Beam information processing method and apparatus, and electronic device

Abstract

The invention provides a beam information processing method and device and electronic equipment, and the method comprises the steps: determining a reference satellite; wherein the reference satellite is a satellite in a target satellite view field range; providing service in response to a target beam of the target satellite, and constructing a target function with optimal performance parameters of the target satellite as an optimization target; solving the target function based on a constraint condition to obtain a target weight coefficient corresponding to the target beam; wherein the constraint condition is used for constraining the gain of the target wave beam at a collinear point, and the collinear point is an intersection point of a vector between the target satellite and the reference satellite and the earth surface. According to the beam information processing method provided by the invention, the potential interference of the target satellite on the receiving station of the satellite in the view field range of the target satellite can be reduced, and meanwhile, the coverage range loss caused by interference avoidance measures can be reduced, so that the utilization rate of the target satellite can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of satellite communication technology, and in particular to a beam information processing method and device, and electronic equipment. Background Art

[0002] With the continuous development and rapid iteration of communication technology, the ground communication system has matured after many major changes, and its deployment in most regions is relatively complete. Despite this, there are still nearly 2.6 billion people in the world who do not have access to the Internet. As an effective supplement to the ground communication system, low-orbit satellites are regarded as the most promising satellite communication system due to their many advantages such as short transmission delay, wide coverage, low launch cost, easy deployment, and mass production. In the future, broadband satellite networks will be highly integrated with ground networks to achieve the integration of air, space, and ground networks.

[0003] In recent years, large-scale satellite constellations have been deployed at an accelerated pace around the world. Under the constraints of scarce radio spectrum resources and limited orbital resources, many issues such as spectrum coexistence must be considered when deploying constellations. The first issue to consider is co-frequency interference. Broadband low-orbit satellite constellations generally use frequency bands such as Ku, Ka, and Q / V, which highly overlap with the operating frequency bands of high-orbit (Geostationary Orbit, GSO) satellites. The co-frequency interference problem between different satellite systems will be inevitable. The interference between satellite systems is mainly divided into the interference of low-orbit (Low Earth Orbit, LEO) satellites to GSO systems and the interference between LEO satellites and other non-Geostationary Orbit (NGSO) systems. The International Telecommunication Union (ITU) has given clear regulations for the above two interference situations, requiring that LEO systems cannot interfere with GSO systems, and low-priority NGSO systems cannot interfere with high-priority NGSO systems.

[0004] At present, the industry's research on the problem of interference between satellite constellations focuses on the interference of NGSO satellites on GSO satellites. The existing interference avoidance measures include power control, spatial isolation angle, progressive tilt, setting a pointing forbidden zone to optimize beam pointing, etc. Among them, power control will lose link performance, and LEO satellites generally use equal power flux density (PFD) coverage, which has clear restrictions on transmission power; progressive tilt requires the satellite to adjust its attitude in real time, which is essentially a physical isolation method; setting a pointing forbidden zone to optimize beam pointing will also lose the satellite's coverage range, and does not take into account the radiation characteristics of the antenna itself. Figure 1The spatial isolation angle strategy shown is the simplest and most effective interference avoidance measure, and is currently widely used in engineering scenarios. However, a larger isolation angle α is generally required to reduce the interference level, which will result in a greater loss of satellite coverage and reduce satellite utilization. In order to ensure global coverage of the system, the number of satellites needs to be increased. In addition, the scale of each constellation continues to increase, which makes the spatial isolation angle strategy no longer applicable. Summary of the invention

[0005] The technical problem to be solved by the present disclosure is to overcome the above-mentioned defects in the prior art and to provide a beam information processing method and device, and an electronic device.

[0006] The present invention solves the above technical problems through the following technical solutions:

[0007] A first aspect of the present disclosure provides a method for processing beam information, comprising the following steps:

[0008] Determine a reference satellite; wherein the reference satellite is a satellite within the field of view of the target satellite;

[0009] In response to the target beam of the target satellite providing a service, constructing an objective function with the performance parameter of the target satellite being optimized as an optimization objective;

[0010] The objective function is solved based on the constraint condition to obtain the target weight coefficient corresponding to the target beam; wherein the constraint condition is used to constrain the gain of the target beam at a collinear point, and the collinear point is the intersection of the vector between the target satellite and the reference satellite and the ground surface.

[0011] Optionally, the step of determining a reference satellite specifically includes:

[0012] Obtain the spatial position of the target satellite and the spatial positions of other satellites;

[0013] respectively calculating off-axis angles of vectors between the target satellite and the other satellites relative to the target satellite;

[0014] Other satellites corresponding to off-axis angles that meet preset conditions are determined as reference satellites; wherein the preset conditions are determined based on the maximum off-axis angle of the target satellite.

[0015] Optionally, the step of constructing an objective function with the optimal performance parameter of the target satellite as the optimization target specifically includes:

[0016] An objective function is constructed with the minimum radiation power of the target satellite as the optimization goal.

[0017] Optionally, the radiation power is determined according to a steering vector covariance matrix of a target direction and an interference direction, the target direction being a pointing angle of the target beam, and the interference direction being a relative angle of the collinear point with respect to the target satellite.

[0018] Optionally, before solving the objective function, the method further includes: performing eigenvalue decomposition on the steering vector covariance matrix, and / or performing singular value decomposition on the steering vector covariance matrix.

