RU2609792C1 - Method of processing signals in modular adaptive antenna array during reception of correlated signals and interference - Google Patents

Abstract

FIELD: communication.

SUBSTANCE: invention relates to radio engineering and communication. Feature of disclosed method of processing signals in modular adaptive antenna array during reception of correlated signals and interference is that signals corresponding to branched part of power converted into M signals, in which there is no component of useful signal, is based on information on directivity modules such change of M converted signals into M_a interfering signals so, that complex amplitudes of components of noise in them approach complex amplitudes of interference in output signals of corresponding modules, while using obtained M_a signals of covariance matrix of noise and size of M_a×M_a, finding optimum for modular adaptive antenna array based on criterion of maximum signal-to-(interference + noise) vector complex weight coefficients, signals, corresponding to part of power summed in M_a modules with specified complex weight coefficients.

EFFECT: high efficiency of suppressing interference, correlated with useful signal.

1 cl, 6 dwg

Description

The invention relates to the field of radio engineering and communications and can be used in radar systems, radio navigation and radio communications, operating in a complex jamming environment.

Known circuits for adaptive antenna arrays that implement the algorithm for maximizing the output ratio of the useful signal power to the sum of the interference and noise powers [1 - Monzingo RA, Miller T.U. Adaptive antenna arrays. Introduction to the theory. M .: Radio and communication, 1986, p. 80-86, 179-240]. For the operation of an adaptive antenna array of this type, a priori information about the direction of arrival of the useful signal is used. Therefore, adaptive antenna arrays of this design are not applicable in radio systems where such information is not available.

In [2 - TIIER, 1967, v. 55, No. 12, p. 78-95] is a diagram of an adaptive antenna array that implements an algorithm to minimize the standard deviation of the received signal from the reference. For the algorithm to work in the device, it is necessary to form a reference signal. This is possible if there is a priori information about the useful signal. And since such information is never complete, the reference signal can significantly differ from the useful one, which causes a significant decrease in the noise immunity of the adaptive antenna array.

The adaptive antenna array, the construction of which is described in [3 - IEEE Trans Antennas and Propag., Vol. AP-26, 1978, No. 2, p. 228-235], implements an algorithm for minimizing output power and has relatively good noise immunity characteristics. However, in the case when there is no interference or its power is less than the power of the useful signal, the useful signal can be suppressed due to minimization of the total output power.

Known adaptive antenna array described in [4 - ed. St. USSR No. 1548820, class H01Q 21/00, claimed 10.13.87, published 07.03.90, bull. No. 9]. This device contains N antenna elements connected through hybrid devices and weight multipliers with the corresponding inputs of the common adder, the first multiplier and 2N adaptive circuits, each of which consists of an integrator, a switch, an amplifier, a variable inverting amplifier, a subtraction unit, a second multiplier and a correlator, moreover, the first and second inputs of the correlator are connected respectively to the output of the hybrid device and the output of the common adder, and the output of the correlator is connected to the first input of the subtraction unit , the second input of which is connected to the output of the first multiplier, and the output of the subtraction unit is connected to the inputs of the amplifier and the adjustable inverting amplifier, the outputs of which are connected to the inputs of the switch, the output of which is connected via the integrator to the second input of the weight multiplier and to the first input of the second multiplier, and the second input the second multiplier is connected to the output of the first multiplier, the first and second inputs of which are combined with the output of the common adder and the second input of the correlator, as well as a signal power estimator, an estimator m interferences, the comparison unit and the control unit, the inputs of the units for evaluating the signal power and the interference power are connected to the output of the common adder, and the outputs are connected to the inputs of the comparison unit, the output of which is connected to the control inputs of the switches, the output of the control unit is connected to the control inputs of adjustable inverted amplifiers and the output is connected to the output of the interference power estimation unit.

Depending on the signal-noise environment, the device operates by minimizing or maximizing the output power, which prevents the suppression of the useful signal and increases the noise immunity of the grating.

