Satellite navigation polarization anti-interference method and device

Abstract

The present invention provides a satellite navigation polarization anti-interference method and device, wherein the method includes: obtaining the vertical polarization response vector and the horizontal polarization response vector of the first orthogonal feeding point and the second orthogonal feeding point, calculating the antenna array gain norm and the antenna array polarization balance difference norm, constructing a multi-polarization interference suppression performance optimization function, and solving it based on the unitary Stiefel manifold constraint to obtain the analog domain polarization weight vector, and inputting it into the corresponding digital controlled amplitude modulator and digital controlled phase modulator for adjustment to obtain the positioning information after interference suppression. The beneficial effect of the present invention: significantly improving the multi-polarization interference suppression, laying a theoretical foundation for the quantitative analysis and performance improvement of the multi-polarization interference suppression of satellite navigation antenna arrays. It not only provides a new perspective for the field of satellite navigation polarization countermeasures, but also provides an effective solution for improving the polarization anti-interference capability of GNSS systems.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation, and in particular to a satellite navigation polarization anti-interference method and apparatus. Background Technology

[0002] With the development of autonomous driving and the low-altitude economy, incidents of satellite navigation being affected by interference signals, resulting in flight delays, drone crashes, and abnormal vehicle and ship trajectories, are frequently reported. The impact is becoming increasingly serious and has attracted widespread attention.

[0003] Multipolar interference drastically degrades the anti-jamming performance of antenna arrays, significantly improving jamming efficiency and saving jamming costs. Currently, it is only qualitatively pointed out that non-ideal antenna polarization response characteristics lead to decreased jamming suppression performance and additional loss of array degrees of freedom, and that simple amplitude-phase weighting cannot eliminate this effect. Quantitative analysis of the effectiveness of multipolar interference suppression is lacking; its influencing factors and evaluation system are unclear, and no effective multipolar interference suppression method has been proposed. Summary of the Invention

[0004] The main objective of this invention is to provide a satellite navigation polarization anti-interference method and apparatus, which aims to solve the problem that multi-polarization interference can drastically degrade the anti-interference performance of antenna arrays.

[0005] This invention provides a satellite navigation polarization anti-interference method, implemented through a ground navigation receiver, a digitally controlled amplitude modulator (DCAM), a digitally controlled phase modulator (DCP), and a combiner. The first and second orthogonal feed points of the ground navigation receiver's antenna are respectively connected to the DCAM and DCP. The DCAM and DCP are connected to the combiner, which is connected to the radio frequency (RF) front-end of the ground navigation receiver. The RF front-end is connected to the baseband processing unit of the ground navigation receiver. The method is applied to the baseband processing unit and includes:

[0006] Obtain the first vertical polarization response vector and the first horizontal polarization response vector of the first orthogonal feed point, and the second vertical polarization response vector and the second horizontal polarization response vector of the second orthogonal feed point;

[0007] The antenna array gain norm and antenna array polarization equalization difference norm are calculated based on the first vertical polarization response vector, the first horizontal polarization response vector, the second vertical polarization response vector, and the second horizontal polarization response vector.

[0008] A multi-polarization interference suppression performance optimization function is constructed based on the antenna array gain norm and the antenna array polarization equalization difference norm.

[0009] The multi-polarization interference suppression performance optimization function is solved based on the Utherstiffer manifold constraint to obtain the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point.

[0010] The first analog domain polarization weight vector is input to the numerically controlled amplitude modulator and numerically controlled phase modulator connected to the first orthogonal feed point, and the second analog domain polarization weight vector is input to the numerically controlled amplitude modulator and numerically controlled phase modulator connected to the second orthogonal feed point for adjustment, so as to obtain the anti-interference positioning information.

[0011] Further, the step of calculating the antenna array gain norm and the antenna array polarization equalization difference norm based on the first vertical polarization response vector, the first horizontal polarization response vector, the second vertical polarization response vector, and the second horizontal polarization response vector includes:

[0012] set up

[0013]

[0014]

[0015]

[0016] in, , These are the first vertical polarization response vector and the first horizontal polarization response vector at the first orthogonal feed point, respectively. and These are the second vertical polarization response vector and the second horizontal polarization response vector at the second orthogonal feed point, respectively, where N represents the number of antennas;

[0017] According to the formula and formula Calculate the antenna array gain norm and the antenna array polarization equalization difference norm; where n represents the nth antenna. Represents the gain norm of the antenna array, The polarization uniformity difference norm of the antenna array is represented. , Indicates azimuth. H represents the pitch angle, and H represents the conjugate transpose. , This represents the vertical polarization signal of the nth antenna. This represents the horizontal polarization signal of the nth antenna. This represents the horizontal polarization signal of the i-th antenna. This represents the horizontal polarization signal of the j-th antenna. This represents the vertical polarization signal of the j-th antenna. This represents the vertical polarization signal of the i-th antenna.

[0018] Furthermore, the step of constructing a multi-polarization interference suppression performance optimization function based on the antenna array gain norm and the antenna array polarization equalization difference norm includes:

[0019] A multi-polarization interference suppression performance optimization function is constructed based on the antenna array gain norm and the antenna array polarization equalization difference norm. ;in, The polarization weight vector of the first analog domain. All contain amplitude and phase information. This is the polarization weight vector for the second analog domain.

[0020] Further, the step of solving the multi-polarization interference suppression performance optimization function based on the Ustifel-like manifold constraint to obtain the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point includes:

[0021] Calculate the gradient of the multipolar interference suppression performance optimization function in Euclidean space and project it onto the Riemann gradient on the Steifel manifold. ;in Representation matrix exist The projection, Represents the Riemann gradient. In Euclidean space The derivative of a point, ;

[0022] set up ,in , , Indicates the first The next iteration , Indicates the first The next iteration ; This represents QR decomposition. Represents the matrix index. This represents the upper triangular matrix in the QR decomposition. This represents the transpose of the upper triangular matrix in the QR decomposition.

