Manifold design method for broadband non-cooperative jamming sampling array

Abstract

The present application belongs to the technical field of anti-wideband non-cooperative interference, and specifically discloses a method for designing a wideband non-cooperative interference sampling array manifold, including: establishing a wideband non-cooperative interference sampling array model and determining the number of array elements; calculating the transient solution of the cancellation weight convergence process under wideband interference and the steady-state solution after the cancellation weight convergence according to the wideband non-cooperative interference cancellation sampling array model; determining performance parameters according to the transient solution and the steady-state solution, and determining the corresponding relationship between the performance parameters and the array manifold; combining the corresponding relationship between the performance parameters and the array manifold with the performance indicators given by the cancellation system to determine the initial sampling array manifold; testing and verifying the initial sampling array manifold, comparing the test data with the performance indicators, and iteratively adjusting the array manifold until the performance indicators are met. This application can improve the sampling array's ability to cope with wideband non-cooperative interference and the performance of the cancellation system.

Description

Technical Field

[0001] The present application belongs to the technical field of anti-wideband non-cooperative interference, and more specifically, relates to a method for designing a manifold of a broadband non-cooperative interference sampling array. Background Art

[0002] The increasingly complex electromagnetic environment has made interference mitigation a crucial consideration for many communication systems. Interference signals can originate from cooperating systems on the same platform, or they can be high-power interference from non-cooperative systems, intentionally or unintentionally. Furthermore, with the continuous evolution of jamming technology, interference signals are becoming increasingly broadband. Compared to narrowband interference, broadband interference has a wider bandwidth and can interfere with more communication frequency bands, forcing anti-interference technology to consider broadband interference. Interference cancellation technology is a key mitigation technique. Sampling the interference signal is a crucial step in interference cancellation. Interference cancellation involves synthesizing a cancellation signal from the sampled signal, which cancels out the interference signal with equal amplitude and antiphase.

[0003] For cooperative interference, the interference signal is known and can be sampled through coupling. However, for non-cooperative interference, the interference signal is unknown, so sampling must be performed using a sampling array. The manifold of the sampling array directly affects the amplitude and phase of the sampled signal, which in turn affects the effectiveness of interference cancellation. The manifold of the sampling array must be designed to meet the cancellation performance of the interference cancellation device.

[0004] During the interference cancellation process, the most important role of the cancellation device is to update the weight vector. According to the convergence state of the weight vector, it can be divided into the transient state during the weight vector convergence process and the steady state after the weight vector converges. At different stages, the weight vector exhibits different cancellation performance. In the transient process during the weight vector convergence process, the convergence speed and convergence stability are crucial; in the steady state process after the weight vector converges, the system's interference cancellation ratio, the array's resolution, and the cancellation blind area become the main manifestations of the cancellation performance. These performances are closely related to the sampling array manifold, and the quantitative relationship between the cancellation performance and the sampling array manifold needs to be calculated through modeling and solving. This quantitative relationship and system indicators are used to guide the design of the sampling array manifold.

[0005] To achieve the design of sampling array manifolds, an objective function is often set and then the array manifold is constrained and solved. There are mainly the following methods: analytical and semi-analytical methods, convex optimization methods, and global optimization algorithms. However, the current methods still have the defects of difficulty in solving complex optimization problems under multiple constraints or inaccurate solution results, which leads to poor accuracy and precision of the array manifold and cannot meet the requirements of broadband non-cooperative interference sampling. Summary of the Invention

[0006] In response to the defects of the existing technology, the purpose of this application is to provide a broadband non-cooperative interference sampling array manifold design method, aiming to solve the problem that the current methods are difficult to solve complex optimization problems under multiple constraints or the solution results are inaccurate, which leads to poor accuracy and precision of the array manifold.

[0007] To achieve the above objectives, the present application provides a broadband non-cooperative interference sampling array manifold design method, comprising:

[0008] Establish a broadband non-cooperative interference sampling array model and determine the number of array elements;

[0009] Calculating a transient solution of a cancellation weight convergence process under broadband interference and a steady-state solution after the cancellation weight convergence according to the broadband non-cooperative interference cancellation sampling array model;

[0010] Determining performance parameters based on the transient solution and the steady-state solution, and determining a corresponding relationship between the performance parameters and the array manifold; the performance parameters include array resolution, cancellation blind area, interference cancellation ratio, system convergence time, and system convergence stability;

[0011] The corresponding relationship between the performance parameters and the array manifold is combined with the performance index given by the cancellation system to determine the initial sampling array manifold;

[0012] The initial sampling array manifold is tested and verified, and the test data is compared with the performance index to iteratively adjust the array manifold until the performance index is met.

[0013] This application can effectively handle broadband non-cooperative interference by establishing a suitable array model. The transient solution describes the changes in the weights of the cancellation system during the convergence process, while the steady-state solution reflects the stable performance of the system after long-term operation. By obtaining the correspondence between performance parameters and array manifolds, the array design and algorithm selection can be optimized, and the initial array manifold can be iteratively adjusted through test verification and performance indicator comparison. This application solves the complex optimization problem of array manifold solution under multiple constraints through array design optimization, cancellation weight optimization, and performance parameter optimization to improve the accuracy and precision of the array manifold, thereby improving the sampling array's ability to respond to broadband non-cooperative interference and the performance of the cancellation system.

