Model generation method and device, significant wave height inversion method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a model generation method and device, a significant wave height inversion method and device, equipment and a storage medium. The model generation method comprises the following steps: acquiring a first actual measurement GNSS-R normalized one-dimensional time delay waveform, and acquiring a first theoretical GNSS-R normalized one-dimensional time delay waveform; obtaining a first time delay range difference corresponding to the first actual measurement GNSS-R normalized one-dimensional time delay waveform and the first theoretical GNSS-R normalized one-dimensional time delay waveform in the same amplitude range; performing incident angle correction on the first time delay range difference to obtain a first time delay difference observed quantity; acquiring a first effective wave height matched with the first time delay inequality observed quantity; and training by using the first time delay inequality observed quantity and the first significant wave height to obtain a significant wave height inversion model. According to the embodiment of the invention, the accuracy of the significant wave height inversion model is improved, so that the accuracy of the significant wave height obtained through the inversion of the significant wave height inversion model can be improved.

Description

Technical Field

[0001] The present application relates to the field of reflection remote sensing technology, and in particular to a model generation, effective wave height inversion method, device, equipment and storage medium. Background Art

[0002] Significant wave height is an important wave parameter that represents the statistical value of the actual wave height. It is defined as the average value of the first 1 / 3 of the wave heights after arranging the wave heights in order of size. It is of great significance for marine disaster warning and emergency management.

[0003] At present, the remote sensing means for quantitatively measuring effective wave height include radar altimeter, wave spectrometer and SAR (Synthetic Aperture Radar). However, there are few remote sensing observation data of effective wave height at present, mainly because radar altimeter and wave spectrometer can only observe the subsatellite point, the observation is only in strip form, and there is a lack of wide swath measurement means, while SAR has high power consumption, cannot observe continuously, and has a narrow swath, resulting in low accuracy of effective wave height. Summary of the invention

[0004] In view of the above problems, the embodiments of the present application propose a model generation, effective wave height inversion method, device, equipment and storage medium to improve the accuracy of the effective wave height.

[0005] According to one aspect of an embodiment of the present application, a method for generating a significant wave height inversion model is provided, the method comprising:

[0006] Obtaining a first measured GNSS-R normalized one-dimensional time delay waveform, and obtaining a first theoretical GNSS-R normalized one-dimensional time delay waveform;

[0007] Obtaining a first delay range difference corresponding to the same amplitude range between the first measured GNSS-R normalized one-dimensional delay waveform and the first theoretical GNSS-R normalized one-dimensional delay waveform;

[0008] Performing incident angle correction on the first time delay range difference to obtain a first time delay difference observation amount;

[0009] Acquire a first effective wave height matching the first time delay difference observation;

[0010] The effective wave height inversion model is trained using the first time delay difference observation and the first effective wave height.

[0011] Optionally, obtaining a first measured GNSS-R normalized one-dimensional time delay waveform includes: obtaining a first measured DDM waveform; denoising the first measured DDM waveform to obtain a first target measured DDM waveform; extracting a value corresponding to a Doppler frequency of 0 in the first target measured DDM waveform as a first target value, dividing the first target value by a peak value in the first target value, and obtaining the first measured GNSS-R normalized one-dimensional time delay waveform.

[0012] Optionally, the denoising process of the first measured DDM waveform to obtain a first target measured DDM waveform includes: calculating a first average value of numerical values ​​corresponding to delays that are less than or equal to a preset delay threshold in the first measured DDM waveform, and using the first average value as the noise floor of the first measured DDM waveform; and subtracting the noise floor of the first measured DDM waveform from the first measured DDM waveform to obtain the first target measured DDM waveform.

[0013] Optionally, obtaining a first theoretical GNSS-R normalized one-dimensional time delay waveform includes: obtaining a first theoretical DDM waveform; denoising the first theoretical DDM waveform to obtain a first target theoretical DDM waveform; extracting a value corresponding to a Doppler frequency of 0 in the first target theoretical DDM waveform as a second target value, dividing the second target value by a peak value in the second target value to obtain the first theoretical GNSS-R normalized one-dimensional time delay waveform.

[0014] Optionally, the denoising process of the first theoretical DDM waveform to obtain a first target theoretical DDM waveform includes: calculating a second average value of numerical values ​​corresponding to delays that are less than or equal to a preset delay threshold in the first theoretical DDM waveform, and using the second average value as the noise floor of the first theoretical DDM waveform; and subtracting the noise floor of the first theoretical DDM waveform from the first theoretical DDM waveform to obtain the first target theoretical DDM waveform.

[0015] Optionally, the method of obtaining the first delay range difference corresponding to the first measured GNSS-R normalized one-dimensional delay waveform and the first theoretical GNSS-R normalized one-dimensional delay waveform in the same amplitude range includes: obtaining the first theoretical mirror reflection point of the first theoretical GNSS-R normalized one-dimensional delay waveform, and obtaining the first amplitude range corresponding to the first delay range centered on the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform; obtaining the first measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform, and obtaining the second delay range centered on the first measured mirror reflection point corresponding to the first measured GNSS-R normalized one-dimensional delay waveform under the first amplitude range; calculating the difference between the second delay range and the first delay range to obtain the first delay range difference.

[0016] Optionally, the obtaining of the first amplitude range corresponding to the first delay range centered on the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform includes: performing linear fitting on the waveform of the first delay range centered on the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform to obtain a first theoretical fitting waveform; and obtaining the amplitude range corresponding to the first delay range in the first theoretical fitting waveform as the first amplitude range.

[0017] Optionally, the obtaining of the first measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform includes:

[0018] Select the preset delay offsets one by one;

[0019] The following cost function is calculated according to each of the delay offsets:

[0020]

[0021] Wherein, J(k) represents the cost function, represents the time delay τ in the first measured GNSS-R normalized one-dimensional time delay waveform i+k The corresponding normalized value is represents the time delay τ in the first theoretical GNSS-R normalized one-dimensional time delay waveform i The corresponding normalized value, k represents the delay offset, N 1 The subscript indicating the lower limit of the delay in the third delay range, N 2 A subscript representing the upper limit of the delay of the third delay range;

[0022] The target delay offset corresponding to the minimum of the cost function is selected, and the delay corresponding to the first theoretical mirror reflection point offset by the target delay offset is used as the measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform.

[0023] Optionally, obtaining the second delay range centered on the first measured mirror reflection point corresponding to the first measured GNSS-R normalized one-dimensional delay waveform under the first amplitude range includes: performing linear fitting on the waveform of the first delay range centered on the first measured mirror reflection point in the first measured GNSS-R normalized one-dimensional delay waveform to obtain a first measured fitting waveform; calculating the delay range corresponding to the first amplitude range in the first measured fitting waveform as the second delay range.

[0024] Optionally, performing incident angle correction on the first time delay range difference to obtain a first time delay difference observation value includes: dividing the first time delay range difference by twice the cosine value of the first incident angle, and determining a ratio obtained as the first time delay difference observation value.

[0025] Optionally, obtaining the first effective wave height that matches the first time delay difference observation includes: matching the first time delay difference observation with the effective wave height measured by the buoy according to a set matching rule to obtain the first effective wave height that matches the first time delay difference observation; the matching rule includes: the spatial distance between the mirror reflection point position corresponding to the GNSS-R measurement and the buoy position corresponding to the buoy measurement is less than a preset distance, and the time interval between the observation time corresponding to the GNSS-R measurement and the observation time corresponding to the buoy measurement is less than a preset duration.

[0026] Optionally, the using the first time delay difference observation and the first significant wave height to train an effective wave height inversion model includes:

[0027] The first time delay difference observation and the first significant wave height are used to perform linear fitting training to obtain the following significant wave height inversion model:

[0028] H s =aΔh+b

[0029] Among them, H S represents the effective wave height, Δh represents the delay difference observation, a represents the first coefficient, and b represents the second coefficient.

[0030] According to another aspect of an embodiment of the present application, a method for inverting effective wave height is provided, the method comprising:

[0031] Acquire a second measured GNSS-R normalized one-dimensional time delay waveform, and acquire a second theoretical GNSS-R normalized one-dimensional time delay waveform;

[0032] Obtaining a second delay range difference corresponding to the same amplitude range between the second measured GNSS-R normalized one-dimensional delay waveform and the second theoretical GNSS-R normalized one-dimensional delay waveform;

[0033] Performing incident angle correction on the second time delay range difference to obtain a second time delay difference observation amount;

[0034] The effective wave height corresponding to the second time delay difference observation is calculated using a pre-trained effective wave height inversion model; the effective wave height inversion model is obtained by the effective wave height inversion model generation method as described in any of the above items.

