CN111781617A - Specular reflection point estimation method based on double-basis scattering vector sea surface elevation model - Google Patents
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Abstract
The invention relates to a method for estimating specular reflection points based on a bistatic scattering vector sea surface elevation model, which comprises the following steps: inputting the position of the receiver, the position of the GNSS satellite and the sea surface height of the DTU10, and outputting the position of the specular reflection point. Based on the steepest gradient descent algorithm and the signal shortest transmission path theory, the position of the specular reflection point is estimated by finding the specular reflection point in the direction of steepest gradient descent and enabling the specular reflection point to meet the requirement of the shortest transmission path of the reflected signal.
Description
Technical Field
The invention relates to a satellite-borne GNSS-R mirror reflection point estimation method, in particular to a satellite-borne GNSS-R mirror reflection point estimation method which carries out iterative calculation by using a steepest gradient descent algorithm of a double-base scattering vector and adds a DTU10 sea surface digital elevation model for calibration.
Background
The method for carrying out ocean remote sensing by utilizing GNSS reflected signals is one of novel technologies of satellite remote sensing technology, and has the advantages of multiple information sources, light weight, spread spectrum processing, wide application range and the like. The GNSS-R (Global Navigation Satellite System-Reflected) technology receives a GNSS direct signal and an echo signal scattered by a reflecting surface by adopting shore-based, airborne and no-load special receiving equipment, obtains two-dimensional related power of the Reflected signal corresponding to a delay Doppler unit in the reflecting surface by cooperative processing, and then obtains physical parameter information of a scattering surface on the earth surface by a certain inversion method.
The uncertainty of the time delay and the Doppler frequency shift of the reflected signal received by the GNSS-R receiver is large, and the reflected signal can be quickly tracked by a method of predetermining the time delay and the Doppler frequency shift. And estimating a mirror reflection point in real time in the GNSS-R receiver according to the navigation ephemeris file and the navigation positioning solution of the receiver to obtain a delay range and a Doppler range of a blaze region, thereby greatly reducing the search range and the tracking time of signals.
Disclosure of Invention
The invention aims to: the satellite-borne GNSS-R specular reflection point estimation method is provided, and the algorithm can be used for estimating the position information of the specular reflection point more accurately. According to the method, the position of the specular reflection point is more accurately estimated by utilizing the position of a receiver, the position of a GNSS satellite and the sea surface height of the DTU10 through an iterative algorithm of steepest gradient descent and the thought of the shortest signal transmission path.
The technical scheme of the invention is as follows: a specular reflection point estimation method based on a double-base scattering vector sea surface elevation model comprises the steps of inputting a receiver position, a GNSS satellite position and a DTU10 sea surface height, and outputting a specular reflection point position. Based on the steepest gradient descent algorithm and the signal shortest transmission path theory, the position of the specular reflection point is estimated by finding the specular reflection point in the direction of steepest gradient descent so as to meet the method that the transmission path of the reflection signal is shortest. The method specifically comprises the following steps:
Wherein r (theta) returns the radius of the earth at the latitude theta in the WGS84 coordinate system; rzIs the projection length of the receiver position vector on the Z axis of the WGS84 coordinate system;
step 2, calculating a bibase scattering vector q (S) by adopting a parameter calculation module A2 according to the position information of the input module A11) And the normal vector n (S)1) (ii) a Selecting dot product method to establish proper gradient function, and calculating to obtain gradientCorrecting the empirical gain K to the direction of the steepest gradient to obtain a next temporary point S ', and mapping the temporary point S' to a WGS84 coordinate system to obtain an estimated point Sn+1The steps of calculating the parameters are as follows:
wherein n is 1,2,3 …, which is the number of iterations;andnormalized biradical scattering vector and normal vector, respectively; s'zIs the projection length of the temporary specular reflection point S' vector on the Z axis of the WGS84 coordinate system;
step 3, adopting a decision module A3 to decide whether to stop iteration according to the corrected amplitude, stopping iteration when the amplitude is smaller than a preset threshold value to obtain a mirror surface estimation point S meeting the condition, and otherwise, judging Sn+1Inputting the data into a parameter calculation module A2 for the next iteration; using unconstrained correctionProjecting the current estimation point on a tangent plane of the surface of the current estimation point, and then performing iteration to reduce the iteration times;
step 4, receiving the mirror surface estimation point S obtained in the last step and an initialized DTU10 sea surface digital elevation model by adopting an input module B1;
step 6, adopting a decision module B3 to find out a point in the grid with the minimum reflection path length; this grid point becomes the new mirror point position estimate and this point is input to the parameter calculation module B2 for the next iteration.
