RU2683140C1 - Adaptive antenna array - Google Patents

Abstract

FIELD: antenna equipment.SUBSTANCE: invention relates to antenna technology and can be used in radio communication systems when receiving signals under the influence of interference, the sources of which are in motion. Adaptive antenna array includes antenna elements that form the N-element antenna array, an adaptive processor, the outputs of which are connected to the inputs of N units for complex signal weighting, a common adder, to which the outputs of the complex signal weighting blocks are connected, the output of the common adder is connected to the adaptive processor, and is also the output of the device.EFFECT: technical result consists in increasing the speed of operation of the adaptive antenna array when receiving a useful signal and suppression of interfering signals in the case of a rapid change in the location of their sources by adjusting the weight coefficient vector based on the gradient approach.1 cl, 11 dwg

Description

The invention relates to antenna technology and can be used in radio communication systems when receiving signals under the influence of interference, the sources of which are in motion.

Known adaptive antenna array [1, p. 56, 2] containing N antenna elements. A device with quadrature channels is introduced into the channel of each antenna element, with the help of which the signal is divided into in-phase and quadrature components, and each of the components is subjected to the operation of multiplication by the weight coefficient. The signals obtained after such processing are added to the adder. The management of the values of weights is carried out using a signal processor.

However, the functioning of this adaptive antenna array when changing the direction of arrival of the useful and interference signals is associated with large computational and time costs.

Known adaptive antenna array [3], containing antenna elements, hybrid devices that provide separation of signals into in-phase and quadrature components, weight multipliers, a common adder, adaptive circuits, band-pass and barrage filters, power measurement units, a comparison unit and a control unit. Using filters, power measurement units, a comparison unit, and a control unit, the output power of the total adder is minimized and maximized in the modes of suppressing interference and extracting a useful signal.

The disadvantage of this adaptive antenna array is the complexity of the circuit and the need for separate execution of the modes of minimizing interference and maximizing the power of the useful signal, which leads to an increase in computational costs and a decrease in speed.

Known adaptive antenna array [4], containing N antenna elements connected through complex weight multipliers with inputs of a common adder, N adaptive circuits, the first inputs of which are connected to the outputs of the corresponding antenna elements, and the second inputs - with the outputs of the common adder. The first outputs of adaptive circuits are connected to the corresponding inputs of complex weight multipliers. The first and second inputs of the output power maximization unit are connected respectively to the first and second outputs of the adaptive circuits, and the outputs are connected to the corresponding inputs of the adaptive circuits. The adaptive antenna array has greater noise immunity with respect to interfering signals, regardless of their frequency band.

However, it is advisable to use such an adaptive antenna array when receiving signals that have a pause during transmission, for example, signals with pseudo-random frequency tuning. In addition, the introduction of a unit for maximizing the output power and changing the connections due to this introduction significantly complicates the adaptive antenna array.

The closest analogue (prototype) is a multifunctional adaptive antenna array [5], which includes N antenna elements, N blocks of complex signal weighting, a common adder, an adaptive processor containing a control vector generating unit, a covariance matrix generating unit for interfering signals, and a reversing unit covariance matrix of interfering signals, a unit for generating a vector of weight coefficients. The outputs of the antenna elements are connected to the corresponding inputs of the integrated signal weighting units and to the inputs of the covariance matrix generation block of the interference signals, which are the corresponding inputs of the adaptive processor. The outputs of the unit for generating the covariance matrix of interfering signals are connected to the corresponding inputs of the unit for reversing the covariance matrix of interfering signals, the outputs of which are connected to the inputs of the unit for generating the vector of weighting coefficients. The outputs of the unit for generating the vector of weighting coefficients, which are the outputs of the adaptive processor, are connected to the control inputs of the integrated weighing units, the outputs of which are connected to a common adder.

The disadvantages of this device, as well as analogues, are the large computational costs and low performance when forming the "zeros" of the antenna array in the direction of arrival of the interfering signals in case of a rapid change in the location of their sources.