[0014] In some embodiments, determining the number of array elements includes:

[0015] Obtaining a relationship between the number of interference sources and the number of elements in the sampling array, and determining the number of elements based on the relationship; the number of interference sources is the number of unrelated linear constraints imposed on the weight vector of the array;

[0016] The number of interference sources is determined according to the maximum number of broadband non-cooperative interference sources that need to be countered in the use scenario of the cancellation device; and the number of array elements is greater than the number of linear constraints.

[0017] In some embodiments, the process of obtaining the transient solution and the steady-state solution includes:

[0018] Determining an initial weight vector, obtaining instantaneous data of the initial weight vector changing with sampling time during an iterative convergence process, and using the instantaneous data as a transient solution;

[0019] Determining a converged weight vector corresponding to the initial weight vector after convergence, and using the converged weight vector as the steady-state solution;

[0020] Obtaining an equivalent amplitude vector and an equivalent phase vector of the convergence weight vector;

[0021] The relationship between the convergence weight vector and the sampling array manifold parameter is determined according to the equivalent amplitude vector and the equivalent phase vector.

[0022] This application can effectively handle broadband non-cooperative interference, improve the system's signal processing capability and interference suppression capability, and optimize the cancellation weight convergence process through transient and steady-state solution analysis, thereby improving the system's response speed and stability.

[0023] In some embodiments, determining the initial sampling array manifold includes:

[0024] An initial array aperture, a maximum distance between boundary elements, and an array element position range are obtained, and the initial sampling array manifold is determined according to the array aperture, the maximum distance between boundary elements, and the array element position range.

[0025] In some embodiments, the method for determining the array aperture includes:

[0026] Obtaining a first relationship between array resolution and interference sampling array manifold using the steady-state solution;

[0027] Determine all interference incident angles, input the interference incident angles into the first relationship, and obtain candidate array apertures corresponding to the interference incident angles;

[0028] Determine whether the maximum array aperture corresponding to each interference incident angle meets the resolution index, and screen the candidate array apertures according to the determination result until the final array aperture is obtained;

[0029] The resolution index is the array resolution required by the cancellation device at all interference incident angles.

[0030] In some embodiments, the method for determining the farthest distance of the boundary element includes:

[0031] Obtaining a second relationship between a broadband interference cancellation ratio and an interference sampling array manifold using the steady-state solution;

[0032] Determine the maximum distance of the boundary element according to the second relationship and the cancellation ratio index;

[0033] The wideband interference cancellation ratio is related to the signal bandwidth, and the wideband interference cancellation ratio is negatively correlated to the array element spacing.

[0034] In some embodiments, the method for determining the array element position range includes:

[0035] Obtaining a third relationship between the cancellation blind zone and the interference sampling array manifold using the steady-state solution;

[0036] According to the third relationship and the blind area cancellation index, the array element position range is determined when the blind area cancellation accounts for the smallest proportion.

[0037] In some embodiments, the method for reducing the array element position range includes:

[0038] Using the transient solution, a fourth relationship between the interference cancellation convergence time and the interference sampling array manifold, and a fifth relationship between the convergence stability and the interference sampling array manifold are obtained;

[0039] selecting, from the array element position range, an array element position combination with the shortest convergence time and the best convergence stability based on the fourth relationship and the convergence time index, and combining the array element positions to form a new array element position range to achieve range reduction;

[0040] The interference cancellation convergence time is the time required for the initial weight vector to converge to a steady state; and the convergence stability is the convergence stability of the weight vector taking into account the convergence step size and loop gain.

[0041] In some embodiments, the iteratively adjusting the array manifold until the performance indicator is satisfied comprises:

[0042] Installing the initial sampling array manifold on a cancellation device, and using the cancellation device to obtain measurement data of the initial sampling array manifold; the measurement data includes an actually measured array resolution and cancellation blind area, as well as a cancellation ratio, convergence time, and convergence stability of the cancellation system;

[0043] Determine whether the measurement data meets the performance index requirements. If all measurement data meet the performance index, determine the final sampling array manifold; if any measurement data does not meet the performance index, readjust the array manifold until all performance indexes are met.

[0044] This application reduces the impact of blind spot elimination and improves the system's accuracy in target detection and positioning through appropriate array manifold design and optimization. Optimizing array manifold and algorithm selection accelerates the system's ability to adapt to interference in complex environments, improving real-time performance and operability.

[0045] In a second aspect, the present application provides an electronic device comprising: at least one memory for storing programs; and at least one processor for executing the programs stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method described in the first aspect or any possible implementation of the first aspect.

[0046] In a third aspect, the present application provides a computer-readable storage medium storing a computer program. When the computer program runs on a processor, the processor executes the method described in the first aspect or any possible implementation of the first aspect.

[0047] In a fourth aspect, the present application provides a computer program product. When the computer program product runs on a processor, it enables the processor to execute the method described in the first aspect or any possible implementation of the first aspect.