[0023] Determine the initial value and calculate On ;

[0024] Combined with step size parameters Calculate along Geodesic equations of direction, updating iterative values ;

[0025] judge Does it meet the convergence condition? If not, then... Iterate from the new starting point until the preset convergence condition is met;

[0026] It will reach the preset convergence condition. It is proposed that the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point are obtained.

[0027] Furthermore, the antenna array of the ground navigation receiver is a seven-element satellite navigation antenna array.

[0028] Furthermore, the antenna is a microstrip antenna.

[0029] This invention also provides a satellite navigation polarization anti-interference device, including a ground navigation receiver, a digitally controlled amplitude modulator (DCAM), a digitally controlled phase modulator (DCP), and a combiner. The first and second orthogonal feed points of the antenna of the ground navigation receiver are respectively connected to the DCAM and the DCP. The DCAM and the DCP are connected to the combiner. The combiner is connected to the radio frequency (RF) front-end of the ground navigation receiver. The RF front-end is connected to the baseband processing unit of the ground navigation receiver. The baseband processing unit includes:

[0030] The acquisition module is used to acquire the first vertical polarization response vector and the first horizontal polarization response vector of the first orthogonal feed point, and the second vertical polarization response vector and the second horizontal polarization response vector of the second orthogonal feed point;

[0031] The calculation module is used to calculate the antenna array gain norm and the antenna array polarization equalization difference norm based on the first vertical polarization response vector, the first horizontal polarization response vector, the second vertical polarization response vector, and the second horizontal polarization response vector.

[0032] The module is used to construct a multi-polarization interference suppression performance optimization function based on the antenna array gain norm and the antenna array polarization equalization difference norm.

[0033] The solution module is used to solve the multi-polarization interference suppression performance optimization function based on the unitary Stieffer manifold constraint to obtain the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point.

[0034] The input module is used to input the first analog domain polarization weight vector into the CNC amplitude modulator and CNC phase modulator connected to the first orthogonal feed point, and to input the second analog domain polarization weight vector into the CNC amplitude modulator and CNC phase modulator connected to the second orthogonal feed point for adjustment, so as to obtain the anti-interference positioning information.

[0035] Furthermore, the computing module includes:

[0036] The settings submodule is used for setting...

[0037]

[0038]

[0039]

[0040] in, , These are the first vertical polarization response vector and the first horizontal polarization response vector at the first orthogonal feed point, respectively. and These are the second vertical polarization response vector and the second horizontal polarization response vector at the second orthogonal feed point, respectively, where N represents the number of antennas;

[0041] The norm calculation submodule is used to calculate the norm based on the formula. and formula Calculate the antenna array gain norm and the antenna array polarization equalization difference norm; where n represents the nth antenna. Represents the gain norm of the antenna array, The polarization uniformity difference norm of the antenna array is represented. , Indicates azimuth. H represents the pitch angle, and H represents the conjugate transpose. , This represents the vertical polarization signal of the nth antenna. This represents the horizontal polarization signal of the nth antenna. This represents the horizontal polarization signal of the i-th antenna. This represents the horizontal polarization signal of the j-th antenna. This represents the vertical polarization signal of the j-th antenna. This represents the vertical polarization signal of the i-th antenna.

[0042] Furthermore, the building module includes:

[0043] A submodule is constructed to build a multi-polarization interference suppression performance optimization function based on the antenna array gain norm and the antenna array polarization equalization difference norm. ;in, The polarization weight vector of the first analog domain. All contain amplitude and phase information. This is the polarization weight vector for the second analog domain.

[0044] Furthermore, the solution module includes:

[0045] The gradient calculation submodule is used to calculate the gradient of the multipolar interference suppression performance optimization function in Euclidean space and project it onto the Riemann gradient on the Stigefair manifold. ;in Representation matrix exist The projection, Represents the Riemann gradient. In Euclidean space The derivative of a point, ;

[0046] The settings submodule is used for setting... ,in , , Indicates the first The next iteration , Indicates the first The next iteration ; This represents QR decomposition. Represents the matrix index. This represents the upper triangular matrix in the QR decomposition. This represents the transpose of the upper triangular matrix in the QR decomposition.

[0047] The determination submodule is used to determine the initial values. and calculate On ;

[0048] The geodesic equation calculation submodule is used to combine step size parameters. Calculate along Geodesic equations of direction, updating iterative values ;

[0049] The inventory submodule is used to determine... Does it meet the convergence condition? If not, then... Iterate from the new starting point until the preset convergence condition is met;

[0050] The vector calculation submodule is used to calculate the vectors that have reached the preset convergence condition. It is proposed that the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point are obtained.

[0051] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of any of the methods described above.

[0052] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any of the methods described above.

[0053] The beneficial effects of this invention are: it significantly improves multi-polarity interference suppression, laying a theoretical foundation for the quantitative analysis and performance enhancement of multi-polarity interference suppression in satellite navigation antenna arrays. It not only provides a new perspective in the field of satellite navigation polarization countermeasures but also offers an effective solution for improving the polarization anti-interference capability of GNSS systems. Attached Figure Description

[0054] Figure 1 This is a flowchart illustrating a satellite navigation polarization anti-interference method according to an embodiment of the present invention;

[0055] Figure 2 This is a schematic block diagram of a satellite navigation polarization anti-interference device according to an embodiment of the present invention;

[0056] Figure 3 This is a schematic block diagram of the structure of a computer device according to an embodiment of this application.

[0057] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0058] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0059] It should be noted that all directional indicators (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicator will also change accordingly. The connection can be a direct connection or an indirect connection.

