KR100241502B1 - Signal processing apparatus and method for minimization of interference and reducing of noise effective at array antenna system - Google Patents

Abstract

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a signal processing apparatus for use in a wireless communication system, and more particularly, to a signal processing apparatus for minimizing interference and reducing the effects of noise by adjusting beam patterns in real time in a receiving system. Not only can it be easily implemented in the communication field, but it also minimizes interference and minimizes noise by adjusting in real time an ideal beam pattern (a beam pattern having a maximum gain in the original signal direction and a minimum gain in the other direction). By reducing the influence, a signal processing apparatus for improving communication quality and increasing communication capacity is provided.

Description

Signal Processing Apparatus and Method for Minimizing Interference and Reducing the Effects of Noise in Array Antenna Systems

1 is a block diagram schematically showing the configuration of a first embodiment of a signal processing apparatus according to the present invention;

FIG. 2 is a detailed configuration diagram of an error vector synthesizing unit of the signal processing apparatus shown in FIG.

3 is a detailed block diagram of an embodiment of an adaptive gain synthesis unit of the signal processing apparatus shown in FIG.

4 is a detailed block diagram of an embodiment of a gain vector updating unit of the signal processing apparatus shown in FIG.

FIG. 5 is a detailed configuration diagram of another embodiment of the gain vector updating unit of the signal processing apparatus shown in FIG.

6 is a detailed block diagram of an embodiment of a scalar synthesis unit of the signal processing device shown in FIG.

FIG. 7 is a detailed configuration diagram of an embodiment of a tracking direction vector synthesizing unit of the signal processing apparatus shown in FIG.

8 is a block diagram schematically showing the construction of a second embodiment of a signal processing apparatus according to the present invention;

9 is a detailed block diagram of an embodiment of the maximum intrinsic synthesis unit of the signal processing apparatus shown in FIG.

FIG. 10 is a detailed configuration diagram of an error vector synthesizing unit of the signal processing apparatus shown in FIG.

FIG. 11 is a detailed block diagram of an embodiment of an adaptive gain synthesis unit of the signal processing device shown in FIG.

12 is a block diagram of an embodiment of a signal processing apparatus according to a third embodiment.

FIG. 13 is a detailed configuration diagram of an embodiment of the matrix calculation approximation unit shown in FIG.

14 is a detailed configuration diagram of an embodiment of the maximum intrinsic compound shown in FIG.

FIG. 15 is a detailed configuration diagram of an embodiment of the error vector synthesis unit shown in FIG. 12. FIG.

FIG. 16 is a detailed block diagram of an embodiment of an adaptive gain synthesis unit of the signal processing device shown in FIG.

FIG. 17 is a schematic diagram illustrating a method of minimizing interference and noise by applying the signal processing technique of the present invention using the optimized complex gain values according to the first to third embodiments to an array antenna system. FIG.

18 is a block diagram schematically showing the construction of a fourth embodiment of a signal processing apparatus according to the present invention.

19 is a detailed block diagram of an embodiment of an error vector synthesizing unit of the signal processing device shown in FIG.

FIG. 20 is a detailed block diagram of an embodiment of a scalar synthesis unit of the signal processing device shown in FIG.

FIG. 21 is a detailed configuration diagram of an embodiment of a tracking direction vector synthesizing unit of the signal processing apparatus shown in FIG. 18;

FIG. 22 is a detailed block diagram of an embodiment of an adaptive gain synthesis unit of the signal processing device shown in FIG.

FIG. 23 is a detailed configuration diagram of an embodiment of a phase delay vector update unit of the signal processing device shown in FIG. 18;

24 is a detailed block diagram of another embodiment of the phase delay vector update unit of the signal processing device shown in FIG. 18;

25 is a schematic diagram illustrating a method of minimizing interference and noise by applying the signal processing technique of the present invention using an optimized phase delay value according to the fourth embodiment to an array antenna system.

* Explanation of symbols for main parts of the drawings

1: array antenna 2: phase delay device

3: delay signal adding device 5, 9: signal processing device

6: receiving device 8: internal product calculating device

11 antenna element 21 phase delay element

51, 91, 131: error vector synthesis unit 52, 92, 132: scalar synthesis unit

53, 93, 133: tracking direction vector synthesizer 54, 94, 134: adaptive gain synthesizer

55: phase delay vector updater 95, 135: gain vector updater

96: autocorrelation matrix generating unit 97, 137: maximum eigenvalue synthesis unit

136: matrix calculation approximation

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a signal processing apparatus used for an array antenna system, and more particularly, to a signal processing apparatus and a method for minimizing interference and reducing the effect of noise by adjusting a beam pattern every snapshot in an array antenna system.

In general, when performing wireless communication, desired signals (hereinafter, referred to as "original signals") and interference signals exist together in a received signal, and a plurality of interference signals exist for one original signal. Since the degree of communication distortion caused by such interference signals is determined by the sum of the original signal powers and the powers of all the interference signals, if the number of the interference signals is large even when the level of the original signal is significantly higher than the level of each of the interference signals, The power increases and communication distortion occurs. In the past, this distortion has serious problems that make it difficult to reproduce the information of the original signal.

Therefore, as a part of updating the above-mentioned problem, many attempts have been made to reduce the influence of the interference signal by using an array antenna. However, most of the techniques developed so far are eigenvalue separation (Eigen Decomposition: Based on the "ED" method, which has not been applied in the field of wireless communication due to the complexity of the system and the processing time thereof, such a prior art is described in detail in the following reference.

References

[1] M. Kaveh and A. J. Barabell, “The Statistical Performance of the MUSIC and Minimun-Norm Algorithms for Resolving Plane Waves in Noise,” IEEE Trans., Acoust., Speech and signal process., Vol. ASSP-34, pp. 331-341, April 1986.

[2] T. Denidni and G. Y. Delisle, “A Nonlinear Algorithm for Output Power Maximization of an Indoor Adaptive Phased Array,” IEEE Electronmagnetic Compatibility, vol. 37, no. 2, pp. 201-209, May, 1995.

However, the conventional signal processing schemes proposed up to now require not only advance information on a desired signal, but also require too much computation, so that the application of the conventional signal processing schemes is difficult in an actual mobile communication environment in which a communication terminal moves quickly in an arbitrary direction. It was almost impossible. In particular, when the direction of the original signal or the number of interference signals is unknown, more computation is required, which makes the implementation even more difficult.

Therefore, the present invention has been made to effectively solve the problems of the prior art as described above, and through the simplified calculation process, the ideal beam pattern (maximum gain in the original signal direction, minimum gain in the other direction) It is an object of the present invention to provide a signal processing apparatus and a method for minimizing interference and reducing the influence of noise by adjusting a beam pattern) having a snapshot.

In order to achieve the above object, the present invention provides a signal processing apparatus for providing a gain vector for every snapshot to reduce the effects of interference and noise in an array antenna system, wherein the plurality of snapshot antennas are provided in each array antenna system. Error vector synthesizing means for calculating an error vector by receiving a signal vector induced in an array antenna element, a previous snapshot output value of the array antenna system, and a gain vector value of the current snapshot; Scalar synthesizing means for receiving an error vector from the error vector synthesizing means and synthesizing and outputting a scalar value necessary for tracking direction vector synthesis; Tracking vector synthesizing means for synthesizing a tracking direction vector by receiving the error vector and the scalar value; Adaptive gain synthesizing means for receiving the signal vector, the tracking direction vector, the previous snapshot output value, and the gain vector value of the current snapshot to obtain an adaptive gain; And gain vector updating means for receiving the tracking direction vector and the adaptive gain value, respectively, and updating the gain vector, wherein the gain vector value is a signal induced in each of a plurality of antenna elements included in the array antenna system. It is characterized by using the value of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix obtained from.

In addition, the gain vector value is determined by the value of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix, or is localized without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. In order to apply only a change in, the eigenvector corresponding to the maximum eigenvalue is set as a constant multiplier, or the eigenvector corresponding to the maximum eigenvalue is set to a value normalized to have a size of 1. do.

In addition, the autocorrelation matrix is obtained by multiplying the autocorrelation matrix in the previous snapshot by the forgetting factor having any value between 0 and 1, as shown in the following equation, and inducing each of the antenna elements in the current snapshot. And a signal matrix obtained from the signal vector for the received signal.

(only, Is the autocorrelation matrix of the J + 1th snapshot, Is the autocorrelation matrix of the Jth snapshot, f is the oblivion factor taking a value between 0 and 1, Ts is the snapshot period, and the superscript H is the Hermitiam operator.

In addition, the gain vector does not change the signal induced in the reference antenna element in order to eliminate the phase difference between the signals induced in the antenna elements in the first snapshot, and subsequently the signals obtained in other antenna elements. Determine the value of the gain vector so as to apply a phase delay by a phase difference with an adjacent antenna element having a phase, and from the second snapshot, obtain the gain vector by updating the gain vector in the previous snapshot, wherein the autocorrelation matrix and the It is characterized in that the Rayleigh quotient defined by the gain vector is updated to obtain maximum.

In order to achieve the above object, the present invention provides a signal processing apparatus for providing a gain vector for every snapshot to reduce the effects of interference and noise in an array antenna system, wherein the array antenna system is provided for each snapshot. Autocorrelation matrix generating means for calculating and outputting an autocorrelation matrix for signal vectors induced in a plurality of array antenna elements; Maximum eigenvalue synthesis means for estimating the maximum eigenvalue of the autocorrelation matrix in the current snapshot; Error vector synthesizing means for inputting the autocorrelation matrix, the maximum eigenvalue, and a gain vector value in the current snapshot to synthesize an error vector; Scalar synthesizing means for receiving the error vector and synthesizing a scalar value necessary for tracking direction vector synthesis; Tracking direction vector synthesizing means for receiving the error vector and the scalar value and synthesizing the tracking direction vector; Adaptive gain synthesizing means for obtaining adaptive gain by receiving the autocorrelation matrix, the tracking direction vector, the maximum intrinsic value in the current snapshot and the gain vector value, respectively; And gain vector updating means for receiving the tracking direction vector and the adaptive gain value, respectively, and updating a gain vector, wherein the gain vector value is a signal induced in each of a plurality of antenna elements included in the array antenna system. It is characterized by using the value of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix obtained from.

In addition, the present invention provides a signal processing apparatus for providing a gain vector for every snapshot to reduce the effects of interference and noise in the array antenna system, a plurality of the array antenna system every snapshot Matrix approximation means for performing an autocorrelation matrix operation on a signal vector induced in an array antenna element of an element, and outputting a gamma vector and a zeta vector by approximating by a vector operation; Maximum eigenvalue synthesis means for estimating a maximum intrinsic value of the autocorrelation matrix by receiving the gain vector from the gamma vector and the current snapshot; Error vector synthesizing means for inputting the gamma vector, the maximum eigenvalue, and a gain vector value in the current snapshot to synthesize an error vector; Synthesizing means for receiving the error vector and synthesizing a scalar value necessary for tracking direction vector synthesis; Tracking direction vector synthesizing means for receiving the error vector and the scalar value and synthesizing the tracking direction vector; Adaptive gain synthesizing means for receiving the zeta vector, the tracking direction vector, the maximum eigenvalue, and the gain vector value, respectively, for obtaining and outputting an adaptive gain; And gain vector updating means for updating a gain vector based on the tracking direction vector and the adaptive gain value, wherein the gain vector value is obtained from a signal induced in each of a plurality of antenna elements included in the array antenna system. It is characterized by using the value of the eigenvector corresponding to the maximum eigenvalue of the obtained autocorrelation matrix.

In addition, the present invention is a signal processing method for providing a gain vector for every snapshot to reduce the effects of interference and noise in an array antenna system, to achieve the above object, a plurality of the array antenna system every snapshot An error vector synthesizing step of calculating an error vector by receiving a signal vector induced in an array antenna element, a previous snapshot output value of the array antenna system, and a gain vector value of the current snapshot; A scalar synthesis step of receiving the error vector and synthesizing and outputting a scalar value necessary for tracking direction vector synthesis; A tracking vector synthesis step of synthesizing a tracking direction vector by receiving the error vector and the scalar value; An adaptive gain synthesis step of receiving the signal vector, the tracking direction vector, the previous snapshot output value, and the gain vector value of the current snapshot to obtain an adaptive gain and output the adaptive gain; And a gain vector updating step of receiving the tracking direction vector and the adaptive gain value, respectively, and updating a gain vector, wherein the gain vector value is a signal induced in each of a plurality of antenna elements included in the array antenna system. It is characterized by using the value of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix obtained from.

