A method for anti-interference in airspace

Abstract

The present invention discloses a spatial domain anti-interference method, which relates to the field of signal processing. The method comprises: based on the power inversion anti-interference method, a weighted processing is performed on the first received signal received by the first antenna module and the second received signal received by the second antenna module to obtain a first composite signal; based on the reference sequence correlation peak search, the first correlation peak is determined according to the first composite signal, and the second correlation peak and the third correlation peak are determined according to the first received signal and the second received signal; the reference signal index position is determined according to the first correlation peak, the second correlation peak and the third correlation peak; based on the MMSE method, the second composite signal after interference suppression is determined according to the reference signal index position, the first received signal and the second received signal. Compared with the prior art, the present invention can meet the interference suppression of a large dynamic range interference-to-signal ratio, and can effectively suppress interference signals in both high interference-to-signal ratio and low interference-to-signal ratio conditions.

Description

Technical Field

[0001] The present invention relates to the field of signal processing technology, and more specifically, to a spatial domain anti-interference method. Background Art

[0002] Anti-interference is an important function of wireless communication systems, and interference suppression is usually performed from multiple dimensions such as time domain, frequency domain, and spatial domain. For co-frequency and full-band interference, the spatial domain anti-interference method is often used. Its principle is to eliminate the interference signal and achieve interference suppression by utilizing the different directions of the useful signal and the interference signal. This method requires the use of a multi-antenna array in hardware. In order to facilitate the antenna layout of communication equipment in the ultra-short wave frequency band, the antenna is generally required to use the simplest dual-antenna array method in actual engineering.

[0003] In the case of dual-antenna array reception, there are two main types of applicable spatial anti-interference algorithms:

[0004] (I) Blind algorithms that do not require prior information, typically the power inversion anti-interference method (PI), which works on the principle of minimizing the array output power under certain constraints to suppress strong signals. However, its disadvantage is that it does not distinguish whether the corresponding signal is a useful signal or an interference signal during the suppression of strong signals. Therefore, it is not suitable for situations where the power of the useful signal is greater than that of the interference signal and the powers of the two signals are equal. In addition, while the strong interference signal is suppressed, the weak useful signal will also lose some energy, which will affect the demodulation of subsequent useful signals.

[0005] (ii) Anti-interference algorithms based on prior information, typically the minimum mean square error (MMSE) anti-interference method based on a reference sequence. This algorithm is suitable for wireless communication systems that contain known reference sequences in the transmission data frames. It minimizes the mean square error between the output signal and the reference sequence by adjusting the channel weighting coefficients of the receiving antenna array, thereby achieving interference signal suppression. However, its disadvantage is that it requires a pre-search for the reference sequence in the received data frame (limited by the demodulation threshold of the reference sequence search). If the interference-to-signal ratio (the power ratio of the interference signal to the useful signal) is high and exceeds the reference sequence correlation search demodulation threshold, the reference sequence cannot be found and the algorithm becomes invalid. Summary of the invention

[0006] In order to overcome the defect of the prior art that it is not possible to perform interference suppression with both low interference-to-signal ratio and high interference-to-signal ratio, the present invention provides a spatial domain anti-interference method.

[0007] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0008] In a first aspect, a spatial domain anti-interference method is applied to a multi-antenna array, wherein the multi-antenna array includes at least a first antenna module and a second antenna module;

[0009] The method comprises:

[0010] Based on a power inversion anti-interference method, a first received signal received by the first antenna module and a second received signal received by the second antenna module are weighted to obtain a first composite signal;

[0011] Based on the reference sequence correlation peak search, determining a first correlation peak value according to the first synthesized signal, and determining a second correlation peak value and a third correlation peak value according to the first received signal and the second received signal;

[0012] Determine a reference signal index position according to the first correlation peak value, the second correlation peak value, and the third correlation peak value;

[0013] Based on the MMSE method, a second composite signal after interference suppression is determined according to the reference signal index position, the first received signal and the second received signal.

[0014] In a second aspect, an electronic device includes:

[0015] A memory for storing computer executable instructions or computer programs;

[0016] The processor is used to implement the method described in the first aspect when executing the computer executable instructions or computer program stored in the memory.

[0017] In a third aspect, a computer program product comprises a computer program or computer executable instructions, wherein when the computer program or computer executable instructions are executed by a processor, the method described in the first aspect is implemented.