However, this implementation of an adaptive antenna array has several disadvantages: an increase in noise immunity is provided only with respect to interfering signals whose frequency band and power exceed the frequency band and useful signal power; the efficiency of the adaptive antenna array is significantly reduced if the interference power is slightly higher than the signal power at the input of the antenna elements; in the case when the number of degrees of freedom of the grating exceeds the number of interference acting on its input and the signal power is less than the total interference power, minimizing the total output power of the adaptive antenna array leads to the suppression of not only interference, but also a useful signal, for example, when a three-element array is exposed to the input useful signal and one interference, an adaptive antenna array that minimizes the output power forms two “zeros” of the radiation pattern: one in the direction of arrival of the interference, and the second in the direction of arrival yes signal.

A common drawback of the considered methods of processing signals in adaptive antenna arrays is the inability of the system to isolate interference, which is strongly correlated with the signal.

The closest in technical essence to the claimed method of processing signals in a modular adaptive antenna array when receiving correlated signals and interference is the method of processing input signals in the M - element adaptive antenna array with M _and adaptive channels (modules) described in [5 - D. Gabrielyan D., Zvezdina M.Yu., Zvezdina Yu.A., Silnitsky S.A. Quasi-optimal signal processing in adaptive radio antenna arrays // Electromagnetic waves and electronic systems, 2009, No. 5, T. 14, P. 52-55], taken as a prototype. The method consists in the fact that the signals received by each Mth channel of the modular adaptive antenna array for a given position of the maximum radiation pattern, which is a mixture of the useful signal, noise and noise, are divided by power into the transmitted and branched parts. The signals corresponding to the transmitted part of the power are summed in M _a modules to obtain the output signals of M _a modules. Is formed using the signals corresponding to the branched part of the power, the two signals A and B matrix size M × M _{as well.} The first matrix is formed using the output signals of the modules in which the signal component is excluded, and the second matrix, with an unknown interference environment, is formed using amplitude-phase distributions providing the formation of isotropic radiation patterns of the modules. Based on the obtained matrices A and B, a covariance interference matrix C = B ^-1 A (B ^-1 ) ^{* is formed} and complex weighting coefficients are determined in the form of a row vector J from M _and elements according to the formula J = J ⁰ C ^-1 , where J ⁰ is the initial vector with which the signals of the modules are summed in the absence of interference, the output signals of the modules with complex weighting factors J are summed, forming the output signal of the adaptive antenna array.

This prototype method allows to exclude the signal component from the covariance matrix and suppress noise similar to the signal spectrum. However, the transformations of the matrices A and B distort the information about the distribution of amplitudes and phases of the interfering signals in space, especially in the case when the radiation pattern of any module with zero in the direction to the signal contains additional zeros. This situation arises when more than two antenna elements are included in the module. As a result, part of the interference can be skipped when solving the adaptation problem, and the weighting coefficients J are quasi-optimal.

The problem to be solved by the alleged invention is aimed at increasing the efficiency of suppressing interference correlated with a useful signal in a modular adaptive antenna array.

To solve this problem, a method for processing signals in a modular adaptive antenna array when receiving correlated signals and interference is proposed, which consists in the fact that for each position of the maximum radiation pattern received by each Mth channel, the signals are divided by power into the transmitted and branched parts, the signals corresponding to last part of the power in the M summed _and modules form interference covariance matrix is determined by the criterion of maximum signal / (noise + interference) vector of complex weighting coefficients factors with which the output signals of the modules are summed, forming the output signal of the adaptive antenna array. In accordance with the invention, the signals corresponding to the branched part of the power are converted into M signals in which the useful signal component is excluded, taking into account information about the radiation patterns of the modules, such a change in the M converted signals in M _{a of the} interference signals is made so that the complex amplitudes of the interference components approach them to complex interference amplitudes in the output signals of the respective modules, and using the obtained M _a interference signals form a covariance interference matrix A of size M _a × _a and M are optimal for adaptive array antenna module according to the criterion of maximum signal / (noise + interference) vector of complex weights, signals corresponding to the last part of the power in the M summed _and integrated modules with predetermined weighting coefficients.