In addition, the present invention is a signal processing method for providing a gain vector for every snapshot to reduce the effects of interference and noise in the array antenna system, in order to achieve the above object, every snapshot of the array antenna system Generating an autocorrelation matrix for calculating and outputting an autocorrelation matrix for signal vectors induced in a plurality of array antenna elements; A maximum eigenvalue synthesis step for estimating the maximum eigenvalue of the autocorrelation matrix in the current snapshot; An error vector synthesizing step of synthesizing an error vector by receiving the autocorrelation matrix, the maximum intrinsic value, and a gain vector value in the current snapshot; A scalar synthesis step of receiving the error vector and synthesizing a scalar value necessary for tracking direction vector synthesis; A tracking direction vector synthesis step of synthesizing a tracking direction vector by receiving the error vector and the scalar value; An adaptive gain synthesis step of obtaining adaptive gain by receiving the autocorrelation matrix, the tracking direction vector, the maximum intrinsic value in the current snapshot and the gain vector value, respectively; And a gain vector updating step of updating a gain vector based on the tracking direction vector and the adaptive gain value, wherein the gain vector value is obtained from a signal induced in each of a plurality of antenna elements included in the array antenna system. It is characterized by using the value of the eigenvector corresponding to the maximum eigenvalue of the obtained autocorrelation matrix.

In addition, the present invention is a signal processing method for providing a gain vector for every snapshot to reduce the effects of interference and noise in an array antenna system, to achieve the above object, a plurality of the array antenna system for each snapshot Performing matrix correlation approximation for performing an autocorrelation matrix operation on a signal vector induced in an array antenna element of the device, and outputting a gamma vector and a zeta vector by approximating by a vector operation; A maximum eigenvalue synthesis step for estimating a maximum intrinsic value of the autocorrelation matrix by receiving the gain vector from the gamma vector and the current snapshot; An error vector synthesizing step of synthesizing an error vector by receiving the gamma vector, the maximum eigenvalue, and a gain vector value of the current snapshot; A scalar synthesis step of receiving the error vector and synthesizing a scalar value necessary for tracking direction vector synthesis; A tracking direction vector synthesis step of synthesizing a tracking direction vector by receiving the error vector and a scalar value; An adaptive gain synthesis step of receiving the zeta vector, the tracking direction vector, the maximum eigenvalue, and the gain vector value, respectively, and obtaining and outputting an adaptive gain; And a gain vector updating step of updating a gain vector based on the tracking direction vector and the adaptive gain value, wherein the gain vector value is obtained from a signal induced in each of a plurality of antenna elements included in the array antenna system. It is characterized by using the value of the eigenvector corresponding to the maximum eigenvalue of the obtained autocorrelation matrix.

In addition, in order to achieve the above object, the present invention provides a signal processing method for providing a gain vector for every snapshot to reduce the effects of interference and noise in an array antenna system,

(a) a first step of setting an initial gain vector using signals induced in each antenna element;

(b) a second step of updating the autocorrelation matrix by substituting the signal vector ρ (k) received through the array antenna into the following equation;

(only, (J + 1) is the autocorrelation matrix of the J + 1th snapshot, Is the autocorrelation matrix of the Jth snapshot, f is the oblivion factor taking a value between 0 and 1, Ts is the snapshot period, and the superscript H is the Hermitiam operator.

(c) a third step of obtaining an adaptive gain ρ (k) using the following equation;

(d) a fourth step of calculating a tracking direction vector x (k) using the following equation;

Error vector r (k + 1) and scalar β (k) are determined as

(e) Gain Vector of Current Snapshot Is the gain vector of the previous snapshot according to A fifth step of updating; And

(Where k is the time index representing the snapshot, ρ (k) is the adaptive gain in the kth snapshot, Is the tracking direction vector, Is normalized to have a size of 1 for each iteration)

(f) a new signal vector for each snapshot Each time receiving a, characterized in that it comprises a sixth step of performing the second step to the fifth step repeatedly.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement the technical idea of the present invention.

The signal processing apparatus and method proposed in the present invention relates to a signal processing technique for maximizing gain in a desired signal direction and minimizing gain in other directions in an array antenna system. It can be explained in two forms. First, there is a method of optimizing the complex gain value to be multiplied by each antenna element of the array antenna, and second, there is a method of optimizing the phase delay value to be applied to each antenna element.

The two can be said to be theoretically equivalent in the end, but since the implementation process is different, each will be described in detail.

In other words, the present invention provides a complex gain vector " By determining the value of ”, ultimately the signals induced in the antenna element and the complex gain vector The signal processing is performed to bring the output of the array antenna, which is the result of the inner inner product of, close to the desired value.

By the way, the complex gain vector When the magnitude of all elements of the signal is normalized to 1, the complex gain vector is applied to the signal value induced in each antenna element. Multiplying the signal by the complex gain vector The phase delay is applied as much as the phase of. Therefore, it may result in determining the value of the phase delay to be added to each antenna element constituting the array antenna.

If the phase delay to be added to the i-th antenna element is phi _i , the same effect can be obtained even by adding a time delay equal to the value of phi _i divided by 2π times the carrier frequency.

Now, we will introduce the basic principles of beam pattern formation that maximize the gain in the direction of the original signal and minimize the gain of other noise sources.

In the case of a linear array antenna whose distance between adjacent antenna elements is λ _c / 2 (where λ _c is the wavelength of the carrier frequency of the input signal), the signal induced in the m th antenna element can be expressed as have.

In Equation (1), θ _k is the angle of incidence of the k-th signal and S _k (t) is the k-th transmission signal seen from the receiving end. In Equation (1), the subscript m denotes the case of the reference antenna. As = 1, numbers are given in the order of phase magnitude of the received or transmitted signal (m = 2, 3, ..., N).

In Equation (1), any one of the M signal components is an original signal (in the present invention, for convenience, the first signal S ₁ (t) is referred to as the "original signal" and the incident angle of the original signal is referred to as "θ ₁ "). The remaining M-1 signals are interference signals and interfere with communication with noise n _m (t).

In addition, Equation (1) is for the case of linear array antennas of equal intervals (λ _c / 2), but the signal processing technique provided in the present invention is a case where the distance between antennas is not equal or linear array is not This is a commonly applied technique.

If the distance between an antenna and a reference antenna is d, the signal of the antenna is different from that of the reference antenna. As much as the phase difference.

Therefore, in the case of non-uniform spacing or nonlinear arrangement, the signal induced in the m-th antenna may be expressed as follows.

In order to make both the phase delay or the time delay to be applied to each antenna element positive, the antenna element in which the signal with the latest phase is induced is used as the reference antenna element in the reception mode, and the signal transmission direction is reversed in the transmission mode. Therefore, the antenna element with the highest phase is used as the reference antenna element.

In this way, when the reference antenna element is selected, the zero phase is always applied (meaning no change) to the signal induced by the reference antenna element of the array antenna, and all other antenna elements have a positive phase difference (or phase delay). Time delay divided by 2π times the carrier frequency).

If the array antenna is composed of N antenna elements, each snapshot receives an N-by-1 signal vector (typically, a vector having N number of elements is called an "N-by-1 vector"). In the Jth snapshot, the autocorrelation matrix can be constructed as follows (see Equation (2)).

Here, the “snapshot” refers to a new gain vector by observing the signal incident on the array antenna. (Or phase delay vector), and according to the signal processing of the present invention, the current (every snap) is calculated by calculating a gain vector (or phase delay vector) corresponding to a newly input signal value at every snapshot. Array antennas adapted to the incident signal value).

In the above formula, double underline denotes a matrix, single underline denotes a vector, T _s denotes a period of a snapshot, and the superscript H denotes a Hermitian operator. N-by-1 signal vectors with N numbers Is the input signal x _m (t), m = 1, 2, ..., N described in the above formula (1), and is configured as follows.

Where the superscript T is a transpose operator.

However, Equation (2) is valid only when the incidence angles of the M signal components do not change, and when each signal source moves during communication, such as a time-variant environment, i.e., a mobile communication environment, the incidence angle is taken every snapshot. Since it is different from one to another, the above equation (2) does not constitute a correct autocorrelation matrix.

Therefore, in a time-variant environment, it is preferable to calculate an autocorrelation matrix by an iterative method by introducing forgetful factors as follows.

(only, Are autocorrelation matrices of the J + 1th and Jth snapshots respectively, and f is an oblivion factor that takes a value between 0 and 1.)

Since the mobile communication environment is time-transformed as described above, it is preferable to calculate the autocorrelation matrix using Equation (4) rather than Equation (2).

As a result of various computer simulations, it has been found that when the signal processing technique of the present invention is applied to a general land mobile communication environment, it is desirable to keep the forgetting factor within a range of 0.8 to 0.99.

Now, the principle of the present invention will be described in more detail the principle of signal processing in the array antenna system to provide the ideal beam pattern with a small amount of calculation through a calculation procedure.

When the eigenvalues of the autocorrelation matrix determined by Equation (2) or Equation (4) are arranged in size order, λ ₁ ≥λ ₂ ≥ ·· ≥λ _N , where the maximum eigenvalue λ 1 is the value of the signal. It is an eigenvalue determined by signal components irrespective of the total number M and the number N of antenna elements.

Therefore, the normalized eigenvector corresponding to the maximum eigenvalue λ ₁ Speaking of It can be seen that is present in the signal subspace as follows.

However, the complex value γ _i is a constant determined by the magnitude and the angle of incidence distribution of the original signal and the interference signal, (θ i) is a direction vector determined by the incident angle θ _i of the i-th incident signal, and is determined as in Equation (6) below.

Here, assume that the level of the desired signal is significantly greater than other signals, i.e., interference signals. In other words,

Eigenvectors of Equation (5) in a signal environment where the condition of Equation (7) is satisfied Can be approximated as

In other words, Is almost the same direction as the direction vector a (θ1) determined by the angle of incidence of the desired signal.

Therefore, the gain vector (or phase delay vector) applied to each antenna element under the condition that the desired signal level is sufficiently larger than the level of each of the interference signals. Corresponding vector of maximum indifference In this case, the beam pattern of the array antenna approximates the maximum gain toward θ ₁ which is the original signal direction.

Therefore, the present invention proposes to set the gain vector (or phase delay vector) of the array antenna as in the following equation (9).

Here, dividing the eigenvector by a constant is for computational convenience when analyzing the performance of the array antenna.

Next, a method of obtaining an optimal gain vector (or phase delay vector) will be described.

As described above, in a signal environment in which the power of the original signal is much higher than the power of each of the interference waves, in order to ensure that the array antenna has an ideal beam pattern that forms a maximum gain in the direction of the original signal, the maximum eigenvalue λ ₁ corresponds to. Normalized Eigenvectors to Can be approximated by determining

However, finding the autocorrelation matrix itself requires a lot of calculations as shown in Equations (2) and (4), and it is not simple to find the eigenvector corresponding to the maximum intrinsic value. To make the problem more difficult, when the signal environment is time-transformed, such as mobile communication, the angle of incidence of the original signal changes every snapshot, so that an eigenvector must be obtained according to the changed angle of incidence.

Therefore, in the signal processing technique according to the present invention, the gain or phase delay value to be applied to the antenna element In the determination of the formula, it is obtained by applying a known conjugate gradient method (CGM: conjugate gradient method) Set a value close to.

First, the gain vector (or phase delay vector) to be obtained Is obtained by updating the vector obtained from the previous snapshot for each snapshot through an iterative process as follows.

However, the independent variable k is a time index representing a snapshot, and ρ (k) and Are the adaptive gain and the search direction vector at the kth snapshot, respectively, Must be normalized to have a size of 1 for each iteration.

From equation (10), the solution to be obtained from the current snapshot is It can be seen that it is obtained by updating by ρ (k) in the direction of.

However, the solution to this concept must solve two problems: first, the initial gain vector (or phase delay vector). You need to decide how to set it up, and then how to determine the adaptive gain and tracking direction vectors for each snapshot.

In the present invention, the solution in the initial state Uses the signal (0) received in the initial state. In other words,

(Where x ₁ (0) is a received signal induced in the reference antenna element, Is the first element of.)

