Low-orbit satellite time-frequency aliasing signal blind source separation method and system

Abstract

The invention relates to the technical field of wireless communication and communication reconnaissance, and particularly discloses a blind source separation method and system for time-frequency aliasing signals of low-orbit satellites, and the method comprises the steps: carrying out the time-frequency synchronization of a plurality of low-orbit satellites; fusing the received signals of the plurality of low-orbit satellites to obtain a fused signal; performing blind source separation on the fusion signal to obtain multiple paths of signals; the multiple paths of signals comprise a target signal and other separation signals; and identifying a target signal from the multiple paths of signals. According to the method, under the condition of signal time-frequency aliasing, a target communication signal is separated to improve communication quality or create favorable conditions for signal feature extraction.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communication and communication reconnaissance, and in particular to a method and system for blind source separation of time-frequency aliasing signals of low-orbit satellites. Background Art

[0002] Satellite Internet can make up for the insufficient coverage of terrestrial Internet in remote areas, plateaus, deserts, the sky and the ocean, and has become an important means of providing ubiquitous connectivity. The space-ground Internet has become one of the important development trends of 5G-A (5G-Advanced) and 6G. Among them, high-orbit satellite communication technology is relatively mature and has the advantage of large transmission capacity, but it faces the problem of excessive transmission delay. At present, the low-Earth orbit satellite (LEO) information network with low latency advantage is rapidly rising; in addition to commercial value, the low-Earth orbit satellite network has strong survivability due to its huge number, and can provide emergency communication guarantee when natural disasters such as earthquakes and tsunamis damage the ground communication infrastructure.

[0003] In the case of cooperative communication, the received signals of low-orbit satellites of other constellations will inevitably contain the same-frequency signals of Starlink. Moreover, low-orbit electronic reconnaissance satellites have become an important platform for communication reconnaissance. In confrontation scenarios, the satellite end is extremely susceptible to co-frequency interference, which will also cause the reconnaissance satellite to receive time-frequency aliasing signals. Therefore, low-orbit satellites are currently facing the problem of signal time-frequency aliasing under low signal-to-noise ratio conditions: for cooperative communication, communication performance will be seriously affected; for communication reconnaissance, it will cause difficulties in the extraction and analysis of target signals. If the aliased signal is separable in the time domain or frequency domain, it can be processed by time domain or frequency domain filtering and other technologies. However, for mixed signals that overlap in both time and frequency domains, conventional filtering technology is difficult to produce results. Therefore, there is an urgent need to carry out research on the separation technology of time-frequency aliasing signals of low-orbit satellites. Summary of the invention

[0004] In view of the above problems, an object of the present invention is to provide a method for blind source separation of low-orbit satellite time-frequency aliasing signals. In the case of signal time-frequency aliasing, this method separates the target communication signal to improve the communication quality or create favorable conditions for signal feature extraction.

[0005] The second object of the present invention is to provide a blind source separation system for low-orbit satellite time-frequency aliasing signals.

[0006] The first technical solution adopted by the present invention is: a method for blind source separation of low-orbit satellite time-frequency aliasing signals, comprising the following steps:

[0007] S100: synchronize the time and frequency of multiple low-orbit satellites, and fuse the received signals of the multiple low-orbit satellites to obtain a fused signal;

[0008] S200: performing blind source separation on the fused signal to obtain a multi-path signal; wherein the blind source separation includes: constructing a fused signal matrix based on the fused signal, and solving the fused signal matrix based on a separation algorithm; the multi-path signal includes a target signal and other separated signals;

[0009] S300: Identify a target signal from the multiple signals.

[0010] Preferably, the step S100 includes:

[0011] Based on the global navigation satellite system, multiple low-orbit satellites are synchronized in time and frequency.

[0012] Preferably, the step S100 includes:

[0013] Each low-orbit satellite sends its received signal to its adjacent low-orbit satellite or ground station via laser or wireless means, and the adjacent low-orbit satellite or ground station fuses the received signals to obtain a fused signal.

[0014] Preferably, the fusion signal matrix is ​​expressed by the following formula:

[0015] R = AS + N (2)

[0016] When there are two source signals and two receiving satellites: In the formula, R = [r1, r2] T is the fusion signal set; S = [s1, s2] T is the source signal set; N = [n1, n2] T is a noise signal set; A=[a 11 , a 12 ; a 21 , a 22 ] is the mixing coefficient matrix, [·] T Represents matrix transpose.

[0017] Preferably, the separation algorithm includes one of the following methods: fast independent separation analysis, joint diagonalization of eigenvalue matrix groups, second-order blind identification, fourth-order blind identification, equivariant adaptive source separation based on independence, information level maximization, maximum likelihood algorithm, and underdetermined separation method based on sparse characteristics of signals in time domain or transform domain.