A comparative analysis of the claimed method and the prototype method shows that the claimed method differs in that the set of actions is changed, namely: two actions are introduced:

- convert the signals corresponding to the branch part of the power of the input signals into M signals in which the component of the useful signal is excluded;

- taking into account the information about the radiation patterns of the modules, such a change of M converted signals into M _{a of} interference signals is made so that the complex amplitudes of the interference components in them approach the complex amplitudes of the interference in the output signals of the corresponding modules;

and the action modes associated with:

- receiving signals at the inputs of M _a modules: sum the signals corresponding to the transmitted part of the power in M _a modules with given complex weighting factors;

- the formation of a covariance interference matrix: form a covariance interference matrix A of size M _a × M _a using the received M _a interference signals;

- finding the vector of complex weighting coefficients: find the optimal vector for complex weighting coefficients for the modular adaptive antenna array using the criterion for the maximum signal / (noise + noise) ratio.

The introduction of two actions and the change in the mode of three actions allows, in comparison with the prototype method, to provide a technical result consisting in increasing the efficiency of suppressing interference correlated with a useful signal.

The combination of distinctive features and properties of the proposed method for processing signals in a modular adaptive antenna array when receiving correlated signals and interference from the literature are unknown, and information sources containing information about similar technical solutions having features similar to those distinguishing the claimed solution from the prototype are not known , as well as properties that match the properties of the proposed solution, therefore, we can assume that it has significant differences, it follows from them that are not obvious way and, therefore, meets the criteria of patentability "novelty" and "inventive step".

The essence of the proposed method is disclosed by figures 1-6.

The figure 1 shows the structural diagram of a modular adaptive antenna array that implements the proposed method of processing signals in a modular adaptive antenna array when receiving correlated signals and interference.

The figure 2 shows the radiation pattern of the module (adaptive channel), including 4 antenna elements. The figure 3 presents the angular dependence characterizing the sensitivity of the modular adaptive antenna array to interference.

The figure 4 presents the radiation pattern of a modular adaptive antenna array before (dashed curve) and after adaptation (solid curve).

Figures 5, 6 show the distributions of the amplitudes and phases of the complex weighting coefficients, respectively, in the channels of the modular adaptive antenna array, connected for clarity by broken lines.

When implementing the proposed method for processing signals in a modular adaptive antenna array when receiving correlated signals and interference, the following sequence of operations is performed:

- the signals received by each M-th channel of a modular adaptive antenna array for a given position of the maximum radiation pattern, which are a mixture of the useful signal, noise and noise, are divided by power into the transmitted and branch parts - 1;

- signals corresponding to the last part of the power in the M summed _and modules with predetermined complex weighting factors in the channels of antenna elements to receive the outputs of module - 2;

- the signals corresponding to the branch part of the power are converted into M signals, in which the component of the useful signal is excluded - 3;

- taking into account the information about the radiation patterns of the modules, such a change M of the converted signals into M _{a of} interference signals so that the complex amplitudes of the noise components in them approach the complex amplitudes of the interference in the output signals of the corresponding modules - 4;

- using the obtained M _a interference signals, form a covariance interference matrix A of size M _a × M _a - 5;

- find the optimal for a modular adaptive antenna array by the criterion of the maximum signal / signal (interference + noise) vector of complex weighting factors - 6;

- summing the output signals from the modules M _and the found optimal for adaptive array antenna module according to the criterion of maximum signal / (noise + interference) vector of complex weights, forming the modular output adaptive antenna array - 7.

