Satellite navigation anti-jamming method based on blind signal separation
By receiving mixed signals with a single antenna and employing a blind signal separation method, the channel consistency and spatial adaptation problems of array antennas in satellite navigation anti-interference technology were solved, enabling signal separation and navigation information extraction under complex layout conditions.
Patent Information
- Application Number
- CN202610591744.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-04-30
- Publication Date
- 2026-07-10
AI Technical Summary
Existing satellite navigation anti-jamming technologies rely on array antennas, which require strict amplitude and phase characteristics of array elements and specific spatial layouts. This leads to complex channel consistency control and difficulties in array spatial adaptation, making it difficult to apply effectively on space-constrained platforms.
A mixture of satellite navigation and interference signals is received using several single antennas. An anti-interference model is established through a blind signal separation method. The mixture matrix is solved to separate the signals and extract navigation information.
It achieves the separation of satellite navigation signals and interference signals in interference environments, reduces dependence on array antenna layout, improves the stability and engineering adaptability of the processing flow, and can effectively extract navigation information under complex layout conditions.
Smart Images
Figure CN122362430A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of communication signal anti-interference technology, and specifically to a satellite navigation anti-interference method based on blind signal separation. Background Technology
[0002] Global Navigation Satellite Systems (GNSS) receive signals with relatively low power upon reaching the ground, making them susceptible to intentional or unintentional electromagnetic interference. Therefore, in the field of satellite navigation anti-interference, existing technologies typically employ array antennas to receive spatial signals from satellites and interference sources, combined with methods such as spatial beamforming, nulling, or space-time adaptive processing to suppress interference signals and maintain the receiver's positioning, velocity measurement, and timing capabilities. In engineering applications, this type of technology usually requires multiple array elements to work collaboratively, and a signal processing model is established based on the array manifold, the spatial relationships between array elements, and the consistency of responses across channels.
[0003] According to the research findings in "Impact on Antijamming Performance of Channel Mismatch in GNSS Antenna Arrays Receivers" (Lu et al., 2016), the anti-jamming performance of existing GNSS arrays is significantly limited by channel mismatch. Interference can only be fully suppressed when the amplitude and phase characteristics of each array channel are consistent. However, in actual engineering implementation, manufacturing errors of analog devices such as low-noise amplifiers, filters, and frequency converters, as well as environmental factors, can cause amplitude and phase inconsistencies between channels, leading to channel mismatch and a decrease in anti-jamming performance. Among these factors, the amplitude fluctuation range and group delay deviation have the most significant impact. Meanwhile, according to the research and analysis in "Inherent Trade-Offs Between the Conflicting Aspects of Designing the Compact Global Navigation Satellite System (GNSS) Anti-Interference Array" (Li et al., 2025), traditional GNSS anti-interference arrays usually use an element spacing of about half a wavelength. As the number of elements increases, the array size will increase rapidly. Under the condition of limited platform space, large-scale array deployment is difficult to achieve. On the other hand, further compressing the element spacing within the limited space will bring about problems such as null widening, mutual coupling enhancement, reduced signal-to-noise ratio after compensation, and reduced receiver availability, thereby further aggravating the difficulties of array antenna in platform adaptation, layout design and engineering implementation.
[0004] Therefore, the fundamental flaw in existing satellite navigation anti-jamming technologies lies in the fact that their anti-jamming models and processing effects are generally based on the stability of the array manifold, the consistency of channel amplitude and phase, and the specific spatial layout relationship of array elements. This subjectes existing technologies to the dual constraints of channel consistency control and array spatial adaptation. On the one hand, strict control and calibration of the amplitude and phase characteristics of array elements are required, increasing the complexity of system implementation and maintenance. On the other hand, the requirements for the overall array size and element spacing further increase the demands on antenna layout and installation space, significantly limiting their application on space-constrained platforms. Therefore, it is necessary to propose a satellite navigation anti-jamming method based on blind signal separation to address the above problems. Summary of the Invention
[0005] To address the aforementioned problems, this invention provides a satellite navigation anti-interference method based on blind signal separation. This method receives a mixed signal of satellite navigation signal and interference signal through several single antennas, separates the satellite navigation signal and interference signal using a blind signal separation method, and extracts navigation information by processing the separated signal data.