The proposed adaptive antenna array is aimed at achieving a technical result - improving the performance of the adaptive antenna array when receiving a useful signal and suppressing interference signals in the case of a rapid change in the location of their sources by adjusting the weight vector based on the gradient approach.

To achieve the specified technical result, an adaptive processor comprising a control vector generation unit, a covariance matrix generating unit for interference signals, a weighting coefficient vector generating unit, a multifunctional adaptive antenna array, which is the closest analogue (prototype) containing N antenna elements, N complex weighting units signals, a common adder, an additional block is introduced for measuring the signal / (noise + noise) ratio. Also, the structure of the block for generating the vector of weighting coefficients, consisting of the block for forming the step, four computing modules, and the storage unit for the vector of weighting coefficients, has been changed. The outputs of the N antenna elements are connected to the information inputs of the N blocks of complex signal weighting and to the inputs of the covariance matrix generation block of the interference signals, which are the corresponding inputs of the adaptive processor. The outputs of the block for generating the covariance matrix of the interference signals are connected to the corresponding inputs of the block for generating the vector of weights, namely, to the first inputs of the first computing module of the block for generating the vector of weights, the first output of the block for forming the step is connected to the second input of the first computing module. The outputs of the first computing module are connected to the first inputs of the third computing module, the second output of the step forming unit is connected to the input of the second computing module, the outputs of which are connected to the second inputs of the third computing module, the outputs of which are connected to the first inputs of the fourth computing module, the second input of which is connected to the output block forming the control vector, the information input of which is connected to an external source. The third input of the fourth computing module is connected to the output of the storage unit of the vector of weights. The output of the fourth computing module, being the output of the weighting vector forming unit and the adaptive processor, is connected to the control inputs of the complex weighting units, as well as to the second input of the weighting vector storage unit. The inputs of the N blocks of complex weighing are connected to a common adder, the output of which is connected to the input of the signal / (noise + noise) ratio measuring unit of the adaptive processor, the output of which is connected to the input of the step forming unit and to the first input of the storage unit of the weight vector. The output of the total adder is also the output of the device.

A comparative analysis of the claimed device and prototype shows that the claimed device is characterized in that:

a unit for measuring the signal / (noise + noise) ratio is introduced into the adaptive processor;

communication between the blocks has been changed: the output of the common adder is connected to an adaptive processor, namely, to the signal / (ratio + noise) measuring unit; the output of the signal / (noise + noise) measuring unit is connected to the weighting vector generation unit; the outputs of the block forming the covariance matrix of the interference signals are connected to the inputs of the block forming the vector of weights;

the structure of the block for the formation of the vector of weighting coefficients is changed.

The combination of distinguishing features of the proposed adaptive antenna array from the available literature is unknown, therefore, it meets the criteria of the invention of "novelty."

An analysis of the known technical solutions (analogues) in the studied area and its adjacent areas allows us to conclude that the elements introduced in the indicated population are unknown, and their introduction into the adaptive antenna array in the indicated manner and with the indicated connections allows us to provide it with a new property - to adjust the weight vector coefficients based on the gradient method in order to quickly change the direction of the "zeros" of the radiation pattern. This property allows you to effectively suppress interference signals whose sources are in motion. In general, this ensures the claimed solution meets the criterion of "inventive step".

The figure 1 shows the structural diagram of an adaptive antenna array.

The figure 2 presents an embodiment of an adaptive processor.

The figure 3 shows a block diagram of the formation of the vector of weights.

The figure 4 shows the graphs of the transition characteristics during the formation of the vector of weights based on the gradient approach for cases when the vector S ₀ (curve 1) and the value of the vector of weights obtained at the previous adjustment stage (curve 2) are taken as the initial values of the vector of weights.

Figure 5 shows a graph of the amplitude variation of the vector of weighting coefficients in the 7th processing channel for the adjustment period for the case when the value of the vector S ₀ is taken as the initial value of the vector of weighting coefficients.

The figure 6 shows a graph of the phase change of the vector of weights in the 7th processing channel for the adjustment period for the case when the value of the vector S ₀ is taken as the initial value of the vector of weights.