[0048] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0049] In general, the above technical solutions conceived by this application have the following beneficial effects compared with the existing technologies:

[0050] (1) This application can effectively handle broadband non-cooperative interference by establishing a suitable array model. The transient solution describes the changes in the weights of the cancellation system during the convergence process, while the steady-state solution reflects the stable performance of the system after long-term operation. By obtaining the corresponding relationship between performance parameters and array manifolds, the array design and algorithm selection can be optimized, and the initial array manifold can be iteratively adjusted through test verification and performance index comparison. This application solves the solution problems existing in the complex optimization of array manifolds under multiple constraints such as array design optimization, cancellation weight optimization, and performance parameter optimization, so as to improve the accuracy and precision of the array manifold, thereby improving the sampling array's ability to respond to broadband non-cooperative interference and the performance of the cancellation system.

[0051] (2) This application models the system from the perspective of array manifolds, solves the weight vectors according to the two states of the system, and then establishes a quantitative mapping relationship between the cancellation performance and the sampling array manifold based on the weight vectors. This is applicable to different broadband non-cooperative interference cancellation systems, and different broadband non-cooperative interference sampling arrays can be designed according to different index requirements. In addition, this application is aimed at the design of broadband non-cooperative interference sampling array manifolds. The interference signal can be a broadband signal. When the interference signal is a narrowband signal, the model is also applicable by simplifying the signal form. Therefore, this application improves the applicability of the non-cooperative interference cancellation system.

[0052] (3) This application provides a theoretical basis for the design of sampling arrays for non-cooperative interference cancellation, solves the difficulties of non-cooperative interference sampling, and takes into account multiple performance indicators such as interference cancellation ratio, array resolution and cancellation blind area, convergence time and convergence stability. The designed array can better improve the overall performance of the interference cancellation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is one of the flow charts of the broadband non-cooperative interference sampling array manifold design method provided in the embodiment of the present application;

[0054] Figure 2 This is the second flow chart of the broadband non-cooperative interference sampling array manifold design method provided in the embodiment of the present application;

[0055] Figure 3 It is a schematic diagram of a broadband non-cooperative interference sampling array and cancellation principle;

[0056] Figure 4 is a graph showing the relationship between array resolution and array aperture under different interference incident angles in this embodiment;

[0057] Figure 5 is a graph showing the relationship between array resolution and interference incident angle under different numbers of array elements in this embodiment;

[0058] Figure 6 This is a relationship diagram of the number of selected array elements and the interference incident angle to verify the array resolution in this embodiment;

[0059] Figure 7 is a simulation diagram of the relationship between the interference cancellation ratio and the distance between the array element and the main antenna in this embodiment;

[0060] Figure 8 Schematic diagram of the blind zone cancellation of this embodiment, wherein (a) is a three-dimensional diagram of the array output signal-to-interference-noise ratio, and (b) is a diagram of the array 3dB blind zone cancellation;

[0061] Figure 9Schematic diagrams of weight vector convergence speeds at different array element positions according to this embodiment, wherein (a) is a weight vector phase convergence time diagram for a "zero-sum" array, (b) is a weight vector amplitude convergence time diagram for a "zero-sum" array, (c) is a weight vector phase convergence time diagram for a non-"zero-sum" array, and (d) is a weight vector amplitude convergence time diagram for a non-"zero-sum" array;

[0062] Figure 10 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0064] The term "and / or" as used herein describes an association between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. The symbol " / " as used herein indicates that the related objects are in an "or" relationship, for example, A / B means either A or B.

[0065] In the specification and claims herein, the terms "first" and "second" are used to distinguish between different objects rather than to describe a specific order of objects. For example, the terms "first relationship" and "second relationship" are used to distinguish between different relationships rather than to describe a specific order of relationships.

[0066] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0067] In the description of the embodiments of the present application, unless otherwise specified, "multiple" means two or more, for example, multiple processing units means two or more processing units, etc.; multiple elements means two or more elements, etc.

[0068] Next, the technical solutions provided in the embodiments of this application are introduced.

[0069] Reference Figure 1 The present application provides a broadband non-cooperative interference sampling array manifold design method, comprising:

[0070] S1. Establish a broadband non-cooperative interference sampling array model and determine the number of array elements;

[0071] S2. Calculate the transient solution of the convergence process of the cancellation weights and the steady-state solution of the cancellation weights after convergence under broadband interference according to the broadband non-cooperative interference cancellation sampling array model;

[0072] S3. Determine performance parameters based on the transient solution and the steady-state solution, and determine the corresponding relationship between the performance parameters and the array manifold; the performance parameters include array resolution, cancellation blind area, interference cancellation ratio, system convergence time and system convergence stability;

[0073] S4. The corresponding relationship between the performance parameters and the array manifold is combined with the performance index given by the cancellation system to determine the initial sampling array manifold;

[0074] S5. Testing and verifying the initial sampling array manifold, comparing the test data with the performance index, and iteratively adjusting the array manifold until the performance index is met.