The structure of the modular adaptive antenna array (ΑΑΡ) (Fig. 1) includes antenna elements 1, phase shifters 2, the first blocks of the complex signal weighting 3, the adders of the modules 4, the second blocks of the complex signal weighting 5, the signal processing device 6, the storage unit of the sets of complex weighting coefficients 7, unit for generating complex weighting functions 8, unit for approximating radiation patterns (MD) of modules in the side lobe region 9, unit for generating covariance interference matrix 10, unit for generating complex cial coefficients 11, the control unit 12 and storage unit patterns 13 modules.

M antenna elements 1 are connected through M phase shifters 2 to the inputs of the first blocks of the complex signal weighting 3, the outputs of which are connected appropriately to the inputs of M _{a of the} adders of the modules 4. The outputs of the adders of the modules 4 through the second blocks of the complex signal weighting 5 are connected to the inputs of the temporary signal processing device 6 The storage unit for sets of complex weighting coefficients 7 is connected via information outputs to the first information inputs of the complex weighting functions forming unit 8, second its information inputs are connected to the corresponding channels of the modular ΑΑΡ (after phase shifters 2). The information outputs of the complex weighting function forming unit 8 are electrically connected to the first information inputs of the approximation unit of the modules DN in the side lobe region 9. The information outputs of the approximating block of the modules DN in the side lobe region 9 are connected to the information inputs of the covariance interference matrix forming unit 10. Information outputs of the forming unit the covariance interference matrix 10 is electrically connected to the information inputs of the complex weighting unit forming unit 11. You The odes of the integrated weighting unit 11 are connected to the control inputs of the second integrated signal weighting units 5. The control inputs of the phase shifters 2 and the first integrated signal weighting units 3 receive information from the first and second information outputs of the control unit 12. Management of the storage unit for the sets of integrated weighting factors 7 is produced by control signals coming from the third outputs of the control device 12. Information outputs of the DN storage unit modules 13 are connected to the second information inputs of the approximation block of the DN of the modules in the region of the side lobes 9, and its control inputs are connected to the fourth outputs of the control device 12. Synchronization of the operation of the devices and blocks of the modular AAP can be performed by the control device 12. The synchronization circuits in FIG. 1 are not shown.

Before considering the functioning of a modular adaptive antenna array that implements the proposed method of signal processing, to substantiate it, we state the following.

. На вход ААР с направления θ₀ поступает сигнал, а в направлениях θ_j (j=1,2,…,J) расположены источники помех.Let there be M - elementary AAR, in which the receiving channels are combined in M _{and of the} controlled modules of M _with channels in each. Let the DN of each antenna channel be described by a complex function

. A signal is input to the AAP input from the direction θ ₀ , and interference sources are located in the directions θ _j (j = 1,2, ..., J).

Suppose that during the time interval t = [t ₀ , t ₀ + T] the complex envelopes of the signal, noise, and noise are described by the functions y (t), x _j (t), and n (t), respectively.

As a result, at the output of the m-th antenna element AAR, an initial mixture of signals, noise and noise is formed, which is described by an expression of the form:

Let the signals from the outputs of the antenna elements are summed in the AAR with the weights corresponding to the complex weighting coefficients (CEC) of the row vector j = (j ₁ , j ₂ ..., j _M ). Then the complex envelope of the signal at the output of the AAR is the sum of the functions (1):

We introduce a rectangular matrix J, which is equal to the number of rows M _and the number of modules controlled AAP, and in each i-th row are non-zero coefficients _with only M, integrated values of which correspond to complex weighting coefficients i-th module. Then at the outputs of the modules a vector of signals is formed:

Given the designations introduced, the output signal AAP is determined by the sum of the output signals of the modules (3), i.e.:

where w is the vector of complex weighting coefficients (CVC) of the AAP modules.

