A method and apparatus for beamforming

Abstract

This paper discloses a beamforming method and apparatus, comprising: converting M radio frequency signals from any Z visible satellites into M digital intermediate frequency (IF) sampling signals; calculating a first filtering coefficient vector for each IF sampling signal using a preset filter based on a preset constraint vector; calculating a second filtering coefficient vector for the beam channel of each visible satellite based on the direction of arrival of each visible satellite; and filtering the IF sampling signals based on the calculated first and second filtering coefficient vectors to obtain Z first output signals; wherein M is the number of array elements of the ground receiver, and the number of spatial interferences in the obtained output signals is greater than M-1. This embodiment of the invention filters the IF sampling signals based on the confirmed first and second filtering coefficient vectors, achieving suppression of spatial interference exceeding the array degrees of freedom, and improving the communication quality of the navigation system.

Description

Technical Field

[0001] This application relates to satellite navigation technology, and more particularly to a method and apparatus for beamforming. Background Technology

[0002] Currently, there are the US Global Positioning System (GPS), the Russian Global Navigation Satellite System (GLONASS), the European Galileo Satellite Navigation System, and the developing Chinese BeiDou Navigation Satellite System. They can provide all-weather, real-time, and continuous high-precision location information and have been widely used for positioning, navigation, timing, and precision measurement of various military and civilian targets.

[0003] The electromagnetic environment in satellite navigation is complex, with numerous modes and statistically variable man-made interferences. High-power-density narrowband and broadband interference, in particular, has become one of the most significant factors disrupting navigation systems. To date, adaptive beamforming technology is the primary method for improving the anti-interference capability of satellite navigation receivers. When suppressing space interference, it creates nulls in the direction of interference arrival by updating the weight vector, thus canceling out the interference. However, theoretically, M array elements can form M-1 nulls. When the number of interferences exceeds M-1, exceeding the array's degrees of freedom, the interference suppression capability deteriorates significantly. Summary of the Invention

[0004] The following is an overview of the subject matter described in detail herein. This overview is not intended to limit the scope of the claims.

[0005] This invention provides a method and apparatus for beamforming that can suppress spatial interference beyond the array's degrees of freedom.

[0006] This invention provides a beamforming method, comprising:

[0007] The M radio frequency signals from any Z visible satellites received are converted into M digital intermediate frequency sampling signals;

[0008] For each acquired digital intermediate frequency sampling signal, the first filtering coefficient vector is calculated based on the preset constraint vector when using the preset filter for filtering;

[0009] Based on the direction of arrival of each visible satellite, calculate the second filtering coefficient vector of the beam channel of each of the Z visible satellites;

[0010] Based on the calculated first and second filter coefficient vectors, the digital intermediate frequency sampling signal is filtered to obtain the Z-channel first output signal.

[0011] Where M is the number of ground receiver array elements, and the number of spatial interferences that cause the output signal is greater than M-1.

[0012] On the other hand, embodiments of the present invention also provide a beamforming apparatus, comprising: a conversion unit, a first calculation unit, a second calculation unit, and a processing unit; wherein,

[0013] The conversion unit is configured to convert the M radio frequency signals from any Z visible satellites into M digital intermediate frequency sampling signals.

[0014] The first calculation unit is configured to: calculate the first filter coefficient vector when filtering with a preset filter for each obtained digital intermediate frequency sampling signal, based on the preset constraint vector;

[0015] The second calculation unit is set to: calculate the second filtering coefficient vector of the beam channel of each of the Z visible satellites according to the direction of arrival of each visible satellite;

[0016] The processing unit is configured to: filter the digital intermediate frequency sampling signal according to the calculated first and second filter coefficient vectors to obtain the Z-channel first output signal;

[0017] Where M is the number of ground receiver array elements, and the number of spatial interferences that cause the output signal is greater than M-1.

[0018] In another aspect, embodiments of the present invention also provide a beamforming apparatus, including a processor and a computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when executed by the processor, implement the multi-beamforming method under super-degrees of freedom.