[0018] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0019] The spatial domain anti-interference method provided by the present invention is implemented based on at least two antenna modules. When the interference-to-signal ratio of the received signal is higher than the correlation peak search threshold, the PI algorithm is used to suppress strong interference to obtain the first synthetic signal and determine the first correlation peak value through the reference sequence correlation peak search; when the interference-to-signal ratio is lower than the correlation peak search threshold, the reference sequence correlation peak search is directly performed on the two received signals to obtain the second correlation peak value and the third correlation peak value, and then the reference sequence index position is determined according to the three correlation peak values ​​to ensure that the reference sequence in the received signal data frame can be searched; after finding the reference sequence, the MMSE method is introduced to the received data frame for processing to achieve interference suppression. Compared with the prior art, the method described in the present invention can meet the interference suppression of a large dynamic range interference-to-signal ratio, and can effectively suppress interference signals in both high interference-to-signal ratio and low interference-to-signal ratio conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1This is a flow chart of the airspace anti-interference method in Example 1 of the present application;

[0021] Figure 2 Schematic diagram of the process of the MMSE method in Example 1 of the present application;

[0022] Figure 3 This is a schematic diagram of the process of searching for peaks related to the reference sequence in Example 1 of the present application;

[0023] Figure 4 This is a schematic diagram of the generation process of the first synthetic signal in Example 1 of the present application;

[0024] Figure 5 This is a flow chart of the spatial domain anti-interference method in Example 2 of the present application. DETAILED DESCRIPTION

[0025] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged in appropriate cases, which is only to describe the distinction mode adopted by the objects of the same attributes in the embodiments of the present application when describing. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment containing a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment. The term "determine" widely covers various actions, and may include acquisition, calculation, calculation, processing, derivation, investigation, search (for example, search in a table, database or other data structure), ascertainment, and similar actions, and may also include reception (for example, receiving information), access (for example, accessing data in a memory) and similar actions, and may also include generation, creation, establishment and similar actions, as well as parsing, selection, selection and similar actions, etc. The relevant definitions of other terms will be given in the following description.

[0026] The drawings are for illustrative purposes only and should not be construed as limiting the present patent;

[0027] In order to better illustrate the present embodiment, some parts in the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0028] It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0029] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0030] Example 1

[0031] This embodiment provides a spatial domain anti-interference method, which is applied to a multi-antenna array, wherein the multi-antenna array includes at least a first antenna module and a second antenna module;

[0032] Referring to FIG. 1 , the method includes:

[0033] Based on the power inversion anti-interference method, a first received signal received by the first antenna module and a second received signal received by the second antenna module are weighted to obtain a first composite signal (i.e., a PI composite signal);

[0034] Based on the reference sequence correlation peak search, determining a first correlation peak value according to the first synthesized signal, and determining a second correlation peak value and a third correlation peak value according to the first received signal and the second received signal;

[0035] Determine a reference signal index position according to the first correlation peak value, the second correlation peak value, and the third correlation peak value;

[0036] Based on the MMSE method, a second composite signal after interference suppression (ie, the MMSE composite signal, which is the final output signal) is determined according to the reference signal index position, the first received signal, and the second received signal.

[0037] In this embodiment, when the interference-to-signal ratio of the received signal is higher than the correlation peak search threshold, the PI algorithm is used to suppress strong interference to obtain the first synthetic signal and determine the first correlation peak value through the reference sequence correlation peak search; when the interference-to-signal ratio is lower than the correlation peak search threshold, the reference sequence correlation peak search is directly performed on the two received signals to obtain the second correlation peak value and the third correlation peak value, and then the reference sequence index position is determined according to the three correlation peak values ​​to ensure that the reference sequence in the received signal data frame can be searched; after finding the reference sequence, the MMSE method is introduced to the received data frame to achieve interference suppression. Compared with the prior art, this embodiment can meet the interference suppression of a large dynamic range of interference-to-signal ratios, and can effectively suppress interference signals in both high and low interference-to-signal ratios.

[0038] In particular, the multi-antenna array is preferably a dual-antenna array.

[0039] In some specific implementations, the one with a higher correlation peak value among the first correlation peak value, the second correlation peak value, and the third correlation peak value is selected as a representative correlation peak value for determining the reference signal index position.

[0040] In some preferred embodiments, referring to FIG. 2 , the determining of the second composite signal after interference suppression includes:

[0041] Determine a reference sequence position according to the reference signal index position, and extract a corresponding predicted reference sequence from the first received signal and the second received signal;

[0042] Determine the secondary weighting coefficient by using the predicted reference sequence and the preset local training sequence ;

[0043] Using the quadratic weighting coefficient , performing secondary weighted processing on the first received signal and the second received signal to obtain the second composite signal.