[0075] Reference Figure 2 The complete process of the broadband non-cooperative interference sampling array manifold design method of the embodiment of the present application includes:

[0076] Array popularity modeling;

[0077] Determine the number of array elements;

[0078] Solve the steady-state solution and transient solution of weight vector;

[0079] Calculate the relationship between resolution and array current; input resolution index; determine array aperture;

[0080] Calculate the relationship between the cancellation ratio and array current; input the cancellation ratio index; determine the maximum distance of the boundary array element;

[0081] Calculate the relationship between the cancellation blind zone and array current; input the cancellation blind zone index; determine the internal array element position range;

[0082] Calculate the relationship between convergence rate and array velocity; compare convergence rates; narrow the range of internal array element positions;

[0083] Calculate the relationship between convergence stability and array manifold; compare convergence stability; determine array element position combinations.

[0084] The above steps are described in detail below.

[0085] The process of determining the number of array elements includes:

[0086] Obtaining a relationship between the number of interference sources and the number of elements in the sampling array, and determining the number of elements based on the relationship; the number of interference sources is the number of unrelated linear constraints imposed on the weight vector of the array;

[0087] The number of interference sources is determined according to the maximum number of broadband non-cooperative interference sources that need to be countered in the use scenario of the cancellation device; and the number of array elements is greater than the number of linear constraints.

[0088] To determine the number of sampling array elements, it is necessary to determine the maximum number N of broadband non-cooperative interference sources that may occur. The number of elements must be greater than N. However, considering the complexity of the backend channel, the number of sampling array elements is generally N+1.

[0089] Reference Figure 3 , Figure 3 This is a schematic diagram of the broadband non-cooperative interference sampling array and cancellation principle of the embodiment of the present application. The sampling array is modeled, and a three-dimensional rectangular coordinate system is established with the main antenna as the coordinate origin. The plane where the main antenna is located is the xoy plane, the coordinates of the main antenna are [0,0,0], and the position coordinates of the mth array element are P M =[x m ,y m ,z m ], the delay of the mth array element relative to the main antenna is τ m ,θ j represents the incident angle of the interference signal, θ s Indicates the incident angle of the useful signal.

[0090] Specifically, the model building process is as follows: a broadband interference signal model is established at a frequency of f l The signal is Broadband interference signals are characterized by multi-tone signals The signal received by the mth sampling array is The signal received by the sampling array is x=[x 1 ,x 2 ,…,x m ,…,x M ] H .

[0091] The following sub-steps are included:

[0092] Sub-step S11: Establish a three-dimensional coordinate system with the main antenna position as the coordinate origin, and the positions of the M array elements are P = [P1, P2, ... P M ] T , where P M =[x m ,y m ,z m] is the position coordinate of the mth array element, and the delay of M array elements relative to the main antenna is τ=[τ1,τ1,…,τ M ], where τ m is the delay of the mth array element relative to the main antenna, as shown in the following formula:

[0093]

[0094] Where x, y, and z are the x-axis, y-axis, and z-axis coordinates of the mth array element position, and θ is the pitch angle of the signal incident direction. is the azimuth of the signal incident direction, and c is the propagation speed of the electromagnetic wave.

[0095] Sub-step S12: Characterizing the broadband interference signal using a multi-tone signal x l The determination method is as follows:

[0096]

[0097] Among them, l represents polyphonic f l The frequency number, γ1 represents the input interference-to-noise ratio, a j represents the steering vector of the array to the interference signal. s(t) represents the useful signal, γ2 represents the input signal-to-noise ratio, a s represents the steering vector of the array to the useful signal; a l represents the amplitude of the lth tone signal, represents the phase of the lth single tone signal.

[0098] Sub-step S13: Obtain the interference signal received by the m-th array element, which can be expressed as:

[0099]

[0100] Among them, τ m is the delay of the mth array element relative to the main antenna;

[0101] The weight vector of m array elements can be expressed as:

[0102] w=[w 1 ,w 2 ,…,w m ,…,w M ] H

[0103] Wherein, the superscript H represents the conjugate transpose;

[0104] The remaining signal after cancellation can be expressed as:

[0105]

[0106] Where K is a constant, including the loop gain of each device in the channel, x H It is the sampling signal received by the sampling array.

[0107] Furthermore, the transient solution and steady-state solution process include:

[0108] Determining an initial weight vector, obtaining instantaneous data of the initial weight vector changing with sampling time during an iterative convergence process, and using the instantaneous data as a transient solution;

[0109] Determining a converged weight vector corresponding to the initial weight vector after convergence, and using the converged weight vector as the steady-state solution;

[0110] Obtaining an equivalent amplitude vector and an equivalent phase vector of the convergence weight vector;

[0111] The relationship between the convergence weight vector and the sampling array manifold parameter is determined according to the equivalent amplitude vector and the equivalent phase vector.

[0112] Specifically, the solution process of the weight vector steady-state solution and transient solution is as follows:

[0113] Sub-step S21: According to the above modeling, the transient difference equation during the weight convergence process is:

[0114]

[0115] Where μ is the convergence step size, is the sampling signal received by the sampling antenna, x e (n) is the residual signal.