[0018] Preferably, the S300 includes:

[0019] A target signal is identified from the multipath signals based on prior information of the target signal, wherein the prior information includes one or more of a carrier frequency, a symbol rate, a bandwidth, and a modulation mode of the target signal.

[0020] Preferably, the S300 further includes: synchronizing, demodulating, and decoding the target signal to restore the information sequence.

[0021] Preferably, the S300 further includes: performing feature extraction on the other separated signals.

[0022] The second technical solution adopted by the present invention is: a blind source separation system for low-orbit satellite time-frequency aliasing signals, comprising a fusion module, a separation module and an identification module;

[0023] The fusion module is used to synchronize the time and frequency of multiple low-orbit satellites and fuse the received signals of the multiple low-orbit satellites to obtain a fused signal;

[0024] The separation module is used to perform blind source separation on the fused signal to obtain a multi-channel signal; wherein the blind source separation includes: constructing a fused signal matrix based on the fused signal, and solving the fused signal matrix based on a separation algorithm; the multi-channel signal includes a target signal and other separated signals;

[0025] The identification module is used to identify a target signal from the multi-path signals.

[0026] Preferably, the identification module is used to perform the following operations:

[0027] A target signal is identified from the multipath signals based on prior information of the target signal, wherein the prior information includes one or more of a carrier frequency, a symbol rate, a bandwidth, and a modulation mode of the target signal.

[0028] Beneficial effects of the above technical solution:

[0029] (1) The present invention discloses a method for blind source separation of low-orbit satellite time-frequency aliasing signals. When a low-orbit satellite receives signals with time-frequency aliasing, the method can effectively separate the target communication signal from other signals, thereby improving the communication quality of the target signal and creating favorable conditions for feature extraction of other separated signals.

[0030] (2) The present invention adopts blind source separation (BSS) to solve the problem of multiple time-frequency aliasing signals obtained by distributed reception of multiple low-orbit satellites, so as to separate multiple source signals from the observed mixed signals by only using the statistical characteristics of the signal in the case of unknown or small amount of prior information; the present invention uses blind source separation and other technologies to separate weak target signals from time-frequency aliasing signals, which is of great significance to low-orbit satellite anti-interference communication and communication reconnaissance.

[0031] (3) The present invention fuses signals through multiple low-orbit satellites, and then uses blind source separation to separate the time-frequency aliased target signal and interference signal (i.e., other separated signals), thereby improving the anti-interference capability of wireless communication and enhancing the ability to extract target signal features. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic flow chart of a method for blind source separation of low-orbit satellite time-frequency aliasing signals provided by an embodiment of the present invention;

[0033] Figure 2 A schematic diagram of a signal time-frequency aliasing situation provided by an embodiment of the present invention;

[0034] Figure 3 A schematic structural diagram of a blind source separation system for low-orbit satellite time-frequency aliasing signals provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0035] The following detailed description of the embodiments of the present invention is further described in detail in conjunction with the accompanying drawings and examples. The detailed description of the following embodiments and the accompanying drawings are used to exemplarily illustrate the principles of the present invention, but cannot be used to limit the scope of the present invention, that is, the present invention is not limited to the preferred embodiments described, and the scope of the present invention is defined by the claims.

[0036] In the description of the present invention, it should be noted that, unless otherwise specified, “plurality” means two or more than two; the terms “first”, “second”, etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance; for ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0037] Embodiment 1

[0038] like Figure 1 As shown, an embodiment of the present invention provides a method for blind source separation of low-orbit satellite time-frequency aliasing signals, comprising the following steps:

[0039] S100: synchronize the time and frequency of multiple low-orbit satellites based on the global navigation satellite system; and fuse the received signals of multiple low-orbit satellites to obtain a fused signal;

[0040] like Figure 2 As shown in the figure, R1, R2, and R3 are low-orbit satellites, T1 and T2 are satellite communication equipment in the target area, T3 is a high-power interference device, and G is a ground gateway (i.e., ground station). Multiple low-orbit satellites can obtain time information through GNSS / GPS or BeiDou system, so R1, R2, and R3 can be synchronized in time and frequency.

[0041] Since T1, T2, and T3 are all within the satellite's beam range, the signals received by each satellite are the aliasing form of the T1, T2, and T3 transmission signals; in particular, in order to achieve a better interference effect, the working frequency band of high-power interference equipment should cover the T1 and T2 signal bands, and the receiving signals of R1, R2, and R3 are further manifested in the form of time-frequency aliasing.

[0042] Fusion of received signals from multiple low-orbit satellites includes:

[0043] Each low-orbit satellite sends its received signal to its adjacent low-orbit satellite (i.e., neighboring satellite) or ground station via laser or wireless means. The adjacent low-orbit satellite or ground station fuses the received signals to obtain a fused signal (i.e., the fused signal).