[0044] Those skilled in the art should understand that the principle of the MMSE spatial domain anti-interference algorithm is to use the mean square error between the local reference sequence and the predicted sequence as the optimization target, obtain the optimal weighting coefficient of each received signal through the least squares optimization algorithm, and perform weighted summation on the signals of each channel to obtain the predicted value to achieve interference suppression.

[0045] In some optional embodiments, in order to improve the reliability of the system in a complex electromagnetic interference environment, the MMSE method uses a windowing method combined with a dilated convolution and a cross-symbol training strategy to generate a more accurate spatial anti-interference weighting coefficient (i.e., the quadratic weighting coefficient) under the condition of fewer training samples, thereby effectively improving the spatial resolution of useful signal sources and interference signal sources, while improving the ability of the received signal to resist interference in the weak signal (near the demodulation sensitivity) space, and optimizing the algorithm's spatial anti-interference performance.

[0046] Further, according to the reference signal index position, a corresponding predicted reference sequence is extracted from the first received signal and the second received signal;

[0047] Performing windowing processing on the predicted reference sequence to obtain a windowed data matrix of two antennas;

[0048] The windowed data matrices of the two antennas are spliced ​​to obtain a data matrix ;

[0049] The data matrix With the local training sequence Perform correlation operation to obtain a cross-correlation vector;

[0050] The data matrix Perform an autocorrelation operation to obtain an autocorrelation matrix, and perform an inverse operation on the autocorrelation matrix to obtain an inverse autocorrelation matrix;

[0051] The inverse autocorrelation matrix is ​​multiplied by the cross-correlation vector to obtain the optimal quadratic weighting coefficient .

[0052] In some specific implementations, the windowing method combined with dilated convolution includes:

[0053] Performing windowing processing on the prediction reference sequences corresponding to the received first channel reception signal and the second channel reception signal to obtain windowed data matrices of the two channels;

[0054] Determine the cross-correlation vector and the autocorrelation matrix according to the windowed data matrices of the two channels;

[0055] A quadratic weighting coefficient is determined according to the mutual correlation vector and the autocorrelation matrix; wherein the quadratic weighting coefficient is used to perform a dilated convolution on the first channel received signal and the second channel received signal to obtain a composite signal after interference suppression.

[0056] The windowing process includes:

[0057] Define the expansion rate parameter to represent the sample point interval between adjacent sampling points;

[0058] Using a filter with a window size and an expansion rate, according to a preset sliding step, the window corresponding to the sequence data at the current moment is respectively shifted leftward and rightward on the time axis, and sliding filtering is performed to obtain the forward window data and the backward window data at the current moment respectively;

[0059] The forward window data, the backward window data and the current time data are spliced ​​to obtain the windowed data matrix; wherein the mathematical expression of the corresponding predicted value at each moment in the windowed data matrix is:

[0060]

[0061] In the formula, Indicates the current moment, Indicates The current moment prediction value of each channel, Represents a splicing operation, represents the expansion rate; Indicates the window size; Indicates The sample value of each channel.

[0062] And, the cross-symbol training strategy includes:

[0063] The sliding step size during windowing is set to be the same as the sampling multiple, so that samples predicted by different windows correspond to different symbols.

[0064] It should be noted that by setting a window, using the sample values ​​of the previous and next moments to predict the sample value of the current moment, and utilizing the correlation between adjacent sample points, the utilization rate of data information is increased, thereby improving the prediction accuracy. To achieve the addition of holes (i.e., the sample intervals between adjacent sampling points), the method can cover a reasonable range of time windows without adding too much computational complexity. Compared with ordinary convolution methods, the hole convolution uses the method of adding holes to balance prediction performance and complexity without adding too much computational complexity on the basis of covering a reasonable range of time windows. In some examples, the hole convolution is implemented by sliding filtering the time series data received by the antenna channel based on the filter.

[0065] It should also be noted that the sliding step size during training (i.e., the process of obtaining the quadratic weighting coefficient) is set to the number of sample points represented by the symbol, i.e., the sampling multiple, which is conducive to increasing the diversity of training data. If the sliding step size is not set to the sampling multiple, there may be some repeated information between training samples. This is because two or more samples may represent the same symbol. The cross-symbol training strategy ensures that the amount of information in the training samples is maximized.