[0116] Solve the difference equation and substitute w(0)=0 to obtain the weighted transient solution:

[0117]

[0118] in:

[0119] R=UAU H

[0120] Λ=diag{λ i}

[0121] i=1,2,3,…,M

[0122] q is the cross-correlation vector between the interference signal received by the sampling array and the interference signal received by the main antenna, expressed as:

[0123]

[0124] R is the autocorrelation matrix of the received signal of the sampling array, which is expressed as:

[0125]

[0126] Sub-step S22: After the weights converge, they can be expressed as a complex constant w m , which can be expressed as:

[0127] w m =k m exp(-jω m τ m )

[0128] The weight vector is expressed as

[0129] The residual interference signal can be expressed as

[0130] By using the residual interference signal to derivate the weight equivalent amplitude and equivalent angular frequency, the optimal weight equivalent angular frequency can be obtained.

[0131] The optimal weight equivalent amplitude satisfies the following formula:

[0132]

[0133] Furthermore, performance parameters are determined based on the transient solution and the steady-state solution, and a corresponding relationship between the performance parameters and the array manifold is determined; the performance parameters include array resolution, cancellation blind area, interference cancellation ratio, system convergence time, and system convergence stability, specifically comprising the following steps:

[0134] Sub-step S31: Calculate the relationship between the sampling array resolution and the array manifold.

[0135] The directional pattern formed by the main antenna and the sampling array is expressed as |1-WA′|, where WA′ represents the product of the weight vector of the sampling array and the steering vector. The directional pattern is in the interference incident direction θ j The main null is formed at s When it is close to the main zero, it will cause the attenuation of the useful signal. j The minimum value that satisfies the useful signal attenuation constraint of αdB is the αdB attenuation resolution of the sampling array. Making |1-WA′|=α, substituting the steady-state solution of the weight vector and the array steering vector, we get the attenuation resolution and the maximum aperture of the array satisfying , M represents the number of sampling antennas, and r represents the spacing between the sampling antennas.

[0136] Sub-step S32: Calculate the relationship between the interference cancellation ratio and the sampling array manifold. The interference signal at each frequency point f l, can be regarded as a vector with an amplitude of 1 and a phase of 0°. The cancellation of multiple sampling antennas can be regarded as the fitting process of multiple vectors to the vector 1∠0° at multiple frequency points. By observing the equivalent angular frequency of the steady-state weights, it can be found that the equivalent frequency ω corresponding to the optimal weight of each antenna m Similarly, the sampling array elements form a positive and negative delay distribution relative to the main antenna, and when the cumulative delay of each sampling array element is zero, the phase of the fitted cancellation signal and the interference signal can be exactly opposite. Therefore, the sampling array elements should be arranged in a way that the delay sum is zero with the main antenna as the center, which will improve the cancellation performance. And the interference cancellation ratio and the delay of the sampling array element from the main antenna meet relationship;

[0137] Sub-step S33: Calculate the relationship between the cancellation blind zone and the sampling array manifold. During cancellation, the pattern will form grid nulls in all directions except the interference direction. When the useful signal is incident from these angles, it will cause attenuation of the useful signal and reduce the output signal-to-interference-and-noise ratio. When the interference signal incident angle is fixed and the useful signal incident angle varies, the relationship between the output signal-to-interference-and-noise ratio and the array manifold satisfies the following relationship:

[0138]

[0139] in,

[0140]

[0141] Sub-step S44: Calculate the relationship between the convergence time and the sampling array manifold. Observing the transient solution of the weight vector, it can be seen that during the weight convergence process, the weight expectation is a linear combination of M exponential decay functions. The convergence time is determined by the weight with the slowest convergence speed, and the exponential decay function decays to e -1 The time required is:

[0142]

[0143] Among them, μ represents the convergence step size, λ i is the i-th eigenvalue of the autocorrelation matrix of the sampling array, K is a constant, and contains the loop gain of each device in the channel.

[0144] Obviously, the minimum eigenvalue corresponds to the exponential function with the slowest convergence speed, which is the time required for the system to converge. The eigenvalue is determined by the autocorrelation matrix of the sampling array, which is:

[0145]

[0146] Sub-step S45: Calculate the relationship between convergence stability and the sampling array manifold. Since the weight update adopts a closed-loop algorithm, the solution is:

[0147]

[0148] in, For w m (n) is irrelevant, and as n increases, G(n) tends to be stable. As the iteration time n increases, if you want the system to be stable, you need to satisfy F(n) n+1 Approximately zero.

[0149]

[0150] The solution is It can be seen that the stability condition of the system is determined by the sampling array manifold τ m related.

[0151] Furthermore, the corresponding relationship between the performance parameters and the array manifold is combined with the performance index given by the cancellation system to determine the initial sampling array manifold;

[0152] This embodiment obtains the initial array aperture, the farthest distance between boundary elements, and the array element position range, and determines the initial sampling array manifold according to the array aperture, the farthest distance between boundary elements, and the array element position range.

[0153] First, the method for determining the array aperture includes:

[0154] Obtaining a first relationship between array resolution and interference sampling array manifold using the steady-state solution;

[0155] Determine all interference incident angles, input the interference incident angles into the first relationship, and obtain candidate array apertures corresponding to the interference incident angles;

[0156] Determine whether the maximum array aperture corresponding to each interference incident angle meets the resolution index, and screen the candidate array apertures according to the determination result until the final array aperture is obtained;

[0157] The resolution index is the array resolution required by the cancellation device at all interference incident angles.