The figure 7 shows a graph of the amplitude of the vector of weighting coefficients in the 7th processing channel for the period of adjustment for the case when the value obtained at the previous stage of adjustment is taken as the initial value of the vector of weighting coefficients.

The figure 8 shows a graph of the phase change of the vector of weighting coefficients in the 7th processing channel for the adjustment period for the case when the value obtained at the previous adjustment step is taken as the initial value of the weighting vector.

The figure 9 presents the radiation patterns of the adaptive antenna array at the initial time T = 0 when changing the angular position of the sources of interfering signals.

The figure 10 presents the radiation patterns of the adaptive antenna array in the middle of the process of adjusting the vector of weight coefficients T / 2 when changing the angular position of the sources of interfering signals.

The figure 11 presents the radiation patterns of the adaptive antenna array in steady state.

The adaptive antenna array (Fig. 1) includes antenna elements 1 forming an N-element antenna array, an adaptive processor 2, the outputs of which are connected to the inputs of N blocks 3 of a complex signal weighting, a common adder 4, to which the outputs of the blocks of 3 complex weighing are connected signals, the output of the total adder 4 is connected to the adaptive processor 2, and also is the output of the device.

Adaptive processor 2 (Fig. 2) includes a control vector generation unit 5, a covariance matrix of interference signals generating unit 6, a weighting coefficient vector generating unit 7, a signal / (noise + noise) measurement unit 8. The outputs of block 6 of the formation of the covariance matrix of interfering signals are connected to the corresponding inputs of block 7 of the formation of the vector of weights, the second input of which is connected to the output of block 5 of the formation of the control vector. The information input of the control vector generation unit 5 is connected to an external source. The output of the weighting coefficient vector generating unit 7 is the output of the adaptive processor 2. The output of the signal / (noise + noise) measuring unit 8 is connected to the weighting vector generating unit 7.

Block 7 of the formation of the vector of weights (Fig. 3) includes a block 9 of the formation of the step, four computing modules 10-13 and block 14 of the storage of the vector of weights. The outputs of the step forming unit 9 are connected to the inputs of the first and second computing modules 10 and 11. The outputs of the first and second computing modules 10 and 11 are connected to the corresponding inputs of the third computing module 12. The outputs of the third computing module 12 and the block are connected to the corresponding inputs of the fourth computing module 13 14 storing the vector of weights. The output of the fourth computing module 13 is connected to the input of the weight vector vector storage unit 14 and is the output of the weight vector vector block 7.

Before considering the functioning of the proposed adaptive antenna array, we carry out a theoretical justification for the reception of a useful signal implemented in the proposed device when exposed to various interference signals whose sources constantly change their position in space.

,

, (

), источники которых постоянно изменяют свое положение в пространстве. Требуется определить и реализовать набор весовых коэффициентов в каналах адаптивной антенной решетки, обеспечивающих максимум отношения сигнал / (помеха + шум) на выходе адаптивной антенной решетки.Consider an N-element antenna array with known emitting aperture geometry, which receives a useful signal from the θ ₀ , ϕ ₀ direction and suppresses interference signals coming from unknown directions

,

, (

) whose sources are constantly changing their position in space. It is required to determine and implement a set of weighting coefficients in the channels of the adaptive antenna array, providing a maximum signal / (noise + noise) ratio at the output of the adaptive antenna array.

The objective function is the maximum SINR

where W is the vector of weights;

R _ss - covariance matrix of the useful signal;

R _nn is the covariance matrix of interference signals;

+ - operation of complex conjugation and transposition.

To maximize the expression (1), it is necessary that the vector of weight coefficients takes an optimal value

where S ₀ is the vector responsible for the formation of the radiation pattern of the adaptive antenna array in the direction of arrival of the useful signal in the absence of interference.

* - operation of complex pairing.

Weighting coefficients obtained on the basis of expression (2) make it possible to form “zeros” of the radiation pattern of the adaptive antenna array in the directions to the sources of interfering signals and suppress them. However, if the sources of the interfering signals are in motion, it is necessary to constantly calculate the inverse covariance matrix of the interfering signals, which is associated with large time and computational costs. In this regard, this approach is more appropriate to apply for stationary sources of interference.