[0006] To achieve the above objectives, the technical solution of the present invention is as follows: a satellite navigation anti-interference method based on blind signal separation, comprising the following steps: Step 1, Mixed Signal Acquisition: Using several single antennas to simultaneously receive a mixed signal containing both satellite navigation signals and interference signals. For mixed signals Perform digital sampling to obtain mixed signal data ; Step 2, Anti-interference model construction: based on the number of single antennas and mixed signals Establish a mathematical model for anti-interference processing of satellite navigation signals; Step 3, Solving the mixing matrix: From the mixed signal data The length of the cut-off is Mixed signal data samples A blind signal separation method was used to analyze the mixed signal data samples. Process and solve the mixture matrix. ; Step 4, Signal Separation Processing: Separate the mixed signal data... Mixture matrix with solution Weighting operations, from mixed signal data Separate satellite navigation signal data and interference signal data in the middle; Step 5, Navigation Information Extraction: Solve the separated signal data to extract navigation information.
[0007] The technical principles of the above solution are as follows: This invention first receives a mixed signal containing satellite navigation signals and interference signals using several single antennas, and then digitally samples the mixed signal to obtain mixed signal data. Subsequently, based on the number of single antennas and the mixed signal, a mathematical model for anti-interference processing of satellite navigation signals is established, transforming the signal reception problem into a mixed signal separation problem. Based on this, mixed signal data samples are extracted from the mixed signal data. And a blind signal separation method was used to separate the mixed signal data samples. The solution mixture matrix is obtained by processing and solving. Then the mixed signal data and the demixing matrix are combined. Weighted calculations are performed to separate satellite navigation signal data from interference signal data. Finally, the separated signal data is processed to extract navigation information, thereby completing the anti-interference processing for satellite navigation.
[0008] The above approach has the following beneficial effects: 1. This invention uses several single antennas to receive a mixed signal of satellite navigation signal and interference signal, and adopts a blind signal separation method to separate the satellite navigation signal and interference signal. It can extract navigation information in the interference environment, thereby solving the problems of existing satellite navigation anti-interference technology relying heavily on array antennas, having strict requirements on the amplitude and phase characteristics of array elements, and having high requirements on antenna layout and layout space.
[0009] 2. This invention processes signals in the order of mixed signal acquisition, anti-interference model construction, solving the mixed matrix, signal separation and processing, and navigation information extraction. The steps are clearly connected, forming a complete anti-interference processing flow, which is conducive to improving the stability and execution efficiency of the processing flow.
[0010] 3. This invention can not only separate satellite navigation signals and interference signals, but also identify signal data from which navigation information can be extracted by solving the separated signal data, thus taking into account both anti-interference processing effect and navigation information extraction effect, and has good engineering adaptability.
[0011] Furthermore, in step one, the number of single antennas satisfy .
[0012] Beneficial effects: This setup ensures that the signal receiver has at least a multi-channel observation foundation, enabling subsequent mixed signal modeling, sample organization, and blind signal separation processing to be feasible. This provides a foundation for solving the mixing matrix and separating satellite navigation signals from interference signals, and improves the feasibility and stability of the entire anti-interference processing flow.
[0013] Furthermore, in step one, the arrangement of several single antennas does not constitute an array manifold with a specific mutual positional relationship.
[0014] Beneficial effects: This setup eliminates the reliance on the fixed geometric manifold relationship of the array antennas and eliminates the need to strictly design the relative positions of each individual antenna according to the array processing method. This reduces the difficulty of deploying individual antennas, reduces the constraints on installation space and layout during deployment, and facilitates implementation in scenarios with limited space or complex layout conditions.
[0015] Furthermore, in step one, the interference pattern of the interference signal does not include the deceptive interference pattern.