The reason for the above equation (11) is that the autocorrelation matrix has a rank of 1 in the first snapshot, so that there is only one signal eigenvalue, and a signal eigenvector can be obtained directly from the input signal vector itself if only noise components are ignored. to be.

In the signal processing technique proposed in the present invention, starting from Equation (11) above, the conjugate gradient method is modified and modified as described below to obtain an adaptive gain and tracking direction vector for each snapshot. Update the solution to (10).

In order to apply the conjugate gradient method to signal processing in a time-transformed mobile communication environment, a price function defined by Rayleigh qhotient can be assumed as shown in Equation (12).

As is easily proved mathematically, the minimum and maximum values of the price function defined by Eq. Converge to the minimum high and maximum high values of Is the corresponding eigenvector.

In order to form the beam pattern that provides the maximum gain in the direction of the desired signal, as described above, the gain vector of the array antenna Since is to be determined as the eigenvector corresponding to the maximum intrinsic value, the present invention obtains an adaptive gain and tracking direction vector that maximizes the price function of Equation (12).

Then, the maximum or minimum value can be obtained by obtaining the condition that the equation (12) is differentially divided by the adaptive gain ρ (k) as follows and the result is set to zero.

The adaptive gain ρ (k) satisfying Equation (13) can be obtained as Equation (14) below.

only,

Re [*] also means the real part of the complex value "*".

Since the positive sign (+) and the negative sign (-) in Equation (14) cause minimization and maximization of the price function, respectively, in the present invention, the negative sign is selected to maximize the price function.

As shown in the constraint of Equation (12), the gain vector (or phase delay vector) of Equation (15) Must be normalized at every step.

Meanwhile, tracking direction vector Early on After setting to, update as follows.

However, error vector And scalar β (k) are determined as follows.

As described above, the overall process of obtaining the optimal gain vector (or phase delay vector) proposed in the present invention is as follows.

First, using the signal initially induced in each antenna element Set the initial solution with. In this case, the autocorrelation matrix Calculate as

Second, new signal vector To update the autocorrelation matrix by substituting into Eq. (4), obtain the adaptive gain using Eq. (14) and (15), and calculate the tracking direction vector using Eq. (16) to (18) to obtain the gain vector. Is updated as shown in equation (10).

Thereafter, it is repeated each time a new signal vector of each snapshot is received.

According to the present invention as described above, since it does not require any prior information on the direction of the original signal as well as the direction of all interference signal components, the overall process is significantly simplified, so that mobile communication can be performed using a known general purpose processor. In most real-time communication environments, such as signal regeneration and transmission, real-time processing is possible. For example, since the total amount of calculation required to obtain the optimal gain vector (or phase delay vector) is about O (3N ² + 12N) for each snapshot as shown in Equations (14) to (18), the mobile terminal In land mobile communication, which does not exceed 150 km / h, signal processing can be performed without technical difficulties even with a standard digital signal processing chip (DSP).

By applying the conjugate slope method as described above, it is possible to obtain a gain vector (or phase delay vector) having a desired beam pattern, and since it is significantly simplified than the conventional method, it is easy to know that the amount of computation required for signal processing is significantly reduced. have. However, as shown in Equation (4), the autocorrelation matrix has to be updated at every snapshot, so if the number of antenna elements of the array antenna is required, the complexity of the system may still be a problem, and an improvement may be needed. have. Therefore, in the present invention, in order to further simplify the whole process, the value of the forgetting factor may be fixed to a specific value when calculating the autocorrelation matrix required by the conjugate slope method as described above. In other words, consider the case in which the forgetting factor is fixed to 0 in Equation (4). In other words, since this means that the autocorrelation matrix is determined only by the current signal vector, all the processes of the conjugate gradient method presented above are greatly reduced.

Also, if the angle of incidence in each snapshot is too large, it becomes impossible to consider past signal values in the autocorrelation matrix anyway, so setting the forgetting factor to 0 can be generally suitably employed in a signal environment.

As described above, when the forgetting factor is fixed, the autocorrelation matrix is simplified as shown in Equation (19).

Applying Eq. (19) above to Eq. (15), the factors that required the calculated amount O (N ² ) in Eq. (15), λ (k), a (k), b (k) It is calculated as follows.

Where y (kT _s ) is the array antenna output at the kth snapshot

Defined as.)

As shown in Equation (20), when the forgetting factor is 0, the autocorrelation matrix is determined only by the current signal vector, so the process of obtaining an optimal gain vector (or phase delay vector) is greatly simplified. Is not updated every snapshot, so the matrix itself does not need to be calculated, and the execution of Equation (4) is omitted.

As a result of computer simulation, when the autocorrelation matrix was calculated in this way and the value of oblivion factor was set to the optimum value, the improvement of about 12dB was obtained for the interference signal and the number of antenna elements for noise An improvement could be obtained. (I.e., the actual noise power at the array antenna output On the other hand, according to the method of approximating the autocorrelation matrix by the instantaneous value, the noise is almost equally improved, and the interference is about 9dB. As a result, the simplified technique of approximating the autocorrelation matrix to the instantaneous value compared to the case of the signal processing by introducing the conjugate gradient method that calculates the autocorrelation matrix by taking into account all the signal values of the past by introducing oblivion factors. It can be seen that it causes a performance degradation of about 3dB, but the overall process is greatly simplified, so the system can be easily realized and cost can be obtained. In addition, when the signal processing in a simplified manner with only the instantaneous signal value, all of the operators of O (N ² ) is lost, so that the calculation amount of the entire process is significantly reduced to about O (11 N).

In order to reduce the complexity of the technique presented in the present invention and to reduce the calculation amount required to obtain the optimum gain vector (or phase delay vector), the method of approximating the autocorrelation matrix using only the instantaneous signal value as described above is simplified. In terms of performance, the performance is considerably inferior to the proposed technique of calculating the autocorrelation matrix by introducing an appropriate forgetting factor and calculating the autocorrelation matrix as the gain vector of each antenna element. . In the improvement of the signal power vs. the interference power, the improvement is not large, but in the bit error probability, the computer simulation shows that the increase is about 10 times or more.

Therefore, the necessity of a method that considers the complexity of the system and the overall performance at the same time has emerged. The overall system is slightly more complicated than the instantaneous signal value method, but a better compromise scheme is proposed as follows for the overall performance, especially the bit error probability. do.

The term that increases the complexity of the system is the matrix calculation term. Section It can be seen that the term.

Therefore, if these two matrix operation terms are simplified, the complexity of the entire system can be significantly reduced without approximating the autocorrelation matrix with the instantaneous signal values.

Each of the above two terms Then, the calculation of these two terms can be simplified as follows.

In the first snapshot, τ (0) and ζ (0) are respectively

Obtained as

From the second snapshot, it is updated as follows.

Where f is an oblivion factor of 0 <f≤1.

If the error vector τ (k + 1) is Since Eq. (2) is approximated as follows.

Where f is an oblivion factor of 0 <f≤1.

Therefore, the two matrix operations terms that occupy most of the complexity of the overall system can be simplified to the following vector calculation terms.

According to Equations (24) and (25), the total calculation amount of the scheme proposed in the present invention is about O (15N). This may be somewhat more complicated than the case of the instantaneous signal method, which is about O (11N), but the simplification is considerably compared to that of the original method (the method of calculating the autocorrelation matrix) that is about O (3N ² + 12N). It is easy to see that it is accomplished.

As a result of computer simulations in various environments, the array antenna designed according to the above equations (24) and (25) shows almost the same performance as the original method in terms of interference cancellation and about 1.5 in terms of bit error probability. It was confirmed that it was only about twice as big as it was.

In addition, it was confirmed that the noise power 1 / N reduction characteristic, which is an inherent characteristic of the array antenna, seems to be the same as the aforementioned two methods.

Hereinafter, the vector calculated by Equation (24) is referred to as a "gamma vector" for convenience and the vector calculated by Equation (25) is called a "zeta vector", respectively.

In order to implement a signal processing apparatus considering both reception and transmission, obtain an optimal gain vector (or phase delay vector) in the reception mode according to the above-described method, and then apply the value to the transmission mode as it is. Can be implemented.

Now, specific embodiments will be introduced.

[First Embodiment]

This embodiment introduces a signal processing technique that repeatedly calculates a gain vector at every snapshot to produce an optimal beam pattern in a communication system employing an array antenna. In other words, in this embodiment, the beam pattern of the entire array antenna is adjusted by applying a complex gain to the signal induced in each antenna element of the array antenna.

1 is a block diagram of a signal processing apparatus according to an embodiment of the present invention. (Output from a device receiving a radio signal using an array antenna (hereinafter referred to as a "receiver")), a reception output value (y (t)) (apparatus for embedding the signal vector and gain vector (hereinafter referred to as "internal computing device") Output), the gain vector value at the current snapshot Are respectively inputted to the error vector synthesis unit 91 for calculating and outputting an error vector, and the scalar synthesis unit for receiving an error vector from the error vector synthesis unit 91 and synthesizing and outputting a scalar value necessary for tracking direction vector synthesis. 92 and the tracking direction vector receiving the outputs of the error vector synthesizing unit and the scalar synthesizing unit. A tracking vector synthesizing unit 93 for synthesizing and outputting the signal, the signal vector p33 (x (t)) and the tracking direction vector , The received output value (y), and the gain vector value in the current snapshot The adaptive gain synthesizing unit 94 obtains and outputs the adaptive gains, respectively, and the gain vector receiving the tracking direction vector and the adaptive gain values in the current snapshot. It is configured to include a gain vector updating unit 95 for updating the.

According to the first embodiment signal processing technique of the present invention, which is constructed and operated as described above, it has a significantly improved calculation amount (about O (11N), which is significantly improved from the conventional case, wherein 'N' is an arrangement The number of elements in the antenna]. By updating a value, each element value of the complex gain vector obtained by the method described above is applied to each of the received signal vector elements induced in each antenna element of the array antenna, and ultimately, optimal for every snapshot. It is possible to provide a beam pattern of. Specific configurations and operations of the respective functional units are illustrated in the description of FIGS. 2 to 7 described later.

FIG. 2 shows a detailed configuration of an embodiment of the error vector synthesizing unit 91 shown in FIG.

As shown in the figure, the error vector synthesizing unit 91 includes: a multiplier 911 for squaring the magnitude of the received output value y (t) and the received signal vector; Receive output value for each element of A multiplier 912 for multiplying the complex conjugate of and the output value squared by the multiplier 911 A multiplier 913 for multiplying by each element of &lt; RTI ID = 0.0 &gt; and &lt; / RTI &gt; The signal vector at the corresponding element output of the multiplier 913 assigned to each element of And a subtractor 914 for subtracting each output value of the multiplier 912 assigned to each element of.

The operation ultimately performed by the error vector synthesizing unit 91 shown in FIG. 2 satisfies the following condition:

Where r is the error vector, x (t) is the received signal vector at the current snapshot, y (t) is the received output value, Is the gain vector and superscript * is the complex conjugate operator. The configuration illustrated in FIG. 2 and Equation (26) are autocorrelation matrix Instantaneous signal This is the case of approximation.

FIG. 3 is a detailed block diagram of an embodiment of the adaptive gain synthesizing unit 94 of the signal processing apparatus shown in FIG.

As shown in the figure, the adaptive gain synthesis unit 94 receives the received signal vector. Complex-conjugate each element of the tracking direction vector A plurality of multipliers 941 for multiplying each of the elements in turn, an adder 946 for adding outputs of the plurality of multipliers 941, and the tracking direction vector. A plurality of multipliers 942 for obtaining the absolute squares of the elements of the element, an adder 945 for adding the outputs of the multipliers 942, and the tracking direction vector. Each element of and the gain vector A multiplier 943 for multiplying the complex conjugates of each element in turn, an adder 944 for adding the outputs of the multipliers 943 together, and a multiplier 949 for squared output of the adder 946 ), A multiplier 947 for multiplying the received output value y (t) and the output of the adder 946, and a multiplier 948 for obtaining an absolute square of the received output value y (t). In the circuit, the multiplier 948 and the multiplier 911 shown in FIG. 2 may also be used), and an adaptation connected to the output terminals of the adders 944, 945 and the multipliers 947, 948, and 949, respectively. The gain calculator 950 is included.

The result of the dot product of the received signal vector and the tracking direction vector (the output of the adder 946) is denoted by A, and the result of multiplying the A by the received output value (the output of the multiplier 947) is denoted by B. The square of A (the output of the multiplier 949) is C, and the result of the dot product of the gain vector and the tracking direction vector (the output of the adder 944) is D, and the tracking direction vector and its own dot product ( If the adder 945 output) is E, the adaptive gain calculating unit 950 calculates the adaptive gain ρ.