[0158] The maximum aperture of the array should be determined based on the broadband interference sampling array resolution |θ-θ j | min Relationship with array aperture to determine, where λ is the wavelength corresponding to the center frequency of the broadband interference signal, and Mr is the maximum aperture of the array.

[0159] Reference Figure 4 , Figure 4 This is a graph showing the relationship between array resolution and array aperture under different interference incident angles in this embodiment. The black line in the figure represents θ j =90°; the red line indicates θ j=60°; the blue line represents θ j =45°; the green line represents θ j =30°. As can be seen from the figure, the array aperture and resolution are negatively correlated.

[0160] Reference Figure 5 , Figure 5 This graph shows the relationship between array resolution and interference incident angle for different numbers of array elements in this embodiment. The black line in the graph represents M = 4; the red line represents M = 6; the blue line represents M = 8; and the green line represents M = 10. The graph shows that resolution and interference incident angle are negatively correlated.

[0161] Reference Figure 6 , Figure 6 This is a relationship diagram of the number of selected array elements and the interference incident angle to verify the array resolution in this embodiment; the black line in the figure indicates M = 4, θ j =90°; the red line indicates M=6, θ j =60°; the blue line indicates M=8, θ j =45°; the green line indicates M=10, θ j =30°.

[0162] Secondly, the method for determining the farthest distance of the boundary element includes:

[0163] Obtaining a second relationship between a broadband interference cancellation ratio and an interference sampling array manifold using the steady-state solution;

[0164] Determine the maximum distance of the boundary element according to the second relationship and the cancellation ratio index;

[0165] Reference Figure 7 , Figure 7 This is a simulation graph showing the relationship between the interference cancellation ratio and the distance between the array element and the main antenna in this embodiment. The black line in the graph represents a bandwidth of 10 MHz, the red line represents a bandwidth of 20 MHz, the blue line represents a bandwidth of 40 MHz, the green line represents a bandwidth of 60 MHz, and the purple line represents a bandwidth of 80 MHz. The graph shows that the interference cancellation ratio is negatively correlated with the distance between the array element and the main antenna.

[0166] The maximum spacing between array elements is determined based on the required cancellation ratio of the system. Based on the steady-state weights, the relationship between the interference cancellation ratio and the sampling array manifold can be obtained as follows:

[0167]

[0168] Among them, τ m is the delay of the mth array element relative to the main antenna, ω l is the angular frequency of the lth tone signal, ω mis the equivalent angular frequency of the mth sampling antenna weight, k m The equivalent amplitude of the mth sampling antenna weight. When the array elements are arranged around the main antenna, forming a distribution of positive and negative delays relative to the main antenna, and the cumulative sum of the delays of each sampling antenna is zero, the cancellation ratio is optimal. The cancellation ratio is negatively correlated with the element delay relative to the main antenna. Given the minimum required cancellation ratio for the system, the maximum element spacing is determined.

[0169] Third, the method for determining the array element position range includes:

[0170] Obtaining a third relationship between the cancellation blind zone and the interference sampling array manifold using the steady-state solution;

[0171] According to the third relationship and the blind area cancellation index, the array element position range is determined when the blind area cancellation accounts for the smallest proportion.

[0172] Reference Figure 8 , Figure 8 Schematic diagram of the blind zone cancellation of this embodiment, (a) is a three-dimensional diagram of the array output signal-to-interference-noise ratio, and (b) is a diagram of the array 3dB blind zone cancellation.

[0173] The range of array element positions should be determined so that the cancellation blind zone ratio meets the system's requirements. Based on the above requirements, the array edge element positions have been determined, and the internal array element positions need to be adjusted to minimize the cancellation blind zone. The cancellation blind zone is determined based on the output signal-to-interference-noise ratio. The relationship between the output signal-to-interference-noise ratio and the array manifold satisfies:

[0174]

[0175] Among them, γ1 is the input signal-to-noise ratio, γ2 is the input interference-to-noise ratio, a s is the steering vector of the useful signal, a j is the steering vector of the interference signal.

[0176] Fourthly, the method for reducing the array element position range includes:

[0177] Using the transient solution, a fourth relationship between the interference cancellation convergence time and the interference sampling array manifold, and a fifth relationship between the convergence stability and the interference sampling array manifold are obtained;

[0178] selecting, from the array element position range, an array element position combination with the shortest convergence time and the best convergence stability based on the fourth relationship and the convergence time index, and combining the array element positions to form a new array element position range to achieve range reduction;

[0179] The interference cancellation convergence time is the time required for the initial weight vector to converge to a steady state; and the convergence stability is the convergence stability of the weight vector taking into account the convergence step size and loop gain.

[0180] Reference Figure 9 , Figure 9 Schematic diagrams of weight vector convergence speeds at different array element positions in this embodiment, (a) is a weight vector phase convergence time diagram for a "zero-sum" array, (b) is a weight vector amplitude convergence time diagram for a "zero-sum" array, (c) is a weight vector phase convergence time diagram for a non-"zero-sum" array, and (d) is a weight vector amplitude convergence time diagram for a non-"zero-sum" array.