, который обеспечивает максимальное значение отношения сигнал/(помеха + шум) (ОСПШ) на выходе ААР при условии, что комплексная огибающая сигнала коррелирована с комплексной огибающей помех.It is necessary to find such a vector

which provides the maximum value of the signal / (interference + noise) (SINR) ratio at the AAR output, provided that the complex envelope of the signal is correlated with the complex envelope of interference.

The average power of the signal received by the AAR during the considered time interval is determined by the expression:

Hereinafter, the symbol “*” as applied to the scalar quantity means complex conjugation, and to the vector - Hermitian conjugation; “-” - sign of statistical averaging over a given time.

Then the average output power of the received AAR signal for the considered time interval is described by a function of the form:

в виде:Let us dwell on the statistical averaging procedure in more detail. Imagine the value

as:

In accordance with the statistical theory of antennas [6 - Problems of antenna technology / Ed. L.D. Bahraha D.I. Voskresensky. M .: Radio and communication, 1989. - 368 p.] The noise of individual channels can be considered statistically independent of each other and from external signals. This allows us to simplify the expression (7) and write it in the form:

- дисперсия внутренних шумов в антенном элементе ААР.Where

- the dispersion of internal noise in the antenna element AAP.

In the absence of interference in expression (8), we can omit all terms that are associated with the complex envelopes x _i (t). As a result, expression (6) in this situation takes the form:

- единичная матрица, а δ_k,l - символы Кронекера.Here is the matrix

is the identity matrix, and δ _{k, l} are Kronecker symbols.

Adaptation theory generally assumes that signal and interference are statistically independent. In this case, terms containing the cross products of the signal and interference are excluded from expression (8), and expression (9) is written as:

ковариационная матрица помех.Where

covariance interference matrix.

From the expression (10) it follows that the SINR value can be represented as a ratio of Hermitian forms

In the theory of matrices there are theorems [7 - Gantmakher F.R. Matrix theory. 4th ed. M: Science. Ch. ed. Phys.-Math. lit. 1988], in accordance with which the maximum ratio of Hermitian forms is achieved provided that

However, as follows from expressions (6) and (7), the presence of terms in them reflecting nonzero covariance of the signal and interference does not allow in the general case to consider a solution of the form (12) optimal.

In this regard, to solve the formulated problem of suppressing adaptive AAR interference correlated with a signal, we consider the following method.

First, we form M sets of KVK according to the formula:

In expression (13), the amplitude matrix W is randomly selected using a random number generator distributed uniformly in the interval from 0 to 1. The values of the vector θ _m are set randomly in the region of the most likely occurrence of interference (in the region of the side lobes Ω) so that θ _m did not fall into the region of the main beam of the AAP.

The obtained distributions make it possible to form M complex weight functions

имеют «нуль» ДН в направлении θ₀ и максимумы в направлениях θ_m.Expression (13) is a formula for the matrix synthesis of “zero” DNs [8 - Zelkin V.G., Sokolov E.G. Antenna synthesis methods: Phased array antennas and antennas with continuous opening. - M .: Owls. Radio. 1980. 296 p.], Therefore, all functions

have “zero” MD in the direction θ ₀ and maxima in the directions θ _m .

We believe that the AAM modules are described by expressions of the form:

, решив задачу минимизации среднеквадратического отклонения для каждого модуля:We approximate the module DNs in the side lobe region using weight functions

by solving the problem of minimizing the standard deviation for each module:

It is known [9 - Bahrakh L.D., Kremenetsky S.D. Synthesis of emitting systems (theory and calculation methods). - M .: Owls. Radio, 1974] that the solution to problem (16) can be obtained by the least squares method in the form:

Where

It follows that expression (17) can be represented in vector form as:

Of interest is the case when the matrix C is diagonal. In this case, up to a constant factor, expression (20) can be represented as:

Expression (21) will be accurate if the AAP channels are placed with a step of 0.5λ, and the region of the side lobes Ω approaches the entire region of visible angles. In this case, the matrix C can be represented as:

It should be noted that the expansion of the side lobe region, i.e. narrowing of the main beam takes place in the case of an increase in the number of antenna elements. This means that expression (21) is valid for multi-element antenna arrays.