[0019] The technical solution of this application includes: converting M radio frequency signals from any Z visible satellites into M digital intermediate frequency (IF) sampling signals; calculating a first filtering coefficient vector for each obtained IF sampling signal using a preset filter based on a preset constraint vector; calculating a second filtering coefficient vector for the beam channel of each of the Z visible satellites based on the direction of arrival of each visible satellite; and filtering the IF sampling signals based on the calculated first and second filtering coefficient vectors to obtain Z first output signals; wherein M is the number of array elements of the ground receiver, and the number of spatial interferences in the obtained output signals is greater than M-1. This embodiment of the invention filters the IF sampling signals based on the confirmed first and second filtering coefficient vectors, achieving suppression of spatial interference exceeding the array degrees of freedom, and improving the communication quality of the navigation system.

[0020] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0021] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of the present invention and do not constitute a limitation on the technical solutions of the present invention.

[0022] Figure 1 This is a flowchart of a beamforming method according to an embodiment of the present invention;

[0023] Figure 2 This is a schematic diagram of beamforming according to an embodiment of the present invention;

[0024] Figure 3 This is a structural block diagram of the beamforming apparatus according to an embodiment of the present invention;

[0025] Figure 4 This is a structural block diagram of a beamforming device according to an embodiment of the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

[0027] The steps illustrated in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in a different order than that presented here.

[0028] Figure 1 This is a flowchart of a beamforming method according to an embodiment of the present invention, as shown below. Figure 1 As shown, it includes:

[0029] Step 101: Convert the M radio frequency signals from any Z visible satellites received into M digital intermediate frequency sampling signals; where M is the number of antenna array elements of the ground receiver.

[0030] In one exemplary instance, this embodiment of the invention converts M radio frequency signals from any Z visible satellites into M digital intermediate frequency (IF) sampling signals, including:

[0031] The M radio frequency signals are processed by analog-to-digital conversion to obtain M digital intermediate frequency sampling signals.

[0032] In one exemplary instance, the digital intermediate frequency sampling signal in this embodiment of the invention includes: satellite signal, interference signal, and background noise signal.

[0033] In this embodiment of the invention, the M-channel digital intermediate frequency sampling signals can be obtained through AD (analog-to-digital converter) processing.

[0034] Step 102: For each obtained digital intermediate frequency sampling signal, calculate the first filtering coefficient vector when filtering with a preset filter according to the preset constraint vector;

[0035] In one exemplary instance, the present invention calculates a first filter coefficient vector when filtering is performed using a preset filter, including:

[0036] Based on the constraint vector, calculate the initial values ​​of the diagonal matrix of the preset filter and the first filter coefficient vector for iteration;

[0037] The first filter coefficient vector is determined based on the calculated diagonal matrix and the initial values ​​of the iteration;

[0038] The first filter coefficient vector for filtering the signal with sampling time point i+1 in the m-th digital intermediate frequency sampled signal is: μ is a constant coefficient, x m (i) represents the signal with sampling time point i in the m-th digital intermediate frequency sampling signal. For y m The adjoint matrix of (i), y m (i) The second output signal corresponding to the m-th digital intermediate frequency sampling signal, w m (0) is the initial value for iteration, F is a diagonal matrix; m and i are positive integers, m = 1, 2, ..., M.

[0039] In one exemplary instance, the embodiments of the present invention are i = 1, 2, ..., L, where L is the total length of the sequence of digital intermediate frequency sampling signals.

[0040] In one exemplary instance, the preset filter in the embodiments of the present invention may include, but is not limited to, a K-order non-recursive filter (FIR) filter.

[0041] In one exemplary instance, the diagonal matrix in this embodiment of the invention... Where b is a preset constraint vector, and I is a preset identity matrix, the dimension of which is determined by b;

[0042] In one exemplary instance, the initial value of the iteration in this embodiment of the invention.

[0043] The constraint vector in this embodiment of the invention can be set by those skilled in the art based on experience; K is the order of the FIR filter; in an exemplary example, this embodiment of the invention designs a K-order FIR filter for each digital intermediate frequency sampling signal, and the m-th filter coefficient vector of the K-order FIR filter can be defined as: w m (i)=[w m1 ,w m2 ,...,w mK ], m=1,2,...,M;w m (i) is a vector composed of K coefficients, which can be obtained through iterative operations. In this embodiment of the invention, the K coefficients of the preset filter used to filter the m-th digital intermediate frequency sampled signal can theoretically be iterated L times.

[0044] Step 103: Calculate the second filtering coefficient vector of the beam channel for each of the Z visible satellites based on the direction of arrival of each visible satellite.