[0066] In particular, for the sampling point at the initial moment, the data cannot shift left on the time axis, and 0 is used as the forward window data at that moment; for the sampling point at the end moment, the data cannot shift right on the time axis, and 0 is used as the backward window data at that moment.

[0067] Furthermore, in order to filter out the interference of each sample point, in some preferred embodiments, when the first channel received signal and the second channel received signal are subjected to sliding filtering using a filter carrying the quadratic weighting coefficient, the sliding step size of the sliding window is set to a single sample point, that is, sample point-by-sample weighted processing is performed to achieve prediction of all sample points.

[0068] In some preferred embodiments, the reference sequence correlation peak search is implemented based on signal energy correlation detection.

[0069] In some optional embodiments, referring to FIG. 3 , the reference sequence correlation peak search includes:

[0070] Design matched filter parameters: determine the I-path matched filter and the Q-path matched filter according to the preset local reference sequence;

[0071] Matched filtering: after decomposing the signal to be processed into an I-path signal and a Q-path signal, input each signal into the I-path matched filter and the Q-path matched filter respectively to obtain corresponding matched filtering results; the signal to be processed is the first synthesized signal, the first received signal or the second received signal;

[0072] Calculating the cross-correlation energy: determining the cross-correlation energy value between the reference sequence of the signal to be processed and the local reference sequence according to the matched filtering result;

[0073] Calculating autocorrelation energy: determining an autocorrelation energy value according to the I-path signal and the Q-path signal;

[0074] The quotient between the mutual correlation energy value and the autocorrelation energy value is taken as the corresponding correlation peak value.

[0075] Exemplarily, the local reference sequence includes but is not limited to a ZC sequence and a chu sequence.

[0076] Further, the determining of the cross-correlation energy value includes:

[0077] The matched filtering result obtained by processing the I-path signal through the I-path matched filter is defined as a first I-path matched filtering result, and the matched filtering result obtained by processing the Q-path matched filter is defined as a first Q-path matched filtering result; the matched filtering result obtained by processing the Q-path signal through the I-path matched filter is defined as a second I-path matched filtering result, and the matched filtering result obtained by processing the Q-path matched filter is defined as a second Q-path matched filtering result;

[0078] The first I-path matched filtering result and the second Q-path matched filtering result, and the first Q-path matched filtering result and the second I-path matched filtering result, are respectively subjected to addition and subtraction operations and square operations to obtain the mutual correlation energy value.

[0079] Furthermore, the expression of the correlation peak is:

[0080]

[0081] In the formula, Represents the local reference sequence Length, Indicates the received signal; represents the subscript index of the local reference sequence; Indicates the position of the slide search.

[0082] It can be understood that in the above formula, the numerator represents the correlation energy between the received signal reference sequence and the local reference sequence (i.e., the cross-correlation energy value), and the denominator represents the received reference sequence energy (i.e., the autocorrelation energy value). Dividing the cross-correlation energy by the autocorrelation energy is actually energy normalization. Otherwise, under different signal strengths, the calculated correlation peak value will continue to change and cannot be uniformly measured. After the signal energy is normalized, a unified scale can be used for comparison.

[0083] It should be emphasized that in the prior art, the method of directly calculating the signal energy is generally used to determine the correlation peak, and the amplitude of the received signal must be within a certain range to accurately determine. The method of signal energy correlation detection in this embodiment can reduce the requirements for the amplitude of the received signal, and can still accurately detect and determine within a large dynamic range of the received signal.

[0084] Those skilled in the art should understand that the reference sequence length can be designed according to the frame length, and selecting a suitable length requires a balance between performance and complexity.

[0085] Further, the determining of the autocorrelation energy value includes:

[0086] The I-path signal and the Q-path signal are squared respectively, and the obtained square results are added to obtain the autocorrelation energy value.

[0087] It can be understood that before the I-path signal and the Q-path signal are squared, the I-path signal and the Q-path signal are delayed.

[0088] In some preferred embodiments, a primary weighting coefficient for performing the primary weighting process is determined based on a power inversion anti-interference method. .

[0089] In some specific implementations, referring to FIG. 4 , the dual antenna array receiving signals are defined as , , the generation process of the first synthetic signal includes:

[0090] Using the power inversion anti-interference method, according to , Calculate the weighted coefficient ;

[0091] Using a primary weighting factor right , After weighted processing is performed on one of the signals, the weighted result is added to the other signal to obtain a PI composite signal (ie, the first composite signal).