[0019] Optionally, the constraint condition is also used to constrain the gain of the target beam in other beam directions, and / or the constraint condition also includes that the gain of the target beam in the main lobe direction is maximum.

[0020] Optionally, the processing method further includes:

[0021] Array elements in a phased array are configured according to the target weight coefficients to optimize the target beam.

[0022] A second aspect of the present disclosure provides a beam information processing device, including:

[0023] A determination module, used to determine a reference satellite; wherein the reference satellite is a satellite within the field of view of the target satellite;

[0024] A construction module, configured to provide services in response to a target beam of the target satellite and to construct an objective function with the performance parameter of the target satellite being optimized as an optimization objective;

[0025] A solution module is used to solve the objective function based on constraint conditions to obtain a target weight coefficient corresponding to the target beam; wherein the constraint conditions are used to constrain the gain of the target beam at a collinear point, and the collinear point is the intersection of the vector between the target satellite and the reference satellite and the ground surface.

[0026] Optionally, the determination module is specifically used to obtain the spatial position of the target satellite and the spatial positions of other satellites; respectively calculate the off-axis angles of the vectors between the target satellite and the other satellites relative to the target satellite; and determine other satellites corresponding to the off-axis angles that meet preset conditions as reference satellites; wherein the preset conditions are determined based on the maximum off-axis angle of the target satellite.

[0027] Optionally, the construction module is specifically used to construct an objective function with minimizing the radiation power of the target satellite as the optimization goal.

[0028] Optionally, the radiation power is determined according to a steering vector covariance matrix of a target direction and an interference direction, the target direction being a pointing angle of the target beam, and the interference direction being a relative angle of the collinear point with respect to the target satellite.

[0029] Optionally, the processing device further comprises a decomposition module, configured to perform eigenvalue decomposition on the steering vector covariance matrix, and / or perform singular value decomposition on the steering vector covariance matrix.

[0030] Optionally, the constraint condition is also used to constrain the gain of the target beam in other beam directions, and / or the constraint condition also includes that the gain of the target beam in the main lobe direction is maximum.

[0031] Optionally, the processing device further includes a configuration module, configured to configure array elements in the phased array according to the target weight coefficients to optimize the target beam.

[0032] A third aspect of the present disclosure provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the first aspect.

[0033] A fourth aspect of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method described in the first aspect when executed by a processor.

[0034] A fifth aspect of the present disclosure provides a computer program product, comprising a computer program, which implements the steps of the method described in the first aspect when executed by a processor.

[0035] Based on the common sense in the art, the above optional conditions can be arbitrarily combined to obtain the preferred embodiments of the present disclosure.

[0036] The positive progressive effect of the present disclosure is that by constructing an objective function with the optimal performance parameters of the target satellite as the optimization target, and solving the objective function by constraining the gain of the target beam at the collinear point, the target weight coefficient for optimizing the target beam can be obtained, thereby reducing the potential interference caused by the target satellite to the receiving station of the satellite within its field of view, and at the same time reducing the coverage loss caused by interference avoidance measures, thereby improving the utilization rate of the target satellite. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Schematic diagram of the spatial isolation angle strategy in the prior art.

[0038] Figure 2 A flowchart of a method for processing beam information provided in Example 1 of the present disclosure.

[0039] Figure 3 A flowchart of step S11 provided in embodiment 1 of the present disclosure.

[0040] Figure 4 A schematic diagram of a satellite communication system interference model provided in Example 1 of the present disclosure.

[0041] Figure 5 A schematic diagram of a LEO satellite body coordinate system provided in Example 1 of the present disclosure.

[0042] Figure 6 A schematic diagram of another LEO satellite body coordinate system provided in Example 1 of the present disclosure.

[0043] Figure 7 A three-dimensional beam pattern corresponding to the traditional beamforming algorithm provided in Example 1 of the present disclosure.

[0044] Figure 8 The three-dimensional beam pattern corresponding to the algorithm proposed in this solution provided in Example 1 of the present disclosure.

[0045] Fig. 9 This is a beam gain contour map corresponding to the traditional beamforming algorithm provided in Example 1 of the present disclosure.

[0046] Fig.10 The beam gain contour map corresponding to the algorithm proposed in this solution provided in Example 1 of the present disclosure.

[0047] Fig.11 A schematic diagram of the EPFD level at the co-linear point of the LEO satellite and the GSO provided in Example 1 of the present disclosure.

[0048] Fig.12 A schematic diagram of the I / N level of a LEO satellite at a collinear point with a NGSO provided in Example 1 of the present disclosure.

[0049] Fig.13 A comparative schematic diagram of the EPFD of GSO collinear points under two algorithms provided in Example 1 of the present disclosure.

[0050] Fig.14 A schematic diagram comparing the I / N of NGSO collinear points under two algorithms provided in Example 1 of the present disclosure.

[0051] Fig.15 This is a structural block diagram of a beam information processing device provided in Example 1 of the present disclosure. DETAILED DESCRIPTION

[0052] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0053] It should be noted that the terms "first", "second", etc., as used in the present disclosure, are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0054] The beam of the target satellite will cause potential interference to the receiving stations of other satellites within its field of view. In order to reduce this potential interference, the embodiment of the present disclosure provides a method for processing beam information. By constructing an objective function with the optimal performance parameters of the target satellite as the optimization target, and solving the objective function by constraining the gain of the target beam at the collinear point, the target weight coefficient for optimizing the target beam can be obtained. Furthermore, configuring the array elements in the phased array according to the target weight coefficient can change the radiation pattern of the target beam, thereby reducing the potential interference caused by the target satellite to the receiving stations of satellites within its field of view, and at the same time reducing the coverage loss caused by interference avoidance measures, thereby improving the utilization rate of the target satellite.

