Low-orbit satellite positioning and tracking method for high-dynamic object

Abstract

The invention discloses a low-orbit satellite positioning and tracking method for a high-dynamic object, and belongs to the technical field of low-orbit satellite communication, and the method comprises the steps: scanning any beam position; receiving a first feedback signal of the beam position, and determining a signal-to-noise ratio of a beam signal; when the signal-to-noise ratio is greater than a first preset signal-to-noise ratio, generating a plurality of sub-beam bits; receiving second feedback signals of a plurality of sub-beam positions, and determining a signal-to-noise ratio of the sub-beam signals; when the signal-to-noise ratio is greater than a second preset signal-to-noise ratio, repeating the steps until the coverage radius is reduced to preset precision; reading the position information of the coverage radius meeting the preset precision, wherein the position information is the position information of the moving object; inputting the position information into a preset prediction model to obtain a predicted spot beam position; and realizing data transmission between the satellite and the moving object by using the predicted spot beam position. According to the method, the user does not need to report the position of the user, cooperation of multiple satellites is not needed, complexity is reduced, and the method is simple and easy to implement.

Description

Technical Field

[0001] The present invention belongs to the technical field of low-orbit satellite communications, and in particular relates to a low-orbit satellite positioning and tracking method for high-dynamic objects. Background Art

[0002] In LEO (low-orbit) satellite systems, it is very challenging to achieve high-dynamic object positioning and beam tracking. Among the related technologies, there are two major types of high-dynamic object tracking, positioning and communication methods suitable for LEO (low-orbit) satellite systems. One type of cyclic scanning positioning method imitates radar detection, which controls the antenna to point to the predetermined airspace through the antenna mechanical axis control unit (ACU) according to the trajectory or guidance data, and then cyclically scans the target area through a wide beam, while using fast FFT to search for target signals. However, this type of method has poor weak signal detection capabilities and is difficult to adapt to satellite communication scenarios. In addition, the wide beam antenna used to track highly dynamic users makes the positioning accuracy poor, making it difficult to meet the needs of stable and efficient communication.

[0003] Another type of solution uses a positioning method based on angle of arrival (DOA) / time difference of arrival (TDOA). By obtaining the DOA / TDOA values ​​of two or more different satellites receiving the same user signal, and then using the measured time difference and measured angle to establish a nonlinear equation about the target source position, the target source position can be effectively estimated by solving the relevant equation. However, this positioning solution is more complicated and requires the participation of multiple satellites at the same time, making users more vulnerable to eavesdropping and difficult to meet user privacy needs.

[0004] Therefore, there is an urgent need to propose a simpler, more feasible and more stable method to achieve the positioning and tracking of high-dynamic objects. Summary of the invention

[0005] In view of this, an object of the present invention is to provide a low-orbit satellite positioning and tracking method for high-dynamic objects, so as to meet the positioning and tracking requirements of high-dynamic objects in a simpler, more feasible and more stable manner.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] According to a first aspect, the present invention provides a low-orbit satellite positioning and tracking method for high-dynamic objects, comprising: scanning any beam position, the number of beam positions is predetermined according to the spot beam size and arrangement mode; receiving a first feedback signal of the beam position, and determining the signal-to-noise ratio of the beam signal; when the signal-to-noise ratio of any beam signal is greater than a first preset signal-to-noise ratio, generating multiple sub-beam positions, each sub-beam position radius is less than the beam position radius, and the overlapping coverage range of the multiple sub-beam positions fully or partially covers the range of the beam position; receiving a second feedback signal of the multiple sub-beam positions, and determining the signal-to-noise ratio of the sub-beam signal; when the signal-to-noise ratio of any one of the multiple sub-beam signals is greater than the second preset signal-to-noise ratio, repeating the steps of generating multiple sub-beam positions to receiving the second feedback signals of the multiple sub-beam positions, and determining the signal-to-noise ratio of the sub-beam signal, until the coverage radius is reduced to a preset accuracy threshold; reading the location information of the coverage radius that meets the preset accuracy threshold, the location information is the location information of the moving object; inputting the location information into a preset prediction model to obtain a predicted spot beam position; and using the predicted spot beam position to realize data transmission between the satellite and the moving object.

[0008] Optionally, the first preset signal-to-noise ratio determination method includes: obtaining an angle between the farthest point of the outer contour of the circle corresponding to the beam radius and a line connecting the satellite projection point and the satellite, and a distance between the satellite and the farthest point of the outer contour of the circle corresponding to the beam radius;

[0009] A first preset signal-to-noise ratio is obtained according to the angle and the distance.

