CN111147103B - Airspace real-time self-adaptive anti-interference system aiming at short-time pulse interference - Google Patents

Airspace real-time self-adaptive anti-interference system aiming at short-time pulse interference Download PDF

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CN111147103B
CN111147103B CN201911276024.9A CN201911276024A CN111147103B CN 111147103 B CN111147103 B CN 111147103B CN 201911276024 A CN201911276024 A CN 201911276024A CN 111147103 B CN111147103 B CN 111147103B
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CN111147103A (en
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马晓峰
王铭
盛卫星
张仁李
韩玉兵
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Nanjing University of Science and Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/69—Spread spectrum techniques
    • H04B1/7163—Spread spectrum techniques using impulse radio
    • H04B1/719—Interference-related aspects
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/023—Interference mitigation, e.g. reducing or avoiding non-intentional interference with other HF-transmitters, base station transmitters for mobile communication or other radar systems, e.g. using electro-magnetic interference [EMI] reduction techniques
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/285—Receivers
    • G01S7/292—Extracting wanted echo-signals
    • G01S7/2923—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods
    • G01S7/2928—Random or non-synchronous interference pulse cancellers
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/35—Details of non-pulse systems
    • G01S7/352—Receivers
    • G01S7/354—Extracting wanted echo-signals
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/36—Means for anti-jamming, e.g. ECCM, i.e. electronic counter-counter measures
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming

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Abstract

The invention discloses a space domain real-time self-adaptive anti-interference system aiming at short-time pulse interference, which comprises a baseband data cache module, a digital beam forming module, a blocking interference space-time estimation module and a null/static beam forming module, wherein the baseband data cache module is used for blocking baseband data according to time T and caching the baseband data according to blocks; the block interference space-time estimation module carries out pulse interference detection on the block baseband data according to blocks, and determines the interference quantity and angle of each block baseband data; the null/static beam forming module is used for calculating a weight coefficient of a null/static beam; and the digital beam forming module carries out beam forming processing according to the weight coefficient corresponding to the blocked baseband data to obtain the anti-interference digital beam. The invention carries out block processing on the data, and the interference characteristic in the data block is directly applied to the block data processing, thereby eliminating the pulse interference and realizing the inhibition of short-time strong pulse interference.

Description

Airspace real-time self-adaptive anti-interference system aiming at short-time pulse interference
Technical Field
The invention belongs to a digital array antenna airspace self-adaptive anti-interference technology, in particular to an airspace real-time self-adaptive anti-interference system aiming at short-time pulse interference.
Background
In communication and radar systems, pulse interference is generated by various reasons, namely interference caused by objective natural environments such as lightning and coexistence of multiple systems and active interference generated by human beings. The pulse interference is typical time domain interference, has the characteristics of burstiness, short duration, large interference power and the like, and can cause serious errors of communication system data at the moment, so that the radar system cannot perform effective target detection and tracking. The conventional adaptive beam forming algorithm is effective in resisting continuous interference in a space domain and has poor effect of inhibiting pulse interference.
Disclosure of Invention
The invention aims to provide a space domain real-time self-adaptive anti-interference system aiming at short-time pulse interference, and solves the problem that the pulse interference with the characteristics of burstiness, short duration, large interference power and the like is difficult to capture and inhibit in real time.
The technical solution for realizing the invention is as follows: a space domain real-time self-adaptive anti-interference system aiming at short-time pulse interference comprises a baseband data caching module, a digital beam forming module, a blocking interference space-time estimation module and a null/static beam forming module, wherein the baseband data caching module is used for blocking baseband data according to time T and caching the baseband data according to blocks; the block interference space-time estimation module is used for blocking the baseband data according to time T and detecting pulse interference according to blocks to determine the interference quantity and angle of each block of baseband data; the null/static beam forming module is used for calculating the weight coefficient of the null beam according to the interference quantity and the interference angle when the block interference space-time estimation module detects the interference, otherwise, directly calculating the weight coefficient of the static beam; the digital beam forming module carries out beam forming processing according to the weight coefficient corresponding to the blocked baseband data to obtain an anti-interference digital beam, wherein T is>TI+TQ，TICalculating time, T, for a block interference space-time estimation moduleQTime is calculated for the corresponding null/static beamforming module.
Preferably, the total duration of the data buffered by the baseband data buffer module is 2T.