[0016] Beneficial effects: This setting clarifies the applicable interference boundary of this scheme, focusing the anti-interference processing on non-deceptive interference signals. This helps maintain the consistency of modeling conditions and subsequent blind signal separation processing targets, avoids unclear processing logic due to mixed interference types, and improves the pertinence and stability of the method when applied.
[0017] Furthermore, in step one, the mixed signal Number of interference signals Less than the number of single antennas ,satisfy .
[0018] Beneficial effects: This setting ensures that the dimension of the received observation is greater than the number of interference signals, which is conducive to meeting the basic dimension conditions for subsequent mixed signal separation processing, making the solution of the mixing matrix more feasible, thereby improving the stability of the separation of satellite navigation signals and interference signals, and providing a more reliable data foundation for accurate extraction of navigation information.
[0019] Furthermore, in step two, in the mathematical model for anti-interference processing of satellite navigation signals, let the number be... Single antenna receiving signal It includes satellite navigation signals within the line of sight of this single antenna. and interference signals The mixed signal is specifically expressed as follows: (1); in For the first The signal arrived with the number [number missing]. The amplitude weighting coefficient of a single antenna; Will The signals received by each individual antenna can be represented in matrix form, resulting in: (2); in It is a mixed signal. To mix the original satellite navigation signal and the interference signal vector, It is a mixed matrix; The specific form is as follows: (3).
[0020] Beneficial effects: This setup expands the mixed signal received by a single antenna from a single-channel representation to a unified matrix representation, making the correspondence between satellite navigation signals, interference signals, and the results received by each single antenna clearer. This provides a unified mathematical foundation for subsequent sample matrix construction, preprocessing, objective function establishment, and solution of the mixed matrix, and helps to transform the signal reception problem into a computable and iterative signal separation problem.
[0021] Furthermore, the hybrid matrix in the mathematical model for anti-interference processing of satellite navigation signals In signal reception, digital sampling, and finally obtaining mixed signal data During the process, the satellite navigation signal strength and interference signal power remain constant, the signal transmission distance to each individual antenna remains unchanged, and the hybrid matrix... Each component does not change with time and is considered constant; the mixture matrix... Represented as: (4).
[0022] Beneficial effects: This setting treats the amplitude weighting relationship in the signal reception process as a stable constant, reducing the impact of time-varying factors on the mixture model, making the mixture matrix expression more stable. This helps maintain the consistency of subsequent sample processing, objective function construction, and iterative solution of the mixture matrix, improving the stability of the model solution process and the reliability of anti-interference processing results.
[0023] Furthermore, in step three, the mixed signal data samples for A matrix, specifically in the form of: (5).
[0024] Beneficial effects: This setting organizes the data samples extracted from the mixed signal data into a unified matrix form, so that the number of single antennas and the length of data samples are clearly correlated in the same data structure. This facilitates the continuous development of subsequent centering, whitening, objective function construction and iterative calculation, and improves the standardization and computational convenience of mixed signal sample processing.
[0025] Furthermore, in step three, a blind signal separation method is used to separate the mixed signal data samples. The processing includes the following steps: S3-1, for mixed signal data samples Preprocessing is required; S3-2, construct the objective function using the fourth-order cumulant of the preprocessed whitened mixed signal data Z; S3-3, Initialize the initial value of the iteration operation and set the loop variable for the iteration operation. The initial value is 1, that is Set intermediate variables for the demixing matrix. It is zero, that is Set the initial values for the demixing matrix iteration. It is a random quantity, that is ; S3-4, Update the solution mixture matrix Based on the objective function constructed in S3-2, according to the formula: (6); Solution to the mixture matrix Perform update calculations; S3-5, Orthogonal solution of mixed matrix Based on the results of the S3-4 iteration calculation, according to the formula: (7); For the updated solution mixing matrix Orthogonalization was performed, where, It is an orthogonal separation matrix. ,satisfy ; S3-6, Standardized Solution Mixture Matrix Based on the orthogonalization calculation results of S3-5, according to the formula: (8); Orthogonal solution of the hybrid matrix Standardization processing is required; S3-7 checks the convergence of the iterative operation. Based on the normalized calculation results in S3-6, a constant less than 1 is set. The standardized solution mixing matrix is subjected to the following conditions. Perform convergence testing: Condition 1: When solving the mixture matrix Satisfy the following formula: (9); make Return to S3-4 to continue the iterative calculation; Condition 2: When solving the mixture matrix Satisfy the following formula: (10); make Output the demixing matrix Stop the iterative calculation.