[0010] Optionally, obtaining a first preset signal-to-noise ratio according to the angle and the distance includes:

[0011]

[0012] Among them, P t is the satellite's transmission power, N0 is the noise power spectrum density, W is the bandwidth, G D represents the user antenna receiving gain, h l (d) is the path loss, c is the speed of light, and f d represents the frequency of the transmitted signal, and d represents the distance between the satellite and the farthest point of the outer contour of the circle corresponding to the beam radius; Among them, Δθ represents the angle between the farthest point of the outer contour of the circle corresponding to the beam radius and the line connecting the satellite projection point and the satellite, θ 3dB Indicates the 3dB beamwidth of the satellite spot beam, Indicates the maximum gain of the satellite antenna, L s =-6.75, L F =0, Y = 1.5θ 3dB ,

[0013] Optionally, the method further comprises: when position information of multiple moving objects is detected, using an optimization algorithm to obtain a maximized total transmission rate; the optimization algorithm is:

[0014]

[0015] sqF max ≥R≥0

[0016]

[0017] Where R(n) represents the total transmission rate; Among them, the logarithmic prefactor Characterizes the resources or system overhead consumed by beam tracking and link maintenance, while It represents the consumption caused by communication delay in each beam hopping, T delay =H / c represents the transmission delay caused by a single beam hop, where c is the speed of light and H represents the height difference between the satellite projection point and the satellite. It represents the probability of continuous communication without interruption, and the logarithmic part represents the expected maximum transmission rate of the user after secondary positioning with an accuracy of r0; r0 represents the radius that meets the accuracy requirement; Δt represents the time interval of a single beam hop of the moving object; R max V represents the distance corresponding to the off-axis angle at which the satellite spot beam can identify the minimum signal-to-noise ratio of the user signal. max represents the maximum relative speed between the user and the satellite, t min Indicates the beam hopping time interval corresponding to the maximum beam hopping frequency.

[0018] Optionally, the position information is input into a preset prediction model to obtain a predicted spot beam position, including:

[0019] The location information is input into a preset prediction model, where the prediction model is a kernel function fitted according to the historical movement trajectory, and the kernel function is a covariance function;

[0020] The horizontal and vertical coordinates of the predicted point beam position are obtained according to the kernel function.

[0021] Optionally, the abscissa and ordinate of the predicted spot beam position are obtained according to the kernel function, including:

[0022]

[0023] Among them, k * is the covariance vector between the test points and the training points, σ f is the standard deviation of the position feedback noise, x Tr is the horizontal coordinate vector of the training sequence; Tr is the ordinate vector of the training sequence; The ordinate representing the predicted spot beam position; The horizontal coordinate representing the predicted spot beam position.

[0024] Optionally, after the position information is input into a preset prediction model to obtain the predicted point beam position, before using the predicted point beam position to realize data transmission between the satellite and the moving object, it includes: determining whether the predicted point beam position is accurate based on whether the moving object is within the predicted point beam position range during the communication process; if it is inaccurate, correcting the predicted point beam position.

[0025] According to a second aspect, an embodiment of the present invention provides a low-orbit satellite positioning and tracking device for high-dynamic objects, including: a scanning module, used to scan any beam position, the number of beam positions is predetermined according to the point beam size and arrangement; a first signal-to-noise ratio determination module, used to receive a first feedback signal of the beam position, and determine the signal-to-noise ratio of the beam signal; a first signal-to-noise ratio comparison module, used to generate a plurality of sub-beam positions when the signal-to-noise ratio of any beam signal is greater than a first preset signal-to-noise ratio, the radius of each sub-beam position is smaller than the radius of the beam position, and the range covered by the superposition of the plurality of sub-beam positions fully or partially covers the range of the beam position; a second signal-to-noise ratio determination module, used to receive a first feedback signal of the sub-beam position, and determine the signal-to-noise ratio of the beam signal; a second feedback signal to determine the signal-to-noise ratio of the sub-beam signal; a second signal-to-noise ratio comparison module, which is used to repeat the step of generating multiple sub-beam positions to receiving the second feedback signal of multiple sub-beam positions when the signal-to-noise ratio of the sub-beam signal is greater than a second preset signal-to-noise ratio, and to determine the signal-to-noise ratio step of the sub-beam signal until the coverage radius is reduced to a preset accuracy threshold; a position determination module, which is used to read the position information of the coverage radius that meets the preset accuracy threshold, the position information being the position information of the moving object; a position prediction module, which is used to input the position information into a preset prediction model to obtain a predicted point beam position; a data transmission module, which is used to complete data transmission with the moving object using the beam at the predicted point beam position.