[0060] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three kinds of relationships. For example, A and B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0061] In addition, in the present invention, descriptions such as "first" and "second" are for descriptive purposes only and should not be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but this must be based on the fact that they can be implemented by ordinary technicians in this field. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0062] Reference Figure 1 This invention proposes a satellite navigation polarization anti-interference method, implemented through a ground navigation receiver, a digitally controlled amplitude modulator (DCAM), a digitally controlled phase modulator (DCP), and a combiner. The first and second orthogonal feed points of the ground navigation receiver's antenna are respectively connected to the DCAM and DCP. The DCAM and DCP are connected to the combiner, which is connected to the RF front-end of the ground navigation receiver. The RF front-end is connected to the baseband processing unit of the ground navigation receiver. The method is applied to the baseband processing unit and includes:

[0063] S1: Obtain the first vertical polarization response vector and the first horizontal polarization response vector of the first orthogonal feed point, and the second vertical polarization response vector and the second horizontal polarization response vector of the second orthogonal feed point;

[0064] S2: Calculate the antenna array gain norm and antenna array polarization equalization difference norm based on the first vertical polarization response vector, the first horizontal polarization response vector, the second vertical polarization response vector, and the second horizontal polarization response vector;

[0065] S3: Construct a multi-polarization interference suppression performance optimization function based on the antenna array gain norm and the antenna array polarization equalization difference norm;

[0066] S4: Solve the multi-polarization interference suppression performance optimization function based on the Uristefair-like manifold constraint to obtain the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point;

[0067] S5: Input the first analog domain polarization weight vector into the CNC amplitude modulator and CNC phase modulator connected to the first orthogonal feed point, and input the second analog domain polarization weight vector into the CNC amplitude modulator and CNC phase modulator connected to the second orthogonal feed point for adjustment to obtain the anti-interference positioning information.

[0068] As described in step S1 above, for any fully polarized far-field electromagnetic wave, its electric field direction is perpendicular to the electromagnetic wave propagation direction. Therefore, the electric field can be decomposed into two orthogonal polarization components: vertical polarization and horizontal polarization. The Jones electric field vector of the far-field electromagnetic wave is then expressed as:

[0069]

[0070] in, Electromagnetic wave polarization vector and These are the vertical polarization component and the horizontal polarization component, respectively. For envelope signal, Let be the vector angle between the electric field and the vertical polarization component. This represents the leading phase of the vertical polarization component relative to the horizontal polarization component. It should be noted that the 's' in the preceding 's(t)' is bolded and is different from the subsequent 's(t)'. The former is a vector, while the latter is an envelope signal.

[0071] The polarization pattern of a satellite navigation antenna can be represented as:

[0072]

[0073] in, This is the antenna polarization pattern. These are the azimuth and elevation angles, respectively. Indicates antenna, and These are the antenna patterns for vertically polarized and horizontally polarized signals, respectively.

[0074] The polarization response of the satellite navigation antenna receiving the signal can be expressed as:

[0075]

[0076] This represents the polarization response of the satellite navigation antenna to the received signal.

[0077] Under strong interference conditions, considering that the power of satellite navigation signals is much weaker than the power of interference signals and noise, and to simplify the analysis, satellite navigation signals are usually ignored. Therefore, the reception of multiple independent polarization interference signals from the same direction by a satellite navigation antenna array can be expressed as follows:

[0078]

[0079] in,

[0080]

[0081]

[0082]

[0083] in, Indicates time, Indicates the number of multipolar interferences. Indicates the number of satellite navigation antennas. For satellite navigation antenna array receiving data vectors, For multi-polarization interference signal steering vector, express Vaticaned Gaussian white noise data vector Indicates that the satellite navigation array antenna receives the first The polarization response of a polarization disturbance. Indicates the first Data received by each satellite navigation antenna Indicates the first The antenna receives the first... The polarization response of a polarization disturbance. The wavelength of the incident signal, For the first The three-dimensional coordinates of each array element The unit propagation vector of a plane wave.

[0084] in, ;

[0085] ;

[0086] It is the transpose of the three-dimensional coordinates of the Nth array element.

[0087] definition

[0088]

[0089] but:

[0090]

[0091] Because the polarization characteristics of each element in a satellite navigation antenna array are not ideal, the ratio of the horizontal polarization response to the vertical polarization response of each satellite navigation antenna is not equal. and Nonlinear correlation. When At this time, multipolar interference will correspond to two steering vectors, and therefore will be equivalent to interference from two directions.

[0092] As described in step S2 above, the antenna array gain norm and the antenna array polarization equalization difference norm are calculated based on the first vertical polarization response vector, the first horizontal polarization response vector, the second vertical polarization response vector, and the second horizontal polarization response vector.

[0093] In one embodiment, step S2, which calculates the antenna array gain norm and the antenna array polarization equalization difference norm based on the first vertical polarization response vector, the first horizontal polarization response vector, the second vertical polarization response vector, and the second horizontal polarization response vector, includes:

[0094] S201: Let

[0095]

[0096]

[0097]

[0098] in, , These are the first vertical polarization response vector and the first horizontal polarization response vector at the first orthogonal feed point, respectively. and These are the second vertical polarization response vector and the second horizontal polarization response vector at the second orthogonal feed point, respectively, where N represents the number of antennas;

[0099] S202: According to the formula and formula Calculate the antenna array gain norm and the antenna array polarization equalization difference norm; where n represents the nth antenna. Represents the gain norm of the antenna array, The polarization uniformity difference norm of the antenna array is represented. , Indicates azimuth. H represents the pitch angle, and H represents the conjugate transpose. , This represents the vertical polarization signal of the nth antenna. This represents the horizontal polarization signal of the nth antenna. This represents the horizontal polarization signal of the i-th antenna. This represents the horizontal polarization signal of the j-th antenna. This represents the vertical polarization signal of the j-th antenna. This represents the vertical polarization signal of the i-th antenna.