Further, by the fermat' S theorem, the estimation of the specular reflection point is regarded as an optimization problem for solving the shortest reflection transmission path, and the specular reflection point S is solved so that the reflection transmission path f (S) is the smallest.
Furthermore, according to Snell's law, the condition that the biradical scattering vector and the curved surface normal are collinear at the mirror surface point is utilized, the earth does not need to be approximated to be a sphere, and the objective function and the constraint function are obtained based on the steepest gradient descent algorithm.
Furthermore, by using the formula (1.2) and adopting a unit difference method to improve the gradient function, the problems that the gradient calculation process of a dot product method and a cross product method is complex and is easily influenced by calculation errors (such as rounding) are solved; at the point of specular reflectionNormalized scattering vectorAnd the normal vectorIs 0, andis directed in the direction of the specular reflection point, resulting in the gradient function definition described above.
Has the advantages that:
compared with the prior art, the invention has the advantages that:
1. the iteration times are few, and compared with a shortest path optimization algorithm and an inscribed sphere method, the iteration times of the algorithm are reduced by about 50%, and the convergence speed is high;
2. the operation time is short, the algorithm of the invention has no complex operation, and the consumed operation resources are less;
3. the precision of the mirror reflection point estimation value is high, the estimation precision of the mirror reflection point of the algorithm is closer to the precision of the shortest path optimization algorithm, and the estimation precision is high.
Drawings
FIG. 1 is a schematic diagram of a geometry relationship of a satellite-borne GNSS-R system;
FIG. 2 is a schematic representation of the geometry of the reflected signal at the surface of the sea;
FIG. 3 is a flowchart of a GNSS-R specular reflection point estimation method based on a bistatic scattering vector and a DTU10 sea surface digital elevation model;
FIG. 4 is the DTU10 average sea height for specular reflection point estimation;
FIG. 5 is a comparison of the results of three methods of estimating specular reflection points;
fig. 6 is a schematic diagram of the positions of the specular reflection estimation points in the delay-doppler domain before and after the DTU10 sea digital elevation model is added.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments, and all other embodiments obtained by a person skilled in the art based on the embodiments of the present invention belong to the protection scope of the present invention without creative efforts.
Referring to fig. 1, a geometric relationship of a satellite-borne GNSS-R system is shown, where T, R, and SP are vector positions of a GNSS satellite, a satellite-borne platform carrying a receiver, and a specular reflection point, respectively; r is the earth radius, theta is the incident angle, ht and hr are the heights of the GNSS satellite and the satellite-borne platform from the earth surface, respectively, and di and dr are the path lengths of the GNSS satellite and the satellite-borne platform to the specular reflection point, respectively.
Referring to fig. 2, a schematic diagram of a geometric relationship of a reflection signal on the sea surface, coordinate vectors of a GNSS satellite, a satellite-borne platform, and a reflection point are respectively: t, R and S. Let the coordinates of the reflection point S be (x, y, ζ), where ζ ═ ξ (x, y) is the sea surface height variable that changes randomly, and its corresponding horizontal position vector r ═ x, y.
Referring to fig. 3, the system of the present invention mainly includes an input module a1, a parameter calculation module a2, a decision module A3, an input module B1, a parameter calculation module B2, and a decision module B3;
the initial input of the invention is the position of the reflected signal receiver, the position of the GNSS satellite and the sea level height digital elevation model of DTU10, and the final output is the position of the mirror reflection point in the GNSS-R geometric relationship.
