A shipborne GNSS-R significant wave height inversion method based on multiple observation fields

Abstract

The present invention discloses a shipborne GNSS-R effective wave height inversion method based on multiple observation fields, comprising the following steps: acquiring real-time four-channel delay-Doppler spectrum data and effective wave height values ​​generated by a ship along a route; preprocessing the real-time four-channel delay-Doppler spectrum data to obtain preprocessed four-channel delay-Doppler spectrum data; extracting observation quantities that are dependent on effective wave height according to the preprocessed delay-Doppler spectrum data; constructing an effective wave height inversion model for multiple observation fields based on 70% of the observation quantity data; extracting an observation quantity value sequence based on 30% of the observation quantity data, inputting the observation quantity value sequence into the effective wave height inversion model to obtain effective wave height inversion values, and simultaneously obtaining a corrected observation quantity value sequence, establishing a multivariate parameter correction model for the corrected observation quantity value sequence, and realizing effective wave height inversion. The method realizes correction of the observation quantity through a joint matrix reconstructed by dimensionality reduction, thereby improving the inversion accuracy.

Description

Technical Field

[0001] The present invention belongs to the field of marine remote sensing and relates to a shipborne GNSS-R effective wave height inversion method based on multiple observation fields. Background Art

[0002] With the rapid development of the marine industry, maritime activities are becoming more and more extensive. Accurately knowing the waves is an important prerequisite for ensuring the safety of all maritime activities. As a representative physical quantity reflecting the waves, significant wave height is very important for maritime safety management and port and dock protection. Traditionally, the measurement of significant wave height parameters is carried out through station-based observations, such as marine meteorological stations and buoys, which can achieve continuous observation of relevant wave parameters, but are limited by high costs, distribution of detection areas, and the complexity of the marine environment. With the development of satellite remote sensing technology, some single-machine radars such as satellite-borne altimeters, scatterometers, and synthetic aperture radars have roughly achieved global-scale detection by actively transmitting microwave signals to the sea surface and receiving reflected signals. Due to the varying degrees of problems such as the cost and accuracy of these equipment, these observation methods have limitations, and the biggest problem is the inability to achieve effective wave height observations with high temporal and spatial resolution.

[0003] In recent years, the integration of remote sensing and navigation technology has become an emerging detection method. GNSS-R, a novel passive microwave remote sensing technology, relies on over 100 navigation satellites operating in real time in space to enable passive detection of the sea surface. While spaceborne GNSS-R can achieve large-scale global inversion, it is severely impacted by coastal areas close to land and lacks real-time observation capabilities, making it difficult to provide accurate information for ship navigation or high-resolution coastal observations. As a new type of maritime sensor, GNSS-R, when carried on ships, uses a bistatic geometry to measure the scattering area around the specular reflection point. This effectively complements conventional backscatter shipborne radar and can address the spatial and temporal extension limitations of other remote sensing technologies. Real-time measurement of significant wave height will help maritime authorities build maritime monitoring networks and is of great significance to intelligent ship navigation, marine science research, and marine engineering. Summary of the Invention

[0004] In order to solve the problem that in coastal areas close to land, satellite-borne GNSS-R is severely affected and lacks real-time observation capabilities, making it difficult to provide relatively accurate information for ship navigation or coastal high-resolution observation, the technical solution adopted by the present invention is: a ship-borne GNSS-R significant wave height inversion method based on multiple observation fields, comprising the following steps: obtaining real-time four-channel delay-Doppler spectrum data and significant wave height values ​​generated by the ship along the route;

[0005] Preprocessing the real-time four-channel delay-Doppler spectrum data to obtain preprocessed four-channel delay-Doppler spectrum data;

[0006] Extract the observation quantity that is dependent on the significant wave height from the pre-processed delay-Doppler spectrum data;

[0007] Based on 70% of the observation data, a significant wave height inversion model for multiple observation fields is constructed;

[0008] Based on 30% of the observation data, the observation value sequence is extracted and input into the significant wave height inversion model to obtain the significant wave height inversion value. At the same time, the corrected observation value sequence is obtained. A multivariate parameter correction model is established for the corrected observation value sequence to realize the significant wave height inversion.

[0009] Furthermore, the observed quantities include the leading edge slope and the average value of the trailing edge slope of the normalized delay curve, as well as the delay window length, the delay Doppler spectrum volume and the satellite elevation angle.