[0055] Example 1

[0056] Figure 2 A flowchart of a beam information processing method provided in this embodiment is provided. The beam information processing method can be executed by a beam information processing device. The beam information processing device can be implemented by software and / or hardware. The beam information processing device can be part or all of an electronic device. The beam information processing method provided in this embodiment is introduced below with an electronic device as the execution subject.

[0057] like Figure 2 As shown, the beam information processing method provided in this embodiment may include the following steps S11 to S13:

[0058] Step S11, determining a reference satellite; wherein the reference satellite is a satellite within the field of view of the target satellite.

[0059] In a specific implementation, the target satellite may be a LEO satellite, a Middle Earth Orbit (MEO) satellite, or other satellites. The reference satellite may include all or part of the satellites within the field of view of the target satellite, such as a GSO satellite, a NGSO satellite, etc. In practical applications, the beam of the target satellite may cause potential interference to the receiving station of the satellite within its field of view, i.e., the reference satellite, such as a ground station or a user terminal.

[0060] Step S12: In response to the target beam of the target satellite providing service, construct an objective function with the performance parameter of the target satellite being optimized as an optimization objective. In a specific implementation, the target beam may be any beam of the target satellite.

[0061] The performance parameters of the target satellite may be radiation power, carrier-to-noise ratio or system capacity, etc. In a specific example, an objective function is constructed with the minimum radiation power of the target satellite as the optimization target, wherein the radiation power of the target satellite includes the gain of the target beam in the direction of its main lobe, the gain of other beams in the direction of their main lobes, and the gain of the target beam at the collinear point. In another specific example, an objective function is constructed with the maximum carrier-to-noise ratio of the target satellite as the optimization target. In another specific example, an objective function is constructed with the maximum system capacity of the target satellite as the optimization target.

[0062] Step S13: Solve the objective function based on the constraint condition to obtain the objective weight coefficient corresponding to the target beam, wherein the constraint condition is used to constrain the gain of the target beam at a collinear point, and the collinear point is the intersection of the vector between the target satellite and the reference satellite and the ground surface.

[0063] It should be noted that when the orbit of the reference satellite is higher than the orbit of the target satellite, the vector between the target satellite and the reference satellite is the vector from the reference satellite to the target satellite; when the orbit of the target satellite is higher than the orbit of the reference satellite, the vector between the target satellite and the reference satellite is the vector from the target satellite to the reference satellite. Specifically, the vector between the target satellite and the reference satellite may also be referred to as a collinear vector. For example, the vector between the target satellite and the GSO satellite may be referred to as a GSO collinear vector, and the intersection of the GSO collinear vector and the surface may be referred to as a GSO collinear point; the vector between the target satellite and the NGSO satellite may be referred to as an NGSO collinear vector, and the intersection of the NGSO collinear vector and the surface may be referred to as an NGSO collinear point.

[0064] In a specific implementation, the constraint condition may include that the gain of the target beam at the collinear point is less than a first preset value. The first preset value may be set according to a threshold value specified by ITU. In practical applications, the gain of the target beam at the collinear point may be normalized, and then the normalized gain of the target beam at the collinear point may be constrained, and ideally the normalized gain may be constrained to 0.

[0065] In this embodiment, after obtaining the target weight coefficient corresponding to the target beam, it can be applied to the phased array of the target satellite to optimize the target beam, thereby reducing the potential interference caused by the target satellite to the receiving station of the satellite within its field of view, and at the same time reducing the coverage loss caused by interference avoidance measures, thereby improving the utilization rate of the target satellite.

[0066] In an optional implementation, the electronic device is an electronic device in a communication system where the target satellite is located, and the processing method further includes: configuring array elements in a phased array according to the target weight coefficients to optimize the target beam.

[0067] In another optional implementation, the electronic device is an electronic device in a ground communication system, and the processing method further includes: sending the target weight coefficient to the communication system where the target satellite is located. In a specific implementation, the communication system where the target satellite is located configures the array elements in the phased array according to the received target weight coefficient to optimize the target beam.

[0068] In order to prevent interference inside the target satellite, the gain of the target beam in other beam directions can also be constrained. In an optional implementation, the constraint condition is also used to constrain the gain of the target beam in other beam directions. In a specific implementation, the constraint condition may include that the gain of the target beam at a collinear point is less than a second preset value. The second preset value can be set according to the threshold value specified by ITU. In practical applications, the gain of the target beam in other beam directions can be normalized, and then the normalized gain of the target beam in other beam directions can be constrained. Ideally, the normalized gain constraint can be set to 0.

[0069] In another optional implementation, the constraint condition also includes that the gain of the target beam in the main lobe direction is maximum. In this implementation, by limiting the gain of the target beam in its main lobe direction to be maximum, the signal transmission rate of the target beam can be increased, thereby improving the user experience.

[0070] In an optional embodiment, Figure 3 As shown, the above step S11 includes:

[0071] Step S111, obtain the spatial position of the target satellite and the spatial positions of other satellites. In a specific implementation, the spatial position of the target satellite can be obtained by obtaining the ephemeris file of the target satellite, and the spatial positions of other satellites can be obtained by obtaining the ephemeris files of other satellites. In some embodiments, the ephemeris file is also called two-line orbital element (TLE).