Preferably, the block interference space-time estimation module performs impulse interference detection on a block-by-block basis, and the specific method for determining the interference angle of each block of baseband data is as follows: selecting a reference array element, and performing cross-correlation processing on each array element and the reference array element to obtain a virtual array element;
and constructing a space-time DOA matrix according to the virtual array elements, and acquiring angle information eigenvalues and eigenvectors contained in the space-time DOA matrix, namely the data angles of each baseband.
Preferably, the specific step of determining the interference angle of each piece of baseband data is as follows:
selecting any 3 antenna units which are not in the same straight line as a guide array element, and respectively receiving data x by the guide array elementj(t) receiving data x with each array elementi(t) performing a correlation calculation, i being 1, 2.. D, j being 1,2,3, the calculation formula being:
Figure BDA0002315581650000021
wherein x isi(t) represents the output of the ith array element;
Figure BDA0002315581650000022
denotes the kth incoming wave sk(t) an autocorrelation function at time τ; a isikAs a guiding vector a for the kth source down arraykThe ith element of (1);
the vector expression is:
r1(τ)＝A·g(τ) r2(τ)＝A·Φ1·g(τ) r3(τ)＝A·Φ2·g(τ)
rj(τ)＝[r1j(τ),…rij(τ)…rDj(τ)]T j＝1,2,3
Figure BDA0002315581650000023
Figure BDA0002315581650000024
Figure BDA0002315581650000025
wherein A ═ a1,＝aK]Is an array flow pattern matrix. diag {. denotes a diagonal matrix, and the elements in parentheses are diagonal elements on the diagonal matrix;
for the correlation vector rj(τ) (j ═ 1,2,3) L samples are taken, and the space-time correlation matrix is obtained as follows:
Figure BDA0002315581650000026
in the formula, TsIs the sampling interval;
the vector expression of the correlation matrix is as follows:
R1(τ)＝A·G R2(τ)＝A·Φ1·G R3(τ)＝A·Φ2·G
Figure BDA0002315581650000027
calculating a cross-correlation matrix:
RT1＝E[R1·R1 H]＝E[AG·GHAH]＝E[ARGGAH]
RT2＝E[R2·R1 H]＝E[AΦ1·GGH·AH]＝E[AΦ1·RGGAH]
RT3＝E[R3·R1 H]＝E[AΦ2·GGH·AH]＝E[AΦ2·RGGAH]
to matrix RT1The characteristic decomposition is carried out to obtain:
RT1＝VsΛsVs H
wherein, VsIs a DXD dimension matrix; lambdasIs a D-order diagonal matrix whose diagonal elements contain K large eigenvalues λiSelecting the eigenvectors v corresponding to the K large eigenvaluesi(i-1, 2) construction of RT1Pseudo-inverse of (2):
Figure BDA0002315581650000031
constructing a spatio-temporal DOA matrix DTi(i ═ 1,2), specifically:
DTi＝RTi+1·RT1 #
for matrix DTi(i-1, 2) performing a feature decomposition, wherein the feature value and the feature vector are phi respectively1And A1,Φ2And A2To phi1，Φ2Performing matching processing by A1、A2A permutation matrix can be obtained:
Figure BDA0002315581650000032
adjusting phi according to the matrix coordinate of the element with the maximum absolute value of each column in P2The positions of the elements on the middle diagonal are such that phi1、Φ2Matching with each other, calculating the cosine u of the incoming wave directionk，vk：
Figure BDA0002315581650000033
arg[·]Represents the argument principal value (cx)i,cyi) The coordinates of the ith array element are represented, and the incoming wave angle of the kth signal obtained from the direction cosine is as follows:
Figure BDA0002315581650000034
Figure BDA0002315581650000035
compared with the prior art, the invention has the following remarkable advantages: 1) the invention carries out block processing on the data, and the interference characteristic in the data block is directly applied to the block data processing, thereby eliminating the pulse interference and realizing the inhibition of short-time strong pulse interference; 2) the invention adopts a modularized realization framework, and can directly utilize the existing algorithm to directly complete the corresponding function; 3) the invention has better angle measurement precision and stability performance and lower computation amount, and can effectively improve the dry-to-noise ratio of the baseband data block through rapid interference detection, thereby carrying out detection and inhibition of pulse interference in a shorter time and improving the anti-pulse interference transmission performance of a communication system.