[0181] In the figure, the blue line represents auxiliary antenna 1, the red line represents auxiliary antenna 2, and the yellow line represents auxiliary antenna 3. It can be seen that in the "zero-sum" array, the weight amplitudes and weight phases of the three auxiliary antennas remain stable over time. In the "non-zero-sum" array, the weight amplitude of auxiliary antenna 2 remains stable, the weight amplitude of auxiliary antenna 1 gradually increases and then remains stable, and the weight amplitude of auxiliary antenna 3 first decreases, then gradually increases, and then remains stable. The weight phases of auxiliary antennas 1 and 2 remain stable, and the weight of auxiliary antenna 3 gradually increases and then remains stable.

[0182] Specifically, the range of array element positions is narrowed down, and within the determined array element range, array element positions that optimize the cancellation convergence time and stability are selected to determine several sets of optimal array element position combinations. The relationship between the cancellation convergence time and the sampling array manifold satisfies the following relationship:

[0183]

[0184] Where μ is the convergence step size, K is the loop gain, and λ min is the minimum eigenvalue of the autocorrelation matrix of the sampling array. The relationship between convergence stability and the sampling array manifold satisfies:

[0185]

[0186] Among them, a l is the amplitude of the lth tone signal, is the phase of the lth tone signal.

[0187] Specifically, obtaining the initial array aperture, the maximum distance of the boundary array elements, and the array element position range includes the following steps:

[0188] Sub-step S41: Determine system parameters, for example, the array αdB attenuation resolution must be less than a°, the cancellation ratio must be greater than bdB, the cancellation blind area must be less than c%, and the convergence time must be less than dμs;

[0189] Sub-step S42: According to the array resolution requirement, the maximum aperture of the sampling array may be determined;

[0190] Sub-step S43: Based on the broadband interference cancellation ratio requirement, it can be determined that the sampling array elements should be placed around the main antenna, and the sum of the delays of all sampling array elements relative to the main antenna should be as close to zero as possible. The positions of boundary array elements can be determined, and multiple combinations of array element positions within the boundary can be obtained.

[0191] Sub-step S44: calculating the array cancellation blind area for each combination, and adjusting the positions of internal array elements based on the calculation to find a range of internal array element positions with a smaller cancellation blind area;

[0192] Sub-step S45: Within the internal array element position range, calculate the convergence time of each array element position within the range and determine whether the system stability is satisfied. Select the array element position combination with the shorter convergence time as the preliminary sampling array manifold.

[0193] Finally, the initial sampling array manifold is tested and verified, and the test data is compared with the performance index to iteratively adjust the array manifold until the performance index is met.

[0194] Specifically, the iterative process includes the following steps:

[0195] Sub-step S51: Arrange the sampling array of the cancellation device according to the preliminarily determined array manifold. Connect the signal source to the transmitting antenna as the useful signal and the interference signal, and inject them from different angles;

[0196] Sub-step S52: measuring whether the cancellation system can converge stably under different interference signal and useful signal incident angles, and measuring the array's resolution, cancellation blind area, interference cancellation ratio, and convergence time;

[0197] Sub-step S53: Determine whether the sampling array manifold meets the requirements. If the requirements are met, the array manifold can be used as the sampling array manifold of the system; if any of the requirements are not met, repeat the above steps and adjust the array element positions until the requirements are met.

[0198] By inputting useful and interfering signals at different angles, the embodiments of the present application can comprehensively evaluate the performance of the cancellation system in actual operation. This testing confirms whether the cancellation system can stably converge in complex signal environments and effectively suppress interfering signals, thereby improving overall system performance. Furthermore, by determining whether the sampling array manifold meets performance requirements and adjusting array element positions as needed, the system optimization cycle can be effectively reduced, enabling rapid identification and resolution of potential issues, thereby accelerating system deployment and application. By repeatedly testing and adjusting the sampling array manifold to ensure that it meets performance requirements, the system's stability and reliability can be improved.

[0199] Reference Figure 10Based on the methods in the above embodiments, an embodiment of the present application provides an electronic device, which may include: a processor 1010, a communications interface 1020, a memory 1030, and a communication bus 1040, wherein the processor 1010, the communications interface 1020, and the memory 1030 communicate with each other via the communication bus 1040. The processor 1010 may call logic instructions in the memory 1030 to execute the methods in the above embodiments.

[0200] In addition, the logic instructions in the above-mentioned memory 1030 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application, 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, which is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application.

[0201] Based on the method in the above embodiment, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method in the above embodiment.

[0202] Based on the method in the above embodiment, an embodiment of the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method in the above embodiment.

[0203] It is understood that the processor in the embodiments of the present application may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0204] The method steps in the embodiments of the present application can be implemented by hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0205] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted via the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)).

[0206] It will be understood that the various numerical numbers involved in the embodiments of the present application are merely distinctions for the convenience of description and are not intended to limit the scope of the embodiments of the present application.

[0207] It is easy for those skilled in the art to understand that the above is only a preferred embodiment of the present application and is not intended to limit the present application. 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 present application.