[0026] Beneficial effects: This setup clearly divides the blind signal separation process into continuous steps such as preprocessing, objective function establishment, initialization, updating, orthogonalization, standardization, and convergence detection, so that the solution process of the mixed matrix has a complete and clear iterative chain, which helps to improve the coherence, operability and convergence stability of the algorithm execution process, and enhances the overall reliability of the separation and processing of satellite navigation signals and interference signals.
[0027] Furthermore, in S3-1, the mixed signal data samples... Preprocessing includes the following steps: S3-1.1, Centralized processing of mixed signal data samples Obtain zero-mean mixed signal data ,in: (11); S3-1.2, Whitening of zero-mean mixed signal data Obtain whitened mixed signal data ,in: (12); Whitening matrix for Matrix, and satisfy: (13); In S3-2, the preprocessed whitened mixed signal data The objective function is constructed using fourth-order cumulants, including whitening and mixing data matrices. The objective function is constructed using fourth-order cumulants. The specific expression is: (14); in This is a penalty factor. Attached Figure Description
[0028] Figure 1 This is a step diagram of an embodiment of the satellite navigation anti-interference method based on blind signal separation of the present invention.
[0029] Figure 2 This is a schematic diagram of the mathematical model of an embodiment of the satellite navigation anti-interference method based on blind signal separation of the present invention.
[0030] Figure 3 This is a waveform diagram of the satellite navigation signal and the interference signal before mixing, representing an embodiment of the satellite navigation anti-interference method based on blind signal separation of the present invention.
[0031] Figure 4This is a waveform diagram of the separated satellite navigation signal and interference signal in an embodiment of the satellite navigation anti-interference method based on blind signal separation of the present invention.
[0032] Figure 5 This is a schematic diagram showing the correlation coefficient curves between satellite navigation signals before and after mixing, and between the separated satellite navigation signal and the mixed signal, in an embodiment of the satellite navigation anti-interference method based on blind signal separation of the present invention. Detailed Implementation
[0033] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0034] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.
[0035] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.
[0036] The following detailed description illustrates the specific implementation method: Implementation, for example, attached Figure 1 As shown, a satellite navigation anti-jamming method based on blind signal separation includes the following steps: Step 1, Mixed Signal Acquisition: Using several single antennas to simultaneously receive a mixed signal containing both satellite navigation signals and interference signals. For mixed signals Perform digital sampling to obtain mixed signal data Number of single antennas satisfy Several single-antenna layouts do not constitute an array manifold with a specific mutual positional relationship; the interference pattern of the interfering signal does not include deceptive interference patterns; mixed signals Number of interference signals Less than the number of single antennas ,satisfy .
[0037] Step 2, Anti-interference model construction: such as Figure 2 As shown, based on the number of single antennas and mixed signals Establish a mathematical model for anti-interference processing of satellite navigation signals; in the mathematical model for anti-interference processing of satellite navigation signals, assume that the number is... Single antenna receiving signal It includes satellite navigation signals within the line of sight of this single antenna. and interference signals The mixed signal is specifically expressed as follows: (1); in For the first The signal arrived with the number [number missing]. The amplitude weighting coefficient of a single antenna; Will The signals received by each individual antenna can be represented in matrix form, resulting in: (2); in It is a mixed signal. To mix the original satellite navigation signal and the interference signal vector, It is a mixed matrix; The specific form is as follows: (3); Hybrid matrix in the mathematical model for anti-interference processing of satellite navigation signals In signal reception, digital sampling, and finally obtaining mixed signal data During the process, the satellite navigation signal strength and interference signal power remain constant, the signal transmission distance to each individual antenna remains unchanged, and the hybrid matrix... Each component does not change with time and is considered constant; the mixture matrix... Represented as: (4).