[0035] According to another aspect of an embodiment of the present application, a significant wave height inversion model generation device is provided, the device comprising:

[0036] A first acquisition module, used to acquire a first measured GNSS-R normalized one-dimensional time delay waveform and a first theoretical GNSS-R normalized one-dimensional time delay waveform;

[0037] A second acquisition module is used to obtain a first delay range difference between the first measured GNSS-R normalized one-dimensional delay waveform and the first theoretical GNSS-R normalized one-dimensional delay waveform in the same amplitude range;

[0038] A first correction module, configured to perform incident angle correction on the first time delay range difference to obtain a first time delay difference observation amount;

[0039] A matching module, used for acquiring a first effective wave height matching the first time delay difference observation value;

[0040] A training module is used to train an effective wave height inversion model using the first time delay difference observation and the first effective wave height.

[0041] Optionally, the first acquisition module includes: a first waveform acquisition submodule, used to acquire a first measured DDM waveform; a first denoising submodule, used to denoise the first measured DDM waveform to obtain a first target measured DDM waveform; a first normalization submodule, used to extract the value corresponding to the Doppler frequency of 0 in the first target measured DDM waveform as the first target value, and divide the first target value by the peak value in the first target value to obtain the first measured GNSS-R normalized one-dimensional time delay waveform.

[0042] Optionally, the first denoising submodule is specifically used to calculate a first average value of the numerical value corresponding to the delay that is less than or equal to a preset delay threshold in the first measured DDM waveform, and use the first average value as the noise floor of the first measured DDM waveform; subtract the noise floor of the first measured DDM waveform from the first measured DDM waveform to obtain the first target measured DDM waveform.

[0043] Optionally, the first acquisition module includes: a second waveform acquisition submodule, used to acquire a first theoretical DDM waveform; a second denoising submodule, used to denoise the first theoretical DDM waveform to obtain a first target theoretical DDM waveform; a second normalization submodule, used to extract the value corresponding to the Doppler frequency of 0 in the first target theoretical DDM waveform as the second target value, and divide the second target value by the peak value in the second target value to obtain the first theoretical GNSS-R normalized one-dimensional time delay waveform.

[0044] Optionally, the second denoising submodule is specifically used to calculate a second average value of the numerical value corresponding to the delay that is less than or equal to a preset delay threshold in the first theoretical DDM waveform, and use the second average value as the noise floor of the first theoretical DDM waveform; subtract the noise floor of the first theoretical DDM waveform from the first theoretical DDM waveform to obtain the first target theoretical DDM waveform.

[0045] Optionally, the second acquisition module includes: a first range acquisition submodule, used to acquire the first theoretical mirror reflection point of the first theoretical GNSS-R normalized one-dimensional delay waveform, and acquire the first amplitude range corresponding to the first delay range centered on the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform; a second range acquisition submodule, used to acquire the first measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform, and acquire the second delay range centered on the first measured mirror reflection point corresponding to the first measured GNSS-R normalized one-dimensional delay waveform under the first amplitude range; and a calculation submodule, used to calculate the difference between the second delay range and the first delay range to obtain the first delay range difference.

[0046] Optionally, the first range acquisition submodule includes: a first fitting unit, used to perform linear fitting on the waveform of the first delay range centered on the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform to obtain a first theoretical fitting waveform; and obtain the amplitude range corresponding to the first delay range in the first theoretical fitting waveform as the first amplitude range.

[0047] Optionally, the second range acquisition submodule includes a reflection point acquisition unit, and the reflection point acquisition unit is used to:

[0048] Select the preset delay offsets one by one;

[0049] The following cost function is calculated according to each of the delay offsets:

[0050]

[0051] Wherein, J(k) represents the cost function, represents the time delay τ in the first measured GNSS-R normalized one-dimensional time delay waveform i+k The corresponding normalized value is represents the time delay τ in the first theoretical GNSS-R normalized one-dimensional time delay waveform i The corresponding normalized value, k represents the delay offset, N 1 The subscript indicating the lower limit of the delay in the third delay range, N 2 A subscript representing the upper limit of the delay of the third delay range;

[0052] The target delay offset corresponding to the minimum of the cost function is selected, and the delay corresponding to the first theoretical mirror reflection point offset by the target delay offset is used as the measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform.

[0053] Optionally, the first range acquisition submodule includes: a second fitting unit, used to perform linear fitting on the waveform of the first delay range centered on the first measured mirror reflection point in the first measured GNSS-R normalized one-dimensional delay waveform to obtain a first measured fitting waveform; and calculate the delay range corresponding to the first amplitude range in the first measured fitting waveform as the second delay range.

[0054] Optionally, the first correction module is specifically used to determine a ratio obtained by dividing the first time delay range difference by twice the cosine value of the first incident angle as the first time delay difference observation value.

[0055] Optionally, the matching module is specifically used to match the first time delay difference observation with the effective wave height measured by the buoy according to a set matching rule to obtain a first effective wave height that matches the first time delay difference observation; the matching rule includes: the spatial distance between the mirror reflection point position corresponding to the GNSS-R measurement and the buoy position corresponding to the buoy measurement is less than a preset distance, and the time interval between the observation time corresponding to the GNSS-R measurement and the observation time corresponding to the buoy measurement is less than a preset duration.

[0056] Optionally, the training module is specifically used to perform linear fitting training using the first time delay difference observation and the first effective wave height to obtain the following effective wave height inversion model:

[0057] H s =aΔh+b

[0058] Among them, H S represents the effective wave height, Δh represents the delay difference observation, a represents the first coefficient, and b represents the second coefficient.

[0059] According to another aspect of an embodiment of the present application, there is provided an effective wave height inversion device, the device comprising:

[0060] A third acquisition module is used to acquire a second measured GNSS-R normalized one-dimensional time delay waveform and a second theoretical GNSS-R normalized one-dimensional time delay waveform;

[0061] A fourth acquisition module, used to obtain a second delay range difference corresponding to the same amplitude range between the second measured GNSS-R normalized one-dimensional delay waveform and the second theoretical GNSS-R normalized one-dimensional delay waveform;

[0062] A second correction module, configured to perform incident angle correction on the second time delay range difference to obtain a second time delay difference observation amount;

[0063] A calculation module is used to calculate the effective wave height corresponding to the second time delay difference observation using a pre-trained effective wave height inversion model; the effective wave height inversion model is obtained by the effective wave height inversion model generation method as described in any of the above items.

[0064] According to another aspect of an embodiment of the present application, an electronic device is provided, comprising a processor and a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium; when the computer program is executed by the processor, the processor executes the effective wave height inversion model generation method as described in any one of the above items, or executes the effective wave height inversion method as described in any one of the above items.

[0065] According to another aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the processor executes the effective wave height inversion model generation method as described in any of the above items, or executes the effective wave height inversion method as described in any of the above items.

[0066] In an embodiment of the present application, an effective wave height inversion based on GNSS-R (Global Navigation Satellite System Reflectometry) technology is proposed, the original waveform is normalized to obtain a GNSS-R normalized one-dimensional time delay waveform, and the delay information of the GNSS-R normalized one-dimensional time delay waveform is used for comparative analysis instead of the power amplitude information to obtain a first time delay difference observation, and then an effective wave height inversion model is trained based on the first time delay difference observation and the matching first effective wave height. Compared with the analysis using power amplitude information, the analysis using time delay information does not require calibration of the signal power, is more direct and has higher accuracy, and does not suffer from problems such as decreased sensitivity in high sea conditions and decreased accuracy when surges dominate. In addition, an incident angle correction is added when calculating the first time delay difference observation, which further improves the accuracy of the first time delay difference observation, thereby improving the accuracy of the effective wave height inversion model, and further improving the accuracy of the effective wave height obtained by inverting the effective wave height inversion model. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the technical solution of the embodiment of the present application, the drawings required for use in the description of the embodiment of the present application will be briefly introduced below. Obviously, the drawings described below are only some drawings of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0068] Figure 1 It is a schematic diagram of the principle of an altimeter and GNSS-R in an embodiment of the present application;