Obtain as

Where F = CRe [D [-BRe [E],

G = Cy ² (t) E,

H = Re [B] -y ² (t) Re [D],

Re [·] means the real number part of the complex “·”.

In addition, when B, C, D, and E are calculated as above, the value is defined as follows.

FIG. 4 is a detailed configuration diagram of an example of the gain vector updater 95 of the signal processing apparatus shown in FIG. 1, and a plurality of multipliers 951 for multiplying the tracking direction vector and the adaptive gain value in the current snapshot. And a plurality of adders 9502 for adding the gain vector from the previous snapshot and the output value of each multiplier 951.

Thus, the gain vector updater updates the gain vector as follows every Jth snapshot:

That is, the gain vector from the next snapshot Means that the value of the current gain vector is determined by varying the magnitude of the current gain vector by an adaptive gain in the direction of the tracking direction vector.

FIG. 5 is a detailed configuration diagram of another embodiment of the gain vector updater 95 of the signal processing apparatus shown in FIG. 1, wherein the number of adders 952 is set when N is the number of antenna elements constituting the array antenna. By adding a plurality of dividers 953 to the configuration of FIG. 4, which divides each output value by the N square root of the adder 952 output value connected to the reference antenna element, the gain vector to be updated is normalized.

Compared with the gain vector update unit shown in FIG. 4, it can be seen that the following differences exist:

First, the gain multiplied by the reference antenna element is always 1 so that no phase plane is applied to the received signal induced in the reference antenna element.

Second, the gain vector Normalize the size of to 1. That is, the gain vector updater 95 shown in this figure updates the gain vector for every Jth snapshot as follows:

Where w ₁ (J + 1) is the updated gain vector, First element.

That is, w ₁ (J + 1) is the gain value for the signal to be received at the reference antenna element in the next snapshot.

FIG. 6 is a detailed configuration diagram of an example of the scalar synthesis unit 92 of the signal processing apparatus shown in FIG. 1, and includes a plurality of multipliers 921 for squaring the absolute values of the elements of the error vector. A divider 923 for dividing the outputs of the multipliers 921 with each other, the divider 923 dividing the output of the adder 922 in the current snapshot with the output of the adder 922 in a previous snapshot, And a code converter 924 that adds a negative sign (−) to the output of the divider 932.

The scalar synthesis section 92 calculates a scalar value β as follows:

The scalar value β calculated by the scalar synthesis section 92 shown in this figure is a tracking direction vector in the previous snapshot. Multiply by to calculate the error vector and the tracking direction vector from the current snapshot. The ultimate goal of calculating the scalar value β is to ensure that the tracking direction vectors in all snapshots are orthogonal to the autocorrelation matrix.

FIG. 7 is a detailed configuration diagram of the tracking direction vector synthesizing unit 93 of the signal processing apparatus shown in FIG. 1. As shown in the drawing, the tracking direction vector synthesizing unit 93 is the error. A plurality of adders 931 which have one input terminal connected to each error vector element r ₁ ... R _N output terminal of the vector combining unit 91 and output a tracking direction vector v ₁ ... v _N to the output terminal; The input terminal receives a tracking direction vector from a previous snapshot of each element output through the adder 931, and receives and multiplies the scalar value β by the other input terminal, and multiplies the result by the adder. A large number of adders 932 are output to 931.

Thus, in the first snapshot, the error vector output from the error vector synthesizing unit 91 is used as the tracking direction vector, and in the case after the second snapshot, the tracking direction in the previous snapshot using the multiplier 932. After multiplying the vector by the scalar value, the result obtained by adding the output value of the multiplier 932 and the error vector in the current snapshot using the adder 931 is synthesized into the tracking direction vector.

Second Embodiment

8 is a schematic block diagram of a signal processing apparatus according to a second embodiment, and as shown in the drawing, an error vector synthesizing unit 91, a scalar synthesizing unit 92, and a tracking direction vector synthesizing unit 93. The autocorrelation matrix generator 96 and the maximum eigenvalue synthesizer 97 in addition to the signal processing device configuration (see FIG. 1) of the first embodiment, which comprises an adaptive gain synthesizer 94 and a gain vector updater 95. It is equipped with more.

The autocorrelation matrix generator 96 receives a received signal vector at every snapshot based on Equation (4) above, calculates and outputs an autocorrelation matrix. The maximum eigenvalue synthesis section 97 estimates the maximum intrinsic value of the autocorrelation matrix in the current snapshot output from the autocorrelation matrix generator 96. The error vector synthesizing unit 91 has an autocorrelation matrix output from the autocorrelation matrix generating unit 96, a maximum intrinsic value output from the maximum eigenvalue synthesizing unit 97, and a gain in the current snapshot for each snapshot. Each vector value is input and the error vector is synthesized and output. The scalar synthesizing unit 92 receives an error vector that is the output of the error vector synthesizing unit 91 and synthesizes and outputs a scalar value necessary for synthesizing the tracking direction vector. The tracking direction vector synthesizing unit 93 receives the error vector and the scalar value and synthesizes and outputs the tracking direction vector. The detailed configuration is the same as that of FIG. The adaptive gain synthesizing unit 94 receives the autocorrelation matrix, the tracking direction vector, the maximum intrinsic value in the current snapshot, and the gain vector value, respectively, and calculates and outputs the adaptive gain for each snapshot. The gain vector updater 95 updates the gain vector based on the tracking direction vector and the adaptive gain value at every snapshot.

The signal processing technique according to the second embodiment, which is constructed and operated as described above, also has a calculation amount of "O (3N ² + 12N) which is significantly improved compared to the conventional case, where 'N' is an array antenna The number of elements of By updating the value of each of the complex gain vectors obtained on each of the received signal vector elements induced in each antenna element of the array antenna, the value of each element of the complex gain vector can be applied, and ultimately, an optimal beam pattern can be provided for every snapshot. .

The configuration and operation of the maximum high value synthesis unit 97, the error vector synthesis unit 91, and the adaptive gain synthesis unit 94 will be described in more detail with reference to FIGS. 9 to 11 and the description thereof. The remaining components (scalar synthesis unit, tracking direction vector synthesis unit, and gain vector update unit) are the same as those in the case of the first embodiment described above, and are omitted in order to avoid duplication.

FIG. 9 is a detailed configuration diagram of an embodiment of the maximum intrinsic synthesizing unit 97 of the signal processing apparatus shown in FIG.

As shown in the figure, the maximum intrinsic synthesis section 97 includes a plurality of multipliers 992 for multiplying each element of each row of the autocorrelation matrix R with each element of the gain vector in the current snapshot. ), A plurality of adders 993 for adding and outputting the outputs of the multipliers 992 connected to the corresponding row, and the output of the adder 993 provided in the same row and the gain vector elements of the corresponding row. Complex conjugate A multiplier 994 for multiplying and outputting a multiplier 994 and a sum of the outputs of the plurality of multipliers 994 provided one for each row as a current estimated maximum intrinsic value λ. Equipped.

As described above, the maximum intrinsic value synthesis section 97 of the signal processing apparatus according to the present invention is an autocorrelation matrix value updated by every autonomous matrix generation unit 96 and a gain vector in the current snapshot. By synthesizing the maximum intrinsic value [lambda], we estimate the maximum intrinsic value [lambda] using the following equation for the gain vector normalized for each snapshot:

FIG. 10 is a detailed block diagram of an embodiment of the error vector synthesizing unit 91 of the signal processing apparatus shown in FIG.

The error vector synthesizing unit 91 based on the autocorrelation matrix value updated by the autocorrelation matrix generating unit every snapshot based on Equation (4) described above, and the gain vector in the current snapshot. And synthesizing the error vector using the estimated maximum intrinsic value (λ). A plurality of multipliers 982 for multiplying each element of each row of each element of the gain vector and the outputs of the multipliers 982 connected to each row, as many as the number of rows of the autocorrelation matrix. 983, a plurality of multipliers 981 for multiplying the current estimated maximum intrinsic lambda and each element of the gain vector, and then the output of the adder 983 from the output of each of these multipliers 981 A plurality of adders 984 for subtracting are included, and the error vector r synthesized by the error vector synthesizing unit 91 is calculated based on the following equation.

FIG. 11 is a detailed configuration diagram of an embodiment of the adaptive gain synthesizing unit 94 of the signal processing apparatus shown in FIG.

The adaptive gain (ρ) synthesis unit 94 includes a plurality of multipliers 261 for multiplying each element of each row of the autocorrelation matrix with each element of the tracking direction vector, and elements of each row of the autocorrelation matrix. And the tracking direction vector are equal to the number of rows of the autocorrelation matrix for adding the product of the elements (output of the multipliers 261) to each other, and the output and gain vector of each of the adders 262, respectively. A plurality of multipliers 263 for multiplying the complex conjugates of the elements, an adder 265 that adds all the outputs of the multipliers 263, and an output of each of the adders 262 and each element of the tracking direction vector. A plurality of multipliers 264 for multiplying complex conjugates, an adder 266 for adding up the outputs of the multipliers 264, and a multiplier for multiplying the complex conjugates of each element of the tracking direction vector and each element of the gain vector. Add both the multipliers 267 and the outputs of the multipliers 267 An adder 268, a plurality of multipliers 269 multiplying each element of the tracking direction vector and its complex conjugate, an adder 270 that adds all the multipliers 269 and an output, and the adder 265, An adaptive gain calculator 271 is provided which receives the output values of 266, 268, and 270, respectively, and calculates adaptive gain.

The adaptive gain calculator 271 outputs the output of the adder 265, the output of the adder 266, the output of the adder 268, and the output of the adder 270. In this case, using the values of A, B, C, and D inputted at each snapshot, the adaptive gain ρ is calculated according to the following equation:

Provided that E = BRe [C] -DRe [A],

F = B-λ D,

G = Re [D] -λRe [C]

In addition, when calculating A, B, C, and D as above, the value is determined as follows:

Third Embodiment

In this embodiment, the advantages and disadvantages of the first and second embodiments described above are layered, and in terms of the complexity of the system, it is inferior to the first embodiment but simpler than the second embodiment, and the second embodiment in terms of overall performance. We present a signal processing apparatus that calculates a gain vector that yields slightly less than, but superior to, the first embodiment.

FIG. 12 is a block diagram of an embodiment of a signal processing apparatus according to a third embodiment. As shown in the drawing, the autocorrelation matrix generating unit 96 of the second embodiment (see FIG. 8) is described. Except for replacing with the matrix calculation approximation unit 136, it has the same structure as the signal processing apparatus of the second embodiment described above.

In the matrix calculation approximation unit 136, instead of directly calculating the value of the autocorrelation matrix, two matrix operations including the autocorrelation matrix are approximated by a vector operation for each snapshot. The vector is output to the maximum intrinsic value combining unit 137, the error vector combining unit 131, and the adaptive gain combining unit 134, respectively. Accordingly, one input of each of the maximum intrinsic value synthesis unit 137, the error vector synthesis unit 131, and the adaptive gain synthesis unit 134 is not the autocorrelation matrix itself as in the above-described second embodiment. The input and output and the overall structure of each functional unit are the same as those of the signal processing apparatus of the second embodiment shown in FIG. 8 except that the resultant matrix operation is a vector (gamma vector and zeta vector).

According to the third embodiment signal processing technique of the present invention, which is constructed and operated as described above, it has a calculation amount of "O (15N) which is significantly improved compared to the conventional case, where 'N' is an arrangement. Means the number of antenna elements. " By updating a value, each element value of the complex gain vector obtained by the method described above is applied to each of the received signal vector elements induced in each antenna element of the array antenna, and ultimately, optimal for every snapshot. It is possible to provide a beam pattern of.