[0038] Step 3, Solving the mixing matrix: From the mixed signal data The length of the cut-off is Mixed signal data samples A blind signal separation method was used to analyze the mixed signal data samples. Process and solve the mixture matrix. Mixed signal data samples for A matrix, specifically in the form of: (5); Blind signal separation method for mixed signal data samples The processing includes the following steps: S3-1, for mixed signal data samples Preprocessing includes the following steps: S3-1.1, Centralized processing of mixed signal data samples Obtain zero-mean mixed signal data ,in: (11); S3-1.2, Whitening of zero-mean mixed signal data Obtain whitened mixed signal data ,in: (12); Whitening matrix for Matrix, and satisfy: (13); S3-2, using preprocessed whitened mixed signal data The objective function is constructed using fourth-order cumulants, including whitening and mixing data matrices. The objective function is constructed using fourth-order cumulants. The specific expression is: (14); in This is a penalty factor.
[0039] S3-3, Initialize the initial value of the iteration operation and set the loop variable for the iteration operation. The initial value is 1, that is Set intermediate variables for the demixing matrix. It is zero, that is Set the initial values for the demixing matrix iteration. It is a random quantity, that is ; S3-4, Update the solution mixture matrix Based on the objective function constructed in S3-2, according to the formula: (6); Solution to the mixture matrix Perform update calculations; S3-5, Orthogonal solution of mixed matrix Based on the results of the S3-4 iteration calculation, according to the formula: (7); For the updated solution mixing matrix Perform orthogonalization; in, It is an orthogonal separation matrix. ,satisfy ; S3-6, Standardized Solution Mixture Matrix Based on the orthogonalization calculation results of S3-5, according to the formula: (8); Orthogonal solution of the hybrid matrix Standardization processing is required; S3-7 checks the convergence of the iterative operation. Based on the normalized calculation results in S3-6, a constant less than 1 is set. The standardized solution mixing matrix is subjected to the following conditions. Perform convergence testing: Condition 1: When solving the mixture matrix Satisfy the following formula: (9); make Return to S3-4 to continue the iterative calculation; Condition 2: When solving the mixture matrix Satisfy the following formula: (10); make Output the demixing matrix Stop the iterative calculation.
[0040] Specifically, to separate satellite navigation signals and interference signals from mixed signals, it is necessary to analyze the mixed signal data. The length of the cut-off is Mixed signal data samples To improve the algorithm's convergence performance and reduce computational load during the calculation process, the mixed signal data samples were processed. After preprocessing, the objective function is constructed, the mixing matrix is iteratively updated, and convergence is checked.
[0041] Step 4, Signal Separation Processing: Separate the mixed signal data... Mixture matrix with solution Weighting operations, from mixed signal data Separate satellite navigation signal data and interference signal data in the middle; Step 5, Navigation Information Extraction: The separated signal data is processed to extract navigation information. Specifically, due to the uncertainty of the order of blind signal separation results, all separated signal data is processed simultaneously. Satellite navigation signal data is identified from the signal data from which navigation information can be extracted, and the navigation information is extracted. Navigation information cannot be extracted from interference signal data.
[0042] The experiment verified the following: Experimental objective: To verify the separation effect of satellite navigation signals and interference signals and the ability to extract navigation information in the presence of interference signals in this embodiment.