[0092] In some preferred embodiments, before performing the reference sequence correlation peak search and / or the MMSE method on the first received signal and the second received signal, delay processing is performed on the first received signal and the second received signal to synchronize the data before and after the processing in the time dimension.

[0093] Example 2

[0094] To facilitate those skilled in the art to implement the method described in Example 1, this embodiment provides a more preferred specific implementation method based on a dual antenna array, referring to FIG5 , including:

[0095] S10, the dual antenna array receiving signals are , , 2 channels of data enter three branches for processing at the same time.

[0096] S20, first branch A: signal , Enter the PI algorithm module of branch A and use the power inversion algorithm to obtain a weighted coefficient , for data , Perform weighted processing (strong signal suppression), search for reference sequence correlation peaks on the synthetic signal after weighted processing, and record the peak value of the correlation peak (i.e. the first correlation peak).

[0097] S30, Second Branch B: Signal , First enter the delay module of branch B data, and then , Perform a reference sequence correlation peak search and record the inspection peak of the correlation peak, i.e. the second correlation peak and the third correlation peak .

[0098] S40, Peak , and , enter the peak comparison selection module, select the one with the higher correlation peak value, and determine the reference signal index position index.

[0099] S50, the third branch C: data , Enter the delay module of branch C, and then enter the MMSE algorithm module. The MMSE method determines the reference sequence position according to the reference signal index position index indication signal, reads the received reference sequence data, and calculates the secondary weighting coefficient together with the local training sequence , and finally the data , Weighted processing is performed to obtain a composite signal after interference suppression.

[0100] It can be understood that the options in the above-mentioned embodiment 1 are also applicable to this embodiment, so they will not be described again here.

[0101] Example 3

[0102] This embodiment provides a computer-readable storage medium, on which is stored at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by a processor, so that the processor executes part or all of the steps of the method provided in Example 1 of the present application.

[0103] It is understood that the storage medium may be transient or non-transient. Exemplarily, the storage medium includes, but is not limited to, a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0104] Exemplarily, the processor may be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA).

[0105] Exemplarily, the read-only memory includes but is not limited to MASK ROM, PROM, EPROM, EEPROM, Flash, etc.

[0106] Exemplarily, the random access memory includes but is not limited to DRAM, SRAM, SDRAM, DDR SDRAM, etc.

[0107] In some examples, a computer program product is provided, which can be implemented in hardware, software or a combination thereof. As a non-limiting example, the computer program product can be embodied as the storage medium, or as a software product, such as an SDK (Software Development Kit).

[0108] As a non-limiting example, a computer program product is provided, the computer program product includes a computer program or a computer executable instruction, the computer program or the computer executable instruction is stored in a computer-readable storage medium. A processor of an electronic device reads the computer program or the computer executable instruction from the computer-readable storage medium, and the processor executes the computer executable instruction, so that the electronic device performs some or all steps of the method described in the embodiment of the present application.

[0109] In some examples, a computer program is provided, comprising a computer-readable code, and when the computer-readable code is run in a computer device, a processor in the computer device executes a part or all of the steps in the method.

[0110] This embodiment also proposes an electronic device, including a memory and a processor, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and when the processor executes the at least one instruction, at least one program, a code set or an instruction set, it implements part or all of the steps of the method described in Example 1.

[0111] In some examples, a hardware entity of the electronic device is provided, including: a processor, a memory and a communication interface; wherein the processor generally controls the overall operation of the electronic device; the communication interface is used to enable the electronic device to communicate with other terminals or servers through a network; the memory is configured to store instructions and applications executable by the processor, and can also cache data to be processed or processed by the processor and various modules in the electronic device (including but not limited to image data, audio data, voice communication data and video communication data), which can be implemented by flash memory (FLASH), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM) or random access memory (RAM).

[0112] The processor may include one or more processing elements. Thus, the processor may include one or more integrated circuits (ICs) configured to perform the functions of the processor. In addition, each integrated circuit may include circuits (e.g., a first circuit, a second circuit, and other circuits, etc.) configured to perform the functions of the processor.

[0113] Furthermore, data may be transmitted between the processor, the communication interface and the memory via a bus, which may include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and memories together.

[0114] It can be understood that the options in the above-mentioned embodiment 1 are also applicable to this embodiment, so they will not be described again here.

[0115] The same or similar reference numerals correspond to the same or similar components;

[0116] The terms used to describe the positional relationship in the drawings are only used for illustrative purposes and should not be construed as limiting the present application;

[0117] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application may be combined with each other.