If the solution to the approximation problem is sufficiently accurate, then for arbitrary sources of interference, the covariance matrix of interference, determined using M _a adaptive channels (modules), will approach the covariance matrix of interference B of the original lattice. As a result, the solution to the problem of suppressing interference can be sought by formula (12).

Consider the operation of a modular adaptive antenna array.

For each position of the maximum of the DN, the signals received by the antenna elements 1, which are a mixture of the useful signal, interfering signals, and channel noise поступ, are fed to the phase shifters 2. In accordance with the information about the direction of the main maximum of the DN coming from the first information input of the control device 12 to the control the inputs of phase shifters 2, phase shifters 2 are tuned, and the main maximum of the beam is oriented in the direction of the useful signal. The signals at the outputs of the phase shifters are divided by power into the transmitted and branched parts. The signals corresponding to the transmitted part of the power are supplied to the first blocks of the complex weighting of signals 3, and the signals corresponding to the branch part of the power are sent to the second inputs of the block for the formation of complex weight functions 8. In the first blocks of the complex weighting of signals 3 using specified KVK corresponding to the required shape DNs stored in the control device 12 and coming from its second information outputs, the input signals are weighted. Weighted signals are fed to the inputs of the adders of the modules 3, where they are added algebraically, forming the output signals of the modules.

At the first inputs of the complex weighting functions forming unit 8, the KVK corresponding to the selected direction of the maximum of the beam are selected from the storage unit of the sets of complex weighting coefficients 7, in which zero is generated for the useful signal in each of the modules. In the block for the formation of complex weighting functions 8, the incoming signals are converted into M signals, in which the component of the useful signal is excluded. In the approximation block of the DN modules in the region of the side lobes 9 based on the information extracted from the storage block of the DNs of the modules 13 and fed to the second information inputs of the approximation block of the DNs of the modules in the region of the side lobes 9 and signals corresponding to M signals with the excluded useful signal component and incoming to the first information inputs of the approximation block of the bottom of the modules in the region of the side lobes 9, M signals are converted into M _and interference signals (by the number of modules) so that complex the plates of the component noise in them approached the complex amplitude of the interference in the output signals of the corresponding modules. In the block for generating the covariance interference matrix 10, using the received M _a interference signals, a covariance interference matrix A of size M _a × M _{a is formed} . Based on the signals corresponding to the elements of the covariance interference matrix A of size M _a × M _a coming from its outputs, the block of complex weighting coefficients 11 determines the optimal weighting factor vector for the modular ΑΑΡ by the criterion of the maximum signal / signal (noise + noise) ratio. The signals corresponding to the components of the vector are supplied to the control inputs of the second blocks of complex weighting signals 5. The signal processing unit 6 interim output signals M _and modules added to the found optimal for modular ΑΑΡ Browse maximum signal / (noise + interference) vector of complex weights coefficients, forming the output signal of the modular AAP.

To confirm the operability and effectiveness of the patented method of processing signals in a modular adaptive antenna array when receiving correlated signals and interference, computer simulation was performed. As an example, consider M = 64, an elementary linear antenna array with a spacing d = 0.5λ between elements.

The bottom of the antenna element is described by a complex function

The interference environment is set using three sources of interference located in the directions θ _1,2,3 = (2,4 °; 3,6 °; 4,4 °). The signal (useful signal) comes from the direction θ ₀ = 0.

The outputs of the antenna elements of the linear antenna array are combined into modules of 4 antenna elements in each, which allows you to get 16 adaptive channels (modules) with identical amplitude amplitudes shown in FIG. 2.