[0026] The method scans multiple beam positions and determines the signal-to-noise ratio based on the feedback signal. It determines whether there is an object within the radiation range of the beam position based on the signal-to-noise ratio and the preset signal-to-noise ratio. If there is an object, the range is narrowed and the steps are repeated until a position that meets the accuracy requirements is obtained. The position is the position of the object and the position is input into the prediction model to estimate the next movement position of the object. Communication is performed according to the estimated position. In this solution, on the basis of ensuring that high-quality communication services can be provided for highly dynamic objects in satellite communication scenarios, the user does not need to report his own position and multiple satellites do not need to cooperate, which reduces complexity and makes the solution simple and easy.

[0027] Other advantages, objectives and features of the present invention will be described in the following description and will be apparent to those skilled in the art to some extent, or those skilled in the art may be taught from the practice of the present invention. The objectives and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to make the purpose, technical solution and beneficial effects of the present invention clearer, the present invention provides the following drawings for illustration:

[0029] Figure 1 A schematic diagram of a satellite communication system composed of a multi-beam LEO satellite and a plurality of high-dynamic objects in the present invention;

[0030] Figure 2 A specific example flow chart of a low-orbit satellite positioning and tracking method for a high-dynamic object according to the present invention;

[0031] Figure 3 It is a schematic diagram of a communication system consisting of a user 1 and a satellite in a beam 1 in the present invention;

[0032] Figure 4 A schematic diagram of a communication system formed with a satellite when a user is located at the farthest point of the outer contour of a circle corresponding to the beam radius in the present invention; DETAILED DESCRIPTION

[0033] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, it can also be the internal connection of two components, it can be a wireless connection, or it can be a wired connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0035] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0036] This method establishes a satellite communication system consisting of a multi-beam LEO satellite and multiple high-dynamic objects, such as Figure 1As shown, the high dynamic object can be a high dynamic moving user, such as a drone. The LEO satellite is equipped with an onboard transceiver, so it can transmit data packets to the user through a service link.

[0037] Assuming that all users are distributed in the LEO satellite coverage area with an orbital height of H, their positions are projected into the same plane, which is approximately a circular plane S with a radius of R0, where H represents the height difference between the satellite projection point and the satellite. In order to improve data transmission capabilities, the satellite supports multiple spot beams, each of which covers a certain area, and the maximum coverage area radius of the spot beam is R max In the absence of prior information, the probability distribution of the target can be considered Obey the angle space S = πR0 2 The distribution in the middle is subject to strength λ and the safety distance is d safe Poisson hard-core process (PHCP), the number of users satisfies Its mean satisfies Assume that the location of user i at time t is i=1,2,...,N, then the azimuth and elevation angles of the beam at the point where user i is at time t are and The corresponding beam center position of user i at time t is

[0038] Assume that in the LEO network, each user moves according to his own trajectory. Therefore, in the 2D space, user u i The motion model at time slot n can be described as:

[0039]

[0040] in Represents user u i At the position of time slot n, v i (n) represents user u i The speed at time slot n, a i (n) represents user u i The acceleration at time slot n, Δt, represents the beam hopping time interval during the satellite detection phase. For highly dynamic objects, the position information changes very quickly, which poses a great challenge to positioning and tracking. Therefore, a solution is needed to solve the problem of user rapid positioning and continuous tracking.

[0041] In order to meet the requirements of simple, feasible and highly stable positioning and tracking of highly dynamic objects, the present invention provides a low-orbit satellite positioning and tracking method for highly dynamic objects, such as Figure 2 As shown, the method includes:

[0042] S101, scanning any beam position, the number of beam positions is predetermined according to the spot beam size and arrangement;

[0043] Exemplarily, in order to improve data transmission capability, the satellite supports multiple spot beams, each spot beam covers a certain area, and this solution uses a cyclic scanning method to scan all beam positions.

[0044] The LEO satellite coverage area is a connected coverage area, such as the S area mentioned above, which requires multiple spot beams (such as Figure 1 The coverage area can only be completely covered by beams 1, 2, 3...N in the coverage area. Therefore, it is necessary to first determine the number of spot beams according to the beam size and arrangement, and generate multiple beam positions. The number of spot beams is Where η is the equivalent coverage factor, R0 is the radius of the LEO satellite coverage area, and R is the radius of the beam position. The corresponding K point beam center angles are k=1,2,...,K.

[0045] S103, receiving a first feedback signal of a beam position, and determining a signal-to-noise ratio of the beam signal;

[0046] Exemplarily, the first feedback signal is a signal received by the satellite at the beam position. According to the first feedback signal, the signal-to-noise ratio of the beam signal can be determined by calculating the signal-to-noise ratio of the signal according to the signal strength of the first feedback signal. The method of calculating the signal-to-noise ratio by signal strength is common knowledge in the art and will not be described in detail here.