[0072] Step S112, respectively calculating the off-axis angle of the vector between the target satellite and the other satellites relative to the target satellite. In a specific implementation, it is necessary to determine the vector between the target satellite and the other satellites according to the spatial position of the target satellite and the spatial positions of the other satellites. In some embodiments, the off-axis angle is also called a scanning angle.

[0073] Step S113: Determine other satellites corresponding to off-axis angles that meet a preset condition as reference satellites, wherein the preset condition is determined according to the maximum off-axis angle of the target satellite.

[0074] In a specific implementation, the maximum off-axis angle of the target satellite is known. In a specific example, the preset condition is that it is less than the maximum off-axis angle of the target satellite. According to the antenna radiation characteristics, the smaller the off-axis angle, the closer to the main lobe, and the more serious the interference. That is, the off-axis angle calculated in step S112 directly affects the interference degree of the target satellite to other satellite receiving stations. When the off-axis angle calculated in step S112 is less than the maximum off-axis angle of the target satellite, the intersection of the vector between the target satellite and other satellites and the ground surface falls within the coverage range of the target satellite, that is, the field of view. In this example, all satellites within the field of view of the target satellite are determined as reference satellites.

[0075] In another specific example, the preset condition is less than a reference off-axis angle, wherein the reference off-axis angle is less than the maximum off-axis angle of the target satellite. According to the antenna radiation characteristics, the greater the off-axis angle, the lower the interference degree in the direction, so this part of the interference can be ignored. In this example, some satellites within the field of view of the target satellite are determined as reference satellites.

[0076] Figure 4 A schematic diagram for illustrating a satellite communication system interference model. Figure 4 In the example shown, an Earth-Centered Earth-Fixed coordinate system (ECEF) is constructed, and a certain LEO satellite is denoted as point L, which corresponds to the above-mentioned target satellite, a certain GSO satellite is denoted as point G, and a certain NGSO satellite is denoted as point N. The longitude and latitude of the LEO satellite in the ECEF coordinate system are θ L and ΦL , the longitude and latitude of the GSO satellite in the ECEF coordinate system are Θ G and Φ G The longitude and latitude of the NGSO satellite in the ECEF coordinate system are Θ N and Φ N At this time, the spatial positions of LEO satellites, GSO satellites and NGSO satellites can be represented by the spatial vectors pointing from the center of the earth to the satellites, which are:

[0077] v OL =[(R e +h L )cosΘ L cosΦ L ,(R e +h L )cosΘ L sinΦ L ,(R e +h L )sinΘ L ];

[0078] v OG =[(R e +h G )cosΘ G cosΦ G ,(R e +h G )cosΘ G sinΦ G ,(R e +h G )sinΘ G ];

[0079] v ON =[(R e +h N )cosΘ N cosΦ N ,(R e +h N )cosΘ N sinΦ N ,(R e +h N )sinΘ N ];

[0080] Among them, R e is the radius of the Earth, h L ,h G and h N They are the orbital altitudes of LEO satellites, GSO satellites and NGSO satellites respectively.

[0081] When LEO satellite is in operation, it always keeps its normal direction aligned with the center of the earth. The vector from GSO satellite to LEO satellite is GSO collinear vector, and the vector from LEO satellite to NGSO satellite is NGSO collinear vector. The off-axis angle of GSO collinear vector relative to LEO satellite is α, and the off-axis angle of NGSO collinear vector relative to LEO satellite is β, which can be expressed as:

[0082]

[0083]

[0084] Among them, v GL =v OL -v OG , v LN =v ON -v OL .

[0085] Assume that the maximum off-axis angle of the LEO satellite is θ off , will be less than θ off The GSO satellite corresponding to the off-axis angle α is determined as the reference satellite, and the off-axis angle θ off The NGSO satellite corresponding to the off-axis angle β is also determined as the reference satellite.

[0086] The following is a detailed description of how to calculate the gain of the target beam at the collinear point.

[0087] First, the relative angle of the collinear point relative to the target satellite is determined, which can be called the relative angle of the collinear vector relative to the target satellite. In a specific implementation, it is necessary to establish a body coordinate system of the target satellite to determine the relative angle, which generally includes a pitch angle and an azimuth angle.

[0088] In a specific example, the target satellite is a LEO satellite in the northern hemisphere. The X-axis of the LEO satellite coordinate system is established with the subsatellite point pointing to the north, the Z-axis is established perpendicular to the X-axis pointing to the north, and the Y-axis is established perpendicular to the X and Z axes pointing to the west. Figure 5 As shown. The unit vectors defining the LEO satellite body coordinate system are x u ,y u 、z u , transform it into the ECEF coordinate system through coordinate transformation, we have:

[0089] x u = -[cosθ L cosΦ L ,cosΘ L sinΦ L ,sinΘ L ];

[0090] z u= -[sinθ L cosΦ L ,sinΘ L sinΦ L ,-cosΘ L ];

[0091] y u =z u × u ;

[0092] The angle between the beam and its projection on the XOY plane is defined as the pitch angle θ, and the angle between the beam projection on the XOY plane and the X axis is defined as the azimuth angle Then the elevation angle and azimuth angle of the collinear vector relative to the LEO satellite can be expressed as:

[0093]

[0094]

[0095] Where r represents a collinear vector, such as the GSO collinear vector or NGSO collinear vector, and p is the projection vector of r on the XOY plane, which can be expressed as:

[0096]

[0097] In another specific example, the target satellite is a LEO satellite in the northern hemisphere. The Z axis of the LEO satellite coordinate system is established with the subsatellite point pointing to the south, the X axis is established perpendicular to the Z axis and the Y axis is established perpendicular to the Z and X axes pointing to the west. Figure 6 As shown. The unit vectors defining the LEO satellite body coordinate system are x u ,y u 、z u , transform it into the ECEF coordinate system through coordinate transformation, we have:

[0098] z u = -[cosθ L cosΦ L ,cosΘ L sinΦ L ,sinΘ L ];

[0099] x u =[sinθ L cosΦ L ,sinΘ L sinΦ L ,-cosΘ L ];

[0100] y u =z u ×u ;

[0101] Similarly, the angle between the beam and the Z axis is defined as the pitch angle θ, and the angle between the projection of the beam on the XOY plane and the X axis is the azimuth angle Then the elevation angle and azimuth angle of the collinear vector relative to the LEO satellite can be expressed as:

[0102]

[0103]

[0104] Where r represents a collinear vector, such as the GSO collinear vector or NGSO collinear vector, and p is the projection vector of r on the XOY plane, which can be expressed as:

[0105]

[0106] Secondly, the gain of the target beam at the collinear point is calculated according to the relative angle of the collinear point with respect to the target satellite.

[0107] The phased array in the target satellite is taken as an example to be a two-dimensional uniform rectangular array, assuming that the array size is M1×M2.

[0108] If the array is evenly distributed in Figure 5 In the YOZ plane shown in the figure, and the array element spacing d in the Y and Z directions is half a wavelength, the beam pointing angle is The steering vector It can be expressed as:

[0109]

[0110] Where, m1=0,1,…,M1-1, m2=0,1,…,M2-1, λ is the working wavelength, (·) T Represents a transpose operation.

[0111] If the array is evenly distributed in Figure 6 In the XOY plane shown in the figure, and the array element spacing d in the X and Y directions is half a wavelength, the beam pointing angle is The steering vector It can be expressed as:

[0112]

[0113] exist Figure 4 In the example shown, the LEO satellite has M beams to provide services to the ground cells, and the main lobe of the beam is pointed as (m=1,2,…,M), the transmit beam pattern after array synthesis can be expressed as:

[0114]

[0115] Among them, w m is the weight coefficient of the mth beam, (·) H represents the conjugate transpose operation. At this time, the gains of beam m at the GSO satellite collinear point and the NGSO satellite collinear point can be expressed as:

[0116]

[0117]

[0118] in, are the elevation and azimuth angles of the GSO collinear vector relative to the LEO satellite, are the elevation and azimuth angles of the NGSO collinear vector relative to the LEO satellite.

[0119] Furthermore, the following objective function and constraint conditions can be constructed with the minimum radiation power of the target satellite as the optimization goal:

[0120]

[0121] Among them, P and Q are the number of GSO satellites and NGSO satellites that are effectively collinear with the LEO satellite, that is, the number of GSO satellites and NGSO satellites within the LEO field of view. The above four constraints are that the gain of beam m in the direction of its main lobe is maximum, the gain of beam m in other beam directions is minimum, the gain of beam m at the GSO collinear point is minimum, and the gain of beam m at the NGSO collinear point is minimum. It should be noted that the gains in the above constraints are obtained by dividing by the maximum gain. Normalization was performed.

[0122] In an optional implementation, the radiated power is determined according to the steering vector covariance matrix of the target direction and the interference direction, the target direction is the pointing angle of the target beam, and the interference direction is the relative angle of the collinear point relative to the target satellite. In this implementation, the radiated power of the target satellite can be simplified to be determined according to the steering vector covariance matrix of the target direction and the interference direction, so as to facilitate the solution of the objective function. Specifically, it can be solved by analytical algorithms such as the minimum variance distortionless response (MVDR) algorithm, the linearly constrained minimum variance (LCMV) algorithm, and the generalized sidelobe canceller (GSC) algorithm, and can also be solved by heuristic algorithms such as genetic algorithms, particle swarm algorithms, and simulated annealing algorithms.

[0123] For large-scale arrays, the solution process involves high-dimensional matrix operations, the computational complexity is high, and the optimization algorithm requires multiple iterations, which takes a long time. In order to reduce the complexity of the solution calculation and improve the efficiency of the calculation, before solving the objective function, the covariance matrix of the steering vector can be eigenvalue decomposed.

[0124] For the large-scale constellation interference avoidance problem, the number of interfering satellites is relatively large, and the correlation of the interference steering vectors is strong. The steering vector covariance matrix is ​​very likely to be a singular matrix. In this case, it is also necessary to perform singular value decomposition on the steering vector covariance matrix.

[0125] In practical applications, the steering vector covariance matrix can be first subjected to eigenvalue decomposition and then subjected to singular value decomposition, that is, two dimensionality reduction processes are performed, thereby greatly improving the computational efficiency.