Since the objective function (1) corresponds to only one global maximum, it is possible to use the gradient method described in [1] to search for it

);where W (j + 1) is the value of the vector of weights at j + 1 iterations (

);

W (j) is the value of the vector of weighting coefficients at the jth iteration;

α (j) is a number that determines the direction and step of adaptation at the jth iteration;

∇ _w (Q) is the gradient of the objective function.

Expression (3) after simple mathematical transformations takes the form

where E is the identity matrix;

dt is the iteration step;

γ is a coefficient characterizing the intensity of adaptation;

ΔW (j) is a vector characterizing adaptation noise.

It should be noted that at the initial moment of time at the first iteration, the value of W (j) is equal to W (0) = S ₀ . Further, with each step, W (j) will tend to W _opt . The main advantage of this method is that there is no need for direct inversion of the covariance matrix of interfering signals. However, expression (4) is effective for the case when the signal sources do not move in space. This is due to the fact that in the case of a change in the radiation direction of at least one of the sources of interfering signals, it is necessary to adjust the weight vector, again starting with W (0) = S ₀ (Fig. 5-6), although the weight vector itself changes slightly . This approach leads to an increase in the transient time (Fig. 4 curve 1) when adjusting the vector of weight coefficients in the processing channels and to reduce the performance of the adaptive antenna array when forming “zeros” of the radiation pattern in the direction of the sources of interfering signals in motion (Fig. 9-11 dashed curve).

To reduce the transient time when adjusting the vector of weight coefficients in the processing channels and to increase the operating speed of the adaptive antenna array when forming the “zeros” of the radiation pattern in the direction of the interference signals whose sources are in motion, it is necessary that for every change in the covariance matrix R _nn recalculation of the vector of weight coefficients based on expression (4), but already taking into account the previous value, since its amplitude and phase characteristics from enyayutsya slightly (FIG. 7-8). The rate of conversion of the vector of weighting coefficients should be several times greater than the rate of change of direction to the source of the useful signal and interference.

In view of the above, expression (3) will take the form

обозначает изменение углового положения источников излучения помеховых сигналов.In expression (5), the index

denotes a change in the angular position of the radiation sources of interfering signals.

Then expression (4) is transformed to the form

, вектор весовых коэффициентов принимает значение вектора, полученного при предыдущем угловом положении источников помех (фиг. 7-8), то есть W(i+1, 0)=W(i, J). Такой подход позволяет уже в начальный момент времени при изменении углового положения источников помеховых сигналов обеспечить формирование «нулей» диаграммы направленности в их направлении (фиг. 9-11 сплошная кривая) и значительно сократить время переходного процесса (фиг. 4 кривая 2). В случае, если изменяется направление излучения полезного сигнала, алгоритм, описанный выше, повторяется, то есть вектор весовых коэффициентов в начальный момент времени принимает значение W(0,0)=S₀.A distinctive feature of the functioning of the adaptive antenna array based on expression (6) is the fact that the weight vector W (i, j) only at the initial moment at the first iteration takes the value W (0,0) = S ₀ , then, when the angular positions of interference sources and, therefore, the covariance matrix of interference signals

, the vector of weights takes the value of the vector obtained at the previous angular position of the interference sources (Fig. 7-8), that is, W (i + 1, 0) = W (i, J). This approach allows already at the initial time when changing the angular position of the sources of interfering signals to ensure the formation of "zeros" of the radiation pattern in their direction (Fig. 9-11 solid curve) and significantly reduce the transition process (Fig. 4 curve 2). If the direction of emission of the useful signal changes, the algorithm described above is repeated, that is, the vector of weight coefficients at the initial time takes the value W (0,0) = S ₀ .

The proposed adaptive antenna array operates as follows.