[0069] Figure 2 It is a flowchart of the steps of a method for generating an effective wave height inversion model according to an embodiment of the present application;

[0070] Figure 3 is a schematic diagram of a GNSS-R normalized one-dimensional delay waveform in an embodiment of the present application;

[0071] Figure 4 is a schematic diagram of a GNSS-R normalized one-dimensional delay waveform linear fitting in an embodiment of the present application;

[0072] Figure 5 is a schematic diagram of a fitting waveform of an embodiment of the present application;

[0073] Figure 6 is a schematic diagram of a change in propagation distance caused by a change in sea level height in an embodiment of the present application;

[0074] Figure 7 is a flowchart of the steps of an effective wave height inversion method according to an embodiment of the present application;

[0075] Figure 8 It is a structural block diagram of a significant wave height inversion model generating device according to an embodiment of the present application;

[0076] Fig. 9 It is a structural block diagram of an effective wave height inversion device according to an embodiment of the present application;

[0077] Fig.10 is a structural block diagram of an electronic device according to an embodiment of the present application;

[0078] Fig.11 It is a structural block diagram of a computer-readable storage medium in an embodiment of the present application. DETAILED DESCRIPTION

[0079] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0080] In the embodiments of the present application, in order to address the defects of measuring effective wave height using radar altimeters, wave spectrometers, and SAR methods, an effective wave height inversion based on GNSS-R is proposed.

[0081] GNSS-R is a relatively new remote sensing method. This technology uses the reflected signals of global navigation satellites (such as the Beidou system, GPS (Global Positioning System), Galileo, etc.) on the earth's surface to detect physical parameters on the earth's surface, such as sea surface wind speed, sea surface height, soil moisture, sea ice parameters, etc. Spaceborne GNSS-R uses low-orbit satellites to receive signals from more than 100 navigation satellites, and has the advantages of sufficient signal sources and global coverage. Since the navigation satellite transmits L-band signals, it has strong penetration and is not affected by clouds, rain and precipitation, and can provide all-day and all-weather observations. In addition, since GNSS-R uses navigation satellite signals as an opportunity signal, the payload does not need to actively transmit signals, and has the advantages of low power consumption, small size, and light weight. It is suitable for being carried by small satellites to form a network observation and provide global high-temporal and spatial resolution observation data.

[0082] Figure 1 FIG. 1 is a schematic diagram of the principle of an altimeter and GNSS-R according to an embodiment of the present application. Figure 1 As shown in the figure, compared with the altimeter, GNSS-R can use multiple mirror reflection points for observation at the same time, and then obtain observation data of multiple strips within a swath width of 1500km to 2500km.

[0083] Spaceborne GNSS-R is a potential new technology for measuring effective wave height. Since GNSS-R is very suitable for constellation networking detection, it can complement existing observation methods and provide global effective wave height observation data with high temporal and spatial resolution.

[0084] In the embodiments of the present application, it is considered that if the satellite-borne GNSS-R effective wave height inversion method is based on observations such as the normalized radar cross section and the leading slope of the unnormalized waveform, that is, an indirect inversion method based on the sea surface roughness. Since the effective wave height is affected by both wind and swell, and the sea surface roughness of GNSS-R mainly reflects wind and wave information, this method has certain limitations, and there are problems such as decreased sensitivity in high sea conditions and decreased accuracy when swell dominates. Therefore, in the embodiments of the present application, it is proposed to use the time delay information of GNSS-R, that is, the distance observation value, to directly measure the effective wave height, which can theoretically obtain higher inversion accuracy.

[0085] The idea of ​​the embodiment of the present application is to first normalize the original waveform, calculate the GNSS-R normalized one-dimensional time delay waveform, and compare the theoretical GNSS-R normalized one-dimensional time delay waveform and the measured GNSS-R normalized one-dimensional time delay waveform near the mirror reflection point. Due to the influence of sea waves, the measured GNSS-R normalized one-dimensional time delay waveform has a lower slope than the theoretical GNSS-R normalized one-dimensional time delay waveform, and the delay range corresponding to the same amplitude is larger. Calculate the delay range difference corresponding to the same amplitude between the measured GNSS-R normalized one-dimensional time delay waveform and the theoretical GNSS-R normalized one-dimensional time delay waveform, and then correct the incident angle to obtain the delay difference observation. Finally, match the delay difference observation with the effective wave height to train the effective wave height inversion model.

[0086] Reference Figure 2 , showing a flow chart of the steps of a method for generating an effective wave height inversion model according to an embodiment of the present application.

[0087] like Figure 2 As shown, the method for generating a significant wave height inversion model may include the following steps:

[0088] Step 201: obtaining a first measured GNSS-R normalized one-dimensional time delay waveform and obtaining a first theoretical GNSS-R normalized one-dimensional time delay waveform.

[0089] In the embodiment of the present application, the first measured GNSS-R normalized one-dimensional time delay waveform refers to the measured GNSS-R normalized one-dimensional time delay waveform used in the effective wave height inversion model generation process, and the first theoretical GNSS-R normalized one-dimensional time delay waveform refers to the theoretical GNSS-R normalized one-dimensional time delay waveform used in the effective wave height inversion model generation process. Therefore, the first measured GNSS-R normalized one-dimensional time delay waveform and the first theoretical GNSS-R normalized one-dimensional time delay waveform can be called training sample data.

[0090] In an optional implementation, the first measured GNSS-R normalized one-dimensional delay waveform may be extracted from the first measured DDM (Delay-Doppler map) waveform.

[0091] The first measured DDM waveform refers to the measured DDM waveform used in the significant wave height inversion model generation process.

[0092] The DDM waveform is the basic observation quantity of GNSS-R. It is a two-dimensional power waveform in the dimensions of delay (in chips, specifically GNSS signal chips) and Doppler frequency (in kHz, etc.). The horizontal axis of the DDM waveform represents the delay, and the vertical axis represents the Doppler frequency. Each combination of delay and Doppler frequency corresponds to a value, which can represent the strength or power of the reflected signal and can be expressed in color depth, grayscale value or specific digital quantity.

[0093] Exemplarily, the process of obtaining the first measured GNSS-R normalized one-dimensional delay waveform may include the following steps A1 to A3:

[0094] Step A1, obtaining a first measured DDM waveform.

[0095] In the embodiment of the present application, the DDM waveform is a basic observation quantity of GNSS-R, and the first measured DDM waveform can be directly obtained from the GNSS-R satellite data.

[0096] Step A2: denoising the first measured DDM waveform to obtain a first target measured DDM waveform.

[0097] Exemplarily, the process of denoising the first measured DDM waveform to obtain a first target measured DDM waveform may include: calculating a first average value of numerical values ​​corresponding to delays in the first measured DDM waveform that are less than or equal to a preset delay threshold, and using the first average value as the noise floor of the first measured DDM waveform; and subtracting the noise floor of the first measured DDM waveform from the first measured DDM waveform to obtain the first target measured DDM waveform.

[0098] For example, the first target measured DDM waveform can be obtained using the following formula (1):

[0099] C r (τ, f) = C (τ, f) - C N (1)

[0100] Wherein, τ represents the time delay, f represents the Doppler frequency, C(τ, f) represents the value corresponding to the time delay τ and the Doppler frequency f in the first measured DDM waveform, and C N represents the noise floor of the first measured DDM waveform, C r (τ, f) represents the corresponding values ​​of the time delay τ and the Doppler frequency f in the measured DDM waveform of the first target.

[0101] The specific value of the delay threshold can be set according to actual needs. For example, the delay threshold can be set to -1.5 chips, -2 chips, -2.5 chips, etc. This embodiment does not limit this.

[0102] Step A3: extract the value corresponding to the Doppler frequency of 0 in the first target measured DDM waveform as the first target value, divide the first target value by the peak value in the first target value, and obtain the first measured GNSS-R normalized one-dimensional delay waveform.

[0103] For example, the first measured GNSS-R normalized one-dimensional delay waveform can be obtained using the following formula (2):

[0104]

[0105] Among them, C r (τ, 0) represents the value of the delay τ corresponding to the Doppler frequency of 0 in the measured DDM waveform of the first target, which is also the value of the first target. r，p represents the peak value in the first target value, It represents the normalized value corresponding to the time delay τ in the first measured GNSS-R normalized one-dimensional time delay waveform.

