CN111241470B - Beam synthesis method and device based on self-adaptive null widening algorithm - Google Patents
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/015—Arrangements for jamming, spoofing or other methods of denial of service of such systems
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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Abstract
The application is applicable to the technical field of navigation, and provides a beam synthesis method and a device based on a self-adaptive null widening algorithm, wherein the method comprises the following steps: constructing an initial covariance matrix for a circular array signal acquired by a circular array; according to the arrangement information and the interference disturbance parameters of the circular array, calculating a zero notch widening algorithm expansion matrix of the circular array signal based on a Laplacian algorithm; obtaining a covariance matrix after the circular array signal correction according to the initial covariance matrix and the null widening algorithm expansion matrix based on the Laplace algorithm; substituting the covariance matrix corrected by the circular array signal into a multi-level wiener filter, and calculating a self-adaptive weight; and carrying out wave beam synthesis on the circular array signal according to the self-adaptive weight. The application can realize the widening of anti-interference nulls without estimating interference, can effectively reduce the calculated amount and improve the beam synthesis efficiency.
Description
Technical Field
The application belongs to the technical field of navigation, and particularly relates to a beam synthesis method and device based on a self-adaptive null widening algorithm.
Background
Global satellite navigation systems (global navigation satellite system, GNSS) are widely used because of their high navigation accuracy and lack of error accumulation over time. However, GNSS signals are very vulnerable to strong interference signal suppression because they arrive at the receiver at a power 20dB lower than the base noise.
At present, an array antenna is usually adopted at a receiver end in engineering, and adaptive nulling is generated upwards by space-time adaptive processing (STAP) on strong interference to realize anti-interference on GNSS signals. The traditional algorithm based on covariance matrix tapered null broadening is only suitable for linear arrays, interference is estimated for the circular arrays to obtain directional information, and the interference is estimated to relate to high-order matrix spatial spectrum analysis, so that the calculated amount is too large, and the high dynamic performance of the anti-interference algorithm is seriously affected.
Disclosure of Invention
In view of the above, the embodiment of the application provides a beam synthesis method and a device based on an adaptive null widening algorithm, so as to solve the problem of overlarge calculated amount of the adaptive null algorithm based on a circular array in the prior art.
A first aspect of an embodiment of the present application provides a beam forming method based on an adaptive null widening algorithm, including:
constructing an initial covariance matrix for a circular array signal acquired by a circular array;
according to the arrangement information and the interference disturbance parameters of the circular array, calculating a zero notch widening algorithm expansion matrix of the circular array signal based on a Laplacian algorithm;
obtaining a covariance matrix after the circular array signal correction according to the initial covariance matrix and the null widening algorithm expansion matrix based on the Laplace algorithm;
substituting the covariance matrix corrected by the circular array signal into a multi-level wiener filter, and calculating a self-adaptive weight;
and carrying out wave beam synthesis on the circular array signal according to the self-adaptive weight.
A second aspect of an embodiment of the present application provides a beam forming apparatus based on an adaptive null widening algorithm, including:
the initial matrix creation module is used for constructing an initial covariance matrix for the circular array signals acquired by the circular array;
the expansion matrix creation module is used for calculating a null widening algorithm expansion matrix of the circular array signal based on the Laplace algorithm according to the arrangement information of the circular array and the interference disturbance parameters;
the matrix correction module is used for obtaining the covariance matrix after the circular array signal correction according to the initial covariance matrix and the zero notch widening algorithm expansion matrix based on the Laplace algorithm;
the weight calculation module is used for substituting the covariance matrix corrected by the circular array signal into a multi-level wiener filter to calculate an adaptive weight;
and the beam synthesis module is used for carrying out beam synthesis on the circular array signal according to the self-adaptive weight.
A third aspect of the embodiments of the present application provides a terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of a beam forming method based on an adaptive nulling broadening algorithm as described above when the computer program is executed.
A fourth aspect of the embodiments of the present application provides a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of a beam forming method based on an adaptive nulling broadening algorithm as described above.