[0045] In one exemplary instance, embodiments of the present invention calculate the second filter coefficient vector for the beam channel of each of the Z visible satellites, including:

[0046] Based on the direction of arrival of each visible satellite, determine the steering vector of the satellite signal of each of the Z visible satellites.

[0047] Based on the determined steering vector, calculate the first correlation matrix of the digital intermediate frequency sampled signal at sampling time point i;

[0048] Based on the calculated first correlation matrix, calculate the signal-to-noise ratio of the digital intermediate frequency sampled signal of each visible satellite at sampling time point i when filtered according to the first filtering coefficient vector;

[0049] Based on the calculated signal-to-noise ratio, the second filter coefficient vector of the beam channel for each visible satellite is determined.

[0050] In one exemplary instance, the present invention calculates the first correlation matrix of the digital intermediate frequency sampled signal at sampling time point i, including:

[0051] For the digital intermediate frequency sampled signal at sampling time point i, calculate the second correlation matrix of the second output signal obtained by filtering according to the first filter coefficient vector;

[0052] Based on the steering vector, calculate the third correlation matrix of the satellite signal of the z-th visible satellite in the digital intermediate frequency sampled signal at sampling time point i;

[0053] The calculated second and third correlation matrices are added together to obtain the first correlation matrix.

[0054] In one exemplary instance, the second correlation matrix in this embodiment of the invention is calculated using the following formula:

[0055]

[0056] In the formula, E represents the mean, y m This indicates the second output signal.

[0057] In one exemplary instance, the second correlation matrix It can be derived from the output data array Y = [y m (i),y m (i-1),y m (i-2),.....y m [i-K+1] is determined.

[0058] In one exemplary instance, the third correlation matrix in this embodiment of the invention is calculated using the following formula:

[0059]

[0060] In the formula, It is the amplitude of the satellite signal of the z-th visible satellite. Let be the steering vector of the satellite signal from the z-th visible satellite. The direction of the incoming wave from the z-th visible satellite is given.

[0061] In one exemplary embodiment of the invention, the steering vector of the satellite signal can be determined based on the antenna array configuration; when the direction of arrival of the z-th visible satellite is... The steering vector of a satellite signal can be represented as: If the smart antenna is an M-element uniform circular array, the radius of the uniform circular array is R = λ / 2, where λ is the wavelength of the carrier signal; the direction of arrival of the incident plane wave is represented by a spherical coordinate system, with the origin O located at the center of the array; the elevation angle θ∈[0,π / 2] of the signal source is the angle between the line connecting the origin to the signal source and the Z-axis, and the azimuth angle... It is the angle between the projection of the line connecting the origin to the signal source onto the XY plane and the positive half-axis of the X-axis (counterclockwise); the angle r between the m-th array element (excluding the center element) and the X-axis. m If there is an incident direction in space... Based on the phase relationship between each array element and the origin, the steering vector of the satellite signal for the far-field parallel wave s(t) can be obtained as follows:

[0062]

[0063] In the formula, ξ=2πRsinθ / λ, r m =2πm / M, m = 1, 2, ..., M.

[0064] In one exemplary instance, the formula for calculating the first correlation matrix is:

[0065]

[0066] In one exemplary instance, embodiments of the present invention calculate the signal-to-noise ratio (SNR) of the digital intermediate frequency (IF) sampled signal of each visible satellite at sampling time point i when filtered according to a first filter coefficient vector, including:

[0067] Based on the first correlation matrix and the first filter coefficient vector, determine the first signal power p of the digital intermediate frequency sampled signal before filtering by the preset filter. x ;

[0068] Based on the third correlation matrix and the first filter coefficient vector, determine the second signal power of the second output signal after filtering by the preset filter.

[0069] The first signal power p at sampling time point i x (i) Subtract the second signal power at sampling time point i Obtain the noise power p at sampling time point i n (i);

[0070] According to noise power p n (i) and the second signal power at sampling time point i Calculate the signal-to-noise ratio ρ z (i);

[0071] Wherein, the subscript z represents the z-th satellite, and z takes any value from 1 to Z.

[0072] In one exemplary instance, the first signal power in an embodiment of the present invention In one exemplary instance, the first signal power at sampling time point i in this embodiment of the invention.

[0073] In one exemplary instance, the second signal power in an embodiment of the present invention In one exemplary instance, the second signal power at sampling time point i in this embodiment of the invention.