[0106] In the embodiment of the present application, the horizontal axis of the first measured GNSS-R normalized one-dimensional delay waveform represents the delay, and the vertical axis represents the normalized value.

[0107] In an optional implementation, the first theoretical GNSS-R normalized one-dimensional delay waveform may be extracted from the first theoretical DDM waveform.

[0108] The first theoretical DDM waveform refers to the theoretical DDM waveform used in the generation process of the significant wave height inversion model.

[0109] Exemplarily, the process of obtaining the first theoretical GNSS-R normalized one-dimensional delay waveform may include the following steps B1 to B3:

[0110] Step B1, obtaining a first theoretical DDM waveform.

[0111] In the embodiment of the present application, a theoretical simulation model can be used to perform simulation calculations to obtain a first theoretical DDM waveform. It should be noted that the theoretical simulation model takes into account the influence of wind speed on the waveform, but does not take into account the influence of effective wave height. Among them, the theoretical simulation module may include but is not limited to a ZV model, a statistical model, and the like. The specific process of performing simulation calculations using the theoretical simulation model can be processed according to actual experience, and this embodiment will not be discussed in detail here.

[0112] Taking the ZV model as an example, simulation calculations can be performed through the following process: Define radar parameters: including transmission frequency, pulse width, pulse repetition frequency, antenna gain, etc. Simulate sea surface scattering: Use the ZV model or a similar sea surface scattering model to calculate the backscattering coefficient at different incident angles. Calculate radar echo: Calculate the received echo power based on the radar equation and the sea surface scattering coefficient. Generate DDM: Construct DDM by simulating echo signals at different distances and speeds (Doppler frequencies).

[0113] Step B2: denoising the first theoretical DDM waveform to obtain a first target theoretical DDM waveform.

[0114] Exemplarily, the process of denoising the first theoretical DDM waveform to obtain a first target theoretical DDM waveform may include: calculating a second average value of numerical values ​​corresponding to delays in the first theoretical DDM waveform that are less than or equal to a preset delay threshold, and using the second average value as the noise floor of the first theoretical DDM waveform; and subtracting the noise floor of the first theoretical DDM waveform from the first theoretical DDM waveform to obtain the first target theoretical DDM waveform.

[0115] In implementation, the above formula (1) can be used to obtain the first target theoretical DDM waveform, and the details can be referred to the relevant description above.

[0116] Step B3, extracting the value corresponding to the Doppler frequency of 0 in the first target theoretical DDM waveform as the second target value, dividing the second target value by the peak value in the second target value, and obtaining the first theoretical GNSS-R normalized one-dimensional delay waveform.

[0117] In implementation, the above formula (2) can be used to obtain the first theoretical GNSS-R normalized one-dimensional delay waveform. For details, please refer to the relevant description above.

[0118] In the embodiment of the present application, the horizontal axis of the first theoretical GNSS-R normalized one-dimensional delay waveform represents the delay, and the vertical axis represents the normalized value.

[0119] Figure 3 Schematic diagram of a GNSS-R normalized one-dimensional delay waveform according to an embodiment of the present application. Figure 3 As shown, the horizontal axis of the GNSS-R normalized one-dimensional delay waveform represents the delay, and the vertical axis represents the normalized value.

[0120] For the GNSS-R normalized one-dimensional delay waveform, when the sea surface is completely calm, the waveform front of the GNSS-R normalized one-dimensional delay waveform depends on the autocorrelation function of the GNSS signal itself. When there are waves, because the waves have crests and troughs, the reflected echoes of the signal at the crests and troughs of the waves have different delays. When the signal hits the crest, the delay decreases and the waveform is advanced; when the signal hits the trough, the delay increases and the waveform is delayed. The larger the waves, the larger the amplitude, the greater the advance and delay of the waveform, and thus the greater the slope of the leading edge of the waveform.

[0121] It should be noted that in the embodiment of the present application, the delay sampling interval for the first theoretical GNSS-R normalized one-dimensional delay waveform and the first measured GNSS-R normalized one-dimensional delay waveform can be set according to actual needs. For example, the delay sampling interval can be set to 0.125 code chips, 0.25 code chips, etc., and this embodiment does not impose any restrictions on this.

[0122] Step 202: Obtain a first delay range difference between the first measured GNSS-R normalized one-dimensional delay waveform and the first theoretical GNSS-R normalized one-dimensional delay waveform in the same amplitude range.

[0123] In an optional implementation, the process of obtaining a first delay range difference corresponding to the first measured GNSS-R normalized one-dimensional delay waveform and the first theoretical GNSS-R normalized one-dimensional delay waveform in the same amplitude range may include the following steps C1 to C3:

[0124] Step C1, obtaining a first theoretical mirror reflection point of the first theoretical GNSS-R normalized one-dimensional delay waveform, and obtaining a first amplitude range corresponding to a first delay range centered on the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform.

[0125] In the embodiment of the present application, the first theoretical mirror reflection point of the first theoretical GNSS-R normalized one-dimensional delay waveform refers to the point (delay point) where the delay is 0 in the first theoretical GNSS-R normalized one-dimensional delay waveform.

[0126] Exemplarily, the process of obtaining a first amplitude range corresponding to a first delay range centered on the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform may include: performing linear fitting on the waveform of the first delay range centered on the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform to obtain a first theoretical fitting waveform; obtaining the amplitude range corresponding to the first delay range in the first theoretical fitting waveform as the first amplitude range corresponding to the first delay range centered on the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform.

[0127] The purpose of linear fitting of the waveform is to approximate the trend in the waveform data by a straight line. For the process of linear fitting, those skilled in the art can use any applicable method based on practical experience, and this embodiment does not limit this. For example, it can be implemented by the least squares method, which will find a straight line so that the sum of the squares of the vertical distances from all points on the waveform to this straight line is minimized. For another example, in Python, the polyfit function of the NumPy library can be used for linear fitting, and so on.

[0128] The specific value of the first delay range can be set according to actual needs, and this embodiment does not limit this. For example, since the effective wave height at the mirror reflection point is measured, the information at the mirror reflection point mainly corresponds to the delay range of -0.25 code chips to 0.25 code chips, so the first delay range can be set to [-0.25, 0.25] code chips. Of course, the first delay range can also be set to a larger or smaller range, such as [-0.2, 0.2] code chips, [-0.3, 0.3] code chips, and so on.

[0129] Figure 4 Schematic diagram of a GNSS-R normalized one-dimensional delay waveform linear fitting in an embodiment of the present application. Figure 4 As shown, (a) represents the GNSS-R normalized one-dimensional delay waveform before linear fitting, the curve in (b) represents the waveform between the delay range [-0.25, 0.25] code bits in the GNSS-R normalized one-dimensional delay waveform in (a), and the straight line in (b) represents the fitting waveform obtained after linear fitting of the above curve.

[0130] In the process of obtaining the first amplitude range corresponding to the first time delay range in the first theoretical fitting waveform, the amplitude corresponding to the lower limit of the first time delay range in the first theoretical fitting waveform (that is, the normalized value) is obtained as the lower limit of the first amplitude range corresponding to the first time delay range, and the amplitude corresponding to the upper limit of the first time delay range in the first theoretical fitting waveform (that is, the normalized value) is obtained as the upper limit of the first amplitude range corresponding to the first time delay range.

[0131] Taking the first delay range of [-0.25, 0.25] chips as an example, the first amplitude range corresponding to the first delay range in the first theoretical fitting waveform can be obtained by the following formula (3) and formula (4):

[0132]

[0133] in, It represents the normalized value corresponding to the time delay of -0.25 in the first theoretical fitting waveform. It represents the amplitude corresponding to the time delay of -0.25 in the first theoretical fitting waveform. It represents the normalized value corresponding to the time delay of 0.25 in the first theoretical fitting waveform. = represents the amplitude corresponding to the time delay of 0.25 in the first theoretical fitting waveform. Therefore, the first amplitude range corresponding to the first time delay range in the first theoretical fitting waveform is

[0134] Step C2, obtaining a first measured mirror reflection point of the first measured GNSS-R normalized one-dimensional time delay waveform, and obtaining a second delay range centered on the first measured mirror reflection point, corresponding to the first measured GNSS-R normalized one-dimensional time delay waveform under the first amplitude range.