[0010] Furthermore, the process of preprocessing the real-time four-channel delay-Doppler spectrum data to obtain the preprocessed four-channel delay-Doppler spectrum data is as follows:

[0011] Normalize the delay curves at different Doppler frequency shifts;

[0012] The four-channel delay-Doppler spectrum data of each frame are annotated with the effective wave height value obtained by the wave meter. First, all NAN values ​​are removed. In addition, a standardized delay waveform is established and a threshold is selected to remove low-quality data.

[0013] Furthermore, the number of normalized delay curves is five, and the delay window length is also the average of the five delay curve chips. The average of the delay curve chip lengths is calculated as follows:

[0014] TDWD=τ right -τ left

[0015] Where τ right and τ left They represent the right and left delay chip values ​​intercepted in the curve respectively.

[0016] Furthermore: the multi-observation measurement field includes multiple single observation measurement fields, and the single observation measurement field includes each observation quantity and the corresponding altitude angle and effective wave height combination; the matrix dimensions of each single observation measurement field remain consistent.

[0017] Furthermore: the satellite elevation angle range is 40°-80°, and the resolution is 0.1°.

[0018] Furthermore: the expression of the multivariate parameter correction model is as follows:

[0019]

[0020] Where: Obs i Represents different observation values, a i represents the corresponding coefficient, and b is the constant term.

[0021] Furthermore, based on 70% of the observation data, the process of constructing the effective wave height inversion model of multiple observation fields is as follows:

[0022] The single observation field is represented by a matrix:

[0023]

[0024] In the matrix, each point represents the LES value at the effective wave height and satellite elevation angle, and TES mn ,DDMV mn ,TDWD mn The same matrix form is maintained, and the matrix dimension changes with the significant wave height value and altitude angle range. The matrix dimension of each single observation field remains consistent. The significant wave height inversion model F of the combined multi-observation field is:

[0025]

[0026] LES represents the leading edge slope, TES represents the trailing edge slope, DDMV represents the delay Doppler spectrum volume, TDWD represents the mean value of the delay curve chip length, and m and n represent the dimensions of the matrix.

[0027] The present invention provides a shipborne GNSS-R significant wave height inversion method based on multiple observation fields, which has the following advantages:

[0028] The corrected multi-observation method accounts for the mutual influence between variables, eliminates observation instability caused by elevation angle, and reduces inversion errors. This method performs a joint matrix analysis on multiple observations, taking into account the influence of satellite elevation angle. The joint matrix reconstructed through dimensionality reduction achieves correction of the observed quantities. Using the corrected observations as independent variables, the established multivariate parameter model reduces the errors caused by individual observations and improves inversion accuracy. Applied to shipborne platforms, it can monitor the navigation environment in real time and achieve high-resolution detection, providing safety and technical support for intelligent ship navigation and maritime safety activities, improving my country's marine monitoring network, and possessing broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0030] Figure 1 This is the flow chart of multi-variable field shipborne GNSS-R significant wave height inversion;

[0031] Figure 2 The geometric diagram of the scattering area formed by the shipborne GNSS-R on the sea surface;

[0032] Figure 3 It is a scatter plot of the effective wave height inversion based on multiple observation fields. DETAILED DESCRIPTION

[0033] It should be noted that, unless there is any conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0034] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is in no way intended to limit the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0035] Figure 1 This is the flow chart of multi-variable field shipborne GNSS-R significant wave height inversion;

[0036] A shipborne GNSS-R significant wave height inversion method based on multiple observation fields includes the following steps:

[0037] S1: Obtain the real-time four-channel delay-Doppler spectrum data and significant wave height values ​​generated by the ship along the route;

[0038] The Delay Doppler Map (DDM) is the power distribution of the navigation satellite reflected signal mapped from space to the Delay Doppler domain.

[0039] S2: Preprocessing the real-time four-channel delay-Doppler spectrum data to obtain preprocessed four-channel delay-Doppler spectrum data;

[0040] S3: extracting observations that are dependent on the significant wave height based on the pre-processed delay-Doppler spectrum data;

[0041] S4: Based on 70% of the observation data, construct a significant wave height inversion model for multiple observation fields;

[0042] S5: Based on 30% of the observation data, an observation value sequence is extracted, and the observation value sequence is input into the effective wave height inversion model to obtain the effective wave height inversion value. At the same time, a corrected observation value sequence is obtained, and a multivariate parameter correction model is established for the corrected observation value sequence to realize the effective wave height inversion.