[0074] In one exemplary instance, the noise power in an embodiment of the present invention Noise power p at sampling time point i n (i) is:

[0075] In one exemplary instance, embodiments of the present invention, along with w m Iterative updates of (i), and P n Synchronized updates.

[0076] In one exemplary instance, the signal-to-noise ratio calculation formula of this invention is as follows:

[0077]

[0078] In one exemplary instance, the second filter coefficient vector of this embodiment of the invention is calculated according to the following formula:

[0079]

[0080] Where, q z (i+1) represents the second filter coefficient vector corresponding to the sampling time point i+1 of the z-th satellite, q z (i) represents the second filter coefficient vector corresponding to the sampling time point i of the z-th satellite, ρ z (i) represents the signal-to-noise ratio at sampling time i corresponding to the z-th satellite, and λ is the preset step coefficient; R x R represents the first correlation matrix; ym The second correlation matrix represents the second output signal.

[0081] In an exemplary embodiment of this application, the second filter coefficient vector of the beam channel of the z-th satellite can be expressed as: These are each coefficients in the second filter coefficient vector of the beam channel of the z-th satellite corresponding to each channel.

[0082] Step 104: Based on the calculated first and second filter coefficient vectors, filter the digital intermediate frequency sampling signal to obtain the Z-channel first output signal.

[0083] In one exemplary instance, embodiments of the present invention perform filtering processing on digital intermediate frequency sampling signals, including:

[0084] The first filtering process is performed on the M-channel digital intermediate frequency sampling signals based on the calculated first filtering coefficient vector;

[0085] For the second output signal after the first filtering process, Z first output signals are obtained based on the second filtering coefficient vector of the beam channel of each of the Z visible satellites.

[0086] According to the confirmed first and second filter coefficient vectors, the digital intermediate frequency sampling signal is filtered, which realizes the suppression of spatial interference when the array degrees of freedom are exceeded, and improves the communication quality of the navigation system.

[0087] In one exemplary instance, the expression for the first output signal of this embodiment of the invention is:

[0088]

[0089] Among them, B z (i) represents the signal with sampling time point i in the first output signal output by the z-th satellite. Represents the second filter coefficient vector q z The transpose conjugate matrix of (i) Indicates w m The transpose conjugate matrix of (i), w m (i) represents the first filter coefficient vector for filtering the signal with sampling time point i in the m-th digital intermediate frequency sampled signal, x m (i) represents the digital intermediate frequency sampled signal at sampling time i, y m (i) is the second output signal obtained after filtering the m-th digital intermediate frequency sampling signal at sampling time point i according to the first filtering coefficient vector.

[0090] In this embodiment of the invention, the first output signal at each sampling time point is accumulated to obtain the final multi-beam output signal of the system.

[0091] Figure 2 This is a schematic diagram of beamforming according to an embodiment of the present invention, as shown below. Figure 2 As shown, in this embodiment of the invention, the radio frequency signal is received by M antenna elements of a ground receiver, and after AD processing, M digital intermediate frequency (IF) sampling signals are obtained. These M IF sampling signals serve as input signals for forming the first output signal and can be represented as x1(i), x2(i), x3(i), ..., x M (i), where i is the sampling time point of each digital intermediate frequency sampling signal (i.e., the time point corresponding to each sampling point, or it can be used as the sampling point number), and i is a positive integer. In this embodiment of the invention, the first filter coefficient vector w of the preset filter is obtained... m (i) and the second filter coefficient vector q of the beam channel z (i) Perform real-time filtering processing, as shown in Figure D. -1 Represents the time-domain delay; through the first filter coefficient vector w m (i) Filtering is performed to obtain the second output signal, which can be obtained by multiplying the first filter coefficient vector with the corresponding tap's digital intermediate frequency sampling signal. Based on the second output signal and the second filter coefficient vector q of the beam channel z (i) The multi-beam signal for each channel can be calculated.

[0092] The embodiments of the present invention can be used in scenarios that exceed the array degrees of freedom to obtain multi-beam signals under super array degrees of freedom, effectively suppressing spatial interference in the first output signal.

[0093] Figure 3 This is a structural block diagram of the beamforming apparatus according to an embodiment of the present invention, as shown below. Figure 3 As shown, it includes: a conversion unit, a first calculation unit, a second calculation unit, and a processing unit; wherein,

[0094] The conversion unit is configured to convert the M radio frequency signals from any Z visible satellites into M digital intermediate frequency sampling signals.