[0135] Due to the existence of errors such as hardware delay, the mirror reflection point (i.e., the position of the delay 0 code chip) of the first measured GNSS-R normalized one-dimensional delay waveform may be inaccurate. Therefore, the first theoretical GNSS-R normalized one-dimensional delay waveform and the first measured GNSS-R normalized one-dimensional delay waveform can be matched, and the delay offset of the first measured GNSS-R normalized one-dimensional delay waveform can be adjusted within a certain range. According to the least squares rule, the optimal offset is searched and the mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform can be obtained, which is called the first measured mirror reflection point.

[0136] Exemplarily, the process of obtaining the first measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform may include the following steps C21 to C23:

[0137] Step C21, selecting preset delay offsets one by one.

[0138] In the embodiment of the present application, a delay offset range can be preset according to actual needs, and the delay offset range includes multiple delay offsets.

[0139] For example, if the delay range of the first measured GNSS-R normalized one-dimensional delay waveform is [-1, 1] chips, and the delay sampling interval is 0.125 chips, the corresponding delay offset range is [-1 / 0.125, 1 / 0.125], that is, [-8, 8]. Therefore, the delay offsets in the delay offset range [-8, 8] are -8, -7, -6, etc., until the delay offset is 8.

[0140] Step C22, respectively calculating the cost function shown in the following formula (5) according to each of the delay offsets:

[0141]

[0142] Wherein, J(k) represents the cost function, represents the time delay τ in the first measured GNSS-R normalized one-dimensional time delay waveform i+k The corresponding normalized value is represents the time delay τ in the first theoretical GNSS-R normalized one-dimensional time delay waveform i The corresponding normalized value, k represents the delay offset, N1 represents the subscript of the delay lower limit of the third delay range, and N2 represents the subscript of the delay upper limit of the third delay range. The subscript represents the position of the delay in all delay sampling points.

[0143] The specific value of the third delay range can be set according to actual needs. For example, the third delay range can be set to [-4, 4] chips, [-5, 5] chips, [-6, 6] chips, etc. This embodiment does not limit this.

[0144] Step C23, selecting the target delay offset corresponding to the minimum of the cost function, and using the delay corresponding to the first theoretical mirror reflection point offset by the target delay offset as the measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform.

[0145] For example, it is assumed that the original delay τ of the first theoretical GNSS-R normalized one-dimensional delay waveform and the first measured GNSS-R normalized one-dimensional delay waveform is as shown in the following formula (6):

[0146] τ=[τ 1 , τ 2 , ...τ m , τN ] (6)

[0147] Where N is the total number of delay sampling points, and the delay sampling interval is △τ = 0.125 code chips, that is, T n+1 1 tau n =△τ.

[0148] Assume that the subscript of the delay corresponding to the first theoretical mirror reflection point of the first theoretical GNSS-R normalized one-dimensional delay waveform is m, that is, τ m =0.

[0149] When J(k) is minimum, m+k is the subscript of the delay corresponding to the first measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform. At this time, the delay τ′ of the first measured GNSS-R normalized one-dimensional delay waveform is adjusted to the following formula (7):

[0150] τ′=[τ′ 1 , τ′ 2 , ...τ′ m , τ′ N ] (7)

[0151] Among them, τ′ i =τ i -kΔτ. At this time, τ′ m+k =T m+k -kΔτ=0.

[0152] Exemplarily, the process of obtaining the second delay range centered on the first measured mirror reflection point, corresponding to the first measured GNSS-R normalized one-dimensional delay waveform under the first amplitude range, may include: performing linear fitting on the waveform of the first delay range centered on the first measured mirror reflection point in the first measured GNSS-R normalized one-dimensional delay waveform to obtain a first measured fitting waveform; and calculating the delay range corresponding to the first amplitude range in the first measured fitting waveform as the second delay range.

[0153] For the first measured GNSS-R normalized one-dimensional delay waveform, the corresponding first delay range τ ′ = [-0.25, 0.25] The waveform within the chip is linearly fitted to obtain the first measured fitting waveform

[0154] Exemplarily, the time delay range corresponding to the first amplitude range in the first measured fitting waveform may be calculated by linear interpolation using the following formula (8) and formula (9):

[0155]

[0156] in, represents the lower limit of the first amplitude range, represents the lower limit of the delay range corresponding to the first amplitude range, Indicates the time delay in the first measured fitting waveform The corresponding normalized value is represents the upper limit of the first amplitude range, represents the upper limit of the delay range corresponding to the first amplitude range, Indicates the first measured fitting waveform delay The corresponding normalized value.

[0157] Step C3: calculate the difference between the second delay range and the first delay range to obtain the first delay range difference.

[0158] Exemplarily, the process of calculating the difference between the second delay range and the first delay range to obtain the first delay range difference may include: calculating a first difference between an upper limit and a lower limit of the first delay range, calculating a second difference between an upper limit and a lower limit of the second delay range, and determining the difference between the second difference and the first difference as the first delay range difference. The unit of the first delay range difference is a chip (specifically a GNSS signal chip).

[0159] For example, the first delay range is [-0.25, 0.25] chips, and the second delay range is Then the first difference between the upper limit and the lower limit of the first delay range is 0.25-(-0.25)=0.5, and the second difference between the upper limit and the lower limit of the second delay range is Therefore, the first time delay range difference is (h 0 -0.5).

[0160] Figure 5 Schematic diagram of a fitting waveform according to an embodiment of the present application. Figure 5 As shown, the fitting waveform with a larger slope is the first theoretical fitting waveform, the fitting waveform with a smaller slope is the first measured fitting waveform, and the first amplitude range corresponding to the first delay range [-0.25, 0.25] chips in the first theoretical fitting waveform is The first amplitude range in the first measured fitting waveform The corresponding delay range, i.e. the second delay range, is The first difference between the upper limit and the lower limit of the first delay range is 0.5, and the second difference between the upper limit and the lower limit of the second delay range is h 0 .

[0161] Step 203: Perform incident angle correction on the first time delay range difference to obtain a first time delay difference observation value.

[0162] Due to the presence of sea surface crests and troughs caused by waves, the second difference is h 0 It will be greater than the first difference of 0.5. The first delay range difference has a linear relationship with the size of the waves, that is, the effective wave height. Since GNSS-R is incident at an oblique angle, the incident angle needs to be corrected.

[0163] Figure 6 FIG. 1 is a schematic diagram of a change in propagation distance caused by a change in sea level height according to an embodiment of the present application. Figure 6 As shown, when there are sea waves, the incident angle is θ, the sea surface height changes by h, and the overall propagation distance changes by about 2hcos(θ).

[0164] Exemplarily, the process of performing incident angle correction on the first time delay range difference to obtain a first time delay difference observation value may include: dividing the first time delay range difference by twice the cosine value of the first incident angle to obtain a ratio, and determining the ratio as the first time delay difference observation value. The first incident angle refers to the incident angle in the process of generating the effective wave height inversion model.

[0165] The first difference between the upper limit and the lower limit of the first delay range is 0.5, and the second difference between the upper limit and the lower limit of the second delay range is h o , taking the first incident angle as θ as an example, the first time delay difference observation Δh can be calculated by the following formula (10):

[0166]

[0167] Step 204: Obtain a first effective wave height that matches the first time delay difference observation.

[0168] Exemplarily, the process of obtaining a first effective wave height that matches the first time delay difference observation may include: matching the first time delay difference observation with the effective wave height measured by the buoy according to a set matching rule to obtain the first effective wave height that matches the first time delay difference observation. The matching rule includes: the spatial distance between the mirror reflection point position corresponding to the GNSS-R measurement and the buoy position corresponding to the buoy measurement is less than a preset distance, and the time interval between the observation time corresponding to the GNSS-R measurement and the observation time corresponding to the buoy measurement is less than a preset duration.

[0169] The specific values ​​of the preset distance and the preset duration can be set according to actual needs. For example, the preset distance can be set to 25 km, the preset duration can be set to 1 hour, and so on. This embodiment does not impose any restrictions on this.

[0170] During the GNSS-R measurement process, a first delay difference observation can be calculated at every preset time interval, and then a corresponding first effective wave height can be matched. Use multiple GNSS-R data (such as GNSS-R data of more than 1 month, etc.) for matching to obtain a matching data set of the first delay difference observation measured by GNSS-R and the first effective wave height measured by the buoy.

[0171] Step 205: Using the first time delay difference observation and the first effective wave height, a training effective wave height inversion model is obtained.