[0047] S105, determining whether the signal-to-noise ratio of the beam signal is greater than a first preset signal-to-noise ratio; when the signal-to-noise ratio of the beam signal is greater than the first preset signal-to-noise ratio, executing step S107, otherwise, executing step S109;

[0048] S107, generating multiple sub-beam positions, wherein the radius of each sub-beam position is smaller than the radius of the beam position, and the overlapping coverage of the multiple sub-beam positions fully or partially covers the range of the beam position;

[0049] S109, scanning the next beam position.

[0050] Exemplarily, the first preset signal-to-noise ratio represents the minimum signal-to-noise ratio for the existence of users within the coverage range of the spot beam, that is, when the signal-to-noise ratio of the beam signal is greater than the first preset signal-to-noise ratio, it indicates that there are users within the current spot beam coverage range; when the signal-to-noise ratio of the beam signal is less than the first preset signal-to-noise ratio, it indicates that there are no users within the current beam coverage range.

[0051] The first preset signal-to-noise ratio may be calculated in advance based on the relationship between the signal-to-noise ratio and the coverage range of the current spot beam, or may be obtained based on the experience of those skilled in the art, and this is not limited in this embodiment. The specific method for determining the first preset signal-to-noise ratio may be to pre-associate the signal-to-noise ratio thresholds of the spot beam in different coverage ranges with the radius corresponding to the coverage range, and store them in a table. When the signal-to-noise ratio of the beam signal is determined based on the first feedback signal, the signal-to-noise ratio threshold of the radius covered by the beam signal is queried in the table by looking up the table, and the signal-to-noise ratio threshold is used as the first preset signal-to-noise ratio. This embodiment does not limit the method for determining the first preset signal-to-noise ratio, and those skilled in the art may determine it as needed.

[0052] When the signal-to-noise ratio of the beam signal is greater than the first preset signal-to-noise ratio, it indicates that there is a user within the coverage range of the beam. In order to further accurately determine the specific location of the user, the beam position needs to be divided into smaller beam positions. Therefore, the satellite generates multiple sub-beam positions within the beam position, and the overlapping coverage range of the multiple sub-beam positions fully or partially covers the range of the beam position.

[0053] The method of generating multiple sub-beam positions is to project three spot beams evenly distributed at 120° from the center of the current beam position at a distance r, and the location of the spot beam is called the sub-beam position. This is equivalent to using the radius as the beam coverage radius of the beam position. The existing beam coverage is divided into three equal parts by a circle, and the corresponding three sub-beams have beam center angles of i=1,2,3.

[0054] When the signal-to-noise ratio of the beam signal is not greater than the first preset signal-to-noise ratio, the current beam position scanning is terminated and the next beam position is scanned.

[0055] S111, receiving second feedback signals of a plurality of sub-beam positions, and determining a signal-to-noise ratio of the sub-beam signal;

[0056] Exemplarily, the sub-beam signal signal-to-noise ratio may be calculated by the signal strength of the second feedback signal. Calculating the signal-to-noise ratio by signal strength is common knowledge in the art and will not be described in detail herein. The method for receiving the second feedback signal of multiple sub-beam positions may be by cyclically scanning the multiple sub-beam positions or by parallel scanning. This embodiment does not limit this and those skilled in the art may determine it as needed.

[0057] S113, determining whether the signal-to-noise ratio of any one of the multiple sub-beam signals is greater than a second preset signal-to-noise ratio; if the signal-to-noise ratio of any one of the multiple sub-beam signals is greater than the second preset signal-to-noise ratio, executing step S115, otherwise, executing step S109;

[0058] S115, determine whether the sub-beam coverage radius is reduced to the preset accuracy threshold; when the sub-beam coverage radius is reduced to the preset accuracy threshold, execute step S117; otherwise, execute step S107 to further reduce the range within this sub-beam coverage radius to achieve further precise positioning.

[0059] Exemplarily, the second preset signal-to-noise ratio represents the minimum signal-to-noise ratio for a user to exist within the coverage range of the sub-beam position, that is, when the signal-to-noise ratio of the sub-beam signal is greater than the second preset signal-to-noise ratio, it indicates that there is a user within the coverage range of the current sub-beam position; when the signal-to-noise ratio of the sub-beam signal is less than the second preset signal-to-noise ratio, it indicates that there is no user within the coverage range of the current sub-beam position.

[0060] The second preset signal-to-noise ratio may be calculated in advance based on the relationship between the signal-to-noise ratio and the coverage of the current sub-beam, or may be obtained based on the experience of a person skilled in the art, and this embodiment does not limit this. The specific method for determining the second preset signal-to-noise ratio is consistent with the method for determining the first preset signal-to-noise ratio, please refer to the description of step S105, which will not be repeated here.