[0118] In different specific implementations, the method or system described in the present application can be implemented in software, hardware or a combination thereof. In addition, the order of the steps of the method can be changed, and various elements can be added, reordered, combined, omitted, modified, etc.

[0119] Obviously, the above embodiments of the present application are merely examples for clearly illustrating the present application, and are not intended to limit the implementation methods of the present application, and are not intended to limit the present application. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above descriptions. Each discrete structure / function module or unit can be integrated together to form an independent part, or each module can exist separately, or two or more modules can be integrated to form an independent part. The structure and function of the discrete components can be implemented as a combined structure or component. For example, the technical solution of the present application is essentially 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, and the computer software product can be stored in a storage medium. It is not necessary and impossible to list all the implementation methods here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the scope of protection of the claims of the present application.

Claims

1. A spatial interference prevention method, characterized in that: Applied to a multi-antenna array, the multi-antenna array comprising at least a first antenna module and a second antenna module; The method comprises: Based on a power inversion anti-interference method, a first received signal received by the first antenna module and a second received signal received by the second antenna module are weighted to obtain a first composite signal; Based on the reference sequence correlation peak search, determining a first correlation peak value according to the first synthesized signal, and determining a second correlation peak value and a third correlation peak value according to the first received signal and the second received signal; Determine a reference signal index position according to the first correlation peak value, the second correlation peak value, and the third correlation peak value; Based on the MMSE method, determining a second composite signal after interference suppression according to the reference signal index position, the first received signal and the second received signal; The reference sequence correlation peak search is implemented based on signal energy correlation detection, including: Determine an I-path matched filter and a Q-path matched filter according to a preset local reference sequence; After decomposing the signal to be processed into an I-path signal and a Q-path signal, inputting each signal into the I-path matched filter and the Q-path matched filter respectively to obtain corresponding matched filtering results; the signal to be processed is the first synthesized signal, the first received signal or the second received signal; Determine a cross-correlation energy value between a reference sequence of the signal to be processed and the local reference sequence according to the matched filtering result; Determining an autocorrelation energy value according to the I-path signal and the Q-path signal; taking the quotient between the mutual correlation energy value and the autocorrelation energy value as the corresponding correlation peak value; and, The determining of the cross-correlation energy value comprises: The matched filtering result obtained by processing the I-path signal through the I-path matched filter is defined as a first I-path matched filtering result, and the matched filtering result obtained by processing the Q-path matched filter is defined as a first Q-path matched filtering result; the matched filtering result obtained by processing the Q-path signal through the I-path matched filter is defined as a second I-path matched filtering result, and the matched filtering result obtained by processing the Q-path matched filter is defined as a second Q-path matched filtering result; Perform addition and subtraction operations and square operations on the first I-path matched filtering result and the second Q-path matched filtering result, and on the first Q-path matched filtering result and the second I-path matched filtering result, respectively, to obtain the cross-correlation energy value; and The expression of the correlation peak is: In the formula, Represents the local reference sequence Length, Indicates the received signal; represents the subscript index of the local reference sequence; Indicates the position of the slide search.

2. A spatial domain anti-interference method according to claim 1, characterized in that: The determining of the second composite signal after interference suppression includes: Determine a reference sequence position according to the reference signal index position, and extract a corresponding predicted reference sequence from the first received signal and the second received signal; Determine the secondary weighting coefficient by using the predicted reference sequence and the preset local training sequence ; Using the quadratic weighting coefficient , performing secondary weighted processing on the first received signal and the second received signal to obtain the second composite signal.

3. The spatial domain anti-interference method according to claim 1, characterized in that: Determining a primary weighting coefficient for performing the primary weighting process based on a power inversion anti-interference method , performing the first weighted processing using the first weighting coefficient to obtain the first synthesized signal.

4. A spatial domain anti-interference method according to any one of claims 1 to 3, characterized in that: Before performing the reference sequence correlation peak search and / or the MMSE method on the first received signal and the second received signal, delay processing is performed on the first received signal and the second received signal to achieve synchronization.

5. An electronic device, characterized in that: include: A memory for storing computer executable instructions or computer programs; The processor is used to implement the method according to any one of claims 1 to 3 when executing the computer executable instructions or computer program stored in the memory.

6. A computer program product comprising a computer program or computer executable instructions, characterized in that When the computer program or computer executable instructions are executed by a processor, the method according to any one of claims 1 to 3 is implemented.

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