[0100] Specifically, in order to obtain a universal law conclusion, we assume that countless interferences of different polarizations are emitted from the same direction, that is... And its total power is set to be fixed. Then the signal covariance matrix received by the antenna array is:

[0101]

[0102]

[0103] The covariance matrix then simplifies to:

[0104] In the anti-interference performance analysis of satellite navigation based on the orthogonal subspace theory of signals, the covariance matrix of the interference signal can be decomposed into an interference subspace and a noise subspace. Furthermore, multi-polarization interference corresponds to two steering vectors, forming two interference subspaces. Therefore, the covariance matrix of the multi-polarization interference received by the antenna array... The eigenvalue decomposition can be expressed as:

[0105]

[0106] in , , ,

[0107] and These are the feature vectors that constitute the interference subspace and the noise subspace, respectively. and These are the eigenvalues ​​corresponding to the polarization interference subspace and the noise subspace, respectively. This can mislead people about the power of the interfering signal. and The impact is as follows:

[0108] but:

[0109]

[0110]

[0111]

[0112]

[0113]

[0114] Define the antenna array gain norm (AGN) as follows: The antenna array polarization equalization difference norm (APEDN) is defined as follows: According to the theory of orthogonal subspaces of signals, the second eigenvalue is... This determines the effectiveness of multipolar interference suppression. The smaller the value, the better the inhibitory effect. When it approaches 0, it means that MPI degenerates into a normal interference type, consuming only one array degree of freedom.

[0115] Therefore, the multi-polarization interference suppression effect of satellite navigation antenna arrays is entirely determined by AGN and APEND. Taking the partial derivatives with respect to AGN and APEND respectively yields:

[0116]

[0117]

[0118] Since the magnitude of the second eigenvalue of the multipolarization interference covariance matrix is ​​opposite to the multipolarization interference suppression performance, it can be seen that when AGN is constant, the satellite navigation polarization interference suppression performance decreases with the increase of APEDN, and when APEDN is constant, the satellite navigation polarization interference suppression performance increases with the increase of AGN.

[0119] As described in step S3 above, a multi-polarization interference suppression performance optimization function is constructed based on the antenna array gain norm and the antenna array polarization equalization difference norm.

[0120] In one embodiment, step S3, which constructs a multi-polarization interference suppression performance optimization function based on the antenna array gain norm and the antenna array polarization equalization difference norm, includes:

[0121] S301: Construct a multi-polarization interference suppression performance optimization function based on the antenna array gain norm and the antenna array polarization equalization difference norm. ;in, The polarization weight vector of the first analog domain. All contain amplitude and phase information. This is the polarization weight vector for the second analog domain.

[0122] Since GNSS signals are right-hand circularly polarized signals, GNSS antennas are also circularly polarized antennas. The most common circular polarization method for patch antennas is the orthogonal feeding method, which means that the feed points are orthogonal in space, and the vertical and horizontal linearly polarized waves with equal amplitude and a 90-degree phase difference are combined through phase shifting, power divider networks, etc.

[0123] Traditional satellite navigation anti-jamming algorithms use amplitude and phase weighting, resulting in the same weighting for both vertical and horizontal polarization responses. This proportional change in the vertical and horizontal polarization responses fails to improve multi-polarization interference suppression performance. Therefore, to avoid the limitation of satellite navigation antennas having fixed polarization characteristics after design, a digitally controlled amplitude modulator and phase modulator are connected after the orthogonal feed points (feed point x and feed point y) of a traditional circularly polarized patch antenna, followed by a combiner. The combined analog signal is then sampled by an RF front-end and an ADC, and then subjected to digital-domain spatial weighting to achieve two-level adaptive anti-jamming (analog and digital). This method can be equivalent to introducing a polarization equalization factor in the analog domain. By adjusting the polarization equalization factor, the AGN (Automatic Gaining Network) can be increased or the APEDN (Automatic Precision Equivalent Network) can be decreased, thereby improving the multi-polarization interference suppression performance of satellite navigation.

[0124] but:

[0125]

[0126]

[0127]

[0128]

[0129] in, , , and Let x and y be the vertical and horizontal polarization response vectors of the patch antenna feed, respectively. Then, the multi-polarization interference suppression performance optimization function expression after amplitude and phase weighting by the analog domain polarization equalization factor is:

[0130]

[0131] in,

[0132]

[0133]

[0134]

[0135]

[0136]

[0137] Furthermore, to avoid the polarization equalization factor optimization tending towards 0 and to ensure normal reception of satellite navigation signals, a constant energy constraint is constructed. Therefore, the optimization objective for suppressing multi-polarization interference from a certain spatial direction is:

[0138]

[0139] As described in step S4 above, the multi-polarization interference suppression performance optimization function is solved based on the Utherine-Steifel manifold constraint to obtain the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point.

[0140] In one embodiment, step S4, which involves solving the multi-polarization interference suppression performance optimization function based on a unitary Stieffer manifold constraint to obtain the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point, includes:

[0141] S401: Calculate the gradient of the multipolar interference suppression performance optimization function in Euclidean space and project it onto the Riemann gradient on the Steifel manifold. ;in Indicates that the matrix is ​​in The projection, Represents the Riemann gradient. In Euclidean space The derivative of a point, ;

[0142] S402: Settings ,in , , Indicates the first The next iteration , Indicates the first The next iteration ; This represents QR decomposition. Represents the matrix index. This represents the upper triangular matrix in the QR decomposition. This represents the transpose of the upper triangular matrix in the QR decomposition.

[0143] S403: Determine initial values and calculate On ;

[0144] S404: Combining step size parameters Calculate along Geodesic equations of direction, updating iterative values ;

[0145] S405: Judgment Does it meet the convergence condition? If not, then... Iterate from the new starting point until the preset convergence condition is met;

[0146] S406: The preset convergence condition will be met. It is proposed that the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point are obtained.

[0147] because It contains both amplitude and phase information, both of which are complex vectors. The function is a complex function. Optimization of complex functions requires using the Cauchy-Riemann CR conditions to determine whether the function is holomorphic and whether its derivative is analytic.