[0172] Exemplarily, the process of training the effective wave height inversion model using the first time delay difference observation and the first effective wave height may include: performing linear fitting training using the first time delay difference observation and the first effective wave height (specifically the above-mentioned matching data set) to obtain the effective wave height inversion model shown in the following formula (11):

[0173] H s =aΔh+b (11)

[0174] Among them, H s represents the effective wave height, Δh represents the delay difference observation, a represents the first coefficient, and b represents the second coefficient.

[0175] The goal of linear fitting is to find an optimal straight line that can best describe the relationship between the data points (the first time delay difference observation and the first effective wave height). For example, it can be achieved by minimizing the sum of the squares of the vertical distances from the data points to the fitting line (i.e., the least squares method), etc. After the linear fitting training is completed, the first coefficient a and the second coefficient b of the effective wave height inversion model shown in the above formula (11) can be obtained.

[0176] In an embodiment of the present application, an effective wave height inversion based on GNSS-R technology is proposed, the original waveform is normalized to obtain a GNSS-R normalized one-dimensional time delay waveform, and the delay information of the GNSS-R normalized one-dimensional time delay waveform is used for comparative analysis instead of the power amplitude information to obtain a first time delay difference observation, and then an effective wave height inversion model is trained based on the first time delay difference observation and the matching first effective wave height. Compared with the analysis using power amplitude information, the analysis using time delay information does not require calibration of the signal power, is more direct and has higher accuracy, and does not have the problems of decreased sensitivity in high sea conditions and decreased accuracy when surges dominate. In addition, an incident angle correction is added when calculating the first time delay difference observation, which further improves the accuracy of the first time delay difference observation, thereby improving the accuracy of the effective wave height inversion model, and further improving the accuracy of the effective wave height obtained by inverting the effective wave height inversion model.

[0177] Reference Figure 7, showing a step flow chart of an effective wave height inversion method according to an embodiment of the present application.

[0178] like Figure 7 As shown, the significant wave height inversion method can include the following steps:

[0179] Step 701, obtaining a second measured GNSS-R normalized one-dimensional time delay waveform, and obtaining a second theoretical GNSS-R normalized one-dimensional time delay waveform.

[0180] In the embodiment of the present application, the second measured GNSS-R normalized one-dimensional time delay waveform refers to the measured GNSS-R normalized one-dimensional time delay waveform used in the effective wave height inversion process, and the second theoretical GNSS-R normalized one-dimensional time delay waveform refers to the theoretical GNSS-R normalized one-dimensional time delay waveform used in the effective wave height inversion process. Therefore, the second measured GNSS-R normalized one-dimensional time delay waveform and the second theoretical GNSS-R normalized one-dimensional time delay waveform can be referred to as data to be processed.

[0181] Exemplarily, obtaining a second measured GNSS-R normalized one-dimensional time delay waveform includes: obtaining a second measured DDM waveform; denoising the second measured DDM waveform to obtain a second target measured DDM waveform; extracting a value corresponding to a Doppler frequency of 0 in the second target measured DDM waveform as a third target value, dividing the third target value by a peak value in the third target value, to obtain the second measured GNSS-R normalized one-dimensional time delay waveform.

[0182] Exemplarily, the denoising process of the second measured DDM waveform to obtain the second target measured DDM waveform includes: calculating a third average value of the values ​​corresponding to the delays in the second measured DDM waveform that are less than or equal to a preset delay threshold, and using the third average value as the noise floor of the second measured DDM waveform; and subtracting the noise floor of the second measured DDM waveform from the second measured DDM waveform to obtain the second target measured DDM waveform.

[0183] Optionally, obtaining a second theoretical GNSS-R normalized one-dimensional time delay waveform includes: obtaining a second theoretical DDM waveform; denoising the second theoretical DDM waveform to obtain a second target theoretical DDM waveform; extracting a value corresponding to a Doppler frequency of 0 in the second target theoretical DDM waveform as a fourth target value, dividing the fourth target value by a peak value in the fourth target value to obtain the second theoretical GNSS-R normalized one-dimensional time delay waveform.

[0184] Optionally, the denoising process of the second theoretical DDM waveform to obtain a second target theoretical DDM waveform includes: calculating a fourth average value of numerical values ​​corresponding to delays that are less than or equal to a preset delay threshold in the second theoretical DDM waveform, and using the fourth average value as the noise floor of the second theoretical DDM waveform; and subtracting the noise floor of the second theoretical DDM waveform from the second theoretical DDM waveform to obtain the second target theoretical DDM waveform.

[0185] Step 702: Obtain a second delay range difference between the second measured GNSS-R normalized one-dimensional delay waveform and the second theoretical GNSS-R normalized one-dimensional delay waveform in the same amplitude range.

[0186] Exemplarily, obtaining a second delay range difference corresponding to the same amplitude range of the second measured GNSS-R normalized one-dimensional delay waveform and the second theoretical GNSS-R normalized one-dimensional delay waveform includes: obtaining a second theoretical mirror reflection point of the second theoretical GNSS-R normalized one-dimensional delay waveform, and obtaining a second amplitude range corresponding to a first delay range centered on the second theoretical mirror reflection point in the second theoretical GNSS-R normalized one-dimensional delay waveform; obtaining a second measured mirror reflection point of the second measured GNSS-R normalized one-dimensional delay waveform, and obtaining a fourth delay range centered on the second measured mirror reflection point corresponding to the second measured GNSS-R normalized one-dimensional delay waveform under the second amplitude range; calculating the difference between the fourth delay range and the first delay range to obtain the second delay range difference.

[0187] Exemplarily, the method of obtaining the second amplitude range corresponding to the first delay range centered on the second theoretical mirror reflection point in the second theoretical GNSS-R normalized one-dimensional delay waveform includes: performing linear fitting on the waveform of the first delay range centered on the second theoretical mirror reflection point in the second theoretical GNSS-R normalized one-dimensional delay waveform to obtain a second theoretical fitting waveform; and obtaining the amplitude range corresponding to the first delay range in the second theoretical fitting waveform as the second amplitude range.

[0188] For the process of obtaining the second measured mirror reflection point of the second measured GNSS-R normalized one-dimensional delay waveform, reference may be made to the above description of the process of obtaining the first measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform.

[0189] Exemplarily, obtaining the fourth delay range centered on the second measured mirror reflection point corresponding to the second measured GNSS-R normalized one-dimensional delay waveform under the second amplitude range includes: performing linear fitting on the waveform of the first delay range centered on the second measured mirror reflection point in the second measured GNSS-R normalized one-dimensional delay waveform to obtain a second measured fitting waveform; calculating the delay range corresponding to the second amplitude range in the second measured fitting waveform as the fourth delay range.

[0190] Step 703: Perform incident angle correction on the second time delay range difference to obtain a second time delay difference observation value.

[0191] Optionally, performing incident angle correction on the second time delay range difference to obtain a second time delay difference observation includes: dividing the second time delay range difference by twice the cosine value of the second incident angle to obtain a ratio, and determining the ratio as the second time delay difference observation. The second incident angle refers to the incident angle in the process of performing effective wave height inversion.

[0192] Step 704: Calculate the effective wave height corresponding to the second time delay difference observation using a pre-trained effective wave height inversion model.

[0193] After obtaining the second time delay difference observation, the effective wave height inversion model shown in the above formula (11) can be used to substitute the second time delay difference observation as Δh into the effective wave height inversion model, so as to calculate the effective wave height H corresponding to the second time delay difference observation: s .

[0194] In the embodiments of the present application, the accuracy of the effective wave height obtained by inverting the effective wave height inversion model can be improved.

[0195] Reference Figure 8 , shows a structural block diagram of an effective wave height inversion model generating device according to an embodiment of the present application.

[0196] like Figure 8 As shown, the significant wave height inversion model generation device may include the following modules:

[0197] A first acquisition module 801 is used to acquire a first measured GNSS-R normalized one-dimensional time delay waveform and a first theoretical GNSS-R normalized one-dimensional time delay waveform;

[0198] A second acquisition module 802 is used to obtain a first delay range difference between the first measured GNSS-R normalized one-dimensional delay waveform and the first theoretical GNSS-R normalized one-dimensional delay waveform in the same amplitude range;

[0199] A first correction module 803, configured to perform incident angle correction on the first time delay range difference to obtain a first time delay difference observation value;

[0200] A matching module 804 is used to obtain a first effective wave height that matches the first time delay difference observation value;

[0201] The training module 805 is used to train an effective wave height inversion model using the first time delay difference observation and the first effective wave height.