The present invention is described in further detail below with reference to the attached drawings.
Drawings
FIG. 1 is a flow chart of a system implementation of the present invention.
Fig. 2 is a schematic diagram of a triangular grid hexagonal array structure with D-19 adopted by the embodiment.
Fig. 3 is a block diagram of a baseband data down-conversion implementation employed by the embodiment.
Fig. 4 is a schematic diagram of a two-dimensional uniform area array.
Detailed Description
A space domain real-time self-adaptive anti-interference system aiming at short-time pulse interference comprises a baseband data caching module, a digital beam forming module, a blocking interference space-time estimation module and a null/static beam forming module, wherein the baseband data caching module is used for blocking baseband data according to time T and caching the baseband data according to blocks; the block interference space-time estimation module carries out pulse interference detection on the block baseband data according to blocks, and determines the interference quantity and angle of each block baseband data; the null/static beam forming module is used for calculating the weight coefficient of the null beam according to the interference quantity and the interference angle when the block interference space-time estimation module detects the interference, otherwise, directly calculating the weight coefficient of the static beam; the digital beam forming module carries out beam forming processing according to the weight coefficient corresponding to the blocked baseband data to obtain an anti-interference digital beam, wherein T is>TI+TQ，TICalculating time, T, for a block interference space-time estimation moduleQTime is calculated for the corresponding null/static beamforming module.
In a further embodiment, the total duration of the data buffered by the baseband data buffer module is 2T.
The block interference space-time estimation module performs pulse interference detection on a block basis, and the specific method for determining the interference angle of each block of baseband data comprises the following steps: selecting a reference array element, and performing cross-correlation processing on each array element and the reference array element to obtain a virtual array element;
constructing a space-time DOA matrix according to the virtual array elements, and acquiring angle information characteristic values and characteristic vectors contained in the space-time DOA matrix, namely the data angle of each baseband;
through selecting a reference array element, performing cross-correlation processing on each array element and the reference array element to obtain a virtual array element; the space-time DOA matrix is constructed, the angle information characteristic value and the characteristic vector contained in the space-time DOA matrix are obtained, and then the multi-target angle is obtained through calculation, and the method specifically comprises the following steps:
suppose that the far field has K incoherent narrow-band sources s1(t),…sk(t),…sK(t) the incident angle is D array element planar arrays, and the pitch angle of the kth information source is thetakIn an azimuth of
Figure BDA0002315581650000041
Unit directional vector is uk＝(uk,vk,wk)，
Figure BDA0002315581650000051
wk＝cosθk(ii) a Consider the element antenna as an omni-directional antenna, k0For wavenumbers, i.e., 2 π/λ, the array output vector is expressed as follows:
x(t)＝As(t)+n(t)
wherein s ═ s1(t),s2(t),…sK(t)]TFor receiving a signal vector, n ═ n1(t),n2(t),…nD(t)]TIs a noise vector, ni(t) represents the space-time independent Gaussian noise on the ith array element, the mean value is 0, and the variance is sigma2；A＝[a1,…aK]Is an array flow pattern matrix, ak＝[a1k,a2k,…aDk]TRepresenting the directionality vector of the kth array under the source,
Figure BDA0002315581650000052
is akThe ith element of (c), (c) and (d)i,cyi) The coordinates of the ith array element are expressed, j is an imaginary number unit and satisfies
Figure BDA0002315581650000053
x(t)＝[x1(t),x2(t),…xD(t)]T，xi(t) represents the output of the ith array element, and the specific form is as follows:
Figure BDA0002315581650000054
i＝1,2,…,D，k＝1,2,...,K；(·)Tindicating transposition.
Selecting any three antenna units which are not in the same straight line as a guide array element, and respectively receiving data x by the guide array elementj(t) receiving data x with each array elementi(t) performing a correlation calculation, i-1, 2.. Q, j-1, 2, 3:
Figure BDA0002315581650000055
wherein the content of the first and second substances,
Figure BDA0002315581650000056
the autocorrelation function of the kth incoming wave is shown, and the signals are independent.