[0043] Steps S1 / S2 / S3 / S4 / S5 are performed sequentially;

[0044] By placing the receiver on board the ship, the real-time four-channel DDM data generated by the GNSS-R receiver and the effective wave height value of the radar wave meter along the route are collected. Figure 2 The shipborne GNSS-R creates a large scattering zone on the sea surface. Since the antenna installation height is related to the ship's height, the scattering zone is concentrated within a smaller delay chip interval, which contains the main information about the sea surface. Therefore, the delay chip interval for generating DDM is set to [-2, 3].

[0045] The quality of received signals is affected by many factors, including variations in satellite transmit power, atmospheric attenuation, multipath effects, and receiver sensitivity, all of which can cause signal distortion. Therefore, the acquired DDM data requires quality control. Low-quality delay-Doppler images that do not form an effective scattering zone are removed, as are frames where the peak power of the reflected signal is less than the noise floor. The delay curve is normalized using the direct signal power as a factor.

[0046] The observed quantities include the leading edge slope and the average value of the trailing edge slope of the normalized delay curve, as well as the delay window length, the delay Doppler spectrum volume and the satellite elevation angle.

[0047] The delay-Doppler spectrum volume is the integral of the power within the specified delay and Doppler interval centered on the mirror reflection point, and is calculated as follows:

[0048]

[0049] Where τ and f represent the delay chip and Doppler shift, and DDM(τ, f) represents the power at that point. The upper and lower limits of the delay integration region are -0.3069 chips and 0.3069 chips, respectively, and the upper and lower limits of the Doppler shift integration region are 100 Hz and -100 Hz, respectively.

[0050] The formulas for calculating the leading and trailing slopes are as follows. Since the effective wave height is related to the slope change, a single stage slope is difficult to characterize the changing relationship between the delay curve and the effective wave height. The leading and trailing slopes obtained from the five curves are averaged.

[0051]

[0052] Among them: LES is the leading edge slope, TES is the trailing edge slope;

[0053] Where τ i Indicates the sequential delay chip value, C W (τ i ) represents the corresponding curve waveform value; the number of selected points n = 3. In order to improve the correlation with the effective wave height, in this embodiment, the leading slope and the trailing slope adopt the average of the leading slope and the trailing slope of the five time delay curves with the Doppler frequency centered at 0.

[0054] The number of normalized delay curves is five, and the delay window length is also the average of the five delay curve chips. The average of the delay curve chip lengths is calculated as follows:

[0055] TDWD=τ right -τ left

[0056] Where: τ right Indicates the delay code value on the right side of the curve, τ left The threshold value set in the intercepted normalized delay curve is 0.85.

[0057] During shipborne experiments, the relative motion of the satellite and the ship causes the satellite's elevation angle to gradually and slightly change. This information can be directly obtained from the receiver, subject to the height and angle limitations of the shipborne experiment antenna. The multi-field matrix has an elevation angle range of 40°-80°, with a resolution of 0.1°.

[0058] The process of preprocessing the real-time four-channel DDM data to obtain the preprocessed four-channel DDM data is as follows:

[0059] Normalize the delay curves at different Doppler frequency shifts;

[0060] The effective wave height value obtained by the wave meter is annotated on the four-channel DDM of each frame. First, all NAN values ​​are removed. In addition, a standardized delay waveform is established and a threshold is selected to remove low-quality data. The threshold range is 0-1. The larger the threshold, the more data is removed. Therefore, the threshold selection is not a fixed value and needs to be adjusted according to the actual data situation.

[0061] Furthermore, a significant wave height inversion model of a multi-observation measurement field is constructed. The significant wave height of each frame of DDM is annotated and obtained based on the satellite elevation angle. The multi-observation measurement field includes multiple single observation measurement fields. The single observation measurement field includes each observation quantity and the corresponding elevation angle and significant wave height combination. The multi-observation measurement field is reconstructed by dimensionality reduction. In the process of constructing the multi-observation measurement field significant wave height inversion model, the matrix dimensions of each single observation measurement field remain consistent.