[0148] by For example, suppose =0, , , ,but:

[0149]

[0150] The necessary condition for the differentiability of a complex function, i.e., the CR condition, is:

[0151]

[0152] but:

[0153]

[0154]

[0155] Obviously If the CR condition is not met, then The CR condition is also not met. Therefore As a non-holomorphic function, it inherently lacks a real derivative; its derivative value approaches a point from different directions is not consistent. Therefore, it is... Non-holomorphic complex functions. For non-holomorphic complex functions, the gradient is usually represented using the formal derivative, i.e., the Wirtinger derivative, which mainly includes the holomorphic derivative and the formal inverse holomorphic derivative. Similarly, using... For example, the holomorphic derivative and the formal inverse holomorphic derivative are respectively:

[0156]

[0157] because:

[0158]

[0159]

[0160] According to the chain rule:

[0161]

[0162]

[0163] It can be seen that the Wirtinger derivative It is a combination of differentiating the real and imaginary parts of the function, therefore... It can be viewed as a derivative in the form of a complex function.

[0164] Similarly The Wirtinger derivative can be expressed as:

[0165]

[0166]

[0167] Stieffer manifold: A Stieffer manifold is a A Riemannian manifold is a set of semiorthogonal matrices.

[0168]

[0169] in, for 3D identity matrix.

[0170] Stigefer manifold gradient: when a first-order continuously differentiable function on a Stigefer manifold is Gradient in Euclidean space gradient with respect to the tangent space projected onto the Steifel manifold The relationship is:

[0171]

[0172] Stiefel manifold geodesics: A geodesic represents the shortest curve between two points on a Riemannian manifold; therefore, the gradient of a Riemannian manifold should be iterated along the direction of its geodesic. At point X on the Stiefel manifold... The geodesic lines of direction are:

[0173]

[0174]

[0175]

[0176] in, Represents the matrix index. This indicates QR decomposition.

[0177] The constant energy constraint is very similar to that of the Stiffer manifold, except that:

[0178] .

[0179]

[0180] The constant energy constraint can be approximately equivalent to a unitary Steenfair-like manifold constraint, which can be expressed as:

[0181]

[0182] It is essentially still an embedded submanifold of a Euclidean space. The tangent space in The definition of is:

[0183]

[0184]

[0185] in .

[0186] because It is an antisymmetric matrix, and ,but

[0187]

[0188] Given an optimization function Within Euclidean space The Riemann gradient of a unitary Stieffer manifold can be calculated by taking the derivative of a point. :

[0189]

[0190] in, Indicates that the matrix is ​​in The projection.

[0191] On a Ustifel-like manifold Along The geodesic equation for direction can be generalized as:

[0192]

[0193]

[0194]

[0195] in, Indicates the first The next iteration , Indicates the first The next iteration .

[0196] Therefore, the gradient descent algorithm under the constraint of a unitary Stiffer manifold can be represented as follows: 1. Determine the initial value. and calculate On 2. Combine step size parameters Calculate along Geodesic equations of direction, updating iterative values ; 3. Judgment Does it meet the convergence condition? If not, then... Use it as a new starting point for iteration until convergence.

[0197] As described in step S5 above, the first analog domain polarization weight vector is input to the CNC amplitude modulator and CNC phase modulator connected to the first orthogonal feed point, and the second analog domain polarization weight vector is input to the CNC amplitude modulator and CNC phase modulator connected to the second orthogonal feed point for adjustment, thereby obtaining the anti-interference positioning information. That is, after obtaining the corresponding first and second analog domain polarization weight vectors, inputting them to the corresponding CNC amplitude modulator and CNC phase modulator can achieve accurate positioning information for the UAV. This significantly improves the multi-polarization interference suppression capability, laying a theoretical foundation for the quantitative analysis and performance improvement of multi-polarization interference suppression in satellite navigation antenna arrays. It not only provides a new perspective in the field of satellite navigation polarization countermeasures but also offers an effective solution for improving the polarization anti-interference capability of GNSS systems.

[0198] In one embodiment, the antenna array of the ground navigation receiver is a seven-element satellite navigation antenna array. A seven-element satellite navigation antenna array is a key component in a satellite navigation system used to enhance signal reception and anti-interference capabilities. By optimizing signal reception and processing, a seven-element antenna array can significantly improve positioning accuracy.

[0199] In one embodiment, the antenna is a microstrip antenna. Microstrip antennas have advantages such as thin profile, small size, and ease of commonality. Furthermore, satellite navigation signals are right-hand circularly polarized signals, so satellite navigation array antennas are all designed as right-hand circularly polarized microstrip antennas. Conventional satellite navigation anti-interference studies typically assume that the satellite navigation antenna is an ideal point source, neglecting antenna pattern characteristics and polarization characteristics. However, due to the structural characteristics of microstrip antennas, as well as limitations in device precision and manufacturing processes, the antenna pattern is not isotropic, and the antenna polarization does not exhibit ideal right-hand circular polarization characteristics, but rather cross-polarization characteristics. In other words, actual satellite navigation array antennas can receive not only right-hand circularly polarized signals but also signals of other polarizations.

[0200] Reference Figure 2 The present invention also provides a satellite navigation polarization anti-interference device, comprising a ground navigation receiver, a digitally controlled amplitude modulator (DCAM), a digitally controlled phase modulator (DCP), and a combiner. The first and second orthogonal feed points of the antenna of the ground navigation receiver are respectively connected to the DCAM and the DCP. The DCAM and the DCP are connected to the combiner. The combiner is connected to the radio frequency (RF) front-end of the ground navigation receiver. The RF front-end is connected to the baseband processing unit of the ground navigation receiver. The baseband processing unit includes:

[0201] The acquisition module 10 is used to acquire the first vertical polarization response vector and the first horizontal polarization response vector of the first orthogonal feed point, and the second vertical polarization response vector and the second horizontal polarization response vector of the second orthogonal feed point.