An additive mixture of the useful signal, noise and interfering signal is received by the N antenna elements 1. A part of the mixture of the useful signal, noise and interfering signal is supplied to the inputs of the blocks 3 of the complex signal weighting. Similarly, the second part of the mixture of the useful signal, noise and the interfering signal is supplied to the corresponding inputs of the adaptive processor 2, namely, to the inputs of the block 6 of the formation of the covariance matrix of the interfering signals.

Let us consider in more detail the functioning of adaptive processor 2. A mixture of useful and interfering signals is fed to the inputs of block 6 for generating a covariance matrix of interfering signals, in which the coefficients of the covariance matrix of interfering signals are formed in accordance with the above relations. The signals corresponding to the coefficients of the covariance matrix of the interfering signals are fed to the inputs of the block 7 of the formation of the vector of weight coefficients. The signal from the block 5 of the formation of the control vector (S ₀ = A _n exp (-ik (x _n sin θ ₀ cos ϕ ₀ + for _n sin θ ₀ sin ϕ ₀ ))) containing information about the direction of arrival of the useful signal and the amplitude-phase distribution of currents in the emitters of the antenna array. The signal about the direction of arrival of the useful signal and the change in the amplitude-phase distribution of currents in the emitters of the antenna array is fed to the information input of the control vector generation unit 5 from an external source. By the control command from the signal / (noise + noise) ratio measuring unit 8, signals corresponding to the elements of the weighting vector are generated in the unit 7 for generating the vector of weighting coefficients. The formation of these signals is performed on the basis of the gradient method.

Let us consider in more detail the functioning of the block 7 of the formation of the vector of weight coefficients. The inputs of the first computing module 10 receives signals from block 6 of the formation of the covariance matrix of interference signals, as well as a signal from block 9 of the step formation. As a result, in the first computing module 10, which stores information about the value of the coefficient γ, the multiplication operation γdtR _{nn is} performed. The signal from the step forming unit 9 is input to the second computing module 11, which stores information about the dimension of the unit matrix E. As a result, the operation (dt-1) E is performed in the second computing module 11. The signals from the first and second computing modules 10 and 11 are fed to the corresponding inputs of the third computing module 12, where the addition operation [[dt-1) E + γdtR _nn ] is performed. Next, the signals from the third computing module 12 are fed to the inputs of the fourth computing module 13. Also, the inputs of the fourth computing module 13 receive signals from the control vector generation unit 5 and from the weight vector storage unit 14, which stores the value of the weight vector calculated in the previous step iterations. In the fourth computing module 13, a vector of weighting coefficients is generated based on expression (6), the value of which is recorded in block 14 for storing the weighting vector. The control actions from the computing module 13 are supplied to the corresponding control inputs of the blocks 3 of the integrated signal weighting. The components of the useful signal, multiplied by their weight coefficients, go to the adder 4, where the signals are summed. From the output of the adder 4, the signal goes to the input of the adaptive processor 2, namely, to the input of the signal / (noise + noise) measuring unit 8, where the SINR is measured and compared with the value obtained in the previous iteration step. If the SINR value is larger than at the previous iteration step, then the signal / (noise + noise) ratio measuring unit 8 gives a command to the step generating unit 9, which generates the value of the next iteration step, and the weight coefficient vector storage unit 14, which generates the signal, characterizing the value of the vector of weights calculated at the previous step of the iteration. If the SINR value is less than at the previous step of the iteration, then the signal / (noise + noise) ratio measuring unit 8 sends a command only to the weight vector vector storage unit 14, which generates a signal characterizing the value of the weight vector calculated at the previous iteration step. This signal is fed to the fourth computing module 13 and then to the control inputs of blocks 3 of the complex signal weighting, then to the adder 4 and to the output of the device. If the source of the useful signal has changed its location, then the value of the vector of weighting coefficients calculated in the previous step is the value of the control vector S ₀ , which is supplied to the fourth computing module 13 from block 5 of the formation of the control vector generated on the basis of the information signal received from an external source.