[0062] A single observation field can be represented by a matrix:

[0063]

[0064] In the matrix, each point represents the LES value at the effective wave height and satellite elevation angle, and TES mn ,DDMV mn ,TDWD mn The same matrix form is maintained, and the matrix dimension changes with the significant wave height value and altitude angle range. The matrix dimension of each single observation field remains consistent, and the combined multi-observation field F is:

[0065]

[0066] LES represents the leading edge slope, TES represents the trailing edge slope, DDMV represents the delay Doppler spectrum volume, TDWD represents the mean value of the delay curve chip length, and m and n represent the dimensions of the matrix;

[0067] By decomposing the combined multi-observation field, the main characteristic components of the matrix are extracted to reconstruct F, and then the corrected multi-observation field model is obtained. F can be expressed as:

[0068] F=ST

[0069] Where: S represents the coefficient matrix, T represents the eigenvector matrix

[0070] Each observation value is extracted from the given 30% DDM data. When a set of observation value sequences (LES, TES, DDMV, TDWD) is input into the reconstructed multi-observation matrix, the significant wave height inversion value of each single observation value is obtained. At the same time, the corrected observation value sequence is obtained. The multivariate parameter model of the corrected value sequence is established as follows:

[0071]

[0072] Where Obs i Represents the different observation values ​​after correction, a i represents the corresponding coefficient, and b is the constant term.

[0073] Figure 3 It is a scatter plot of the effective wave height inversion based on multiple observation fields.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A shipborne GNSS-R significant wave height inversion method based on multiple observation fields, characterized by: The following steps are involved: Obtain real-time four-channel delay-Doppler spectrum data and significant wave height values ​​generated along the ship's route; Preprocessing the real-time four-channel delay-Doppler spectrum data to obtain preprocessed four-channel delay-Doppler spectrum data; Extract the observation quantity that is dependent on the significant wave height from the pre-processed delay-Doppler spectrum data; Based on 70% of the observation data, a significant wave height inversion model for multiple observation fields is constructed; Based on 30% of the observation data, the observation value sequence is extracted and input into the significant wave height inversion model to obtain the significant wave height inversion value. At the same time, the corrected observation value sequence is obtained. A multivariate parameter correction model is established for the corrected observation value sequence to realize the significant wave height inversion.

2. The method for inverting significant wave height using shipborne GNSS-R based on multiple observation fields according to claim 1, characterized in that: The observed quantities include the leading edge slope and the average value of the trailing edge slope of the normalized delay curve, as well as the delay window length, the delay Doppler spectrum volume and the satellite elevation angle.

3. The method for inverting significant wave height using shipborne GNSS-R based on multiple observation fields according to claim 1, characterized in that: The process of preprocessing the real-time four-channel delay-Doppler spectrum data to obtain the preprocessed four-channel delay-Doppler spectrum data is as follows: Normalize the delay curves at different Doppler frequency shifts; The four-channel delay-Doppler spectrum data of each frame are annotated with the effective wave height value obtained by the wave meter. First, all NAN values ​​are removed. In addition, a standardized delay waveform is established and a threshold is selected to remove low-quality data.

4. The method for inverting significant wave height using shipborne GNSS-R based on multiple observation fields according to claim 2, characterized in that: The number of normalized delay curves is five, and the delay window length is also the average of the five delay curve chips. The average of the delay curve chip lengths is calculated as follows: In the formula and They represent the right and left delay chip values ​​intercepted in the curve respectively.

5. The method for inverting significant wave height using shipborne GNSS-R based on multiple observation fields according to claim 1, characterized in that: The multi-observation measurement field includes multiple single observation measurement fields, and the single observation measurement field includes each observation quantity and a corresponding altitude angle and effective wave height combination; the matrix dimensions of each single observation measurement field remain consistent.

6. The method for inverting significant wave height using shipborne GNSS-R based on multiple observation fields according to claim 2, characterized in that: The satellite elevation angle range is 40°-80°, and the resolution is 0.1°.

7. The method for inverting significant wave height using shipborne GNSS-R based on multiple observation fields according to claim 1, characterized in that: The expression of the multivariate parameter correction model is as follows: Where: Represents different observation values, represents the corresponding coefficient, is a constant term.

8. The method for inverting significant wave height using shipborne GNSS-R based on multiple observation fields according to claim 1, characterized in that: Based on 70% of the observation data, the process of constructing the effective wave height inversion model of multiple observation fields is as follows: The single observation field is represented by a matrix: In the matrix, each point represents the effective wave height and satellite elevation angle. LES value, The same matrix form is maintained, and the matrix dimension changes with the significant wave height value and altitude angle range. The matrix dimension of each single observation field remains consistent. The significant wave height inversion model F of the combined multi-observation field is: LES represents the leading edge slope, TES represents the trailing slope, DDMV represents the volume of the delay-Doppler spectrum, TDWD represents the mean value of the chip length of the delay curve, m, n Represents the dimension of the matrix.

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