[0043] Experimental Method: The GPS satellite navigation system L1 frequency C / A code satellite navigation signal was selected as the satellite navigation signal, and a noise-modulated frequency (FM) interference signal was selected as the interference signal. The center frequency of the noise-modulated frequency interference signal was made consistent with the center frequency of the L1 signal of the satellite navigation system, and the interference-to-signal ratio was 30 dB after normalization of the satellite navigation signal amplitude. The frequency modulation function had a mean of zero, a variance of 0.3, and followed a normal distribution within a given interval. Five single antennas were used to simultaneously receive the mixed signal of the superimposed satellite navigation signal and the noise-modulated frequency interference signal. The received mixed signal was processed according to the technical solution of this embodiment to separate the satellite navigation signal and the interference signal. The separated signal was then processed to extract navigation information. To analyze the signal quality before and after separation and evaluate the algorithm performance, a correlation coefficient was introduced as an evaluation criterion. The correlation coefficient is used to measure the similarity between the estimated signal and the original signal.
[0044] Experimental results: The waveforms of the pre-mixed satellite navigation signal and interference signal are as follows: Figure 3 As shown, the waveforms of the separated satellite navigation signal and interference signal are as follows: Figure 4 As shown, the correlation coefficient curves between the satellite navigation signals before and after mixing, and the correlation coefficient curve between the separated satellite navigation signals and the mixed signals are as follows: Figure 5 As shown. By Figure 4 It can be seen that, compared with the signal before mixing, the separated satellite navigation signal and the interference signal still have amplitude uncertainty, but the effective separation of satellite navigation signal and interference signal has been achieved.
[0045] Results Analysis: Ten sets of mixed signals containing satellite navigation signals and interference signals were generated at 1dB intervals from 25dB to 34dB interference-to-signal ratio. Following the technical solution of this embodiment, the satellite navigation signals and interference signals were separated from the mixed signals. The correlation coefficients between the satellite navigation signals before and after separation, and between the separated satellite navigation signals and the mixed signals, were calculated. The results are as follows: Figure 5 As shown. By Figure 5It can be seen that the satellite navigation signals before and after mixing have good correlation, and the correlation coefficient between the separated satellite navigation signal and the mixed signal is significantly improved. At the same time, as the interference-to-signal ratio increases, the correlation coefficient between the satellite navigation signals before and after mixing and after separation is relatively stable, while the correlation coefficient between the separated satellite navigation signal and the mixed signal decreases significantly. This indicates that this embodiment has a good separation effect on satellite navigation signals and interference signals, and can recover satellite navigation signals relatively stably.
[0046] This embodiment receives a mixture of satellite navigation signals and interference signals using several single antennas. By combining blind signal separation processing, demixing matrix solving, signal separation, and navigation information extraction, it can effectively separate satellite navigation signals and interference signals in the presence of noise-induced frequency modulation interference and complete navigation information extraction. This verifies that the technical solution of this embodiment has good anti-interference processing capabilities and navigation information extraction capabilities.
[0047] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.
Claims
1. A satellite navigation anti-interference method based on blind signal separation, characterized in that, Includes the following steps: Step 1, Mixed Signal Acquisition: Using several single antennas to simultaneously receive a mixed signal containing both satellite navigation signals and interference signals. For mixed signals Perform digital sampling to obtain mixed signal data ; Step 2, Anti-interference model construction: based on the number of single antennas and mixed signals Establish a mathematical model for anti-interference processing of satellite navigation signals; Step 3, Solving the mixing matrix: From the mixed signal data The length of the cut-off is Mixed signal data samples A blind signal separation method was used to analyze the mixed signal data samples. Process and solve for the mixture matrix. ; Step 4, Signal Separation Processing: Separate the mixed signal data... Mixture matrix with solution Weighting operations, from mixed signal data Separate satellite navigation signal data and interference signal data in the middle; Step 5, Navigation Information Extraction: Solve the separated signal data to extract navigation information.
2. The satellite navigation anti-interference method based on blind signal separation according to claim 1, characterized in that, In step one, the number of single antennas satisfy .
3. The satellite navigation anti-interference method based on blind signal separation according to claim 2, characterized in that, In step one, the arrangement of several single antennas does not constitute an array manifold with a specific mutual positional relationship.