[0202] Optionally, the first acquisition module 801 includes: a first waveform acquisition submodule, used to acquire a first measured DDM waveform; a first denoising submodule, used to denoise the first measured DDM waveform to obtain a first target measured DDM waveform; a first normalization submodule, used to extract the value corresponding to the Doppler frequency of 0 in the first target measured DDM waveform as the first target value, and divide the first target value by the peak value in the first target value to obtain the first measured GNSS-R normalized one-dimensional time delay waveform.

[0203] Optionally, the first denoising submodule is specifically used to calculate a first average value of the numerical value corresponding to the delay that is less than or equal to a preset delay threshold in the first measured DDM waveform, and use the first average value as the noise floor of the first measured DDM waveform; subtract the noise floor of the first measured DDM waveform from the first measured DDM waveform to obtain the first target measured DDM waveform.

[0204] Optionally, the first acquisition module 801 includes: a second waveform acquisition submodule, used to acquire a first theoretical DDM waveform; a second denoising submodule, used to denoise the first theoretical DDM waveform to obtain a first target theoretical DDM waveform; a second normalization submodule, used to extract the value corresponding to the Doppler frequency of 0 in the first target theoretical DDM waveform as the second target value, and divide the second target value by the peak value in the second target value to obtain the first theoretical GNSS-R normalized one-dimensional time delay waveform.

[0205] Optionally, the second denoising submodule is specifically used to calculate a second average value of the numerical value corresponding to the delay that is less than or equal to a preset delay threshold in the first theoretical DDM waveform, and use the second average value as the noise floor of the first theoretical DDM waveform; subtract the noise floor of the first theoretical DDM waveform from the first theoretical DDM waveform to obtain the first target theoretical DDM waveform.

[0206] Optionally, the second acquisition module 802 includes: a first range acquisition submodule, used to acquire the first theoretical mirror reflection point of the first theoretical GNSS-R normalized one-dimensional delay waveform, and acquire the first amplitude range corresponding to the first delay range centered on the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform; a second range acquisition submodule, used to acquire the first measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform, and acquire the second delay range centered on the first measured mirror reflection point corresponding to the first measured GNSS-R normalized one-dimensional delay waveform under the first amplitude range; and a calculation submodule, used to calculate the difference between the second delay range and the first delay range to obtain the first delay range difference.

[0207] Optionally, the first range acquisition submodule includes: a first fitting unit, used to perform linear fitting on the waveform of the first delay range centered on the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform to obtain a first theoretical fitting waveform; and obtain the amplitude range corresponding to the first delay range in the first theoretical fitting waveform as the first amplitude range.

[0208] Optionally, the second range acquisition submodule includes a reflection point acquisition unit, and the reflection point acquisition unit is used to:

[0209] Select the preset delay offsets one by one;

[0210] The following cost function is calculated according to each of the delay offsets:

[0211]

[0212] Wherein, J(k) represents the cost function, represents the time delay τ in the first measured GNSS-R normalized one-dimensional time delay waveform i+k The corresponding normalized value is represents the time delay τ in the first theoretical GNSS-R normalized one-dimensional time delay waveform i The corresponding normalized value, k represents the delay offset, N 1 The subscript indicating the lower limit of the delay in the third delay range, N 2 A subscript representing the upper limit of the delay of the third delay range;

[0213] The target delay offset corresponding to the minimum of the cost function is selected, and the delay corresponding to the first theoretical mirror reflection point offset by the target delay offset is used as the measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform.

[0214] Optionally, the first range acquisition submodule includes: a second fitting unit, used to perform linear fitting on the waveform of the first delay range centered on the first measured mirror reflection point in the first measured GNSS-R normalized one-dimensional delay waveform to obtain a first measured fitting waveform; and calculate the delay range corresponding to the first amplitude range in the first measured fitting waveform as the second delay range.

[0215] Optionally, the first correction module 803 is specifically configured to determine a ratio obtained by dividing the first time delay range difference by twice the cosine value of the first incident angle as the first time delay difference observation value.

[0216] Optionally, the matching module 804 is specifically used to match the first time delay difference observation with the effective wave height measured by the buoy according to a set matching rule to obtain a first effective wave height that matches the first time delay difference observation; the matching rule includes: the spatial distance between the mirror reflection point position corresponding to the GNSS-R measurement and the buoy position corresponding to the buoy measurement is less than a preset distance, and the time interval between the observation time corresponding to the GNSS-R measurement and the observation time corresponding to the buoy measurement is less than a preset duration.

[0217] Optionally, the training module 805 is specifically configured to perform linear fitting training using the first time delay difference observation and the first significant wave height to obtain the following significant wave height inversion model:

[0218] H s =aΔh+b

[0219] Among them, H s represents the effective wave height, Δh represents the delay difference observation, a represents the first coefficient, and b represents the second coefficient.

[0220] Reference Fig. 9 , shows a structural block diagram of an effective wave height inversion device according to an embodiment of the present application.

[0221] like Fig. 9 As shown, the significant wave height inversion device may include the following modules:

[0222] The third acquisition module 901 is used to acquire a second measured GNSS-R normalized one-dimensional time delay waveform and a second theoretical GNSS-R normalized one-dimensional time delay waveform;

[0223] A fourth acquisition module 902 is used to obtain a second delay range difference corresponding to the same amplitude range between the second measured GNSS-R normalized one-dimensional delay waveform and the second theoretical GNSS-R normalized one-dimensional delay waveform;

[0224] A second correction module 903, configured to perform incident angle correction on the second time delay range difference to obtain a second time delay difference observation value;

[0225] The calculation module 904 is used to calculate the effective wave height corresponding to the second time delay difference observation by using a pre-trained effective wave height inversion model; the effective wave height inversion model is obtained by the effective wave height inversion model generation method as described in any of the above items.

[0226] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0227] In an embodiment of the present application, an electronic device is also provided. The electronic device may include a processor and a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium; when the computer program is executed by the processor, the processor executes the significant wave height inversion model generation method of any of the above embodiments, or executes the significant wave height inversion method of any of the above embodiments.

[0228] Reference Fig.10 , shows a structural block diagram of an electronic device according to an embodiment of the present application. Fig.10 As shown, the electronic device 100 includes a processor 1001 and a computer-readable storage medium 1002 , on which a computer program 10021 is stored.

[0229] The processor 1001 is used to execute the computer program 10021 stored on the computer-readable storage medium 1002. When executing the computer program 10021, the processor 1001 executes the significant wave height inversion model generation method of any of the above-mentioned embodiments, or executes the significant wave height inversion method of any of the above-mentioned embodiments, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0230] The processor 1001 mentioned above may include but is not limited to: a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0231] The computer-readable storage medium 1002 mentioned above may include but is not limited to: read-only memory (ROM), random access memory (RAM), compact disc read-only memory (CD-ROM), electronic erasable programmable read-only memory (EEPROM), hard disk, floppy disk, flash memory, etc.

[0232] In an embodiment of the present application, a computer-readable storage medium is further provided, on which a computer program is stored. The computer program can be executed by a processor of an electronic device. When the computer program is executed by the processor, the processor executes the effective wave height inversion model generation method of any of the above-mentioned embodiments, or executes the effective wave height inversion method of any of the above-mentioned embodiments.

[0233] Reference Fig.11 , shows a block diagram of a computer-readable storage medium according to an embodiment of the present application. Fig.11 As shown, a computer program 1101 is stored on the computer-readable storage medium 110. When the computer program 1101 is executed by the processor, the processor executes the significant wave height inversion model generation method of any of the above-mentioned embodiments, or executes the significant wave height inversion method of any of the above-mentioned embodiments, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0234] The various embodiments in this specification are interrelated, and each embodiment is described in a progressive manner. Each embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments can be referenced to each other.

[0235] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0236] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application.

[0237] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0238] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0239] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0240] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0241] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0242] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0243] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. In summary, the content of this specification should not be understood as limiting the present application.

Claims

1. A method for generating an effective wave height inversion model, characterized in that: The method comprises: Obtaining a first measured GNSS-R normalized one-dimensional time delay waveform, and obtaining a first theoretical GNSS-R normalized one-dimensional time delay waveform; Obtaining a first delay range difference corresponding to the same amplitude range between the first measured GNSS-R normalized one-dimensional delay waveform and the first theoretical GNSS-R normalized one-dimensional delay waveform; Performing incident angle correction on the first time delay range difference to obtain a first time delay difference observation amount; Acquire a first effective wave height matching the first time delay difference observation; The effective wave height inversion model is trained using the first time delay difference observation and the first effective wave height.