[0126] In the above example, the above formula (1) can be simplified as follows:

[0127]

[0128] Where R is the covariance matrix of the guidance vector in the target direction and the interference direction, C is the constraint matrix, and f is the response vector. For formula (1) and formula (2), the constraint matrix C, the covariance matrix R, and the response vector f can be expressed as:

[0129]

[0130] R=CC H ;

[0131] f=[1,0,0,0] T ;

[0132] First, perform eigenvalue decomposition on the R matrix, and we have:

[0133]

[0134] Take the eigenvectors corresponding to the main eigenvalues ​​to form the matrix P, that is, P = [q1, q2, ..., q k ], where q k is the kth column of Q, and then the R matrix is ​​reconstructed into R' through the P matrix, and then: R'=PP H ;

[0135] The R' matrix contains the main features of the R matrix, that is, it contains the dominant steering vector information, and the matrix dimension is also reduced. Further, the singular value decomposition algorithm is used to calculate the pseudo-inverse of the R matrix, and we have:

[0136]

[0137]

[0138] After adopting the singular value decomposition algorithm, the matrix dimension involved in calculating the pseudo-inverse of the R matrix is ​​reduced, which can greatly reduce the amount of calculation. Combining the Lagrange multiplier method and the above calculation steps, the optimal solution of the objective function in the above formula (1) can be obtained as:

[0139] In order to improve the robustness of the algorithm, diagonal loading can be further performed to update the optimal solution of the above objective function to: Among them, I is the identity matrix and ε is a very small positive real number.

[0140] The following is a detailed explanation using a real scenario as an example. The 566 GSO satellites currently in orbit form a GSO satellite constellation, and the 4144 Starlink first-generation satellites form an NGSO satellite constellation. The same frequency range is the Ku band 10.7-11.7GHz, and the single beam bandwidth is 250MHz. The LEO satellite uses the orbital parameters of a domestic low-orbit satellite system as a reference, with an orbital altitude of 1160km and an orbital inclination of 89.5°. Assume that the LEO satellite has 4 service beams, of which 1 staring beam serves a fixed cell, and 3 hopping beams jump in real time according to business needs. Take the arc segment of the LEO satellite running for 5 minutes for analysis, and the fixed cell is located in the center of the arc segment.

[0141] First, the spatial position of each satellite at each moment is obtained by obtaining the ephemeris files of 566 GSO satellites and 4144 NGSO satellites. Similarly, the spatial position of the LEO satellite is obtained. Taking the 199th second of the arc as an example, the latitude of the LEO satellite is 0 at this time. According to the maximum off-axis angle of the LEO satellite, there are 128 GSO satellites and 9 NGSO satellites in its field of view. Then the relative angles of the 128 GSO collinear points and the 9 NGSO collinear points relative to the LEO satellite are calculated. At this time, the pointing angles of the four service beams are known, the pointing angle of the staring beam is (-14.2151°, -0.9684°), and the pointing angles of the other three service beams are: (30°, -30°), (-25°, 20°), (20°, 20°).

[0142] Assuming that the LEO satellite system adopts a 24x24 two-dimensional uniform array with an operating frequency of 11.7GHz, an array optimization problem is constructed. When considering the optimization of a single service beam, namely the target beam, the remaining service beams are interference terms. At this time, the constraints include the constraints of 4 service beams, the constraints of 128 GSO collinear points, and the constraints of 9 NGSO collinear points. The constraint matrix C is a complex matrix of size 576x141, and the R matrix is ​​a complex matrix of size 576x576. The steering vectors have strong correlations, and the R matrix is ​​a rank-deficient matrix (rank(R)=116), which is difficult to solve using traditional algorithms. Therefore, the R matrix is ​​first decomposed by eigenvalues, the main eigenvalues ​​in the R matrix are extracted, and the R matrix is ​​reconstructed using the eigenvectors corresponding to the main eigenvalues. Then the reconstructed R matrix is ​​subjected to singular value decomposition to obtain its pseudo-inverse. Finally, the target weight coefficient corresponding to the target beam is calculated by combining the Lagrange multiplier method and diagonal loading.

[0143] In order to intuitively reflect the advantages of the algorithm proposed in this scheme over the traditional beamforming algorithm, Figure 7 and Figure 8 The three-dimensional beam patterns corresponding to the two algorithms at the current moment are given respectively. Fig. 9 and Fig.10 The beam gain contour maps corresponding to the two algorithms at the current moment are given respectively. Among them, the green mark indicates the service beam pointing of the LEO satellite, the red mark indicates the relative position of the GSO collinear point, and the blue mark indicates the relative position of the NGSO satellite collinear point. By comparing Figure 7 and Figure 8 And contrast Fig. 9 and Fig.10It can be found that under the traditional beamforming algorithm, the beam gain at the collinear point is too high, which will cause strong interference when the LEO satellite serves the service cell. After adopting the algorithm proposed in this scheme, when the beam is pointed to the service cell, the beam radiation forms a null band covering the GSO collinear point, and at the same time, it can also form an accurate zero point for each NGSO collinear point. The gain of the beam pointing to the collinear point is greatly reduced, which can alleviate the potential strong interference to the GSO satellite receiving station and the NGSO satellite receiving station, and even avoid interference.

[0144] Furthermore, in order to quantitatively describe the interference suppression capability of the proposed algorithm compared with the traditional beamforming algorithm, the EPFD (Equivalent Power FluxDensity) level of the LEO satellite at 128 GSO collinear points and the I / N level of the LEO satellite at 9 NGSO collinear points are statistically analyzed and plotted at the same time, as shown in the figure below. Fig.11 and Fig.12 By comparison Fig.11 and Fig.12 It can be found that when using the traditional beamforming algorithm, the EPFD or I / N values ​​at many collinear points are above the interference threshold and do not meet international regulations. At this time, the isolation angle needs to be increased to reduce interference. After adopting the algorithm proposed in this scheme, the EPFD at each GSO collinear point or the I / N at each NGSO collinear point is significantly reduced, and the interference to the GSO satellite receiving station and the NGSO satellite receiving station is greatly alleviated, which can provide a feasible technical solution for large-scale constellation coexistence.