Claims

1. A broadband non-cooperative interference sampling array manifold design method, characterized in that: include: Establish a broadband non-cooperative interference sampling array model and determine the number of array elements; Calculating a transient solution of a cancellation weight convergence process under broadband interference and a steady-state solution after the cancellation weight convergence according to the broadband non-cooperative interference cancellation sampling array model; Determining performance parameters based on the transient solution and the steady-state solution, and determining a corresponding relationship between the performance parameters and the array manifold; The performance parameters include array resolution, cancellation blind area, interference cancellation ratio, system convergence time and system convergence stability; The corresponding relationship between the performance parameters and the array manifold is combined with the performance index given by the cancellation system to determine the initial sampling array manifold; The initial sampling array manifold is tested and verified, and the test data is compared with the performance index to iteratively adjust the array manifold until the performance index is met.

2. The broadband non-cooperative interference sampling array manifold design method according to claim 1, characterized in that: The determining the number of array elements includes: Obtaining a relationship between the number of interference sources and the number of elements in the sampling array, and determining the number of elements based on the relationship; the number of interference sources is the number of unrelated linear constraints imposed on the weight vector of the array; The number of interference sources is determined according to the maximum number of broadband non-cooperative interference sources that need to be countered in the use scenario of the cancellation device; and the number of array elements is greater than the number of linear constraints.

3. The broadband non-cooperative interference sampling array manifold design method according to claim 1, characterized in that: The process of obtaining the transient solution and the steady-state solution includes: Determining an initial weight vector, obtaining instantaneous data of the initial weight vector changing with sampling time during an iterative convergence process, and using the instantaneous data as a transient solution; Determining a converged weight vector corresponding to the initial weight vector after convergence, and using the converged weight vector as the steady-state solution; Also includes: Obtaining an equivalent amplitude vector and an equivalent phase vector of the convergence weight vector; The relationship between the convergence weight vector and the sampling array manifold parameter is determined according to the equivalent amplitude vector and the equivalent phase vector.

4. The broadband non-cooperative interference sampling array manifold design method according to claim 3, characterized in that: The determining of the initial sampling array manifold comprises: An initial array aperture, a maximum distance between boundary elements, and an array element position range are obtained, and the initial sampling array manifold is determined according to the array aperture, the maximum distance between boundary elements, and the array element position range.

5. The broadband non-cooperative interference sampling array manifold design method according to claim 4, characterized in that: The method for determining the array aperture includes: Obtaining a first relationship between array resolution and interference sampling array manifold using the steady-state solution; Determine all interference incident angles, input the interference incident angles into the first relationship, and obtain candidate array apertures corresponding to the interference incident angles; Determine whether the maximum array aperture corresponding to each interference incident angle meets the resolution index, and screen the candidate array apertures according to the determination result until the final array aperture is obtained; The resolution index is the array resolution required by the cancellation device at all interference incident angles.

6. The broadband non-cooperative interference sampling array manifold design method according to claim 4, characterized in that: The method for determining the farthest distance of the boundary element includes: Obtaining a second relationship between a broadband interference cancellation ratio and an interference sampling array manifold using the steady-state solution; Determine the maximum distance of the boundary element according to the second relationship and the cancellation ratio index; The wideband interference cancellation ratio is related to the signal bandwidth, and the wideband interference cancellation ratio is negatively correlated to the array element spacing.

7. The broadband non-cooperative interference sampling array manifold design method according to claim 4, characterized in that: The method for determining the array element position range includes: Obtaining a third relationship between the cancellation blind zone and the interference sampling array manifold using the steady-state solution; According to the third relationship and the blind area cancellation index, the array element position range is determined when the blind area cancellation accounts for the smallest proportion.

8. The broadband non-cooperative interference sampling array manifold design method according to claim 4, characterized in that: The method for narrowing the array element position range includes: Using the transient solution, a fourth relationship between the interference cancellation convergence time and the interference sampling array manifold, and a fifth relationship between the convergence stability and the interference sampling array manifold are obtained; selecting, from the array element position range, an array element position combination with the shortest convergence time and the best convergence stability based on the fourth relationship and the convergence time index, and combining the array element positions to form a new array element position range to achieve range reduction; The interference cancellation convergence time is the time required for the initial weight vector to converge to a steady state; and the convergence stability is the convergence stability of the weight vector taking into account the convergence step size and loop gain.

9. The broadband non-cooperative interference sampling array manifold design method according to claim 1, characterized in that: The iterative adjustment of the array manifold until the performance index is met includes: Installing the initial sampling array manifold on a cancellation device, and using the cancellation device to obtain measurement data of the initial sampling array manifold; the measurement data includes an actually measured array resolution and cancellation blind area, as well as a cancellation ratio, convergence time, and convergence stability of the cancellation system; Determine whether the measurement data meets the performance index requirements. If all measurement data meet the performance index, determine the final sampling array manifold; if any measurement data does not meet the performance index, readjust the array manifold until all performance indexes are met.

10. An electronic device, characterized in that: include: at least one memory for storing a computer program; At least one processor is used to execute the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method according to any one of claims 1 to 9.

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