Compared with the prior art, the embodiment of the application has the beneficial effects that: firstly, constructing an initial covariance matrix for a circular array signal acquired by a circular array; according to the arrangement information and the interference disturbance parameters of the circular array, calculating a zero notch widening algorithm expansion matrix of the circular array signal based on a Laplacian algorithm; then, according to the initial covariance matrix and the zero notch widening algorithm expansion matrix based on the Laplace algorithm, obtaining a covariance matrix after the circular array signal correction; substituting the covariance matrix corrected by the circular array signal into a multi-level wiener filter, and calculating a self-adaptive weight; and finally, carrying out wave beam synthesis on the circular array signal according to the self-adaptive weight. According to the method, the covariance matrix of the circular array signal is updated by creating the extension matrix, the widening of anti-interference nulls can be achieved without estimating interference, the calculated amount can be effectively reduced, the self-adaptive weight is calculated according to the updated covariance matrix and the multistage wiener filter, and therefore the calculated amount can be further reduced, and the beam synthesis efficiency is improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a beam forming method based on an adaptive null widening algorithm according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an implementation flow of S102 in FIG. 1 according to an embodiment of the present application;
FIG. 3 is a schematic diagram of an implementation flow of S105 in FIG. 1 according to an embodiment of the present application;
fig. 4 is a diagram illustrating a circular array arrangement according to an embodiment of the present application;
FIG. 5 is a schematic diagram of null widening curves under two algorithms provided by an embodiment of the present application;
fig. 6 is a schematic structural diagram of a beam forming device based on an adaptive null widening algorithm according to an embodiment of the present application;
fig. 7 is a schematic diagram of a terminal device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
In order to illustrate the technical scheme of the application, the following description is made by specific examples.
In one embodiment, as shown in fig. 1, fig. 1 shows a flow of a beam forming method based on an adaptive null widening algorithm according to an embodiment of the present application, and the process is detailed as follows:
s101: and constructing an initial covariance matrix for the circular array signals acquired by the circular array.
In this embodiment, first, the antenna acquisition data of the circular array needs to be acquired, and then the antenna acquisition number is calculatedThe autocorrelation matrix of the data, i.e., the initial covariance matrix. The initial covariance matrix may be: r is R x ＝X(n)X(n) H, wherein ,Rx The initial covariance matrix is represented, and X (n) represents a data input matrix corresponding to the antenna acquisition data. The number of shots is set according to the requirement. The number of shots may be set to 128 in this embodiment.
S102: and calculating a zero notch widening algorithm expansion matrix of the circular array signal based on the Laplacian algorithm according to the arrangement information of the circular array and the interference disturbance parameters.
In this embodiment, as shown in fig. 4, fig. 4 shows a case of seven-array-element uniform circular array arrangement, where the array arrangement is a uniform circular array, and in this embodiment, a 7-array-element circular array is adopted, and arrangement information of the array can be determined according to signal parameters of the circular array.
In this embodiment, the disturbance parameter is the standard deviation of the disturbance angle change, and may be counted by the priori information. According to the embodiment, the Laplace null widening algorithm expansion matrix of the circular array is determined according to the interference disturbance parameters and the arrangement information of the circular array.
S103: and obtaining the covariance matrix after the circular array signal correction according to the initial covariance matrix and the null widening algorithm expansion matrix based on the Laplace algorithm.
In this embodiment, a matrix obtained by tapering the covariance matrix may be obtained according to the initial covariance matrix of the circular array signal and the null widening algorithm extension matrix based on the laplace algorithm.
S104: substituting the covariance matrix corrected by the circular array signal into a multi-level wiener filter, and calculating the self-adaptive weight.
In this embodiment, the multi-level wiener filter is a correlated subtracted multi-level wiener filter, and a relation between the multi-level wiener filter and the covariance matrix is established according to a weight calculation formula of the multi-level wiener filter and the covariance matrix of the circular array, so that the weight calculation formula of the multi-level wiener filter is optimized, and an adaptive weight is calculated according to the weight calculation formula of the multi-level wiener filter and the corrected covariance matrix.
The application realizes that the Laplace null widening algorithm is directly applied to the multistage wiener filter, thereby reducing the calculated amount.