2. The method according to claim 1, characterized in that Obtaining a first measured GNSS-R normalized one-dimensional delay waveform, including: Obtaining a first measured DDM waveform; De-noising the first measured DDM waveform to obtain a first target measured DDM waveform; A value corresponding to a Doppler frequency of 0 in the first target measured DDM waveform is extracted as a first target value, and the first target value is divided by a peak value in the first target value to obtain the first measured GNSS-R normalized one-dimensional time delay waveform.

3. The method according to claim 2, characterized in that The denoising process of the first measured DDM waveform to obtain a first target measured DDM waveform includes: Calculating a first average value of values ​​corresponding to delays less than or equal to a preset delay threshold in the first measured DDM waveform, and using the first average value as the noise floor of the first measured DDM waveform; The first target measured DDM waveform is obtained by subtracting the noise floor of the first measured DDM waveform from the first measured DDM waveform.

4. The method according to claim 1, characterized in that Get the first theoretical GNSS-R normalized one-dimensional delay waveform, including: Obtaining a first theoretical DDM waveform; De-noising the first theoretical DDM waveform to obtain a first target theoretical DDM waveform; The value corresponding to the Doppler frequency of 0 in the first target theoretical DDM waveform is extracted as the second target value, and the second target value is divided by the peak value in the second target value to obtain the first theoretical GNSS-R normalized one-dimensional delay waveform.

5. The method according to claim 4, characterized in that The denoising process of the first theoretical DDM waveform to obtain a first target theoretical DDM waveform includes: Calculating a second average value of values ​​corresponding to delays less than or equal to a preset delay threshold in the first theoretical DDM waveform, and using the second average value as the noise floor of the first theoretical DDM waveform; The first target theoretical DDM waveform is obtained by subtracting the noise floor of the first theoretical DDM waveform from the first theoretical DDM waveform.

6. The method according to claim 1, characterized in that The obtaining of a first delay range difference between the first measured GNSS-R normalized one-dimensional delay waveform and the first theoretical GNSS-R normalized one-dimensional delay waveform in the same amplitude range includes: Obtaining a first theoretical mirror reflection point of the first theoretical GNSS-R normalized one-dimensional time delay waveform, and obtaining a first amplitude range corresponding to a first delay range centered at the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional time delay waveform; Obtaining a first measured mirror reflection point of the first measured GNSS-R normalized one-dimensional time delay waveform, and obtaining a second delay range corresponding to the first measured GNSS-R normalized one-dimensional time delay waveform under the first amplitude range and centered at the first measured mirror reflection point; A difference between the second delay range and the first delay range is calculated to obtain the first delay range difference.

7. The method according to claim 6, characterized in that The obtaining of a first amplitude range corresponding to a first delay range centered at the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform includes: Performing linear fitting on a waveform of a first delay range centered at the first theoretical mirror reflection point in the first theoretical GNSS-R normalized one-dimensional delay waveform to obtain a first theoretical fitting waveform; An amplitude range corresponding to the first time delay range in the first theoretical fitting waveform is obtained as the first amplitude range.

8. The method according to claim 6, characterized in that The step of obtaining the first measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform includes: Select the preset delay offsets one by one; The following cost function is calculated according to each of the delay offsets: Wherein, J(k) represents the cost function, represents the time delay τ in the first measured GNSS-R normalized one-dimensional time delay waveform i+k The corresponding normalized value is represents the time delay τ in the first theoretical GNSS-R normalized one-dimensional time delay waveform i The corresponding normalized values, k represents the delay offset, N1 represents the subscript of the delay lower limit of the third delay range, and N2 represents the subscript of the delay upper limit of the third delay range; The target delay offset corresponding to the minimum of the cost function is selected, and the delay corresponding to the first theoretical mirror reflection point offset by the target delay offset is used as the measured mirror reflection point of the first measured GNSS-R normalized one-dimensional delay waveform.

9. The method according to claim 6, characterized in that The obtaining of a second delay range centered on the first measured mirror reflection point corresponding to the first measured GNSS-R normalized one-dimensional delay waveform in the first amplitude range includes: Performing linear fitting on a waveform of a first delay range centered at the first measured mirror reflection point in the first measured GNSS-R normalized one-dimensional delay waveform to obtain a first measured fitting waveform; A time delay range corresponding to the first amplitude range in the first measured fitting waveform is calculated as the second time delay range.

10. The method according to claim 1, characterized in that The performing incident angle correction on the first time delay range difference to obtain a first time delay difference observation amount includes: A ratio obtained by dividing the first time delay range difference by twice the cosine value of the first incident angle is determined as the first time delay difference observation value.

11. The method according to claim 1, characterized in that: The obtaining of a first effective wave height matching the first time delay difference observation value comprises: Matching the first time delay difference observation amount with the effective wave height measured by the buoy according to a set matching rule to obtain a first effective wave height matching the first time delay difference observation amount; The matching rules include: the spatial distance between the mirror reflection point position corresponding to the GNSS-R measurement and the buoy position corresponding to the buoy measurement is less than a preset distance, and the time interval between the observation time corresponding to the GNSS-R measurement and the observation time corresponding to the buoy measurement is less than a preset duration.

12. The method according to claim 1, characterized in that The step of training an effective wave height inversion model using the first time delay difference observation and the first effective wave height comprises: The first time delay difference observation and the first significant wave height are used to perform linear fitting training to obtain the following significant wave height inversion model: H s =aΔh+b Among them, H s represents the effective wave height, Δh represents the delay difference observation, a represents the first coefficient, and b represents the second coefficient.

13. A method for inverting effective wave height, characterized in that: The method comprises: Acquire a second measured GNSS-R normalized one-dimensional time delay waveform, and acquire a second theoretical GNSS-R normalized one-dimensional time delay waveform; Obtaining a second delay range difference corresponding to the same amplitude range between the second measured GNSS-R normalized one-dimensional delay waveform and the second theoretical GNSS-R normalized one-dimensional delay waveform; Performing incident angle correction on the second time delay range difference to obtain a second time delay difference observation amount; The effective wave height corresponding to the second time delay difference observation is calculated using a pre-trained effective wave height inversion model; the effective wave height inversion model is obtained by the effective wave height inversion model generation method according to any one of claims 1 to 12.

14. A significant wave height inversion model generation device, characterized in that: The device comprises: A first acquisition module, used to acquire a first measured GNSS-R normalized one-dimensional time delay waveform and a first theoretical GNSS-R normalized one-dimensional time delay waveform; A second acquisition module is used to obtain a first delay range difference between the first measured GNSS-R normalized one-dimensional delay waveform and the first theoretical GNSS-R normalized one-dimensional delay waveform in the same amplitude range; A first correction module, configured to perform incident angle correction on the first time delay range difference to obtain a first time delay difference observation amount; A matching module, used for acquiring a first effective wave height matching the first time delay difference observation value; A training module is used to train an effective wave height inversion model using the first time delay difference observation and the first effective wave height.

15. An effective wave height inversion device, characterized in that: The device comprises: A third acquisition module is used to acquire a second measured GNSS-R normalized one-dimensional time delay waveform and a second theoretical GNSS-R normalized one-dimensional time delay waveform; A fourth acquisition module, used to obtain a second delay range difference corresponding to the same amplitude range between the second measured GNSS-R normalized one-dimensional delay waveform and the second theoretical GNSS-R normalized one-dimensional delay waveform; A second correction module, configured to perform incident angle correction on the second time delay range difference to obtain a second time delay difference observation amount; A calculation module is used to calculate the effective wave height corresponding to the second time delay difference observation using a pre-trained effective wave height inversion model; the effective wave height inversion model is obtained by the effective wave height inversion model generation method according to any one of claims 1 to 12.

16. An electronic device, characterized in that: The electronic device comprises a processor and a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program; When the computer program is executed by the processor, the processor executes the significant wave height inversion model generating method according to any one of claims 1 to 12, or executes the significant wave height inversion method according to claim 13.

17. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor executes the significant wave height inversion model generation method according to any one of claims 1 to 12, or executes the significant wave height inversion method according to claim 13.

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