The functions of the modules are explained in detail below:
1. the input module A1 calculates an initial specular reflection point estimate S based on receiver position information R and GNSS-R satellite position information T and on a projected point on the earth1。
2. The parameter calculation module A2 calculates the bibase scattering vector q (S) and the normal vector n (S) according to the position information of the input module A1. Selecting dot product method to buildThe gradient function of (2), calculating the obtained gradientCorrecting the empirical gain K to the direction of the steepest gradient to obtain a next temporary point S', and mapping the temporary point to a WGS84 coordinate system to obtain an estimated point Sn+1The steps of calculating the parameters are as follows:
wherein the content of the first and second substances,andnormalized scatter vector and normal vector, respectively.
3. The decision module A3 decides whether to stop the iteration according to the corrected amplitude, stops the iteration when the amplitude is less than a certain threshold value, and otherwise, stops the iteration Sn+1Input to the parameter calculation module a2 for the next iteration. Using unconstrained correctionThe iteration is carried out after the projection is carried out on the tangent plane of the surface of the current estimation point, so that the iteration times can be greatly reduced.
4. The input module B1 receives the specular estimation points S obtained in the previous step and the initialized DTU10 sea surface digital elevation model.
5. The parameter calculation module B2 constructs a large three-dimensional grid of points around the estimated specular reflection points. The grid has uniform latitude and longitude spacing and is conformal to the WGS84 ellipsoid at each point. At each grid point, the 1 ° resolution DTU10 data is bilinearly interpolated to find the height value for each grid point, replacing the original height with the sea level height of DTU 10. The reflection path length f(s) of each grid point is calculated.
6. Decision block B3, find the point in the grid with the smallest reflection path length. This grid point becomes the new mirror point position estimate and this point is input to the parameter calculation module B2 for the next iteration.
According to another aspect of the present invention, based on the above system, there is also provided a specular reflection point estimation method based on a bistatic scattering vector sea surface elevation model, including the following steps:
Wherein r (theta) returns the radius of the earth at the latitude theta in the WGS84 coordinate system; rzIs the projection length of the receiver position vector on the Z axis of the WGS84 coordinate system;
step 2, calculating a bibase scattering vector q (S) by adopting a parameter calculation module A2 according to the position information of the input module A11) And the normal vector n (S)1) (ii) a Selecting dot product method to establish proper gradient function, and calculating to obtain gradientCorrecting the empirical gain K to the direction of the steepest gradient to obtain a next temporary point S ', and mapping the temporary point S' to a WGS84 coordinate system to obtain an estimated point Sn+1The steps of calculating the parameters are as follows:
wherein n is 1,2,3 …, which is the number of iterations;andnormalized biradical scattering vector and normal vector, respectively; s'zIs the projection length of the temporary specular reflection point S' vector on the Z axis of the WGS84 coordinate system;
step 3, adopting a decision module A3 to decide whether to stop iteration according to the corrected amplitude, stopping iteration when the amplitude is smaller than a preset threshold value to obtain a mirror surface estimation point S meeting the condition, and otherwise, judging Sn+1Inputting the data into a parameter calculation module A2 for the next iteration; using unconstrained correctionProjecting the current estimation point on a tangent plane of the surface of the current estimation point, and then performing iteration to reduce the iteration times;
step 4, receiving the mirror surface estimation point S obtained in the last step and an initialized DTU10 sea surface digital elevation model by adopting an input module B1;
step 6, adopting a decision module B3 to find out a point in the grid with the minimum reflection path length; this grid point becomes the new mirror point position estimate and this point is input to the parameter calculation module B2 for the next iteration.
Referring to fig. 4, for the DTU10 average sea level height for specular reflection point estimation, DTU10 is a sea average sea level height dataset provided by the national space agency in denmark.
Referring to fig. 5, a comparison graph of operation results of the three methods for estimating the specular reflection points shows that the coordinate distances of the specular reflection points calculated by the three methods are all within 5 km. From the aspect of running time, the estimation algorithm of the inscribed sphere is more complex, so the running time is longest, and the scattering vector method adopts a unit difference method to establish a simpler gradient function, so the running time is shortest; from the aspect of iteration times, the scattering vector method has the minimum iteration times. The scattering vector method is proved to have higher calculation efficiency.