которая показывает, что после применения формулы (13) все комплексные весовые функции обеспечивают формирование глубокого нуля в направлении на источник сигнала. При этом в области боковых лепестков чувствительность ААР изменяется в диапазоне 37…47 дБ в пределах от -60° до 60°. При формировании функций

используются все элементы ААР без группировки по модулям, что позволяет избежать появления дополнительных нулей ДН.In FIG. 3 shows the angular dependence of the function

which shows that after applying formula (13), all complex weight functions provide the formation of a deep zero in the direction of the signal source. Moreover, in the region of the side lobes, the AAR sensitivity varies in the range of 37 ... 47 dB in the range from -60 ° to 60 °. When forming functions

all AAR elements are used without grouping by modules, which avoids the appearance of additional MD zeros.

A comparison of FIG. 2 and FIG. 3 shows that the dynamic range of the sensitivity of a conventional AAR to interference is much higher, which is associated with changes in the adaptive channel pattern in the “zero” pattern of the pattern in FIG. 2. In addition, the usual ΑΑΡ does not allow to exclude completely the signal component from the mixture of signal and interference, which affects the suppression of noise correlated with the signal.

In FIG. Figure 4 shows DN Н before (dashed curve) and after adaptation (solid curve). In FIG. 5 and FIG. Figure 6 shows the distribution of complex weights in the channels ΑΑΡ. For convenience, the values of the amplitudes and phases of the complex weights are connected by segments.

From the analysis of FIG. 4 it follows that the theoretical depth of the formed dips in the directions to the interference sources reaches -90 dB. The areas of “zeros” in the formed pattern are located with a period that is associated with the orientation of the “zeros” of the pattern of the module (adaptive channel).

A modular adaptive antenna array that implements the patented method can be built on the basis of microwave devices widely used in development and well-developed in the manufacture of microwave devices: antenna elements controlled by analog or digital phase shifters, integrated signal weighting units, and signal adders [see for example: 10 - Active phased antenna arrays / Ed. DI. Voskresensky and A.I. Kanaschenkova. - M .: Radio engineering, 2004. S. 66-82, 121-130]. To create electronic storage, computing and control units (numbered 6-13 in Fig. 1), there is a developed elemental base, in particular programmable logic integrated circuits and digital signal processors, which provide the implementation of control and data processing functions. In particular, the domestic signal controller 1892 BM3T has such capabilities [11 - I. Pletneva. Implementation of control algorithms for adaptive antenna arrays based on a digital signal controller // Izv. universities. Electronics, 2009, No. 3, p. 61-67].

The above materials confirm compliance with the criterion of "industrial applicability" of the proposed method.

Thus, the patented method of processing signals in a modular adaptive antenna array when receiving correlated signals and interference is practically feasible and provides the declared technical result, which consists in increasing the efficiency of suppressing interference correlated with a useful signal in the absence of a priori information about the directions of their arrival without disrupting the operating mode the work of a modular adaptive antenna array.

Claims (1)

A method of processing signals in a modular adaptive antenna array when receiving correlated signals and interference, consisting in the fact that for each position of the maximum radiation pattern received by each Mth channel, the signals are divided by power into the transmitted and branched parts, the signals corresponding to the transmitted part of the power are summed in M _a modules, form a covariance interference matrix, determine by the criterion of the maximum signal / signal (interference + noise) the vector of complex weighting coefficients, with which the output s module signals, forming the output signal of the adaptive antenna array, characterized in that the signals corresponding to the branch part of the power are converted into M signals, in which the component of the useful signal is excluded, and taking into account information about the radiation patterns of the modules, such a change in M converted signals into M _and interference signals signals to the complex amplitudes of the interference components in these complex amplitudes approaching the noise in the output signals of the respective modules, while using the received M signals _but the odds iruyut covariance matrix of interference A of size M _and × M _and find an optimum for modular adaptive array antenna according to the criterion of maximum signal / (interference + noise) vector of complex weights, signals corresponding to the last part of the power summed in M _and with desired complex modules weighting factors.

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