[0095] The first calculation unit is configured to: calculate the first filter coefficient vector when filtering with a preset filter for each obtained digital intermediate frequency sampling signal, based on the preset constraint vector;

[0096] The second calculation unit is set to: calculate the second filtering coefficient vector of the beam channel of each of the Z visible satellites according to the direction of arrival of each visible satellite;

[0097] The processing unit is configured to: filter the digital intermediate frequency sampling signal according to the calculated first and second filter coefficient vectors to obtain the Z-channel first output signal;

[0098] Where M is the number of array elements of the ground receiver, and the number of spatial interferences that result in the output signal is greater than M-1.

[0099] In one exemplary instance, the conversion unit of this embodiment of the invention is configured as follows:

[0100] The M radio frequency signals are processed by analog-to-digital conversion to obtain M digital intermediate frequency sampling signals.

[0101] In one exemplary instance, the first computing unit of this embodiment of the invention is configured as follows:

[0102] Based on the preset constraint vector, calculate the initial values ​​of the diagonal matrix of the preset filter and the first filter coefficient vector for iteration;

[0103] The first filter coefficient vector is determined based on the calculated diagonal matrix and the initial values ​​of the iteration;

[0104] The first filter coefficient vector for filtering the signal with sampling time point i+1 in the m-th digital intermediate frequency sampled signal is: μ is a constant coefficient, x m (i) represents the signal with sampling time point i in the m-th digital intermediate frequency sampling signal. For y mThe adjoint matrix of (i), y m (i) The second output signal corresponding to the m-th digital intermediate frequency sampling signal, w m (0) is the initial value for iteration, F is a diagonal matrix; m and i are positive integers, m = 1, 2, ..., M.

[0105] In one exemplary instance, the second computing unit of this embodiment of the invention is configured as follows:

[0106] Based on the direction of arrival, determine the steering vector of the satellite signal of each of the Z visible satellites;

[0107] Based on the determined steering vector, calculate the first correlation matrix of the digital intermediate frequency sampled signal at sampling time point i;

[0108] Based on the calculated first correlation matrix, calculate the signal-to-noise ratio of the digital intermediate frequency sampled signal of each visible satellite at sampling time point i when filtered according to the first filtering coefficient vector;

[0109] Based on the calculated signal-to-noise ratio, the second filter coefficient vector of the beam channel for each visible satellite is determined.

[0110] In one exemplary instance, the second calculation unit of this embodiment of the invention is configured to calculate the first correlation matrix of the digital intermediate frequency sampled signal at sampling time point i, including:

[0111] For the digital intermediate frequency sampled signal at sampling time point i, calculate the second correlation matrix of the second output signal obtained by filtering according to the first filter coefficient vector;

[0112] Based on the steering vector, calculate the third correlation matrix of the satellite signal of the z-th visible satellite in the digital intermediate frequency sampled signal at sampling time point i;

[0113] The calculated second and third correlation matrices are added together to obtain the first correlation matrix.

[0114] In one exemplary instance, the second correlation matrix in this embodiment of the invention is calculated using the following formula:

[0115]

[0116] In the formula, E represents the mean, y m This indicates the second output signal.

[0117] In one exemplary instance, the third correlation matrix in this embodiment of the invention is calculated using the following formula:

[0118]

[0119] In the formula, It is the amplitude of the satellite signal of the z-th visible satellite. Let be the steering vector of the satellite signal from the z-th visible satellite. The direction of the incoming wave from the z-th visible satellite is given.

[0120] In one exemplary instance, the second calculation unit in this embodiment of the invention is configured to: calculate the signal-to-noise ratio of the digital intermediate frequency sampled signal of each visible satellite at sampling time point i when filtered according to the first filter coefficient vector, including:

[0121] Based on the first correlation matrix and the first filter coefficient vector, determine the first signal power p of the digital intermediate frequency sampled signal before filtering by the preset filter. x ;

[0122] Based on the third correlation matrix and the first filter coefficient vector, determine the second signal power of the second output signal after filtering by the preset filter.

[0123] The first signal power p at sampling time point i x (i) Subtract the second signal power at sampling time point i Obtain the noise power p at sampling time point i n (i);

[0124] According to noise power p n (i) and the second signal power at sampling time point i Calculate the signal-to-noise ratio ρ z (i);

[0125] Wherein, the subscript z represents the z-th satellite, and z takes any value from 1 to Z.