S105: and carrying out wave beam synthesis on the circular array signal according to the self-adaptive weight.
In this embodiment, the anti-interference processing of the circular array signal can be completed according to the adaptive weight, so as to implement beam synthesis of the circular array signal.
As can be seen from the above embodiments, in this embodiment, an initial covariance matrix is first constructed for a circular array signal acquired by a circular array; according to the arrangement information and the interference disturbance parameters of the circular array, calculating a zero notch widening algorithm expansion matrix of the circular array signal based on a Laplacian algorithm; then, according to the initial covariance matrix and the zero notch widening algorithm expansion matrix based on the Laplace algorithm, obtaining a covariance matrix after the circular array signal correction; substituting the covariance matrix corrected by the circular array signal into a multi-level wiener filter, and calculating a self-adaptive weight; and finally, carrying out wave beam synthesis on the circular array signal according to the self-adaptive weight. According to the method, the covariance matrix of the circular array signal is updated by creating the extension matrix, the widening of anti-interference nulls can be achieved without estimating interference, the calculated amount can be effectively reduced, the self-adaptive weight is calculated according to the updated covariance matrix and the multistage wiener filter, and therefore the calculated amount can be further reduced, and the beam synthesis efficiency is improved.
In one embodiment, as shown in fig. 2, fig. 2 shows a specific implementation flow of S102 in fig. 1, and the procedure is detailed as follows:
s201: acquiring signal parameters of a circular array signal acquired by the circular array; and obtaining the arrangement information of the circular array according to the signal parameters of the circular array signals.
In this embodiment, the signal parameters include pitch angle, azimuth angle, wavelength, and the like of the circular array signal. Setting the pitch angle of the circular array signal received by the circular array as theta and the azimuth angle as thetaWave number of signal with wavelength lambdaThe vector is shown in formula (1):
wherein ,representing the beam vector.
Let M be the number of array elements, then the array arrangement of the uniform circular array without the circle center is shown as formula (2):
wherein m represents the array element sequence number, r m Representing the array arrangement of the mth array element.
In this embodiment, assuming that the radius of the circular array is d, the position vector of the m-th array element obtained by the formula (2) is shown as the formula (3):
P m ＝d[cosr m ,sinr m ] T (3)
in the formula (3), P m Representing the m-th element position vector.
The airspace guide vector of the circular array signal obtained by the formula (1) and the formula (3) is shown as the formula (4):
in this embodiment, the q-th interference signal is set in the high dynamic environment as shown in the following formula (5):
in the formula (5), θ q For the initial incoming pitch angle of the disturbance signal,for interfering signal initiationAzimuth angle is formed; Δθ q For the pitch angle variation amplitude of the interference signal, < >>Is the azimuth angle variation amplitude of the interference signal, and is subject to the mean value of 0 and the variance of 0Laplace distribution of (C); />Representing the interference signal to the pitch angle true value, < >>The true value of azimuth is for the interfering signal.
S202: and determining a maximum expansion angle according to the interference disturbance parameter.
S203: and determining a null widening algorithm expansion matrix of the circular array signal based on a Laplacian algorithm according to the arrangement information of the circular array, the maximum expansion angle and the signal parameters of the circular array signal.
In one embodiment, the null widening algorithm expansion matrix based on the laplace algorithm of the circular array signal is:
in the formula (6), the amino acid sequence of the compound,representing the element of the nth row and the nth column in the expansion matrix of the null-dip widening algorithm based on the Laplace algorithm, and xi max Represents the maximum expansion angle, r m Representing the arrangement information of the mth array element in the circular array, r n And representing the arrangement information of the nth array element in the circular array, wherein lambda represents the wavelength of a circular array signal, and d represents the radius of the circular array.
In the present embodimentIn the method, the power of satellite signals is far lower than the power of noise level, and the covariance matrix R of the circular array is obtained x Mainly governed by the interference and noise covariance matrix. Assuming that the receiver noise is zero in mean and varianceIs a gaussian white noise of (c). At this time, a Laplace algorithm average covariance matrix is constructed as shown in formula (7):
in the formula (7), the amino acid sequence of the compound,is the q-th interference power; />Is->Is a joint probability density function of (1); delta mn Is a Kronecker delta function, < >>(m, n) represents an mth row and an nth column element in the Laplace algorithm average covariance matrix.