[0061] When the signal-to-noise ratio of the sub-beam signal is greater than the second preset signal-to-noise ratio, it indicates that there is a user within the coverage range of the sub-beam. In order to further reduce the range where the user may exist, if the coverage range accuracy of the sub-beam does not reach the preset accuracy threshold, the sub-beam needs to be split to generate multiple beams, and the signal-to-noise ratio of the generated beam and the preset signal-to-noise ratio are repeatedly determined until the coverage range accuracy of the beam reaches the preset accuracy threshold. The preset accuracy threshold can be determined by those skilled in the art as needed, and this embodiment does not limit it.

[0062] When multiple sub-beam positions are generated by projecting three spot beams evenly spaced 120° apart from each other at a distance r from the center of the current beam position, this precise positioning process takes time Δt represents the beam hopping time interval during the satellite detection phase, r0 is the preset accuracy threshold, that is, the radius that meets the accuracy requirement, R is the radius of the beam position, and h represents the channel gain.

[0063] S117, reading the location information of the coverage radius that meets the preset accuracy threshold, where the location information is the location information of the moving object;

[0064] S119, inputting the position information into a preset prediction model to obtain a predicted spot beam position;

[0065] Exemplarily, the preset prediction model can be a Gaussian process based machine learning (GPML) model, or it can be a prediction model established based on a maximum likelihood (ML) estimator, a Kalman filter, and an echo signal. This embodiment does not limit the preset prediction model, and technicians in this field can determine it as needed.

[0066] S121, using the predicted spot beam position to achieve data transmission between the satellite and the moving object.

[0067] The method scans multiple beam positions and determines the signal-to-noise ratio according to the feedback signal, and judges whether there is an object within the radiation range of the beam position according to the size of the signal-to-noise ratio and the preset signal-to-noise ratio. If there is an object, the range is narrowed, and the steps are repeated until a position that meets the accuracy requirements is obtained. The position is the position of the object, and the position is input into the prediction model to estimate the next movement position of the object, and communicate according to the estimated position. In this solution, on the basis of ensuring that high-quality communication services can be provided for highly dynamic objects in satellite communication scenarios, users do not need to report their own positions to protect user privacy, and multiple satellites do not need to cooperate, which reduces complexity and makes the solution simple and easy.

[0068] As an optional implementation manner of the present invention, the first preset signal-to-noise ratio determination method includes:

[0069] Obtain the angle between the farthest point of the outer contour of the circle corresponding to the beam radius and the line connecting the satellite projection point and the satellite, and the distance between the satellite and the farthest point of the outer contour of the circle corresponding to the beam radius; obtain a first preset signal-to-noise ratio based on the angle and the distance.

[0070] Exemplarily, in this solution, a channel model is established, assuming that the channel gain between the user and the satellite is:

[0071] h=G D h s h l G satellite

[0072] Among them, G D represents the user antenna receiving gain, h s represents channel fading, h l represents the path loss, G satellite represents the satellite signal gain, and its expression is: L F =0

[0073]

[0074] Where Δθ is the off-axis angle. and the user's position, where For the corresponding user u i Received beam vector from satellite, is the satellite relative to user u i The beam vector a sent by the satellite R,i The elevation and azimuth angles; θ 3dB is the 3dB beamwidth of the satellite spot beam, Indicates the maximum gain of the satellite antenna. According to the ITU-RS.1528 standard, we know that L s =-6.75, L F =0, Y = 1.5θ 3dB ,

[0075] by Figure 1 Take beam point 1 as an example. In beam point 1, Figure 3 As shown, the distance between the satellite and user 1 is:

[0076] d=H / (cosΔθcosθ R,i );

[0077] Where H represents the height difference between the satellite projection point and the satellite.

[0078] The frequency of the transmitted signal is f d , the speed of light is c, then the path loss is given by the formula:

[0079]

[0080] From this, we can know that the signal-to-noise ratio formula between the satellite and the user is:

[0081]

[0082] Among them, P t is the satellite's transmission power, N0 is the noise power spectrum density, and W is the bandwidth. The corresponding signal-to-noise ratio can be calculated based on the user's off-axis angle Δθ.

[0083] According to the above channel modeling, the signal-to-noise ratio can be solved by calculating the user's off-axis angle, and the larger the off-axis angle, the lower the signal-to-noise ratio. Therefore, the minimum signal-to-noise ratio threshold when there is a user within the beam range can be determined by calculating the maximum off-axis angle within the beam range.

[0084] Then, the case where the off-axis angle is the largest is when the user is located at the farthest point of the outer contour of the circle corresponding to the beam radius. Therefore, it can be assumed that the user is located at the farthest point of the outer contour of the circle corresponding to the beam radius, and then the minimum signal-to-noise ratio threshold when there is a user within the beam range is determined based on the angle between the farthest point of the outer contour of the circle corresponding to the beam radius and the line connecting the satellite projection point and the satellite, and the distance between the satellite and the farthest point of the outer contour of the circle corresponding to the beam radius, that is, the first preset signal-to-noise ratio. It should be noted that the second preset signal-to-noise ratio can also be obtained in the same way.