[0126] In one exemplary instance, the expression for the second filter coefficient vector in this embodiment of the invention is:

[0127]

[0128] Where, q z (i+1) represents the second filter coefficient vector corresponding to the sampling time point i+1 of the z-th satellite, q z (i) represents the second filter coefficient vector corresponding to the sampling time point i of the z-th satellite, ρ z (i) represents the signal-to-noise ratio at sampling time point i corresponding to the z-th satellite, and λ is the preset step coefficient; R x R represents the first correlation matrix; ym The second correlation matrix represents the second output signal.

[0129] In one exemplary instance, the expression for the first output signal in this embodiment of the invention is:

[0130]

[0131] Among them, B z (i) represents the signal with sampling time point i in the first output signal output by the z-th satellite. Represents the second filter coefficient vector q z The transpose conjugate matrix of (i); Indicates w m The transpose conjugate matrix of (i), w m (i) represents the first filter coefficient vector for filtering the signal with sampling time point i in the m-th digital intermediate frequency sampled signal, x m (i) represents the digital intermediate frequency sampled signal at sampling time i, y m (i) is the second output signal obtained by filtering the m-th digital intermediate frequency sampling signal according to the first filtering coefficient vector when the sampling time point is i.

[0132] This application also provides a beamforming apparatus 1, such as... Figure 4 As shown, it includes a processor 11 and a computer-readable storage medium 12, which stores instructions that, when executed by the processor 11, implement the above-described beamforming method.

[0133] In the exemplary embodiments of this application, any of the aforementioned beamforming methods are applicable to this device embodiment, and will not be described in detail here.

[0134] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

Claims

1. A method for beam forming, comprising: converting M-channel received radio frequency signals of any Z visible satellites into M-channel digital intermediate frequency sample signals; calculating, for each obtained digital intermediate frequency sample signal, a first filter coefficient vector when filtering with a preset filter according to a preset constraint vector; calculating a second filter coefficient vector of a beam channel of each of the Z visible satellites according to a direction of arrival of each of the Z visible satellites; filtering the digital intermediate frequency sample signals according to the calculated first filter coefficient vector and the second filter coefficient vector to obtain Z-channel first output signals; wherein M is a number of ground receiver array elements, a number of spatial interferences for obtaining the output signals is greater than M-1; the calculating the second filter coefficient vector of the beam channel of each of the Z visible satellites comprises: determining a steering vector of a satellite signal of each of the any Z visible satellites according to the direction of arrival; calculating a first correlation matrix of the digital intermediate frequency sample signal at a sampling time point i according to the determined steering vector; calculating a signal-to-noise ratio of the digital intermediate frequency sample signal of each of the visible satellites when filtering according to the first filter coefficient vector at the sampling time point i according to the calculated first correlation matrix; and determining the second filter coefficient vector of the beam channel of each of the visible satellites according to the calculated signal-to-noise ratio.

2. The method of claim 1, wherein, the calculating the first filter coefficient vector when filtering with the preset filter according to the preset constraint vector comprises: calculating a diagonal matrix of the preset filter and an iterative initial value of the first filter coefficient vector according to the preset constraint vector; determining the first filter coefficient vector according to the calculated diagonal matrix and the iterative initial value; The first filtering coefficient vector of the preset filter for filtering the signal of the sampling time point i+1 in the mth digital intermediate frequency sampling signal is: μ is a constant coefficient, x m (i) is the signal of the sampling time point i in the mth digital intermediate frequency sampling signal, is y m is the adjoint matrix of (i), y m (i) is the second output signal corresponding to the mth digital intermediate frequency sampling signal, w m (0) is an iteration initial value, F is a diagonal matrix; m and i are positive integers, m=1, 2, …, M, i=1, 2, …, L, and L is the total length of the sequence of the digital intermediate frequency sampling signal.

3. The method according to claim 1 or 2, characterized in that, the calculating the first correlation matrix of the digital intermediate frequency sample signal at the sampling time point i comprises: calculating a second correlation matrix of a second output signal obtained by filtering the digital intermediate frequency sample signal at the sampling time point i according to the first filter coefficient vector; calculating a third correlation matrix of a satellite signal of the zth visible satellite in the digital intermediate frequency sample signal at the sampling time point i according to the steering vector; adding the calculated second correlation matrix and the third correlation matrix to obtain the first correlation matrix.