Because of delta theta q ，Independent of each other, will->Performing first-order Taylor series expansion to obtain (8):
substituting formula (8) into formula (7) to obtain formula (9):
order theThe integral first term in equation (9) is shown as equation (10):
similarly, let theThe integral second term in equation (8) is shown as equation (11):
substituting formula (10) and formula (11) into (9) to obtain formula (12):
thereby obtaining the m-th row and n-th column elements of the nulling stretching expansion matrix of Laplace distribution as shown in formula (13):
will D mn ，F mn Substitution (13) is carried out to obtain a null widening expansion matrix meeting Laplace distribution, and the null widening expansion matrix is shown as a formula (14):
in the formula (14)
Since no reference is made to the specific disturbance direction, the maximum angle required to meet the expansion in motion is considered, and whenIn this case, equation (14) can be simplified to equation (15) according to the trigonometric function expansion:
in the formula (15), the corresponding zeta of the maximum expansion angle is satisfied max May be determined from a priori information. Thus, the null widening expansion matrix meeting Laplace distribution is obtained.
In one embodiment, the specific implementation flow of S103 in fig. 1 includes:
and solving Hadamard products of an initial covariance matrix of the circular array signal and a zero notch widening algorithm expansion matrix based on a Laplace algorithm to obtain a corrected covariance matrix.
In one embodiment, S104 in fig. 1 specifically includes:
by calculation:
obtaining the self-adaptive weight;
in formula (16), W CSA-MWF Representing the adaptive weight, h 0 Representing the initial weight of the desired signal, T D Representing a reduced rank matrix representing a set of matched filter weights;representing the corrected covariance matrix.
In this embodiment, the structure of the correlated subtracted multi-level wiener filter CSA-MWF is shown in fig. 1, which is consistent with that of a common multi-level wiener filter, and is also a generalized sidelobe canceller, the upper branch is a desired signal branch, the lower branch performs orthogonal decomposition on a desired signal steering vector to obtain interference and noise, and then performs subtraction on the two paths to realize cancellation of the interference. The CSA-MWF does not need to explicitly calculate the blocking matrix, is smaller in calculation amount compared with the GRS-MWF of the multistage wiener filter, and can wait for better performance under small snapshot. However, the covariance matrix of the input signal is not needed in the whole iteration process of the conventional CSA-MWF, so that the covariance matrix cannot be utilized for reconstruction to achieve the purpose of null widening. Therefore, equivalent processing is carried out on the CSA-MWF algorithm, and the relation between the self-adaptive weight obtained by the algorithm and the covariance matrix of the input data is established, so that the zero notch widening algorithm can be directly applied.
In this embodiment, the conventional CSA-MWF output weight is as shown in equation (17):
W CSA-MWF ＝h 0 -T D w d (17)
in the formula (17), h 0 Representing the initial weights of the desired signal, a distortion-free response multi-stage wiener filter is obtained if it is equal to the steering vector of the desired signal, where the specific direction will not be constrained, i.e. h, for simplicity of calculation 0 ＝δ mk ，δ mk ＝[1,0,…,0]；
In formula (17), w d Representing equivalent weights of the cancellation branches and satisfying the relation (18)
In the formula (18), T D ＝[h 1 ,h 2 ,…,h D ]； T D To reduce the rank matrix, a set of matched filter weights is represented, T D ＝[h 1 ,h 2 ,…,h D ]And (2) andwherein D is the total iteration times of the algorithm; h is a i Representing the i-th stage matched filter weights.
Because ofThen
In the formula (20), R x ＝E(x(n)x(n) H ) An autocorrelation matrix, i.e., a covariance matrix, of the data is acquired for the antenna.