FIG. 13 shows a detailed configuration of an embodiment of the matrix calculation approximation unit 136 shown in FIG. As shown in the figure, the matrix calculation approximation unit 136 is a signal vector applied from an external receiver 7. A multiplier 1401 for multiplying each component of the complex conjugate of the output value y (t) output from the external dot product calculating device 8, and each element of the gamma vector in the previous snapshot and the forgetting A plurality of multipliers 1403 for multiplying the factor f, a plurality of multipliers 1408 for multiplying each element of the zetavector in the previous snapshot with the forgetting factor f, the multiplier 1408 and the output And a plurality of multipliers 1410 for multiplying the adaptive gain ρ, which is the output of the adaptive gain synthesis unit 134, and a number for adding the outputs of the multiplier 1410 and the output of another multiplier 1403, respectively. An adder 1404, a plurality of adders 1402 for adding the output of the adder 1404 and the output of the multiplier 1401, and the complex conjugate of each element of the signal vector and each element of the tracking direction vector. And a plurality of multipliers 1405 for multiplying by An adder 1411 for adding all outputs, and the received signal vector to the output of the adder 1411 A plurality of multipliers 1406 for multiplying each element of, another output of the multiplier 1408 and a multiplier 1409 for multiplying the scalar β, and another output of the multiplier 1409 It is composed of a plurality of adders (1407) for adding the output of the multiplier (1406), respectively, by using the output of the adder (1402) as a gamma vector, the maximum intrinsic synthesis unit 137 and the error vector synthesis unit 131 ) And the output of the adder 1407 is a zeta vector And output to the adaptive gain synthesis unit 134.

FIG. 14 shows a detailed configuration of one embodiment of the maximum intrinsic compound 137 shown in FIG. As shown in the figure, the maximum intrinsic synthesis unit 137 is a gamma vector applied from the matrix calculation unit approximation unit 136 shown in FIG. Each element of and the gain vector from the current snapshot And a multiplier 1501 for multiplying each element of the complex solution, and an adder 1502 for adding the output of the multiplier to output the output of the adder 1502 to the maximum intrinsic value?.

FIG. 15 illustrates a detailed configuration of an error vector combining unit 131 shown in FIG. As shown in the figure, the error vector synthesizing unit 1312 receives the maximum intrinsic value λ from the maximum intrinsic synthesizing unit 137 and obtains a gain vector in the current snapshot. A plurality of multipliers 1601 for multiplying with each element of and the gamma vector from the output of the multiplier 1601 And a subtractor 1602 for subtracting each element of.

What the apparatus shown in FIG. 12 ultimately performs is an error vector satisfying the following condition.

Is the output of the maximum intrinsic synthesis section 137, and w is the gain vector in the current snapshot. Is a gamma vector that is one of two outputs of the matrix approximation unit.

FIG. 16 is a detailed block diagram of an embodiment of the adaptive gain synthesizing unit 134 of the signal processing apparatus shown in FIG.

As shown in the figure, the adaptive gain synthesis unit 134, the tracking direction vector A plurality of multipliers 1704 for obtaining absolute squares, an adder 1708 for adding outputs of the multipliers 1704, and the tracking direction vector. A plurality of multipliers 1703 for sequentially multiplying the complex conjugates of each element of the gain vector with each other, an adder 1707 for adding outputs of the multipliers 1703, and the zeta vector Each element of and the gain vector A plurality of multipliers 1701 for multiplying each element of a complex conjugate of a multiplier, an adder 1705 for adding outputs of the multipliers 1701, and the zeta vector Each element of and the tracking direction vector An adaptive gain calculation unit connected to a plurality of multipliers 1702 multiplying complex conjugates of an adder, an adder 1706 that adds all the outputs of the multiplier 1702, and an output terminal of the adders 1705, 1706, 1707, and 1708. 1709.

If the adder 1705 outputs A, the output of the adder 1706 is B, the output of the adder 1707 is C, and the output of the adder 1708 is D, The adaptive gain calculation unit 1709 calculates the adaptive gain ρ

Obtain as

Where E = BRe [C] -DRe [A]

F = B-λD

G = Re [A] -λRe [C],

λ is the maximum intrinsic value,

Re [·] means the real part of the complex “·”.

In addition, if the above

to be.

FIG. 17 is a schematic diagram illustrating a method of minimizing interference and noise by applying the signal processing technique of the present invention using the optimized complex gain values according to the first to third embodiments to an array antenna system. Denotes an array antenna, 7 denotes a receiver, 8 denotes a dot product calculating device, and 9 denotes a signal processing device.

As shown in the figure, the signal receiving system includes a plurality of antenna elements 11, arranged at predetermined positions and intervals, and arranged to apply a received signal to each antenna element at the rear end of the array antenna 1. And a receiving device (7) which synthesizes the signal vectors at every snapshot by performing processing necessary for receiving signals such as frequency low-transition, demodulation, etc. with respect to the signal vectors induced by the antenna elements and output from the array antenna (1). And a dot product calculating device 8 for synthesizing the output values y (t) of the array antennas by dot-in each element (x ₁ ... X _N ) of the signal vector output from the receiving device 7 and a gain vector of an appropriate value. ) And each element (x ₁ ... X _N ) of the signal vector output from the receiver 7 is processed using the output value y (t) of the dot product calculating device 8 to obtain an appropriate gain vector value ( w ₁ ... w _N ) is obtained and then provided to the dot product calculating device 8. The signal processing apparatus 9 is provided.

As shown in the figure, the array antenna system includes a receiving device 7, a signal processing device 9, and an internal calculation device 8, in which each antenna element 11 is provided. Receives the received signal vector by shifting the frequency of the received received signal to the low range and undergoing a demodulation lamp. Create In the technique of the present invention, when used in a CDMA signal environment, a correlator for correlating a demodulated received signal with a chip code assigned to a desired signal is also included in the receiver 7.

And the received signal output to the receiving device 7 Is provided to the signal processing device 9 and the dot product calculating device 8. In addition, the signal processing apparatus 9 receives the received signal from the current snapshot. Optimal Gain Vector Using Array Antenna Output Signal (y (t)) in Previous Snapshot Yields. And optimum gain vectors calculated by the first to third embodiments. Is sent to the dot product calculating device 8, and the dot product calculating device 8 receives the received signal at the current snapshot. And gain vector Are computed from each other to calculate the reception output value y (t).

The signal processing apparatus 9 of the present invention uses the method as described above to receive the received signal every snapshot. Optimal gain vector for By calculating and providing to the internal product calculating device 8, the array antenna system ultimately refers to an optimal beam pattern (a beam pattern having a maximum gain in the original signal direction and a minimum gain in other directions). Each snapshot is provided to minimize the effects of interference and noise.

Fourth Embodiment

In the present embodiment, a signal processing technique for obtaining and providing a phase delay vector for maximizing gain in the original signal direction in a signal environment where the magnitude of the original signal is much higher than that of each interference signal will be described.

18 is a block diagram schematically showing the configuration of a fourth embodiment of a signal processing apparatus according to the present invention, in which 51 is an error vector synthesis unit, 52 is a scalar synthesis unit, 53 is a tracking direction vector synthesis unit, and 54 is an adaptation. The gain combiner 55 denotes a phase delay vector update unit, respectively.

As illustrated in the drawing, the signal processing apparatus according to the present embodiment includes a received signal vector induced in a plurality of antenna elements of an array antenna every snapshot. And the received output value y (t) and the phase delay vector at the previous snapshot. Is connected so that the error vector Is connected to one output terminal of the error vector synthesizing unit 51 and the error vector synthesizing unit 51 and calculates an error vector. Is connected to a scalar synthesis unit 52 for synthesizing and outputting a scalar value β necessary for tracking direction vector synthesis, the other output terminal of the error vector synthesis unit 51, and an output terminal of the scalar synthesis unit 52; Tracking direction vector A tracking direction vector synthesizing unit 53 for synthesizing and outputting a signal; , Received output value y (t), the tracking direction vector Phase Delay Vectors in, and Previous Snapshots Are applied to obtain the adaptive gain (ρ) for each snapshot and output the adaptive gain synthesis unit (54), and the tracking direction vector in the current snapshot. And phase delay vector by inputting adaptive gain value (ρ), respectively It includes a phase delay vector update unit 55 for updating the.

The error vector synthesizing unit 51 is an undelayed received signal vector from the plurality of antenna elements 11 of the array antenna (x ₁ (t) x ₂ (t) ... x _N (t)) and a phase delay vector. (phi ₁ ... phi _N ) and the reception output value y (t) are input, and the error vectors r ₁ (t) ... r _N (t) are synthesized and output. The scalar synthesis unit 52 receives an error vector r ₁ (t) ... r _N (t) from the error vector synthesis unit 51 and synthesizes a scalar value β to obtain the tracking direction vector synthesis unit ( 53). The tracking direction vector synthesizing unit 53 receives the error vector r ₁ (t) ... r _N (t) and a scalar value (β). Synthesize and output The adaptive gain synthesizing unit comprises the undelayed received signal vectors (x ₁ (t) x ₂ (t) ... x _N (t)) from the plurality of antenna elements 11, and the phase delay vectors φ ₁ ... _N ), the received output value y (t), and the tracking direction vector Are input to the phase delay vector update unit 55 by synthesizing the adaptive gains p. In addition, the phase delay vector update unit 55 performs the tracking direction vector. And an adaptive gain (ρ) receives the phase delay vector (φ ₁ ... φ _N) the received signal, for each snapshot, by updating the outputs By calculating and providing an optimal phase delay vector for, ultimately, the array antenna system has an optimal beam pattern with the maximum gain in the original signal direction and the minimum gain in the other direction. Minimize the effects of noise.

19 shows a detailed configuration of an error vector synthesizing unit 51 of the signal processing apparatus according to the fourth embodiment.

As shown in the drawing, the error vector synthesizing unit obtains the phase delayed signals based on the phase delay vectors of the signals induced in the antenna elements 11 at each snapshot, and adds the values of the elements of the vector to each other. A signal vector obtained from a multiplier 511 that squares the reception output value y (t) of the array antenna and the signals induced in the antenna elements 11 A plurality of multipliers 512 multiplying the received output values y (t) of the array antennas by the elements of the array antennas and phase delays of the output values squared by the multipliers 511 by each element value of the phase delay vector. A plurality of adders subtracting the vector value of the result multiplied by the multipliers 512 from the plurality of phase delay elements 513 and the vector value obtained by phase delaying through the plurality of phase delay elements 513. 514, and the result of each adder 514 is determined as the value of each element of the error vector.

The error vector synthesizing unit 51 shown in FIG. 19 is a device for processing the received actual signal value without the frequency low shift. Ultimately, the error vector synthesizer 51 intends to perform an error vector satisfying the following equation. To calculate.

However, as described above, since the autocorrelation matrix is calculated using only the current input signal (instantaneous value), it can be simply implemented as shown in FIG. Therefore, the error vector Is the phase delay vector As is near to the phase of the eigenvector, its magnitude converges to zero.

20 is a detailed configuration diagram of an example of the scalar synthesis unit 52 of the signal processing apparatus according to the fourth embodiment, wherein the scalar synthesis unit 52 is the magnitude of each element of the error vector in the current snapshot. A multiplier 521 that squares s, an adder 522 that adds all squares of the elements of the error vector, and the adder 522 output from the previous snapshot to the adder in the current snapshot. 522) a divider 525 for dividing the output, and a sign converter 526 for applying a negative sign (-) to the result output of the divider 525.

Tracking direction vector Tracking direction vector from previous snapshot on update Quadratic vector in the current snapshot by multiplying Tracking direction vector by adding to Yields.

As described above, the ultimate goal of synthesizing the scalar value β is that all tracking direction vectors are calculated for each snapshot. It is to calculate a scalar value such that they are orthogonal to each other with respect to the autocorrelation matrix. Therefore, when the scalar value is accurately calculated, the optimal phase delay vector can be calculated with the minimum amount of computation.

21 shows a detailed configuration of an embodiment of the tracking direction vector synthesizing unit 53 of the signal processing apparatus according to the fourth embodiment.

As shown in the figure, the tracking direction vector synthesizing unit 53 has one input terminal connected to each of the error vector elements r ₁ ..r _N of the error vector synthesizing unit 51 and the tracking direction to the output terminal. A plurality of adders 531 for outputting a vector (v ₁ ... v _N ), and a value from a previous snapshot for each element of the tracking direction vector outputted through the adder 531 as one input terminal; The other input stage includes a plurality of multipliers 532 that receive and multiply the scalar value β and output the result to the adder 531.

Thus, in the first snapshot, the error vector output from the error vector synthesizing unit 51 is used as the tracking direction vector, and in the case after the second snapshot, the tracking direction of the previous snapshot is stored using the multiplier 532. After multiplying a scalar value, the result obtained by adding the output value of the multiplier 532 and the error vector in the current snapshot by using the adder 531 is synthesized into the tracking direction vector.

