entire wave point cloud signal.

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