[0145] The calculation formula of EPFD is as follows:

[0146]

[0147] Where N is the number of NGSO satellite transmitters within the visible range of the GSO earth station; i is the i-th transmitter in the NGSO satellite system; P i is the i-th transmitter power in the NGSO satellite system; G t (θ i ) is the off-axis angle of the i-th transmitting antenna in the NGSO satellite system, θ i Gain; d i is the distance between the i-th transmitter in the NGSO satellite system and the receiver in the GSO satellite system; is the off-axis angle of the GSO satellite system receiving end corresponding to the i-th transmitter in the NGSO satellite system, and its gain is G r,max is the maximum gain of the receiving antenna of the GSO satellite earth station.

[0148] The calculation formula of interference-to-noise ratio I / N is as follows:

[0149]

[0150] in, is the transmission power of the mth interference beam, is the transmitting antenna gain of the mth interference beam in the interference direction, G r (θ r ) is the receiving antenna gain of the ground NGSO user terminal in the interference direction, d s is the distance from the target satellite to the ground NGSO satellite user terminal, λ is the operating wavelength, k is the Boltzmann constant, T is the noise temperature, and B is the system bandwidth.

[0151] Furthermore, the data of the entire 5-minute arc segment is analyzed, ignoring the change in the longitude of the LEO satellite, which moves from 11°S to 4°N. Fig.13 and Fig.14 , the maximum EPFD of the GSO collinear point and the maximum I / N of the NGSO collinear point are evaluated under the traditional beamforming algorithm and the algorithm proposed in this scheme. Fig.13 In the figure, the dark blue dotted line and the light blue solid line represent the EPFD values ​​of the GSO collinear point under the traditional beamforming algorithm and the algorithm proposed in this scheme, respectively; the green dotted line represents the time period when the EPFD meets the threshold value specified by the ITU under the traditional beamforming algorithm, which is the actual serviceable time period of the LEO satellite; the red dotted line and the gray dotted line represent the EPFD threshold value specified by the ITU, and the probability of not exceeding the threshold value is 100% and 0%, respectively. Fig.14 In the figure, the dark blue dotted line and the light blue solid line represent the I / N values ​​of the NGSO collinear point under the traditional beamforming algorithm and the algorithm proposed in this scheme, respectively; the green dotted line represents the time period when both EPFD and I / N meet the threshold values ​​specified by ITU under the traditional beamforming algorithm, which is the actual serviceable time period of the LEO satellite; the red dotted line represents the I / N threshold value specified by ITU.

[0152] Through statistical analysis of the arc segments of the LEO satellite operation, it can be seen that under the traditional beamforming algorithm and the algorithm proposed in this scheme, the time ratios of the GSO collinear point meeting the EPFD threshold value are 65.12% and 83.06% respectively; the isolation angles required to not interfere with the GSO system are 23.77° and 6.24° respectively; the time ratios of the NGSO collinear point not meeting the I / N threshold value are 14.29% and 0 respectively; and the available time ratios of the LEO satellite in the entire arc segment are 55.81% and 83.06% respectively. It can be seen that the algorithm proposed in this scheme can significantly reduce the isolation angle, thereby reducing the coverage loss of the LEO satellite, and can also increase the available time of the LEO satellite, thereby improving the utilization rate of the LEO satellite.

[0153] It should be noted that when LEO satellites are operating, there will inevitably be scenarios where the collinear point is close to or overlaps with the service beam direction. At this time, the traditional beamforming algorithm exhibits extremely strong interference, and the algorithm proposed in this scheme has no feasible solution. It can only shut down the beam and switch to other available satellites to take over the service.

[0154] In practical applications, it is also possible to construct an objective function that takes the carrier-to-noise ratio of the target satellite or the maximum system capacity as the optimization target. The calculation formula for the carrier-to-noise ratio is as follows:

[0155]

[0156] Among them, P t is the transmit power of the target beam, F m is the transmit beam gain of the target beam in the target direction, G r is the receiving antenna gain, d is the satellite-to-earth distance, λ is the operating wavelength, k is the Boltzmann constant, T is the noise temperature, and B is the system bandwidth.

[0157] The system capacity is calculated as follows:

[0158] C sys =B log2(1+C / N)·η;

[0159] Where η is the spectrum efficiency.

[0160] This embodiment also provides a beam information processing device 30, such as Fig.15 As shown, it includes a determination module 31, a construction module 32 and a solution module 33. The determination module 31 is used to determine a reference satellite; wherein the reference satellite is a satellite within the field of view of the target satellite. The construction module 32 is used to provide services in response to the target beam of the target satellite, and to construct an objective function with the optimal performance parameters of the target satellite as the optimization target. The solution module 33 is used to solve the objective function based on constraints to obtain the target weight coefficient corresponding to the target beam; wherein the constraints are used to constrain the gain of the target beam at a collinear point, and the collinear point is the intersection of the vector between the target satellite and the reference satellite and the ground surface.