22 is a detailed block diagram of an embodiment of the adaptive gain synthesizing unit 54 of the signal processing apparatus according to the fourth embodiment.

As shown in the figure, the adaptive gain synthesizing unit 54 performs the signal vector. Each element of and the tracking direction vector A plurality of multipliers 541b connecting each element of the circuit in turn and the tracking direction vector; A multiplier 541a for squaring each element of and the tracking direction vector An adder 543a for adding squared values of the elements of each other to the tracking direction vector; The phase delay vector at the current snapshot A plurality of phase delay elements 542 and a phase delayed tracking direction vector for phase delaying by An adder 543b for adding each element value of the multiplier, an adder 543c for adding the outputs of the plurality of multipliers 541b, a multiplier 544 for squaring the output of the adder 543c, A multiplier 545 for multiplying the output of the array antenna (y (t)) in the current snapshot with the output of the adder 543c, and for squaring the array antenna output value (y (t)) in the current snapshot A multiplier 546, and an adaptive gain calculator 547 connected to the outputs of the adders 543a and 543b and the multipliers 544 and 545 and 546, respectively.

The output of the adder 543c is A, the A and the received output value y (t) of the array antenna are the multiplier 545 output B, and the A value is squared with the multiplier 544. One value is C, the output of the adder 543b is D, the output of the adder 543a is E, and the product of the product of C and D minus the value of E and B is F. The result of subtracting the product of E and the square of the array antenna reception output value (y ² (t)) from C is G, and the square of the array antenna reception output value (y ² (t)) from B is D. When H is subtracted from H, the adaptive gain calculation unit 547 concludes that the square root of the result of subtracting four times the product of F and G from G squared is subtracted from -G again. Synthesize and output the result of dividing by 2, that is, the adaptive gain (ρ) expressed by the following formula:

Where F = CD-BE,

G = Cy ² (t) E,

H = By ² (t) D.

23 is a detailed configuration diagram of an embodiment of the phase delay vector update unit 55 of the signal processing apparatus according to the fourth embodiment.

As shown in the figure, the phase delay vector updating unit 55 is the adaptive gain synthesizing unit corresponding to the corresponding tracking direction vector element v _{i for} each output element of the tracking direction vector (v ₁ ... V _N ). A multiplier 551 for multiplying the adaptive gain value ρ output from 54 and the received signal Phase delay vector of the oscillator (osc) output signal which generates the signal of carrier frequency A plurality of phase delay elements 552 for phase-delaying each element of, a plurality of adders 553 for adding the output of the multiplier 551, and the output of the phase delay element 552, and the adder 553. And a phase detector 554 for calculating the phase delay of each element to be used in the current snapshot from the result value of. The phase delay vector updating unit 55 constructed and operated as described above is configured to be used in the current snapshot. Received signal vector Each element of is delayed by each element of the updated phase delay vector (ie, the phase delay vector of the current snapshot) from the previous snapshot.

24 is a detailed configuration diagram of another embodiment of the phase delay vector update unit 55 of the signal processing apparatus according to the fourth embodiment, and is shown in FIG. 23 in the configuration of each element of the phase delay vector update unit shown in FIG. In addition, each device is further equipped with an output of a normalized phase delay vector value.

As the phase delay vector update unit 55 according to this embodiment is shown in the figure, each element (v ₁ ... v _N) output of the tracking direction vector, a multiplier 551, the phase delay elements 552, The size of the first element φ ₁ and the last element φ _N of the phase delay vector calculated by the phase detector 554 in each snapshot having the adder 553 and the phase detector 554. In addition, the selection element 555 for selecting an element having a small size by comparing with and the adder 556 for subtracting and outputting the value selected by the selection element 555 from the output value of the phase detector 554, respectively. It is equipped.

The phase delay vector update unit 55 configured as described above has a phase delay value applied to the reference antenna element of the array antenna to be 0 in calculating the phase delay value, and is applied to all subsequent antenna elements. In order to make the phase delay value to be zero, the magnitude is compared by comparing the magnitudes of the first element φ ₁ and the last element φ _N of the phase delay vector calculated by the phase detector 554 at every snapshot. By selecting a small element, the value obtained by subtracting the output value of each phase detector 554 is output as a normalized phase delay vector.

For reference, the "reference antenna" is an antenna element in which a signal of the latest phase is induced in a reception mode, and an antenna element emitting a signal having the fastest phase in a transmission mode. In other words, if this is physically explained, the antenna is farthest from the other party to communicate with (both transmitting and receiving).

25 is a schematic diagram illustrating a method of minimizing interference and noise by applying the signal processing technique of the present invention using an optimized phase delay value according to the fourth embodiment to an array antenna system, in which 1 is an array antenna. 2 denotes a phase delay device, 3 denotes a delay signal adding device, and 5 denotes a signal processing device.

The array antenna system shown in the figure is provided with a plurality of antenna elements 11 and arranged at predetermined positions and intervals to receive the received signals and provide them to the phase delay device 2 and the signal processing device 5 at the rear stage. A phase delay device 2 comprising a plurality of phase natural elements 21 for receiving a signal from the array antenna 1 and a plurality of phase natural elements 21 for phase-delaying a signal induced in each antenna element as desired. ), A delay signal adder 3 which calculates an output value of the array antenna by adding each of the signals which are appropriately phase delayed through the phase delay unit 2, and the signal obtained by the array antenna 1; And a signal processing device 5 for processing the vector to provide an appropriate phase delay value to the phase delay device 2.

In addition, by calculating a phase delay vector for forming a beam pattern that provides the maximum gain in the direction of the desired signal and adding it to the received signal, the difference between the original signal and the interference signal is further increased to minimize the effects of noise and interference. can do. In particular, the reception system using the signal processing apparatus of FIG. 18 as described above is very suitable when the signal environment itself is significantly larger than the desired signal.

As introduced in the first to fourth embodiments described above, when the signal processing apparatus of the present invention that provides an ideal beam pattern is provided in a base station of a mobile communication system, it is possible to increase the communication capacity and improve the communication quality. The battery life of all domestic terminals can be greatly increased. That is, the base station sets the main lobe only in the direction of the subscriber to communicate with, thus enabling smooth communication even if the transmission power of the mobile terminal is significantly lowered.

Names of the functional units (e.g., matrix vector approximation unit, maximum intrinsic synthesizing unit, etc.) for the signal processing apparatus and method applied in the present invention, and names of the respective signals synthesized in the respective functional units (e.g., zeta Vectors, gamma vectors, error vectors, tracking direction vectors, etc.) are merely named for convenience of description, and it is common knowledge in the art that substantially the same functional units or signals may be represented by different names. Self-explanatory

In addition, the present invention has been described in detail according to a preferred embodiment, but this is for the purpose of description, not limiting the technical spirit of the present invention, various substitutions or modifications are possible within the scope of the technical spirit of the present invention It is obvious to those skilled in the art.

As described above, the present invention has the following effects.

First, in the array antenna system, the beam pattern is adjusted every snapshot to provide an ideal beam pattern (that is, a beam pattern having a maximum gain in the original signal direction and a minimum gain in the other direction) to minimize interference. In addition to significantly reducing the effects of noise, the function can be implemented through a much simpler calculation process than the conventional method, so that it can be easily applied to the field of time-converted communication, thereby improving communication quality and subscriber capacity. It is effective.

Claims (51)