4. The method of claim 3, wherein, the second correlation matrix is calculated by the following formula: where E denotes averaging, y m denotes the second output signal.

5. The method of claim 3, wherein, the third correlation matrix is calculated by the following formula: wherein is the amplitude of the satellite signal of the zth visible satellite, is the direction vector of the satellite signal of the zth visible satellite, is the direction of arrival of the satellite signal of the zth visible satellite.

6. The method of claim 1 or 2, wherein, the calculating the signal-to-noise ratio of the digital intermediate frequency sample signal of each of the visible satellites when filtering according to the first filter coefficient vector at the sampling time point i comprises: determining a first signal power p of the digital intermediate frequency sampling signal before filtering by the preset filter according to the first correlation matrix and the first filter coefficient vector x ; determining a second signal power of a second output signal filtered by the preset filter according to the third correlation matrix and the first filter coefficient vector The first signal power p at sampling time point i x (i) Subtract the second signal power at sampling time point i Obtain the noise power p at sampling time point i n (i); According to the noise power p n (i) and the second signal power at the sampling time point i The signal-to-noise ratio p z (i); wherein subscript z represents the zth satellite, and z takes any value in 1 to Z.

7. The method of claim 6, wherein, an expression of the second filter coefficient vector is: wherein q z is the second filter coefficient vector corresponding to the zth satellite at the sampling time point i+1, q z is the second filter coefficient vector corresponding to the zth satellite at the sampling time point i, p z is the signal-to-noise ratio at the sampling time point i of the zth satellite, and l is a preset step coefficient; R x represents the first correlation matrix; R ym represents the second correlation matrix of the second output signal.

8. The method of claim 1 or 2, wherein, an expression of the first output signal is: where B z (i) is a signal at the sampling time point i in the first output signal output by the zth satellite, denotes a second filter coefficient vector q z (i) is a transposed conjugate matrix of (i); denotes w m (i) is a transposed conjugate matrix of (i), w m (i) denotes a first filter coefficient vector for filtering a signal at the sampling time point i in the mth digital intermediate frequency sampling signal, x m (i) denotes a digital intermediate frequency sampling signal at the sampling time point i, y m (i) is a second output signal obtained by filtering the mth digital intermediate frequency sampling signal at the sampling time point i according to the first filter coefficient vector.

9. An apparatus for beamforming, comprising: a converting unit, a first calculating unit, a second calculating unit, and a processing unit; wherein the converting unit is configured to convert M-channel received radio frequency signals of any Z visible satellites into M-channel digital intermediate frequency sample signals; the first calculating unit is configured to calculate, for each obtained digital intermediate frequency sample signal, a first filter coefficient vector when filtering with a preset filter according to a preset constraint vector; the second calculating unit is configured to calculate a second filter coefficient vector of a beam channel of each of the Z visible satellites according to a direction of arrival of each of the Z visible satellites; and the processing unit is configured to filter the digital intermediate frequency sample signals according to the calculated first filter coefficient vector and the second filter coefficient vector to obtain Z-channel first output signals. The second computing unit is configured to calculate a second filter coefficient vector of a beam channel of each of the Z visible satellites according to a direction of arrival of each of the visible satellites; The processing unit is configured to filter the digital intermediate frequency sampling signals according to the calculated first filter coefficient vector and the second filter coefficient vector to obtain Z first output signals; Wherein, M is the number of ground receiver array elements, the number of spatial interferences of the output signals is greater than M-1; the second filter coefficient vector of the beam channel of each of the Z visible satellites comprises: determining a steering vector of a satellite signal of each of the Z visible satellites according to the direction of arrival; calculating a first correlation matrix of the digital intermediate frequency sampling signals at a sampling time point i according to the determined steering vector; calculating a signal-to-noise ratio of the digital intermediate frequency sampling signals of each of the visible satellites at the sampling time point i when the first filter coefficient vector is used for filtering according to the calculated first correlation matrix; and determining the second filter coefficient vector of the beam channel of each of the visible satellites according to the calculated signal-to-noise ratio.

10. An apparatus for beamforming, comprising a processor and a computer readable storage medium having instructions stored therein, the instructions, when executed by the processor, cause the processor to perform operations comprising: When the instructions are executed by the processor, the method for beam forming according to any one of claims 1-8 is implemented.

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