[0085] like Figure 4As shown, the farthest point of the outer contour of the circle corresponding to the beam radius is any point on the outer contour of the circle, such as point A, and the satellite projection point is point O. The angle between the farthest point of the outer contour of the circle corresponding to the beam radius and the line connecting the satellite projection point and the satellite, that is, the off-axis angle, is Δθ. The distance between the satellite and the farthest point of the outer contour of the circle corresponding to the beam radius, that is, the distance between the satellite and the user, is d.

[0086] Since the radiation range of the beam is known, the angle between the farthest point of the outer contour of the circle corresponding to the beam radius and the line connecting the satellite projection point and the satellite, as well as the distance between the satellite and the farthest point of the outer contour of the circle corresponding to the beam radius can be calculated.

[0087] According to the Pythagorean theorem, Wherein R is the beam radius, then using the above signal-to-noise ratio formula, the first preset signal-to-noise ratio can be obtained.

[0088] This solution determines the minimum signal-to-noise ratio threshold when there is a user within the beam range by calculating the maximum off-axis angle within the beam range, and the calculation is simple and convenient.

[0089] As can be inferred from the previous point, assuming that the system coverage radius is R0, the initial coverage radius of the spot beam is R, and there are N users in the system at the same time, if the difference within the beam is ignored, and the probability of the target appearing in the same wave position is the same, which is equal to the probability at the center of the wave position, then after introducing the equivalent coverage factor η according to the beam overlap relationship, assuming that the time required for scanning a single wave position is Δt, the total There are beam positions to scan, and the average time taken for all targets to be discovered satisfies:

[0090]

[0091] As an optional implementation of the present invention, according to the above inference, when all scanning positions are scanned, until the positioning of N users is completed, a total of The distance an object moves in a single beam hop time is vΔt, and SNR(R0) can be obtained from the signal-to-noise ratio formula. i The corresponding maximum transmission rate in each total positioning cycle is:

[0092]

[0093] Among them, the logarithmic prefactor Characterizes the resources or system overhead consumed by beam tracking and link maintenance, while It represents the consumption caused by communication delay in each beam hopping, T delay =H / c represents the transmission delay caused by a single beam hop, where c is the speed of light, It represents the probability of continuous communication without interruption, and the logarithmic part represents the expectation of the user's maximum transmission rate after secondary positioning with an accuracy of r0.

[0094] For LEO satellite S0 and all users u i The maximum average transmission rate used for transmission between the two can be optimized by establishing the following model: By changing the following optimization problem, the maximum total transmission rate can be obtained;

[0095]

[0096] sqF max ≥R≥0

[0097]

[0098] Where R(n) represents the total transmission rate; r0 represents the radius that meets the accuracy requirement; Δt represents the time interval of a single beam hop of the moving object; R max V represents the distance corresponding to the off-axis angle at which the satellite spot beam can identify the minimum signal-to-noise ratio of the user signal. max represents the maximum relative speed between the user and the satellite, t min Indicates the beam hopping time interval corresponding to the maximum beam hopping frequency.

[0099] As an optional implementation manner of the present invention, inputting the position information into a preset prediction model to obtain a predicted spot beam position includes:

[0100] The position information is input into a preset prediction model, which is a kernel function fitted according to the historical movement trajectory, and the kernel function is a covariance function; the horizontal and vertical coordinates of the predicted point beam position are obtained according to the kernel function.

[0101] Exemplarily, when the present embodiment uses a Gaussian process based machine learning (GPML) model as a preset prediction model, the model building method may be: obtaining the user's historical location data and dividing it into a training set and a test set.

[0102] The training sequence D of the training set Tr ={nN Tr ,nN Tr +1,...,n-1} and the test sequence D of the test set Te ={n} The labels corresponding to these two data sets are set to L Tr = {P[nN Tr ],P[nN Tr +1],...,P[n-1]} and L Te={P[n]}. In Gaussian process machine learning (GPML), given a training sequence and a sequence label to learn the kernel of the Gaussian process model, the mapping function F between the training sequence and the label can be determined as:

[0103] L Tr [n] = F(D Tr [n])

[0104] Using the learned mapping function, we can obtain the test label L from the test sequence {n} Te , that is, the predicted position {P[n]} is:

[0105]

[0106] The process of obtaining the predicted spot beam position can be:

[0107] Assuming that the x-axis component and y-axis component of the user's position trajectory are independent, the user's horizontal coordinate x[n] and vertical coordinate y[n] can be predicted respectively. At the same time, since the user's flight path is a simple curve with a high probability, the square exponential covariance function is selected as the kernel (covariance function). , can be defined as:

[0108]

[0109] Among them, x p Represents the horizontal axis of the test set, x q represents the horizontal coordinate of the training set. For the selected kernel, the predicted prediction point beam position horizontal coordinate x[n] can be calculated by the following formula:

[0110]

[0111] where k * is the covariance vector between the test points and the training points, σ f is the standard deviation of the position feedback noise, x Tr is the horizontal coordinate vector of the training sequence.