The study of the obtained patterns was carried out on the basis of an antenna array of a rectangular aperture of 10 × 10 emitters (N = 100). The direction of arrival of the useful signal in the angle θ varies from 0 ° to 10 °, in the angle ϕ it does not change and is equal to 0 °. AAR is affected by four 30 dB each interference. The directions of arrival of the interference signals along the angle ϕ do not change and are equal to 0 °. The direction of arrival along the θ angle of the first interference varies from -17 ° to 12 °, the second from 17 ° to 32 °, the third from 28 ° to 38 °, and the fourth from 45 ° to 55 °. The adaptation noise level is -50 dB. The coefficient characterizing the intensity of adaptation γ, taken equal to 0.3.

The simulation results are shown in figures 4-11.

Adaptive antenna array can be implemented on a modern element base. The implementation of the entered blocks is straightforward.

The foregoing confirms compliance with the criterion of "industrial applicability" of the proposed technical solution.

It follows from the foregoing that the adaptive antenna array provides the selection of the useful signal from the received set of useful and interference signals with unknown parameters, the sources of which are in motion, in real time.

Thus, the introduction of a new block for measuring the signal / (noise + noise) ratio, as well as changing the structure of the block for generating the vector of weighting coefficients, allows to obtain a technical result consisting in increasing the speed of the adaptive antenna array when receiving a useful signal and suppressing interference signals in case of a quick change the location of their sources due to the adjustment of the vector of weight coefficients based on the gradient approach.

Literature

1. Monzingo R.A., Miller T.U. Adaptive Antenna Arrays: Introduction to Theory: Per. from English - M .: Radio and communications, 1986. - 448 p.

2. Copyright certificate 1506569. Device for receiving broadband signals with an adaptive antenna array / V.I. Zhuravlev, T.O. Bock - Bulletin of inventions No. 33, 06/25/1987 - H04L 7/02.

3. Copyright certificate 1548820. Adaptive antenna array / L.A. Marchuk, V.V. Popovsky, V.I. Evdokimov S.M. Krymov, I.V. Sergeev. - Bulletin of inventions No. 9, 03/07/1990, H0 / Q 21/00.

4. Patent 2099838 (RF). Adaptive antenna array / A.V. Kolinko, V.F. Komarovich, Marchuk L.A., Savelyev A.N. - Publ. 12/20/97 - H01021 / 00.

5. Patent 2579996 (RF). Multifunctional adaptive antenna array / A.N. Novikov, D.S. Makhov. - Publ. 04/10/16 - H01Q 21/00.

Claims (1)

An adaptive antenna array containing N antenna elements, N blocks of complex signal weighting, a common adder, an adaptive processor comprising a control vector generating unit, a covariance matrix generating unit for interference signals, a weighting vector generating unit, characterized in that the adaptive processor is additionally introduced with a unit measuring the signal / (noise + noise) ratio, and also changed the structure of the block for forming the vector of weight coefficients, consisting of a block for forming the step, four ex computational modules and a storage unit for the vector of weighting coefficients, the outputs of N antenna elements being connected to the information inputs of N units of complex signal weighting and to the inputs of the covariance matrix of interference signals, which are the corresponding inputs of the adaptive processor, the outputs of the covariance matrix of interference signals are connected to the corresponding the inputs of the block for the formation of the vector of weighting coefficients, namely, to the first inputs of the first computing module and the formation of the vector of weighting factors, the first output of the step forming unit is connected to the second input of the first computing module, the outputs of the first computing module are connected to the first inputs of the third computing module, the second output of the step forming unit is connected to the input of the second computing module, the outputs of which are connected to the second inputs of the third computing module, the outputs of which are connected to the first inputs of the fourth computing module, the second input of which is connected to the output of the unit control vector, the information input of which is connected to an external source, and the third input of the fourth computing module is connected to the output of the weight vector storage unit, the output of the fourth computing module, being the output of the weight vector and the adaptive processor, is connected to the control inputs of the complex weighing units as well as to the second input of the weight vector storage unit, the inputs of N complex weighing units are connected to the total An output, whose output is connected to the input of the signal / (noise + noise) ratio measuring unit of the adaptive processor, the output of which is connected to the input of the step forming unit and to the first input of the weight vector storage block, the output of the total adder is also the output of the device.

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