[0044] The received signals can be fused between R1, R2 and R3 through laser or wireless communication, and the low-orbit satellite and the ground gateway can communicate at high speed through the C, Ku or Ka bands. For satellites in transparent forwarding working mode, the fused signal can be obtained at the ground gateway. For satellites with signal processing functions, the processing can be performed on the low-orbit satellite (satellite end). Therefore, the signal separation work disclosed in the present invention can be performed either on the satellite end or on the ground end.

[0045] The present invention synchronizes the time and frequency of multiple low-orbit satellites to make the fused signal more accurate.

[0046] S200: performing blind source separation on the fused signal to obtain multi-path signals;

[0047] Low-orbit satellites or ground stations use the fused signals to perform blind source separation, including:

[0048] A fusion signal matrix is ​​constructed based on the fusion signal, and the fusion signal matrix is ​​solved based on a separation algorithm to obtain multi-channel signals, wherein the multi-channel signals include target signals and other separated signals, and the other separated signals include interference signals, noise signals, other communication signals, etc.

[0049] The separation algorithms include fast independent separation analysis (fastICA), joint diagonalization of eigenvalue matrices (JADE), second-order blind identification (SOBI), fourth-order blind identification (FOBI), equivariant adaptive source separation based on independence (EASI), information level maximization (InfoMax), maximum likelihood (ML) algorithm, and one of the underdetermined separation methods based on the sparse characteristics of the signal in the time domain or transform domain.

[0050] The blind source separation process of the present invention is described by taking the fusion of two satellite signals as an example; assuming that the communication signal is s1 and the co-frequency interference signal is s2, under the condition of linear instantaneous mixing, the received signals r1 and r2 obtained by fusion of the two satellites can be expressed in the form of formula (1):

[0051]

[0052] Where r1 is the fusion signal received by satellite 1; r2 is the fusion signal received by satellite 2; a ij (1≤i≤2, 1≤j≤2) is the mixing coefficient, which represents the mixing relationship from the source signal to the received signal; n1 and n2 are noise signals; s1 is the communication signal; and s2 is the interference signal.

[0053] It can be seen from formula (1) that each received signal contains both the useful communication signal s1 and the interference signal s2, so a good communication effect cannot be achieved.

[0054] Formula (1) can be further written into the matrix form shown in formula (2), that is, the fusion signal matrix is ​​expressed by the following formula:

[0055] R = AS + N (2)

[0056] When there are two source signals and two receiving satellites: In the formula, R = [r1, r2] T is the fusion signal set; S = [s1, s2] T is the source signal set; N = [n1, n2] T is a noise signal set; A=[a 11 , a 12 ; a 21 , a 22 ] is the mixing coefficient matrix, [·] T Represents matrix transpose.

[0057] For the fusion signal shown in formula (2), the inverse matrix W≈A of the mixing matrix can be solved by blind source separation methods such as fast independent component analysis (fastICA), joint approximate diagonalization of feature matrix groups (JADE), second-order blind identification (SOBI), fourth-order blind identification (FOBI), equivariant adaptive source separation based on independence (EASI), information maximization (Infomax), maximum likelihood (ML) algorithm, and underdetermined separation methods based on the sparse characteristics of the signal in the time domain or transform domain. -1 , and then the signal separation is achieved through formula (3):

[0058] Y = WR ≈ A -1 (AS + N) = S + N' (3)

[0059] Where, Y represents the multi-channel signal; S represents the source signal; N' represents the noise signal; W represents the inverse matrix of the mixing matrix A; R is the fusion signal set; S is the source signal set; N is the noise signal set; A = [a 11 , a 12 ; a 21 , a 22 ] is the mixing matrix.

[0060] Formula (3) shows that the Y multi-channel signal is only the sum of the source signal and the noise signal. Each source signal contains only s1 or s2. Therefore, Y = [y1, y2] T Among them, one signal is an accurate estimate of the useful signal s1, and the other signal is an accurate estimate of the interference signal s2.

[0061] Formula (1) is explained by taking an ideal linear instantaneous mixing as an example. For the cases of fading channel and Doppler delay, the signals can be separated by converting them into the frequency domain.

[0062] S300: identifying a target signal from the multiple signals;

[0063] The low-orbit satellite or ground station identifies the target signal from the separated multi-path signals, including: identifying the target signal from the multi-path signals based on prior information of the target signal, wherein the prior information includes the carrier frequency, symbol rate, bandwidth, modulation mode, etc. of the target signal.

[0064] Furthermore, the S300 further includes: performing subsequent communication signal processing on the target signal;

[0065] The subsequent communication signal processing of the target signal by the low-orbit satellite or ground station includes: the low-orbit satellite or ground station synchronizes, demodulates, and decodes the target signal to restore the information sequence.

[0066] Furthermore, the S300 also includes: the low-orbit satellite or ground station extracts features of other separated signals, including: estimating communication parameters, cumulants and cyclic statistics of other separated signals, such as carrier frequency, modulation mode, symbol rate, etc.