[0112] Similarly, the vertical coordinate of the predicted point beam position When , the kernel is:

[0113]

[0114] Among them, y p Represents the ordinate of the test set; y p Represents the ordinate of the training set;

[0115] For the selected kernel, the predicted point beam position abscissa It can be calculated by the following formula:

[0116]

[0117] where k * is the covariance vector between the test points and the training points, σ f is the standard deviation of the position feedback noise, y Tr is the ordinate vector of the training sequence.

[0118] The training process includes: the first step is to project three spot beams evenly distributed at 120° from the current spot beam center at a distance of r0 based on the precise positioning results. The spot beam radius is r0. The received signal SNR is used to detect which spot beam the current user appears in after leaving the current spot beam range, and the user's movement direction is preliminarily determined. The second step is to repeat the first step with the new spot beam as the center, and record the current spot beam center position as the training set. The third step is to use the GPML algorithm to predict the user's next position based on the current training set. Step 4: Verify the prediction result based on the user's location. If the user appears continuously in the predicted spot beam position, it proves that the prediction algorithm is accurate and repeats step 3. If the user does not appear in the predicted spot beam position, it proves that the prediction algorithm training set data is insufficient and repeats step 1. Step 5: User data transmission is completed and communication ends.

[0119] This solution uses Gaussian process machine learning and only requires the user's past location information as input. It can achieve very efficient online prediction without additional training overhead, thereby providing users with continuous, stable, high-quality communication services and protecting user privacy to the greatest extent.

[0120] As an optional implementation, after the location information is input into a preset prediction model to obtain the predicted point beam position, before the predicted point beam position is used to realize data transmission between the satellite and the moving object, it includes: determining whether the predicted point beam position is accurate based on whether the moving object is within the predicted point beam position range during the communication process; if it is inaccurate, correcting the predicted point beam position.

[0121] Exemplarily, in order to avoid the cumulative error caused by a single prediction, which leads to a decrease in the overall accuracy of tracking, this embodiment proposes a method of repeatedly correcting the prediction results to avoid such problems. Specifically, whether there is a large deviation between the user position and the predicted value is determined based on whether the user is within the beam range during the communication process. When there is a large deviation, it is considered that the verification is inaccurate and needs to be corrected. The correction process can specifically be to retrain the preset prediction model, use the previous beam position and the current actual position of the moving object as learning samples, retrain the preset prediction model, and then repeat the prediction and correction until the accuracy of the predicted beam position and the user's actual position reaches a preset threshold.

[0122] It should be noted that in step S101, the scanning beam position needs to control the beam vector according to the azimuth angle, and in the subsequent process of accurately determining the user position, the beam vector also needs to be controlled according to the azimuth angle. Here is a solution method for the beam vector:

[0123] Assume that S0 represents the LEO satellite and u i ,i=1,2,…,N represents the user. Assume u i Equipped with a size of N i =X i ×Y i The satellite is equipped with a uniform planar array (UPA) antenna of size N0 = X0 × Y0. The entire array is on the XOY plane, and the antenna unit spacing along the X axis is d x , the antenna unit spacing along the Y axis is d y The direction of the target is represented by the azimuth angle φ and the pitch angle θ. The azimuth angle φ is the angle between the projection of the target direction on the XOY plane and the X-axis, and the pitch angle θ is the angle between the target direction and the Z-axis.

[0124] Assumptions is the satellite relative to user u i The beam vector a sent by the satellite R,i The elevation and azimuth angles, Is user u i The beam vector a received by the user relative to the satellite T,i The pitch angle and azimuth angle of the corresponding user u i The received beam vector a from the satellite R,i With user u i The beam vector a sent to the satellite T,i Should meet:

[0125]

[0126] where α S,i and β S,iis the phase difference between two adjacent antennas in the x and y axis directions in the satellite antenna array, where α u,i and β u,i is the phase difference between two adjacent antennas in the x and y axis directions in the user antenna array, λ is the wavelength of the radar electromagnetic wave, x and i are the row and column numbers of the antenna unit respectively, and a xk is the amplitude weighting coefficient of the (x,k)th antenna element. Correspondingly, the maximum beam pointing The corresponding antenna phase difference can be obtained as follows:

[0127]

[0128] Because the user knows their own location and the satellite location, It is known that the corresponding (α u,i ,β u,i ). Thus, the satellite beam vector and the user beam vector are determined.