Referring to fig. 6, a schematic diagram of the positions of the specular reflection estimation points in the delay-doppler domain before and after adding the DTU10 sea digital elevation model is shown, wherein the symbols: gamma was the result before DYU10 addition and □ was the result after DTU10 addition.
Although illustrative embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the embodiments, but various changes may be apparent to those skilled in the art, and it is intended that all inventive concepts utilizing the inventive concepts set forth herein be protected without departing from the spirit and scope of the present invention as defined and limited by the appended claims.
Claims (4)
1. A specular reflection point estimation method based on a double-basis scattering vector sea surface elevation model is characterized by comprising the following steps:
step 1, receiving receiver position information R and GNSS-R satellite position information T by adopting an input module A1, and calculating initial specular reflection point estimation S according to a projection point on the earth1;
Wherein r (theta) returns the radius of the earth at the latitude theta in the WGS84 coordinate system; rzIs the projection length of the receiver position vector on the Z axis of the WGS84 coordinate system;
step 2, calculating a bibase scattering vector q (S) by adopting a parameter calculation module A2 according to the position information of the input module A11) And the normal vector n (S)1) Selecting dot product method to establish proper gradient function, calculating to obtain gradient ▽ f (S)1) Correcting to obtain a next temporary point S 'according to the empirical gain K in the direction of the steepest gradient descending, and mapping the temporary point S' to a WGS84 coordinate system to obtain an estimated point Sn+1The steps of calculating the parameters are as follows:
S'=Sn-K▽f(Sn) (0.3)
wherein n is 1,2,3 …, which is the number of iterations;andnormalized biradical scattering vector and normal vector, respectively; s'zIs the projection length of the temporary specular reflection point S' vector on the Z axis of the WGS84 coordinate system;
step 3, adopting a decision module A3 to decide whether to stop iteration according to the corrected amplitude, stopping iteration when the amplitude is smaller than a preset threshold value to obtain a mirror surface estimation point S meeting the condition, and otherwise, judging Sn+1Inputting to a parameter calculation module A2 for next iteration, and performing unconstrained correction K ▽ f (S)n) Projecting the current estimation point on a tangent plane of the surface of the current estimation point, and then performing iteration to reduce the iteration times;
step 4, receiving the mirror surface estimation point S obtained in the last step and an initialized DTU10 sea surface digital elevation model by adopting an input module B1;
step 5, constructing a three-dimensional point grid around the estimated specular reflection point by adopting a parameter calculation module B2; the grid has uniform latitude and longitude spacing and is conformal to the WGS84 ellipsoid at each three-dimensional point; at each grid point, carrying out bilinear interpolation on DTU10 data with the resolution of 1 degree to find the height value of each grid point, and replacing the original height with the sea surface height of DTU 10; calculating a reflection path length f(s) of each grid point;
step 6, adopting a decision module B3 to find out a point in the grid with the minimum reflection path length; this grid point becomes the new mirror point position estimate and this point is input to the parameter calculation module B2 for the next iteration.
2. The method for estimating specular reflection points based on the bistatic scattering vector sea surface elevation model according to claim 1, wherein the method comprises the following steps:
by using Fermat' S theorem, the estimation of the specular reflection point is regarded as an optimization problem for solving the shortest reflection transmission path, and the reflection transmission path f (S) is minimized by solving the specular reflection point S.
3. The method for estimating specular reflection points based on the bistatic scattering vector sea surface elevation model according to claim 1, wherein the method comprises the following steps:
according to the Snell's law, the objective function and the constraint function are obtained based on the steepest gradient descent algorithm by utilizing the condition that the biradical scattering vector and the curved surface normal are collinear at the mirror surface point without approximating the earth as a sphere.
4. The method for estimating specular reflection points based on the bistatic scattering vector sea surface elevation model according to claim 1, wherein the method comprises the following steps:
the gradient function is improved by using a formula (1.2) and a unit difference method, and gradient calculation of a dot product method and a cross product method is avoidedThe process is complicated; normalized scattering vector at specular reflection pointAnd the normal vectorIs 0, andis directed in the direction of the specular reflection point, resulting in the gradient function definition described above.
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