Because ofSo there are:
then
Substituting the formula (23) and the formula (24) into the formula (18) to obtain:
substituting the formula (25) into the formula (17) to obtain another weight expression mode of the CSA-MWF algorithm:
substituting the covariance matrix corrected by the circular array signal into the formula (26) to obtain the CSA-MWF output weight value subjected to the zero notch widening by the Laplace algorithm
In one embodiment, fig. 3 illustrates a specific implementation flow of S105 in fig. 1, which includes:
s301: acquiring an input data matrix of the circular array signal;
s302: and multiplying the self-adaptive weight with the input data matrix of the circular array signal to complete the beam forming of the circular array signal.
In this embodiment, a matrix of input data, i.e., a matrix X (n) of antenna acquisition data, is provided.
As can be seen from the above embodiments, in this embodiment, the autocorrelation matrix is calculated by using the signals acquired by the array antennas, and then the expansion matrix is calculated according to the array arrangement information and the prior information of the interference disturbance parameters. And multiplying the expansion matrix with the signal autocorrelation matrix to obtain a matrix which is subjected to covariance matrix tapering. And substituting the new autocorrelation matrix into the optimized CSA-MWF to calculate the self-adaptive weight. And finally, completing the wave beam synthesis of the array signals according to the calculated self-adaptive weight, and realizing the self-adaptive null widening of the interference incoming direction.
The algorithm provided by the embodiment can realize the widening of the anti-interference null without estimating interference, and widens the application range on the premise of reducing the calculated amount. Meanwhile, the weight calculation mode of the CSA-MWF algorithm is re-optimized, the relation between the CSA-MWF algorithm and the covariance matrix of the input data is established, the Laplace null widening algorithm is directly applied to the multi-level wiener filter, and the calculated amount is reduced again. The embodiment combines the universality of the Laplace null widening algorithm and the characteristics of low calculated amount and small required snapshot number of the multistage wiener filter, and is a scheme very suitable for engineering. The method can be applied to various fields of satellite communication, electronic reconnaissance, navigation research application, electronic countermeasure (interference, anti-interference) and the like.
In one embodiment of the present application, the simulation effect evaluation process for the above method is as follows:
setting a simulation environment, wherein the signal is a B3 frequency band Beidou signal, the carrier-to-noise ratio is 44dB, the pitch angle is 50 degrees, and the azimuth angle is 10 degrees; the array is a 7-array element uniform circular array, and the radius is half wavelength; the interference is narrow-band interference with a dry-to-noise ratio of 69dB, the pitch angle is 30 degrees, and the azimuth angle is 200 degrees; number of shots 128. Comparing the anti-interference self-adaptive nulls generated by the common CSA-MWF algorithm with nulls processed by Laplace algorithm. The simulation results are shown in fig. 5. Curve 41 in fig. 5 shows a null-stretching curve under a normal WMF algorithm, and curve 42 in fig. 5 shows a null-stretching curve processed by the Laplace algorithm provided in this embodiment. Both algorithms can be seen to be accurate in interference to generate nulls, but the nulls are wider obviously after being processed by the Laplace algorithm, which shows that the nulling widening algorithm is effective.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present application.
In one embodiment, as shown in fig. 6, fig. 6 shows a structure of a beam forming apparatus 100 based on an adaptive null widening algorithm according to an embodiment of the present application, which includes:
an initial matrix creation module 110, configured to construct an initial covariance matrix for a circular array signal acquired by a circular array;
the expansion matrix creation module 120 is configured to calculate a null widening algorithm expansion matrix of the circular array signal based on a laplace algorithm according to the arrangement information of the circular array and the interference disturbance parameter;
the matrix correction module 130 is configured to obtain a covariance matrix after the circular array signal correction according to the initial covariance matrix and the null widening algorithm expansion matrix based on the laplace algorithm;
the weight calculation module 140 is configured to substitute the covariance matrix corrected by the circular array signal into a multi-level wiener filter, and calculate an adaptive weight;
and the beam synthesis module 150 is configured to perform beam synthesis on the circular array signal according to the adaptive weight.