[0202] The calculation module 20 is used to calculate the antenna array gain norm and the antenna array polarization equalization difference norm based on the first vertical polarization response vector, the first horizontal polarization response vector, the second vertical polarization response vector, and the second horizontal polarization response vector.

[0203] Module 30 is used to construct a multi-polarization interference suppression performance optimization function based on the antenna array gain norm and the antenna array polarization equalization difference norm;

[0204] The solver module 40 is used to solve the multi-polarization interference suppression performance optimization function based on the unitary Stieffer manifold constraint to obtain the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point.

[0205] The input module 50 is used to input the first analog domain polarization weight vector into the CNC amplitude modulator and CNC phase modulator connected to the first orthogonal feed point, and to input the second analog domain polarization weight vector into the CNC amplitude modulator and CNC phase modulator connected to the second orthogonal feed point for adjustment, so as to obtain the anti-interference positioning information.

[0206] In one embodiment, the computing module 20 includes:

[0207] The settings submodule is used for setting...

[0208]

[0209]

[0210]

[0211] in, , These are the first vertical polarization response vector and the first horizontal polarization response vector at the first orthogonal feed point, respectively. and These are the second vertical polarization response vector and the second horizontal polarization response vector at the second orthogonal feed point, respectively, where N represents the number of antennas;

[0212] The norm calculation submodule is used to calculate the norm based on the formula. and formula Calculate the antenna array gain norm and the antenna array polarization equalization difference norm; where n represents the nth antenna. Represents the gain norm of the antenna array, The polarization uniformity difference norm of the antenna array is represented. , Indicates azimuth. H represents the pitch angle, and H represents the conjugate transpose. .

[0213] In one embodiment, the building module 30 includes:

[0214] A submodule is constructed to build a multi-polarization interference suppression performance optimization function based on the antenna array gain norm and the antenna array polarization equalization difference norm. ;in, The polarization weight vector of the first analog domain. All contain amplitude and phase information. This is the polarization weight vector for the second analog domain.

[0215] In one embodiment, the solving module 40 includes:

[0216] The gradient calculation submodule is used to calculate the gradient of the multipolar interference suppression performance optimization function in Euclidean space and project it onto the Riemann gradient on the Stigefair manifold. ;in Representation matrix exist The projection, Represents the Riemann gradient. In Euclidean space The derivative of a point, ;

[0217] The settings submodule is used for setting... ,in , , Indicates the first The next iteration , Indicates the first The next iteration ; This represents QR decomposition. Represents the matrix index;

[0218] The determination submodule is used to determine the initial values. and calculate On ;

[0219] The geodesic equation calculation submodule is used to combine step size parameters. Calculate along Geodesic equations of direction, updating iterative values ;

[0220] The inventory submodule is used to determine... Does it meet the convergence condition? If not, then... Iterate from the new starting point until the preset convergence condition is met;

[0221] The vector calculation submodule is used to calculate the vectors that have reached the preset convergence condition. It is proposed that the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point are obtained.

[0222] In one embodiment, the antenna array of the ground navigation receiver is a seven-element satellite navigation antenna array.

[0223] In one embodiment, the antenna is a microstrip antenna.

[0224] In a specific embodiment, a 7-element satellite navigation antenna array at the BeiDou B3I frequency (1268MHz) was simulated using CST Studio Suite 2023. The vertical and horizontal polarization responses of each satellite navigation antenna at different azimuth and elevation angles were obtained. Following the multi-polarization interference suppression analysis model based on signal orthogonal subspaces and the calculation method for AGN and APEND indices, the first and second eigenvalues ​​of AGN, APEND, and the signal covariance matrix at each elevation and azimuth angle were calculated. The satellite navigation antenna array is affected by element mutual coupling and element positions, making the specific manifestations of AGN and APEND complex and difficult to represent with concrete expressions. However, it can still be seen that both AGN and APEND decrease with increasing elevation angle. At a constant elevation angle, APEND fluctuates with changes in azimuth angle, while the fluctuation of AGN is not significant.

[0225] When the AGN is constant, the satellite navigation polarization interference suppression performance increases with the increase of the APEDN, and when the APEDN is constant, the satellite navigation polarization interference suppression performance decreases with the increase of the APEDN. This is because the relationship between interference suppression performance and pitch angle cannot be directly determined from the AGN or APEND.

[0226] The magnitudes of the first and second eigenvalues ​​of the signal covariance matrix also depend primarily on the pitch angle, decreasing as the pitch angle increases. However, under a fixed elevation angle, the magnitude of the second eigenvalue fluctuates with changes in azimuth angle, with significant fluctuations at high elevation angles, while the first eigenvalue exhibits smaller fluctuations.

[0227] Since the multi-polarization interference suppression performance of a satellite navigation antenna array depends entirely on the magnitude of the second eigenvalue, the performance ultimately improves with increasing elevation angle, with a maximum difference in suppression performance exceeding 15 dB. Furthermore, the suppression performance exhibits periodic fluctuations with changes in azimuth angle, and the range of these fluctuations increases with increasing elevation angle. Moreover, since the APEND value changes almost in tandem with the second eigenvalue, the satellite navigation polarization interference suppression performance depends primarily on the APEDN.

[0228] The DOA range of multi-polarization interference is set as [x°, y°], where x is the elevation angle range and y is the azimuth angle range. The simulation domain polarization equalization factor corresponding to different DOA ranges of multi-polarization interference is solved by the multi-polarization interference suppression performance optimization algorithm based on QUSM-ADAM. The interference suppression effect is compared with the traditional satellite navigation interference suppression effect to obtain the heat map distribution and statistical characteristics of the multi-polarization interference suppression performance improvement effect.

[0229] The improvement in multipolar interference suppression performance increases as the DOA range of multipolar interference decreases, and is basically consistent with the distribution of the second eigenvalue. The suppression effect of multipolar interference at low elevation angles is higher than that at high elevation angles.