A signal processing apparatus for providing a gain vector for every snapshot to reduce the effects of interference and noise in an array antenna system, comprising: a signal vector induced in a plurality of array antenna elements provided in the array antenna system at each snapshot; Error vector synthesizing means for calculating an error vector by receiving the previous snapshot output value of the array antenna system and the gain vector value of the current snapshot; Scalar synthesizing means for receiving an error vector from the error vector synthesizing means and synthesizing and outputting a scalar value necessary for tracking direction vector synthesis; Tracking vector synthesizing means for synthesizing a tracking direction vector by receiving the error vector and the scalar value; Adaptive gain synthesizing means for receiving the signal vector, the tracking direction vector, the previous snapshot output value, and the gain vector value of the current snapshot to obtain an adaptive gain; And gain vector updating means for receiving the tracking direction vector and the adaptive gain value, respectively, and updating the gain vector, wherein the gain vector value is a signal induced in each of a plurality of antenna elements included in the array antenna system. And a eigenvector value corresponding to the maximum eigenvalue of the autocorrelation matrix obtained from the signal processing device. The signal processing apparatus according to claim 1, wherein the gain vector value is determined by a value of an eigenvector corresponding to a maximum eigenvalue of the autocorrelation matrix. The eigenvalue corresponding to the maximum eigenvalue of claim 1, wherein the gain vector value is configured to apply only a local change without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. A signal processing device characterized in that the vector is determined by a constant multiple. The eigenvalue corresponding to the maximum eigenvalue of claim 1, wherein the gain vector value is configured to apply only a local change without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. A signal processing apparatus characterized in that the vector is set to a value normalized to have a size of 1. 2. The autocorrelation matrix of claim 1, wherein the autocorrelation matrix is obtained by multiplying the autocorrelation matrix of the previous snapshot by the forgetting factor having any one value between 0 and 1, as shown in the following equation. And a signal matrix obtained from the signal vector for the signal induced by the antenna element. (only, Is the autocorrelation matrix of the J + 1th snapshot, Is the autocorrelation matrix of the Jth snapshot, f is the forgetting factor taking values between 0 and 1, T _S is the snapshot period, and the superscript H is the Hermitiam operator. 2. The gain vector of claim 1, wherein the gain vector does not change the signal induced in the reference antenna element in order to eliminate the phase difference between the signals induced in the antenna elements in the first snapshot, The gain vector is determined by applying a phase delay to a phase difference with an adjacent antenna element having a later phase, and is obtained by updating the gain vector from the previous snapshot from the second snapshot, in each snapshot. And obtaining and updating a Rayleigh quotient defined by the autocorrelation matrix and the gain vector. 2. The apparatus of claim 1, wherein (a) the error vector synthesizing means comprises: multiplication means (911) for squaring a previous snapshot output value of the array antenna system; A plurality of multiplication means (912) for internalizing the previous snapshot output value in the received signal vector of the current snapshot; A plurality of multiplication means (913) for multiplying the output value of the multiplication means with each element of a gain vector; And a plurality of subtraction means 914 for subtracting each output value of the multiplication means 912 assigned to each element of the received signal vector from the corresponding element output value of the multiplication means 913 assigned to each element of the gain vector. And (b) said adaptive gain synthesizing means comprises: a plurality of multiplication means (941) for complexly conjugating each element of said received signal vector with each element of said tracking direction vector; Addition means (946) for adding the outputs of the plurality of multiplication means (941) to each other; A plurality of multiplication means (942) for obtaining an absolute value square of each element of the tracking direction vector; Addition means (945) for adding the outputs of the multiplication means (942) to each other; A plurality of multiplication means (943) for multiplying the complex conjugates of each element of the tracking direction vector and each element of the gain vector; Addition means (944) for adding the outputs of the multiplication means (943) to each other; Multiplication means (949) for squaring the output of said addition means (946); Multiplication means (947) for multiplying the direct snapshot output value with the output of the overlay means (946); Multiplication means (948) for obtaining an absolute square of the direct snapshot output value; And adaptive gain calculation means 950 connected to the output ends of the addition means 944, 945 and multiplication means 947, 948, 949, respectively (c) the gain vector updating means being tracked in the current snapshot. A plurality of multiplication means 951 for multiplying the direction vector and the adaptive gain value; And a plurality of addition means 952 for adding the gain vector in the previous snapshot and the output value of each multiplication means 951, wherein (d) the scalar synthesis means is squared with the absolute value of each element of the error vector. A plurality of multiplication means 921 for performing; Addition means (922) for adding the outputs of the multiplication means (921) to each other; Division means (923) for dividing the output of the addition means (922) in the current snapshot by the output of the addition means (922) in the previous snapshot; And code conversion means (924) for applying a negative sign (−) to the output of the division means (923). The result of multiplying the received signal vector and the tracking direction vector (the output of the addition means 946) is A, and the result of multiplying A by the previous output value of the array antenna system (the multiplication). The output of the means 947 is B, the square of A (the output of the multiplication means 949) is C, and the gain vector and the tracking direction vector are internalized (the addition means 944). ), And the tracking direction vector and its own inner product (which is the output of the addition means 945) are E, and the adaptive gain calculating means 950 adapts according to the following equation. A signal processing apparatus characterized by obtaining a gain (ρ). (Where, F = C · Re [D ] -B · Re [E], G = C- | y (t) | 2 E, H = Re [B] - | y (t) | 2 · Re [D ], Re [·] is the real part of the complex “·”. 8. The gain vector updating means according to claim 7, wherein each gain value of the plurality of adding means (952) is multiplied by N square root of the output value of the adding means (952) connected to a reference antenna element. Wherein N is a plurality of dividing means (953) all divided by the array antenna element of the array antenna system. A signal processing apparatus that provides a gain vector for every snapshot to reduce the effects of interference and noise in an array antenna system, wherein each snapshot is applied to signal vectors induced in a plurality of array antenna elements provided in the array antenna system. Autocorrelation matrix generating means for calculating and outputting an autocorrelation matrix for the output; Maximum eigenvalue synthesis means for estimating the maximum eigenvalue of the autocorrelation matrix at the current snapshot; Error vector synthesizing means for inputting the autocorrelation matrix, the maximum eigenvalue, and a gain vector value in the current snapshot to synthesize an error vector; Scalar synthesizing means for receiving the error vector and synthesizing a scalar value necessary for tracking direction vector synthesis; Tracking direction vector synthesizing means for receiving the error vector and the scalar value and synthesizing the tracking direction vector; Adaptive gain synthesizing means for obtaining adaptive gain by receiving the autocorrelation matrix, the tracking direction vector, the maximum intrinsic value in the current snapshot and the gain vector value, respectively; And gain vector updating means for receiving the tracking direction vector and the adaptive gain value, respectively, and updating the gain vector, wherein the gain vector value is a signal induced in each of a plurality of antenna elements included in the array antenna system. And a eigenvector value corresponding to the maximum eigenvalue of the autocorrelation matrix obtained from the signal processing device. The signal processing apparatus according to claim 10, wherein the gain vector value is determined by a value of an eigenvector corresponding to a maximum eigenvalue of the autocorrelation matrix. The eigenvalue corresponding to the maximum eigenvalue of claim 10, wherein the gain vector value is configured to apply only a local change without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. A signal processing device characterized in that the vector is determined by a constant multiple. The eigenvalue corresponding to the maximum eigenvalue of claim 10, wherein the gain vector value is configured to apply only a local change without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. A signal processing device characterized in that the vector is set to a value normalized to have a size of 1. The antenna element of claim 10, wherein the autocorrelation matrix is obtained by multiplying the autocorrelation matrix in a previous snapshot by a forgetting factor having any value between 0 and 1. And a signal matrix obtained from a signal vector with respect to the induced signal to obtain the following equation. (only, Is the autocorrelation matrix of the J + 1th snapshot, Is the autocorrelation matrix of the Jth snapshot, f is the forgetting factor taking values between 0 and 1, T _S is the snapshot period, and the superscript H is the Hermitiam operator. The method of claim 10, wherein the gain vector is not changed to the signal induced in the reference antenna element in order to eliminate the phase difference between the signals induced in each antenna element in the first snapshot, and the gain vector is induced in other antenna elements. For the signals, the value of the gain vector is determined so as to apply a phase delay by a phase difference with an adjacent antenna element having a later phase, and the second snapshot is obtained by updating the gain vector in the previous snapshot, And updating to obtain a maximum Rayleigh quotient defined by the autocorrelation matrix and the gain vector. 11. The apparatus of claim 10, wherein (a) said error vector synthesizing means comprises: a plurality of multiplication means (982) for multiplying each element of each row of said autocorrelation matrix with each element of a gain vector; A plurality of addition means (983) provided for each row of the autocorrelation matrix to add the outputs of the multiplication means (982) to each other; A plurality of multiplication means 981 for multiplying each element of the current estimated maximum intrinsic value and the gain vector; And a plurality of addition means 984 for sequentially subtracting the outputs of the plurality of addition means 983 provided correspondingly from each output of the multiplication means 981 provided for each row of the autocorrelation matrix. And (b) a maximum intrinsic synthesis means comprising: a plurality of multiplication means (992) for multiplying each element of each row of the autocorrelation matrix with each element of the gain vector in the current snapshot; A plurality of addition means (993) for adding and outputting the outputs of the plurality of multiplication means (992) respectively provided for the same row of the autocorrelation matrix; A plurality of multiplication means (994) for multiplying and outputting the output of the addition means (993) and the complex conjugate of the gain vector elements in the same row; And adding means 995 for outputting the sum of the outputs of the multiplication means 994, one for each row, to a current estimated maximum intrinsic value, and (c) the adaptive gain synthesizing means comprises the autocorrelation matrix. A plurality of multiplication means 261 for multiplying each element of each row of with each element of the tracking direction vector; Adding means (262) provided for each row to add together the products of elements of each row of the autocorrelation matrix and elements of a tracking direction vector; A plurality of multiplication means (263) for multiplying the output of each of the addition means (262) and the complex conjugate of each element of the gain vector; Addition means (265) for adding all of the outputs of the multiplication means (263); A plurality of multiplication means (264) for multiplying the output of each of the addition means (262) and the complex conjugate of each element of the tracking direction vector; Addition means (266) for adding all of the outputs of the plurality of multiplication means (264); A plurality of multiplication means (267) for multiplying the complex conjugates of each element of said tracking direction vector and each element of said gain vector; Addition means (268) for adding up the outputs of the multiplication means (267); A plurality of multiplication means (269) for multiplying each element of said tracking direction vector with its complex conjugate; Addition means (270) for adding all of the outputs of the multiplication means (269); And adaptive gain calculating means (271) for calculating adaptive gain by inputting the outputs of the adding means (265, 266, 268, 270). 17. The method of claim 16, wherein the output of the adding means 265 is A, the output of the adding means 266 is B, the output of the adding means 268 is C, and the output of the adding means 270 is D. In this case, the adaptive gain calculating means 271 calculates the adaptive gain ρ according to the following equation using the values of A, B, C, and D input for every snapshot. Processing unit. (Where E = B-Re [C]-D-Re [A], F = B-λ D, G = Re [D]-λ Re [C], λ is the maximum eigenvalue, ] Is the real part of the complex "·"). A signal processing apparatus that provides a gain vector for every snapshot to reduce the effects of interference and noise in an array antenna system, wherein each snapshot is applied to signal vectors induced in a plurality of array antenna elements provided in the array antenna system. Matrix computation approximation means for performing an autocorrelation matrix operation on the same, and outputting a gamma vector and a zeta vector by approximating by a vector operation; Maximum eigenvalue synthesis means for estimating a maximum intrinsic value of the autocorrelation matrix by receiving the gain vector from the gamma vector and the current snapshot; Error vector synthesizing means for inputting the gamma vector, the maximum eigenvalue, and a gain vector value in the current snapshot to synthesize an error vector; Synthesizing means for receiving the error vector and synthesizing a scalar value necessary for tracking direction vector synthesis; Tracking direction vector synthesizing means for receiving the error vector and the scalar value and synthesizing the tracking direction vector; Adaptive gain synthesizing means for receiving the zeta vector, the tracking direction vector, the maximum eigenvalue, and the gain vector value, respectively, for obtaining and outputting an adaptive gain; And gain vector updating means for updating a gain vector based on the tracking direction vector and the adaptive gain value, wherein the gain vector value is obtained from a signal induced in each of a plurality of antenna elements included in the array antenna system. And a eigenvector value corresponding to the maximum eigenvalue of the obtained autocorrelation matrix. 19. The signal processing apparatus according to claim 18, wherein the gain vector value is determined by a value of an eigenvector corresponding to a maximum eigenvalue of the autocorrelation matrix. The eigenvalue corresponding to the maximum eigenvalue of claim 18, wherein the gain vector value is configured to apply only a local change without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. A signal processing device characterized in that the vector is determined by a constant multiple. The eigenvalue corresponding to the maximum eigenvalue of claim 18, wherein the gain vector value is configured to apply only a local change without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. A signal processing device characterized in that the vector is set to a value normalized to have a size of 1. 19. The method of claim 18, wherein the autocorrelation matrix is obtained by multiplying the autocorrelation matrix in the previous snapshot by the forgetting factor having a value of 0 to 1, as shown in the following equation. And a signal matrix obtained from the signal vector for the signal induced in each antenna element. (only, Is the autocorrelation matrix of the J + 1th snapshot, Is the autocorrelation matrix of the Jth snapshot, f is an oblivion factor taking a value between 0 and 1, T _S is the snapshot period, and the superscript H is the Hermitiam operator. 19. The method of claim 18, wherein the gain vector is not changed in the signal induced in the reference antenna element in order to eliminate the phase difference between the signals induced in the antenna elements in the first snapshot, and the gain vector is not changed in other antenna elements. The gain vector is determined by applying a phase delay to a phase difference with an adjacent antenna element having a later phase, and is obtained by updating the gain vector from the previous snapshot from the second snapshot, in each snapshot. And updating to obtain a maximum Rayleigh quotient defined by the autocorrelation matrix and the gain vector. 19. The apparatus of claim 18, wherein the error vector synthesizing means comprises: a plurality of multiplication means (1601) for multiplying each element of the current estimated maximum intrinsic value and the gain vector in turn; And a plurality of subtraction means (1602) for sequentially subtracting each element of the gamma vector from each output of the multiplication means (1601). 