In one embodiment, the expansion matrix creation module 120 in fig. 6 includes:
the arrangement information acquisition unit is used for acquiring signal parameters of the circular array signals acquired by the circular array; obtaining arrangement information of the circular array according to signal parameters of the circular array signals;
the expansion angle calculation unit is used for determining a maximum expansion angle according to the interference disturbance parameters;
the expansion matrix creation unit is used for determining a zero-dip widening algorithm expansion matrix of the circular array signal based on the Laplace algorithm according to the arrangement information of the circular array, the maximum expansion angle and the signal parameters of the circular array signal.
In one embodiment, the null widening algorithm expansion matrix based on the laplace algorithm of the circular array signal is:
wherein ,representing the element of the nth row and the nth column in the expansion matrix of the null-dip widening algorithm based on the Laplace algorithm, and xi max Represents the maximum expansion angle, r m Representing the arrangement information of the mth array element in the circular array, r n Representing the arrangement information of the nth array element in the circular array, lambda represents the wavelength of the circular array signal,d represents the radius of the circular array.
In one embodiment, the matrix modification module 130 in fig. 6 includes: and solving Hadamard products of the initial covariance matrix of the circular array signal and the null widening algorithm expansion matrix based on the Laplace algorithm to obtain a corrected covariance matrix.
In one embodiment, the weight calculation module 140 in fig. 6 includes:
by calculation:
obtaining the self-adaptive weight;
wherein ,WCSA-MWF Representing the adaptive weight, h 0 Representing the initial weight of the desired signal, T D Representing a reduced rank matrix,representing the corrected covariance matrix.
In one embodiment, the beam forming module 150 in fig. 6 includes:
an input data matrix acquisition unit, configured to acquire an input data matrix of the circular array signal;
and the beam synthesis unit is used for multiplying the self-adaptive weight with the input data matrix of the circular array signal to complete the beam synthesis of the circular array signal.
Fig. 7 is a schematic diagram of a terminal device according to an embodiment of the present application. As shown in fig. 7, the terminal device 700 of this embodiment includes: a processor 70, a memory 71, and a computer program 72 stored in the memory 71 and executable on the processor 70. The steps of the various method embodiments described above, such as steps 101 through 105 shown in fig. 1, are performed by the processor 70 when executing the computer program 72. Alternatively, the processor 70, when executing the computer program 72, performs the functions of the modules/units of the apparatus embodiments described above, such as the functions of the modules 110-150 shown in fig. 6.
The computer program 72 may be divided into one or more modules/units which are stored in the memory 71 and executed by the processor 70 to complete the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing the specified functions, which instruction segments are used to describe the execution of the computer program 72 in the terminal device 700.
The terminal device 700 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, etc. The terminal device may include, but is not limited to, a processor 70, a memory 71. It will be appreciated by those skilled in the art that fig. 7 is merely an example of a terminal device 700 and does not constitute a limitation of the terminal device 700, and may include more or less components than illustrated, or may combine certain components, or different components, e.g., the terminal device may further include an input-output device, a network access device, a bus, etc.
The processor 70 may be a central processing unit (Central Processing Unit, CPU), or may be another general purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), an off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 71 may be an internal storage unit of the terminal device 700, for example, a hard disk or a memory of the terminal device 700. The memory 71 may be an external storage device of the terminal device 700, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal device 700. Further, the memory 71 may also include both an internal storage unit and an external storage device of the terminal device 700. The memory 71 is used for storing the computer program as well as other programs and data required by the terminal device. The memory 71 may also be used for temporarily storing data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the apparatus/terminal device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. . Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (7)
1. The beam forming method based on the adaptive null widening algorithm is characterized by comprising the following steps:
constructing an initial covariance matrix for a circular array signal acquired by a circular array;
according to the arrangement information and the interference disturbance parameters of the circular array, calculating a zero notch widening algorithm expansion matrix of the circular array signal based on a Laplacian algorithm;
obtaining a covariance matrix after the circular array signal correction according to the initial covariance matrix and the null widening algorithm expansion matrix based on the Laplace algorithm;
substituting the covariance matrix corrected by the circular array signal into a multi-level wiener filter, and calculating a self-adaptive weight;
carrying out wave beam synthesis on the circular array signal according to the self-adaptive weight;
the method for calculating the zero notch widening algorithm expansion matrix of the circular array signal based on the Laplacian algorithm according to the arrangement information of the circular array and the interference disturbance parameters comprises the following steps:
acquiring signal parameters of a circular array signal acquired by the circular array, and acquiring arrangement information of the circular array according to the signal parameters of the circular array signal;
determining a maximum expansion angle according to the interference disturbance parameters;
determining a zero notch widening algorithm expansion matrix of the circular array signal based on a Laplacian algorithm according to the arrangement information of the circular array, the maximum expansion angle and the signal parameters of the circular array signal;
the zero notch widening algorithm expansion matrix based on the Laplace algorithm of the circular array signal is as follows:
wherein ,representing the element of the nth row and the nth column in the expansion matrix of the null-dip widening algorithm based on the Laplace algorithm, and xi max Represents the maximum expansion angle, r m Representing the arrangement information of the mth array element in the circular array, r n And representing the arrangement information of the nth array element in the circular array, wherein lambda represents the wavelength of a circular array signal, and d represents the radius of the circular array.