[0230] Table 1

[0231]

[0232] As shown in Table 1, when the multipolar interference is less than the DOA range of [2°, 2°], the multipolar interference suppression performance is improved by up to 33.87 dB. When the multipolar interference is less than the DOA range of [10°, 10°], the overall improvement in multipolar interference suppression performance is also greater than 20 dB. Furthermore, the improvement in PDF is relatively concentrated, with std stable between 4.62 and 7.77 dB. The mean and median are basically consistent, and the difference between the upper and lower quartiles is also basically consistent, without drastic fluctuations with changes in the DOA range of the multipolar interference. Therefore, this indicates that the optimized algorithm not only has superior performance but also relatively stable performance and good robustness.

[0233] The convergence speeds of P-GD (Projection gradient descent), P-Momentum (Projection Momentum), P-RMSprop (Projection Root Mean Square Propagation), P-ADAM (Projection ADAM), QUSM-GD, and QUSM-ADAM algorithms were compared in multi-polarity interference suppression performance optimization functions across different DOA ranges. Since the polarization factors obtained directly from GD, Momentum, RMSprop, and ADAM iterations do not satisfy the constraints, projection scaling is applied to the polarization factors to satisfy the constant energy constraint, thus yielding the P-GD, P-Momentum, P-RMSprop, and P-ADAM algorithms.

[0234] The proposed algorithm has the best interference suppression effect and the fastest convergence speed. It only needs 10 iterations to basically achieve convergence. The P-RMSprop, P-ADAM and QUSM-GD algorithms require an average of 30-40 iterations to achieve stable convergence, while the P-GD and P-Momentum algorithms cannot converge within 50 iterations.

[0235] With the development of electromagnetic wave polarization, multi-polarization interference suppression has become a new hot topic in satellite navigation countermeasures. However, there is currently a lack of in-depth analysis and solutions for multi-polarization interference suppression. Therefore, this paper first constructs a multi-polarization interference receiving model based on polarization decomposition and a multi-polarization interference suppression analysis model based on signal orthogonal subspace. Antenna array gain norm (AGN) and antenna array polarization equalization difference norm (APEDN) are introduced as performance evaluation indicators. Then, a multi-polarization interference suppression performance optimization function based on polarization equalization factor is constructed, and a multi-polarization interference suppression performance optimization algorithm based on QUSM-ADAM is proposed. Experimental results show that the proposed algorithm has fast convergence speed and significantly improves multi-polarization interference suppression performance. When the angle of arrival (DOA) of multi-polarization interference is less than [10°, 10°], the average suppression effect is improved by more than 20dB. This research lays a theoretical foundation for the quantitative analysis and performance improvement of multi-polarization interference suppression for satellite navigation antenna arrays. It not only provides a new perspective for the field of satellite navigation polarization countermeasures but also provides an effective solution for improving the polarization anti-interference capability of GNSS systems.

[0236] Reference Figure 3 This application also provides a computer device, which may be a server, and its internal structure may be as follows: Figure 3 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores various polarization response vectors, etc. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it can implement the satellite navigation polarization anti-interference method described in any of the above embodiments.

[0237] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer equipment on which the present application is applied.

[0238] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, can implement the satellite navigation polarization anti-interference method described in any of the above embodiments.

[0239] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media provided in this application and used in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0240] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0241] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0242] Foundational technologies in artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0243] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A satellite navigation polarization anti-interference method, characterized in that, This is achieved through a ground navigation receiver, a digitally controlled amplitude modulator (DCAM), a digitally controlled phase modulator (DCP), and a combiner. The first and second orthogonal feed points of the ground navigation receiver's antenna are respectively connected to the DCAM and the DCP. The DCAM and the DCP are connected to the combiner, which is connected to the RF front-end of the ground navigation receiver. The RF front-end is connected to the baseband processing unit of the ground navigation receiver. The method is applied to the baseband processing unit and includes: Obtain the first vertical polarization response vector and the first horizontal polarization response vector of the first orthogonal feed point, and the second vertical polarization response vector and the second horizontal polarization response vector of the second orthogonal feed point; The antenna array gain norm and antenna array polarization equalization difference norm are calculated based on the first vertical polarization response vector, the first horizontal polarization response vector, the second vertical polarization response vector, and the second horizontal polarization response vector. A multi-polarization interference suppression performance optimization function is constructed based on the antenna array gain norm and the antenna array polarization equalization difference norm. The multi-polarization interference suppression performance optimization function is solved based on the Utherstiffer manifold constraint to obtain the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point. The first analog domain polarization weight vector is input to the CNC amplitude modulator and CNC phase modulator connected to the first orthogonal feed point, and the second analog domain polarization weight vector is input to the CNC amplitude modulator and CNC phase modulator connected to the second orthogonal feed point for adjustment to obtain anti-interference positioning information; The steps of calculating the antenna array gain norm and the antenna array polarization equalization difference norm based on the first vertical polarization response vector, the first horizontal polarization response vector, the second vertical polarization response vector, and the second horizontal polarization response vector include: set up in, , These are the first vertical polarization response vector and the first horizontal polarization response vector at the first orthogonal feed point, respectively. and These are the second vertical polarization response vector and the second horizontal polarization response vector at the second orthogonal feed point, respectively, where N represents the number of antennas; According to the formula and formula Calculate the antenna array gain norm and the antenna array polarization equalization difference norm; where n represents the nth antenna. Represents the gain norm of the antenna array, The polarization uniformity difference norm of the antenna array is represented. , Indicates azimuth. H represents the pitch angle, and H represents the conjugate transpose. , This represents the vertical polarization signal of the nth antenna. This represents the horizontal polarization signal of the nth antenna. This represents the horizontal polarization signal of the i-th antenna. This represents the horizontal polarization signal of the j-th antenna. This represents the vertical polarization signal of the j-th antenna. This represents the vertical polarization signal of the i-th antenna; The step of constructing a multi-polarization interference suppression performance optimization function based on the antenna array gain norm and the antenna array polarization equalization difference norm includes: A multi-polarization interference suppression performance optimization function is constructed based on the antenna array gain norm and the antenna array polarization equalization difference norm. ;in, The polarization weight vector of the first analog domain. All contain amplitude and phase information. This is the polarization weight vector for the second analog domain.