4. The satellite navigation anti-interference method based on blind signal separation according to claim 3, characterized in that, In step one, the interference pattern of the interference signal does not include the deceptive interference pattern.
5. The satellite navigation anti-interference method based on blind signal separation according to claim 4, characterized in that, In step one, the mixed signal Number of interference signals Less than the number of single antennas ,satisfy .
6. The satellite navigation anti-interference method based on blind signal separation according to claim 5, characterized in that, In step two, within the mathematical model for anti-interference processing of satellite navigation signals, the part numbered... Single antenna receiving signal Includes satellite navigation signals within the line of sight of this single antenna. and interference signals The mixed signal is specifically expressed as follows: （1）； in For the first The signal arrived with the number [number missing]. The amplitude weighting coefficient of a single antenna; Will The signals received by each individual antenna can be represented in matrix form, resulting in: （2）； in It is a mixed signal. To mix the original satellite navigation signal and the interference signal vector, It is a mixed matrix; The specific form is as follows: （3）。 7. The satellite navigation anti-interference method based on blind signal separation according to claim 6, characterized in that, Hybrid matrix in the mathematical model for anti-interference processing of satellite navigation signals In signal reception, digital sampling, and finally obtaining mixed signal data During the process, the satellite navigation signal strength and interference signal power remain constant, the signal transmission distance to each individual antenna remains unchanged, and the hybrid matrix... Each component does not change with time and is considered constant; the mixture matrix... Represented as: （4）。 8. The satellite navigation anti-interference method based on blind signal separation according to claim 7, characterized in that, In step three, the mixed signal data samples for A matrix, specifically in the form of: （5）。 9. The satellite navigation anti-interference method based on blind signal separation according to claim 8, characterized in that, In step three, a blind signal separation method is used to separate the mixed signal data samples. The processing includes the following steps: S3-1, for mixed signal data samples Preprocessing is required; S3-2, using preprocessed whitened mixed signal data The objective function is constructed using fourth-order cumulants; S3-3, Initialize the initial value of the iteration operation and set the loop variable for the iteration operation. The initial value is 1, that is Set intermediate variables for the demixing matrix. It is zero, that is Set the initial values for the demixing matrix iteration. It is a random quantity, that is ; S3-4, Update the solution mixture matrix Based on the objective function constructed in S3-2, according to the formula: （6）； Solution to the mixture matrix Perform update calculations; S3-5, Orthogonal solution of mixed matrix Based on the results of the S3-4 iteration calculation, according to the formula: （7）； For the updated solution mixing matrix Perform orthogonalization; in, It is an orthogonal separation matrix. ,satisfy ; S3-6, Standardized Solution Mixture Matrix Based on the orthogonalization calculation results of S3-5, according to the formula: （8）； Orthogonal solution of the hybrid matrix Standardize the process; S3-7 checks the convergence of the iterative operation. Based on the normalized calculation results in S3-6, a constant less than 1 is set. The standardized solution mixing matrix is subjected to the following conditions. Perform convergence testing: Condition 1: When solving the mixture matrix Satisfy the following formula: （9）； make Return to S3-4 to continue the iterative calculation; Condition 2: When solving the mixture matrix Satisfy the following formula: （10）； make Output the demixing matrix Stop the iterative calculation.
10. The satellite navigation anti-interference method based on blind signal separation according to claim 9, characterized in that, In S3-1, for mixed signal data samples Preprocessing includes the following steps: S3-1.1, Centralized processing of mixed signal data samples Obtain zero-mean mixed signal data ,in: （11）； S3-1.2, Whitening of zero-mean mixed signal data Obtain whitened mixed signal data ,in: （12）； Whitening matrix for Matrix, and satisfy: （13）； In S3-2, the preprocessed whitened mixed signal data The objective function is constructed using fourth-order cumulants, including whitening and mixing data matrices. The objective function is constructed using fourth-order cumulants. The specific expression is: （14）； in This is a penalty factor.