2. The beam forming method based on the adaptive null widening algorithm according to claim 1, wherein the obtaining the covariance matrix after the circular array signal correction according to the initial covariance matrix and the null widening algorithm expansion matrix based on the laplace algorithm comprises:
and solving Hadamard products of the initial covariance matrix of the circular array signal and the null widening algorithm expansion matrix based on the Laplace algorithm to obtain a corrected covariance matrix.
3. The beam forming method based on the adaptive null widening algorithm according to claim 1, wherein substituting the covariance matrix corrected by the circular array signal into a multi-stage wiener filter, and calculating the adaptive weight comprises:
by calculation:
obtaining the self-adaptive weight;
wherein ,WCSA-MWF Representing the adaptive weight, h 0 Representing the initial weight of the desired signal, T D Representing a reduced rank matrix,representing the corrected covariance matrix.
4. The beam forming method based on the adaptive null widening algorithm according to claim 1, wherein the beam forming the circular array signal according to the adaptive weight comprises:
acquiring an input data matrix of the circular array signal;
and multiplying the self-adaptive weight with the input data matrix of the circular array signal to complete the beam forming of the circular array signal.
5. A beam forming device based on an adaptive null widening algorithm, comprising:
the initial matrix creation module is used for constructing an initial covariance matrix for the circular array signals acquired by the circular array;
the expansion matrix creation module is used for calculating a null widening algorithm expansion matrix of the circular array signal based on the Laplace algorithm according to the arrangement information of the circular array and the interference disturbance parameters;
the matrix correction module is used for obtaining the covariance matrix after the circular array signal correction according to the initial covariance matrix and the zero notch widening algorithm expansion matrix based on the Laplace algorithm;
the weight calculation module is used for substituting the covariance matrix corrected by the circular array signal into a multi-level wiener filter to calculate an adaptive weight;
the beam synthesis module is used for carrying out beam synthesis on the circular array signal according to the self-adaptive weight;
the expansion matrix creation module includes:
the arrangement information acquisition unit is used for acquiring signal parameters of the circular array signals acquired by the circular array, and acquiring arrangement information of the circular array according to the signal parameters of the circular array signals;
the expansion angle calculation unit is used for determining a maximum expansion angle according to the interference disturbance parameters;
the expansion matrix creation unit is used for determining a zero-dip widening algorithm expansion matrix of the circular array signal based on the Laplace algorithm according to the arrangement information of the circular array, the maximum expansion angle and the signal parameters of the circular array signal;
the zero notch widening algorithm expansion matrix based on the Laplace algorithm of the circular array signal is as follows:
wherein ,representing the element of the nth row and the nth column in the expansion matrix of the null-dip widening algorithm based on the Laplace algorithm, and xi max Represents the maximum expansion angle, r m Representing the arrangement information of the mth array element in the circular array, r n And representing the arrangement information of the nth array element in the circular array, wherein lambda represents the wavelength of a circular array signal, and d represents the radius of the circular array.
6. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 4 when the computer program is executed.
7. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 4.
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