[0067] Embodiment 2

[0068] like Figure 3 As shown, an embodiment of the present invention provides a low-orbit satellite time-frequency aliasing signal blind source separation system, including a fusion module, a separation module and an identification module;

[0069] The fusion module is used to synchronize the time and frequency of multiple low-orbit satellites and fuse the received signals of the multiple low-orbit satellites to obtain a fused signal;

[0070] The separation module is used to perform blind source separation on the fused signal to obtain a multi-channel signal; wherein the blind source separation includes: constructing a fused signal matrix based on the fused signal, and solving the fused signal matrix based on a separation algorithm; the multi-channel signal includes a target signal and other separated signals;

[0071] The identification module is used to identify a target signal from the multi-path signals.

[0072] The identification module is used to perform the following operations:

[0073] A target signal is identified from the multipath signals based on prior information of the target signal, wherein the prior information includes one or more of a carrier frequency, a symbol rate, a bandwidth, and a modulation mode of the target signal.

[0074] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the embodiments of the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0075] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0076] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0077] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0078] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks.

[0079] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for blind source separation of low-orbit satellite time-frequency aliasing signals, characterized in that: The following steps are involved: S100: synchronize the time and frequency of multiple low-orbit satellites, and fuse the received signals of the multiple low-orbit satellites to obtain a fused signal; S200: performing blind source separation on the fused signal to obtain a multi-path signal; wherein the blind source separation includes: constructing a fused signal matrix based on the fused signal, and solving the fused signal matrix based on a separation algorithm; the multi-path signal includes a target signal and other separated signals; S300: Identify a target signal from the multiple signals.

2. The method for blind source separation of low-orbit satellite time-frequency aliasing signals according to claim 1, characterized in that: The step S100 includes: Based on the global navigation satellite system, multiple low-orbit satellites are synchronized in time and frequency.

3. The method for blind source separation of low-orbit satellite time-frequency aliasing signals according to claim 1, characterized in that: The step S100 includes: Each low-orbit satellite sends its received signal to its adjacent low-orbit satellite or ground station via laser or wireless means, and the adjacent low-orbit satellite or ground station fuses the received signals to obtain a fused signal.

4. The method for blind source separation of low-orbit satellite time-frequency aliasing signals according to claim 1, characterized in that: The fusion signal matrix is ​​expressed by the following formula: R = AS + N (2) When there are two source signals and two receiving satellites: In the formula, R = [r1, r2] T is the fusion signal set; S = [s1, s2] T is the source signal set; N = [n1, n2] T is a noise signal set; A=[a 11 , a 12 ; a 21 , a 22 ] is the mixing coefficient matrix, [·] T Represents matrix transpose.

5. The method for blind source separation of low-orbit satellite time-frequency aliasing signals according to claim 1, characterized in that: The separation algorithm includes one of the following methods: fast independent separation analysis, joint diagonalization of eigenvalue matrix groups, second-order blind identification, fourth-order blind identification, equivariant adaptive source separation based on independence, information maximization, maximum likelihood algorithm, and underdetermined separation method based on sparse characteristics of signal time domain or transform domain.

6. The method for blind source separation of low-orbit satellite time-frequency aliasing signals according to claim 1, characterized in that: The S300 includes: A target signal is identified from the multipath signals based on prior information of the target signal, wherein the prior information includes one or more of a carrier frequency, a symbol rate, a bandwidth, and a modulation mode of the target signal.

7. The method for blind source separation of low-orbit satellite time-frequency aliasing signals according to claim 1, characterized in that: The S300 also includes: synchronizing, demodulating, and decoding the target signal to restore the information sequence.

8. The method for blind source separation of low-orbit satellite time-frequency aliasing signals according to claim 1, characterized in that: The S300 further includes: performing feature extraction on the other separated signals.

9. A blind source separation system for low-orbit satellite time-frequency aliasing signals, characterized in that: It includes fusion module, separation module and recognition module; The fusion module is used to synchronize the time and frequency of multiple low-orbit satellites and fuse the received signals of the multiple low-orbit satellites to obtain a fused signal; The separation module is used to perform blind source separation on the fused signal to obtain a multi-channel signal; wherein the blind source separation includes: constructing a fused signal matrix based on the fused signal, and solving the fused signal matrix based on a separation algorithm; the multi-channel signal includes a target signal and other separated signals; The identification module is used to identify a target signal from the multi-path signals.

10. The blind source separation system for low-orbit satellite time-frequency aliasing signals according to claim 9, characterized in that: The identification module is used to perform the following operations: A target signal is identified from the multipath signals based on prior information of the target signal, wherein the prior information includes one or more of a carrier frequency, a symbol rate, a bandwidth, and a modulation mode of the target signal.

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