2. The satellite navigation polarization anti-interference method as described in claim 1, characterized in that, The step of solving the multi-polarization interference suppression performance optimization function based on the Ustifel-like manifold constraint to obtain the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point includes: Calculate the gradient of the multipolar interference suppression performance optimization function in Euclidean space and project it onto the Riemann gradient on the Steifel manifold. ;in Representation matrix exist The projection, Represents the Riemann gradient. In Euclidean space The derivative of a point, ; set up ,in , , Indicates the first The next iteration , Indicates the first The next iteration ; This represents QR decomposition. Represents the matrix index. This represents the upper triangular matrix in the QR decomposition. This represents the transpose of the upper triangular matrix in the QR decomposition. Determine the initial value and calculate On ; Combined with step size parameters Calculate along Geodesic equations of direction, updating iterative values ; judge Does it meet the convergence condition? If not, then... Iterate from the new starting point until the preset convergence condition is met; It will reach the preset convergence condition. It is proposed that the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point are obtained.

3. The satellite navigation polarization anti-interference method as described in claim 1, characterized in that, The antenna array of the ground navigation receiver is a seven-element satellite navigation antenna array.

4. The satellite navigation polarization anti-interference method as described in claim 1, characterized in that, The antenna is a microstrip antenna.

5. A satellite navigation polarization anti-jamming device for implementing the satellite navigation polarization anti-jamming method according to any one of claims 1 to 4, characterized in that, The system includes a ground navigation receiver, a digitally controlled amplitude modulator (DCAM), a digitally controlled phase modulator (DCP), and a combiner. The first and second orthogonal feed points of the ground navigation receiver's antenna are respectively connected to the DCAM and the DCP. The DCAM and the DCP are connected to the combiner. The combiner is connected to the radio frequency (RF) front-end of the ground navigation receiver. The RF front-end is connected to the baseband processing unit of the ground navigation receiver. The baseband processing unit includes: The acquisition module is used to acquire the first vertical polarization response vector and the first horizontal polarization response vector of the first orthogonal feed point, and the second vertical polarization response vector and the second horizontal polarization response vector of the second orthogonal feed point; The calculation module is used to calculate the antenna array gain norm and the antenna array polarization equalization difference norm based on the first vertical polarization response vector, the first horizontal polarization response vector, the second vertical polarization response vector, and the second horizontal polarization response vector. The module is used to construct a multi-polarization interference suppression performance optimization function based on the antenna array gain norm and the antenna array polarization equalization difference norm. The solution module is used to solve the multi-polarization interference suppression performance optimization function based on the unitary Stieffer manifold constraint to obtain the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point. The input module is used to input the first analog domain polarization weight vector into the CNC amplitude modulator and CNC phase modulator connected to the first orthogonal feed point, and to input the second analog domain polarization weight vector into the CNC amplitude modulator and CNC phase modulator connected to the second orthogonal feed point for adjustment, so as to obtain the anti-interference positioning information.

6. The satellite navigation polarization anti-interference device as described in claim 5, characterized in that, The computing module includes: The settings submodule is used for setting... in, , These are the first vertical polarization response vector and the first horizontal polarization response vector at the first orthogonal feed point, respectively. and These are the second vertical polarization response vector and the second horizontal polarization response vector at the second orthogonal feed point, respectively, where N represents the number of antennas; The norm calculation submodule is used to calculate the norm based on the formula. and formula Calculate the antenna array gain norm and the antenna array polarization equalization difference norm; where n represents the nth antenna. Represents the gain norm of the antenna array, The polarization uniformity difference norm of the antenna array is represented. , Indicates azimuth. H represents the pitch angle, and H represents the conjugate transpose. , This represents the vertical polarization signal of the nth antenna. This represents the horizontal polarization signal of the nth antenna. This represents the horizontal polarization signal of the i-th antenna. This represents the horizontal polarization signal of the j-th antenna. This represents the vertical polarization signal of the j-th antenna. This represents the vertical polarization signal of the i-th antenna.

7. The satellite navigation polarization anti-interference device as described in claim 6, characterized in that, The building module includes: A submodule is constructed to build a multi-polarization interference suppression performance optimization function based on the antenna array gain norm and the antenna array polarization equalization difference norm. ;in, The polarization weight vector of the first analog domain. All contain amplitude and phase information. This is the polarization weight vector for the second analog domain.

8. The satellite navigation polarization anti-interference device as described in claim 7, characterized in that, The solution module includes: The gradient calculation submodule is used to calculate the gradient of the multipolar interference suppression performance optimization function in Euclidean space and project it onto the Riemann gradient on the Stigefair manifold. ;in Representation matrix exist The projection, Represents the Riemann gradient. In Euclidean space The derivative of a point, ; The settings submodule is used for setting... ,in , , Indicates the first The next iteration , Indicates the first The next iteration ; This represents QR decomposition. Represents the matrix index. This represents the upper triangular matrix in the QR decomposition. This represents the transpose of the upper triangular matrix in the QR decomposition. The determination submodule is used to determine the initial values. and calculate On ; The geodesic equation calculation submodule is used to combine step size parameters. Calculate along Geodesic equations of direction, updating iterative values ; The inventory submodule is used to determine... Does it meet the convergence condition? If not, then... Iterate from the new starting point until the preset convergence condition is met; The vector calculation submodule is used to calculate the vectors that have reached the preset convergence condition. It is proposed that the first analog domain polarization weight vector of the first orthogonal feed point and the second analog domain polarization weight vector of the second orthogonal feed point are obtained.

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