[0161] In an optional embodiment, the determination module is specifically used to obtain the spatial position of the target satellite and the spatial positions of other satellites; respectively calculate the off-axis angles of the vectors between the target satellite and the other satellites relative to the target satellite; and determine other satellites corresponding to the off-axis angles that meet preset conditions as reference satellites; wherein the preset conditions are determined based on the maximum off-axis angle of the target satellite.

[0162] In an optional implementation, the construction module is specifically used to construct an objective function with minimizing the radiation power of the target satellite as an optimization goal.

[0163] In an optional embodiment, the radiation power is determined based on a steering vector covariance matrix of a target direction and an interference direction, wherein the target direction is a pointing angle of the target beam, and the interference direction is a relative angle of the collinear point relative to the target satellite.

[0164] In an optional embodiment, the processing device further includes a decomposition module for performing eigenvalue decomposition on the steering vector covariance matrix and / or performing singular value decomposition on the steering vector covariance matrix.

[0165] In an optional implementation, the constraint condition is also used to constrain the gain of the target beam in other beam directions, and / or the constraint condition also includes that the gain of the target beam in the main lobe direction is maximum.

[0166] In an optional implementation, the processing device further includes a configuration module, configured to configure array elements in the phased array according to the target weight coefficients to optimize the target beam.

[0167] It should be noted that the beam information processing device in this embodiment may specifically be a separate chip, a chip module or an electronic device, or may be a chip or a chip module integrated into an electronic device.

[0168] The various modules / units included in the beam information processing device described in this embodiment may be software modules / units or hardware modules / units, or may be partially software modules / units and partially hardware modules / units.

[0169] Example 2

[0170] This embodiment provides an electronic device, including at least one processor and a memory in communication with the at least one processor. The memory stores a computer program that can be run by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the steps of the beam information processing method in Embodiment 1.

[0171] In an optional embodiment, the electronic device is an electronic device in a communication system where the target satellite is located, and is used to configure array elements in the phased array according to target weight coefficients corresponding to the target beam to optimize the target beam.

[0172] In another optional implementation, the electronic device is an electronic device in a ground communication system, and is used to send the target weight coefficient corresponding to the target beam to the communication system where the target satellite is located. In a specific implementation, the communication system where the target satellite is located configures the array elements in the phased array according to the received target weight coefficient to optimize the target beam.

[0173] Example 3

[0174] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for processing beam information in Embodiment 1 are implemented.

[0175] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0176] In a possible implementation manner, the present disclosure may also be implemented in the form of a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the method for processing beam information in Example 1 are implemented.

[0177] Among them, the computer program for executing the present disclosure can be written in any combination of one or more programming languages, and the computer program can be executed completely on the electronic device, partially on the electronic device, as a separate software package, partially on the electronic device and partially on a remote device, or completely on the remote device.

[0178] Although the specific embodiments of the present disclosure are described above, those skilled in the art should understand that this is only an example, and the protection scope of the present disclosure is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present disclosure, but these changes and modifications all fall within the protection scope of the present disclosure.

Claims

1. A method for processing beam information, characterized in that: The following steps are involved: Determine a reference satellite; wherein the reference satellite is a satellite within the field of view of the target satellite; In response to the target beam of the target satellite providing a service, constructing an objective function with the performance parameter of the target satellite being optimized as an optimization objective; The objective function is solved based on the constraint condition to obtain the target weight coefficient corresponding to the target beam; wherein the constraint condition is used to constrain the gain of the target beam at a collinear point, and the collinear point is the intersection of the vector between the target satellite and the reference satellite and the ground surface.

2. The processing method according to claim 1, characterized in that The step of determining the reference satellite specifically includes: Obtain the spatial position of the target satellite and the spatial positions of other satellites; respectively calculating off-axis angles of vectors between the target satellite and the other satellites relative to the target satellite; Other satellites corresponding to off-axis angles that meet preset conditions are determined as reference satellites; wherein the preset conditions are determined based on the maximum off-axis angle of the target satellite.

3. The processing method according to claim 1, characterized in that: The step of constructing an objective function with the optimal performance parameter of the target satellite as the optimization target specifically comprises: An objective function is constructed with the minimum radiation power of the target satellite as the optimization goal.

4. The processing method according to claim 3, characterized in that: The radiation power is determined according to the steering vector covariance matrix of the target direction and the interference direction, the target direction is the pointing angle of the target beam, and the interference direction is the relative angle of the collinear point with respect to the target satellite.

5. The processing method according to claim 4, characterized in that: Before solving the objective function, the method further includes: performing eigenvalue decomposition on the steering vector covariance matrix, and / or performing singular value decomposition on the steering vector covariance matrix.

6. The processing method according to claim 1, characterized in that: The constraint condition is also used to constrain the gain of the target beam in other beam directions, and / or the constraint condition also includes that the gain of the target beam in the main lobe direction is maximum.

7. The processing method according to any one of claims 1 to 6, characterized in that: The processing method also includes: Array elements in a phased array are configured according to the target weight coefficients to optimize the target beam.

8. A beam information processing device, characterized in that: include: A determination module, used to determine a reference satellite; wherein the reference satellite is a satellite within the field of view of the target satellite; A construction module, configured to provide services in response to a target beam of the target satellite and to construct an objective function with the performance parameter of the target satellite being optimized as an optimization objective; A solution module is used to solve the objective function based on constraint conditions to obtain a target weight coefficient corresponding to the target beam; wherein the constraint conditions are used to constrain the gain of the target beam at a collinear point, and the collinear point is the intersection of the vector between the target satellite and the reference satellite and the ground surface.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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