[0129] Finally, it should be noted that the above preferred 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 through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. A low-orbit satellite positioning and tracking method for highly dynamic objects, characterized in that: include: Scan any beam position, the number of beam positions is predetermined based on the spot beam size and arrangement; receiving a first feedback signal of a beam position and determining a signal-to-noise ratio of the beam signal; When the signal-to-noise ratio of any beam signal is greater than a first preset signal-to-noise ratio, multiple sub-beam positions are generated, the radius of each sub-beam position is smaller than the radius of the beam position, and the range covered by the superposition of the multiple sub-beam positions fully or partially covers the range of the beam position; receiving a second feedback signal of a plurality of sub-beam positions and determining a signal-to-noise ratio of the sub-beam signal; When the signal-to-noise ratio of any one of the multiple sub-beam signals is greater than a second preset signal-to-noise ratio, repeating the steps of generating multiple sub-beam positions to receiving second feedback signals of the multiple sub-beam positions, and determining the signal-to-noise ratio of the sub-beam signal until the coverage radius is reduced to a preset accuracy threshold; Read the location information of the radiation radius coverage radius that meets the preset accuracy threshold, where the location information is the location information of the moving object; Inputting the position information into a preset prediction model to obtain a predicted spot beam position; The predicted spot beam position is used to realize data transmission between satellite and moving objects.

2. The method according to claim 1, characterized in that The first preset signal-to-noise ratio determination method includes: Obtain the angle between the farthest point of the outer contour of the circle corresponding to the beam radius and the line connecting the satellite projection point and the satellite, as well as the distance between the satellite and the farthest point of the outer contour of the circle corresponding to the beam radius; A first preset signal-to-noise ratio is obtained according to the angle and the distance.

3. The method according to claim 2, characterized in that According to the angle and the distance, a first preset signal-to-noise ratio is obtained, including: Among them, P t is the satellite's transmission power, N0 is the noise power spectrum density, W is the bandwidth, G D represents the user antenna receiving gain, h l (d) is the path loss, c is the speed of light, and f d represents the frequency of the transmitted signal, and d represents the distance between the satellite and the farthest point of the outer contour of the circle corresponding to the beam radius; Among them, Δθ represents the angle between the farthest point of the outer contour of the circle corresponding to the beam radius and the line connecting the satellite projection point and the satellite, θ 3dB Indicates the 3dB beamwidth of the satellite spot beam, Indicates the maximum gain of the satellite antenna, L s =-6.75, L F =0, Y = 1.5θ 3dB , 4. The method according to claim 1, characterized in that Also includes: When the position information of multiple moving objects is detected, the optimization algorithm is used to maximize the total transmission rate; the optimization algorithm is: Where R(n) represents the total transmission rate; Among them, the logarithmic prefactor Characterizes the resources or system overhead consumed by beam tracking and link maintenance, while It represents the consumption caused by communication delay in each beam hopping, T delay =H / c represents the transmission delay caused by a single beam hop, where c is the speed of light and H represents the height difference between the satellite projection point and the satellite. It represents the probability of continuous communication without interruption, and the logarithmic part represents the expected maximum transmission rate of the user after secondary positioning with an accuracy of r0; r0 represents the radius that meets the accuracy requirement; Δt represents the time interval of a single beam hop of the moving object; R max V represents the distance corresponding to the off-axis angle at which the satellite spot beam can identify the minimum signal-to-noise ratio of the user signal. max represents the maximum relative speed between the user and the satellite, t min Indicates the beam hopping time interval corresponding to the maximum beam hopping frequency.

5. The method according to claim 1, characterized in that Input the position information into the preset prediction model to obtain the predicted spot beam position, including: The location information is input into a preset prediction model, where the prediction model is a kernel function fitted according to the historical movement trajectory, and the kernel function is a covariance function; The horizontal and vertical coordinates of the predicted point beam position are obtained according to the kernel function.

6. The method according to claim 5, characterized in that The horizontal and vertical coordinates of the predicted spot beam position are obtained according to the kernel function, including: Among them, k * is the covariance vector between the test points and the training points, σ f is the standard deviation of the position feedback noise, x Tr is the horizontal coordinate vector of the training sequence; Tr is the ordinate vector of the training sequence; The ordinate representing the predicted spot beam position; The horizontal coordinate representing the predicted spot beam position.

7. The method according to any one of claims 1 to 6, characterized in that: After the position information is input into the preset prediction model to obtain the predicted spot beam position, before the predicted spot beam position is used to realize data transmission between the satellite and the moving object, it includes: Determine whether the predicted beam position is accurate according to whether the moving object is within the predicted point beam position range during the communication process; When it is inaccurate, the predicted point beam position is corrected.

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