19. The apparatus of claim 18, wherein the matrix calculation approximation means comprises: a plurality of multipliers 1401 for respectively multiplying each element of the received signal vector by the complex conjugate (y *) of the current output value; A plurality of multipliers 1403 for multiplying each element of the gamma vector in the previous snapshot by the forgetting factor f; A plurality of multipliers 1408 for multiplying each element of the zetavector in the previous snapshot by the forgetting factor f; A plurality of multipliers 1410 for multiplying the multiplier 1408 with an output and an adaptive gain ρ which is an output of the adaptive gain synthesis allowance; A plurality of adders (1404) for adding the output of the multiplier (1410) and the output of the multiplier (1403), respectively; A plurality of adders 1402 for adding the output of the adder 1404 and the output of the multiplier 1401; A plurality of multipliers (1405) for multiplying the complex conjugate of each element of the signal vector and each element of the tracking direction vector in turn; An adder 1411 for adding all of the plurality of multiplier outputs; The received signal vector at the output of the adder 1411 A plurality of multipliers 1406 for multiplying each element of; A plurality of multipliers (1409) for multiplying the output of the multiplier (1408) with the scalar (β); And a plurality of adders 1407 for adding the output of the multiplier 1409 and the output of the multiplier 1406, respectively, and the output of the adder 1402 as the gamma vector, and the output of the adder 1407. The signal processing device, characterized in that the calculation as a zeta vector. 26. The apparatus of claim 25, wherein the maximum intrinsic synthesis means comprises: a plurality of multiplication means (1501) for multiplying each element of the gamma vector and each element of the complex vector of the gain vector in the current snapshot; And addition means (1502) for adding and outputting all of the outputs of the plurality of multiplication means (1501). 27. The apparatus of claim 26, wherein the adaptive gain synthesizing means comprises: a plurality of multiplying means 1701 for sequentially multiplying the complex conjugates of each element of the zeta vector and each element of the gain vector, which is one output of the matrix calculation approximation means; Addition means (1705) for adding all of the outputs of the plurality of multiplication means (1701); A plurality of multiplication means 1702 for multiplying the complex conjugates of each element of the zeta vector and each element of the tracking direction vector; Addition means (1706) for adding all of the outputs of the plurality of multiplication means (1702); A plurality of multiplication means (1703) for multiplying the complex conjugate of each element of said tracking direction vector and each element of a gain vector; Addition means (1707) for adding up the outputs of the plurality of multiplication means (1703); A plurality of multiplication means (1704) for multiplying each element of the tracking direction vector by its complex conjugate; Addition means (1708) for adding all of the outputs of the plurality of multiplication means (1704); And adaptive gain calculating means (1709) for calculating adaptive gain with the outputs of the plurality of adding means (1705, 1706, 1707, and 1708) as inputs. 28. The method of claim 27, wherein the output of the adding means 1705 is A, the output of the adding means 1706 is B, the output of the adding means 1707 is C, and the output of the adding means 1708 is D. In this case, the adaptive gain calculating means 1709 calculates the adaptive gain ρ according to the following equation using the values of A, B, C, and D input for every snapshot. Processing unit. (Where E = B-Re [C]-D-Re [A], F = B-λ D, G = Re [A]-λ Re [C], λ is the maximum eigenvalue, ] Is the real part of the complex "·"). A signal processing method for providing a gain vector for every snapshot in order to reduce the effects of interference and noise in an array antenna system, wherein each snapshot is a signal vector and the array induced in a plurality of array antenna elements of the array antenna system. An error vector synthesizing step of calculating an error vector by receiving a previous snapshot output value of the antenna system and a gain vector value of the current snapshot; A scalar synthesis step of receiving the error vector and synthesizing and outputting a scalar value necessary for tracking direction vector synthesis; A tracking vector synthesis step of synthesizing a tracking direction vector by receiving the error vector and the scalar value; Adaptive gain synthesizing means for receiving the signal vector, the tracking direction vector, the previous snapshot output value, and the gain vector value of the current snapshot to obtain an adaptive gain; And gain vector updating means for receiving the tracking direction vector and the adaptive gain value, respectively, and updating the gain vector, wherein the gain vector value is a signal induced in each of a plurality of antenna elements included in the array antenna system. And a eigenvector value corresponding to the maximum eigenvalue of the autocorrelation matrix obtained from the method. The signal processing method according to claim 29, wherein the gain vector value is determined by a value of an eigenvector corresponding to a maximum eigenvalue of the autocorrelation matrix. The eigenvalue corresponding to the maximum eigenvalue according to claim 29, wherein the gain vector value is such that only a local change is made without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. A signal processing method characterized in that the vector is determined by a constant multiple. The eigenvalue corresponding to the maximum eigenvalue according to claim 29, wherein the gain vector value is such that only a local change is made without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. A signal processing method characterized in that a vector is set to a value normalized to have a size of 1. 30. The method of claim 29, wherein the gain vector is not changed to a signal induced in the reference antenna element in order to eliminate a phase difference between the signals induced in the antenna elements in the first snapshot, and is applied to other antenna elements. The gain vector is determined by applying a phase delay to a phase difference with an adjacent antenna element having a later phase, and is obtained by updating the gain vector from the previous snapshot from the second snapshot, in each snapshot. And updating and obtaining a Rayleigh quotient defined by the autocorrelation matrix and the gain vector to a maximum. A signal processing apparatus that provides a gain vector for every snapshot to reduce the effects of interference and noise in an array antenna system, wherein each snapshot is a magnetic signal for a signal vector induced in a plurality of array antenna elements of the array antenna system. Generating an autocorrelation matrix for calculating and outputting a correlation matrix; A maximum eigenvalue synthesis step for estimating the maximum eigenvalue of the autocorrelation matrix in the current snapshot; An error vector synthesis step of synthesizing an error vector by receiving the autocorrelation matrix, the maximum eigenvalue, and a gain vector value in the current snapshot; A scalar synthesis step of receiving the error vector and synthesizing a scalar value necessary for tracking direction vector synthesis; A tracking direction vector synthesis step of synthesizing a tracking direction vector by receiving the error vector and the scalar value; An adaptive gain synthesis step of obtaining adaptive gain by receiving the autocorrelation matrix, the tracking direction vector, the maximum intrinsic value in the current snapshot and the gain vector value, respectively; And gain vector updating means for updating a gain vector based on the tracking direction vector and the adaptive gain value, wherein the gain vector value is obtained from a signal induced in each of a plurality of antenna elements included in the array antenna system. And a eigenvector value corresponding to the maximum eigenvalue of the obtained autocorrelation matrix. 35. The signal processing method according to claim 34, wherein the gain vector value is determined by a value of an eigenvector corresponding to a maximum eigenvalue of the autocorrelation matrix. The eigenvalue corresponding to the maximum eigenvalue of claim 34, wherein the gain vector value is such that only a local change is made without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. A signal processing method characterized in that the vector is determined by a constant multiple. The eigenvalue corresponding to the maximum eigenvalue of claim 34, wherein the gain vector value is such that only a local change is made without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. A signal processing method characterized in that a vector is set to a value normalized to have a size of 1. 35. The antenna element of claim 34, wherein the autocorrelation matrix is obtained by multiplying the autocorrelation matrix in a previous snapshot by a forgetting factor having any value between 0 and 1 in size. And a signal matrix obtained from a signal vector with respect to the induced signal to obtain the following equation. (only, Is the autocorrelation matrix of the J + 1th snapshot, Is the autocorrelation matrix of the Jth snapshot, f is the forgetting factor taking values between 0 and 1, T _S is the snapshot period, and the superscript H is the Hermitiam operator. 35. The method according to claim 34, wherein the gain vector does not change the signal induced in the reference antenna element in order to eliminate the phase difference between the signals induced in the antenna elements in the first snapshot, and the other antenna elements do not change. The gain vector is determined by applying a phase delay to a phase difference with an adjacent antenna element having a later phase, and is obtained by updating the gain vector from the previous snapshot from the second snapshot, in each snapshot. And updating and obtaining a Rayleigh quotient defined by the autocorrelation matrix and the gain vector to a maximum. A signal processing method for providing a gain vector for every snapshot in order to reduce the effects of interference and noise in an array antenna system, wherein each snapshot is a magnetic signal for a signal vector induced in a plurality of array antenna elements of the array antenna system. Performing matrix correlation approximation for approximating the vector operation to output a gamma vector and a zeta vector; A maximum eigenvalue synthesis step for estimating a maximum intrinsic value of the autocorrelation matrix by receiving the gain vector from the gamma vector and the current snapshot; An error vector synthesizing step of synthesizing an error vector by receiving the gamma vector, the maximum eigenvalue, and a gain vector value of the current snapshot; A synthesis step of synthesizing a scalar value required for tracking direction vector synthesis by receiving the error vector; A tracking direction vector synthesis step of synthesizing a tracking direction vector by receiving the error vector and a scalar value; An adaptive gain synthesis step of receiving the zeta vector, the tracking direction vector, the maximum eigenvalue, and the gain vector value, respectively, and obtaining and outputting an adaptive gain; And gain vector updating means for updating a gain vector based on the tracking direction vector and the adaptive gain value, wherein the gain vector value is obtained from a signal induced in each of a plurality of antenna elements included in the array antenna system. And a eigenvector value corresponding to the maximum eigenvalue of the obtained autocorrelation matrix. 41. The signal processing method according to claim 40, wherein the gain vector value is determined by a value of an eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. The eigenvalue corresponding to the maximum eigenvalue according to claim 40, wherein the gain vector value is such that only a local change is applied without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. A signal processing method characterized in that the vector is determined by a constant multiple. The eigenvalue corresponding to the maximum eigenvalue according to claim 40, wherein the gain vector value is such that only a local change is applied without affecting the beam pattern characteristic of the eigenvector corresponding to the maximum eigenvalue of the autocorrelation matrix. A signal processing method characterized in that a vector is set to a value normalized to have a size of 1. 41. The method of claim 40, wherein the autocorrelation matrix is obtained by multiplying the autocorrelation matrix in a previous snapshot by the forgetting factor having a value of 0 to 1, as shown in the following equation. And a signal matrix obtained from a signal vector for the signal induced in each antenna element. (only, Is the autocorrelation matrix of the J + 1th snapshot, Is the autocorrelation matrix of the Jth snapshot, f is the forgetting factor taking values between 0 and 1, T _S is the snapshot period, and the superscript H is the Hermitiam operator. 41. The method of claim 40, wherein the gain vector does not change the signal induced in the reference antenna element in order to eliminate the phase difference between the signals induced in the antenna elements in the first snapshot, and the other antenna elements do not change. The gain vector is determined by applying a phase delay to a phase difference with an adjacent antenna element having a later phase, and is obtained by updating the gain vector from the previous snapshot from the second snapshot, in each snapshot. And updating and obtaining a Rayleigh quotient defined by the autocorrelation matrix and the gain vector to a maximum. 41. The method of claim 40, wherein the error vector synthesizing step comprises: a plurality of multiplication steps (1601) for multiplying each element of the current estimated maximum intrinsic value and the gain vector in turn; And a plurality of subtraction steps (1602) for sequentially subtracting each element of the gamma vector from the result output of the multiplication step (1601). 41. The method of claim 40, wherein the synthesis of maximum indifference comprises: a plurality of multiplication steps (1501) for multiplying each element of the gamma vector and each element of the complex conjugate of the gain vector in the current snapshot; And an addition step (1502) for adding and outputting all the result outputs of the multiplication step (1501). 41. The method of claim 40, wherein the adaptive gain synthesizing step comprises: a multiplication step (1701) for multiplying the complex conjugates of each element of the zeta vector and each element of the gain vector, which are the outputs of the matrix calculation approximation step; An addition step 1705 for adding all of the result outputs of the multiplication step 1701; A multiplication step (1702) for sequentially multiplying the complex conjugates of each element of the zeta vector and each element of the tracking direction vector; An addition step 1706 for adding up all the result outputs of the multiplication step 1702; A multiplication step (1703) for multiplying the complex conjugates of each element of said tracking direction vector and each element of a gain vector; An addition step 1707 for adding all of the result outputs of the multiplication step 1703; A multiplication step (1704) of multiplying each element of the tracking direction vector by its complex conjugate; An addition step 1708 for adding up all the result outputs of the multiplication step 1704; And an adaptive gain calculation step (1709) of calculating adaptive gain by inputting result outputs of the addition steps (1705, 1706, 1707, and 1708). 49. The method of claim 48, wherein the output of the adding step 1705 is A, the output of the adding step 1706 is B, the output of the adding step 1707 is C, and the adding step 1708 is performed. When the output is D, the adaptive gain calculating step 1709 calculates the adaptive gain ρ according to the following equation using the values of A, B, C, and D input for every snapshot. Signal processing method for adjusting the beam pattern to reduce the effects of interference and noise in the array antenna system, characterized in that. (Where E = B-Re [C]-D-Re [A], F = B-λ D, G = Re [A]-λ Re [C], λ is the maximum eigenvalue, ] Is the real part of the complex "·"). 42. The method of claim 41, wherein the matrix approximation step comprises: a multiplication step 1401 for multiplying each component of the received signal vector by the complex conjugate (y *) of the current output value; A multiplication step (1403) for multiplying each element of the gamma vector in the previous snapshot by the forgetting factor (f); A multiplication step (1408) for multiplying each element of the zetavector in the previous snapshot by the forgetting factor (f); A multiplication step (1410) for multiplying the output of the multiplication step (1408) with the adaptive gain (ρ) which is the output of the adaptive gain synthesis step; An addition step (1404) for adding the output of the multiplication step (1410) and the output of the multiplication step (1403), respectively; An addition step 1402 for adding the output of the addition step 1404 and the output of the multiplication step 1401; A multiplication step (1405) for multiplying the complex conjugate of each element of the signal vector and each element of the tracking direction vector in turn; An addition step 1411 for adding all of the multiplication step outputs; The received signal vector at the output of the addition step 1411 A multiplication step 1406 for multiplying each element of; A multiplication step (1409) for multiplying the output of the multiplication step (1408) with the scalar (β); And an addition step 1407 for adding the output of the multiplication step 1409 and the output of the multiplication step 1406, respectively, wherein the output of the addition step 1402 is the gamma vector, and the addition step ( A signal processing room characterized by calculating the output of 1407 as a zeta vector. A signal processing method for providing a gain vector for every snapshot in order to reduce the effects of interference and noise in an array antenna system, the method comprising: (a) a first step of setting an initial gain vector by using a signal induced in each antenna element; ; (b) Signal vector received through array antenna A second step of updating the autocorrelation matrix by substituting the following equation; (only, Is the autocorrelation matrix of the J + 1th snapshot, Is the autocorrelation matrix of the Jth snapshot, f is the forgetting factor taking values between 0 and 1, T _S is the snapshot period, and the superscript H is the Hermitiam operator. (c) a third step of obtaining an adaptive gain ρ (k) using the following equation; (d) Tracking direction vector using the following formula Calculating a fourth step; (But initial Set to, the error vector And scalar β (k) are determined as (e) Gain Vector of Current Snapshot Is the gain vector of the previous snapshot according to A fifth step of updating; And (Where k is the time index representing the snapshot, ρ (k) is the adaptive gain in the kth snapshot, Is the tracking direction vector, Is normalized to have a size of 1 for each iteration) (f) a new signal vector for each snapshot And a sixth step of repeating the second to fifth steps each time.