The vector of the formula is represented as:
r1(τ)＝A·g(τ) r2(τ)＝A·Φ1·g(τ) r3(τ)＝A·Φ2·g(τ) (2)
rj(τ)＝[r1j(τ),…rij(τ)…rDj(τ)]T j＝1,2,3 (3)
Figure BDA0002315581650000057
Figure BDA0002315581650000058
Figure BDA0002315581650000059
for the correlation vector rj(τ) (j ═ 1,2,3) L samples are taken, and the space-time correlation matrix is obtained as follows:
Figure BDA00023155816500000510
in the formula, TsIs the sampling interval;
the vector expression of the correlation matrix is as follows:
R1(τ)＝A·G R2(τ)＝A·Φ1·G R3(τ)＝A·Φ2·G (8)
Figure BDA0002315581650000061
calculating a cross-correlation matrix:
RT1＝E[R1·R1 H]＝E[AG·GHAH]＝E[ARGGAH] (10)
RT2＝E[R2·R1 H]＝E[AΦ1·GGH·AH]＝E[AΦ1·RGGAH] (11)
RT3＝E[R3·R1 H]＝E[AΦ2·GGH·AH]＝E[AΦ2·RGGAH] (12)
to matrix RT1The characteristic decomposition is carried out to obtain:
RT1＝VsΛsVs H (13)
wherein, VsIs a DXD dimension matrix; lambdasIs a D-order diagonal matrix whose diagonal elements contain K large eigenvalues λiSelecting the eigenvectors v corresponding to the K large eigenvaluesi(i-1, 2) construction of RT1Pseudo-inverse of (2):
Figure BDA0002315581650000062
constructing a spatio-temporal DOA matrix DTi(i ═ 1,2), specifically:
DTi＝RTi+1·RT1 # (15)
for matrix DTi(i-1, 2) performing a feature decomposition, wherein the feature value and the feature vector are phi respectively1And A1,Φ2And A2To phi1，Φ2Performing matching processing by A1、A2A permutation matrix can be obtained:
Figure BDA0002315581650000063
adjusting phi according to the matrix coordinate of the element with the maximum absolute value of each column in P2The positions of the elements on the middle diagonal are such that phi1、Φ2Matching with each other, calculating the cosine u of the incoming wave directionk，vk：
Figure BDA0002315581650000064
arg[·]Represents the argument principal value (cx)i,cyi) The coordinates of the ith array element are represented, and the incoming wave angle of the kth signal obtained from the direction cosine is as follows:
Figure BDA0002315581650000071
the null/static beam forming module is used for calculating the weight coefficient of the null beam according to the interference quantity and the interference angle when the block interference space-time estimation module detects the interference, otherwise, the implementation method for directly calculating the weight coefficient of the static beam specifically comprises the following steps:
the two-dimensional area array can be seen as a combination of M transverse one-dimensional uniform linear arrays and N longitudinal one-dimensional uniform linear arrays, as shown in fig. 4.
The array factor expression of the two-dimensional uniform area array is as follows:
Figure BDA0002315581650000072
omega in the formulam，nRepresenting the weighting coefficients of the mth row and nth column of the array,
Figure BDA0002315581650000073
dxand dyRespectively, the array element spacing in two directions. Array factor F (u, v) and weight coefficient ωm，nThe relationship of two-dimensional discrete Fourier transform is satisfied, and fast Fourier transform can be used for accelerated calculation. In addition, the triangular grid structure array can be converted into a rectangular grid array with equal row-column array element spacing through coordinate 'stretching' and 'rotation' transformation. The array after the 'expansion' and 'rotation' processing can be optimized and calculated according to the optimization method of the rectangular grid array. Two-dimensional FFT and two-dimensional inverse fast Fourier change can be utilized to accelerate conversion between array element weight coefficients and array factors in the beam forming iteration process. Wherein, the formula of the directional diagram obtained by using two-dimensional IFFT to calculate and shape is given in the above formula, and the expression of obtaining the weight coefficient by using two-dimensional IFFT and the array factor F (u, v) is given in the following formula:
Figure BDA0002315581650000074
the number of sampling points is J multiplied by K, and J > M, K > N are required. Except that the M multiplied by N points are effective, the rest values in the calculated weight coefficients fall outside the aperture of the array antenna, and can be removed in a subsequent processing mode.
In addition, during the process of such alternate conversion, correction of the directional diagram, generation of interference null, and the like need to be considered at the same time, and these can be conveniently realized by adding a subset projection model.
The directional diagram correction projection method comprises the following steps:
the array factor expected by each iteration can be obtained by correcting the directional diagram obtained by the previous iteration optimization. The array factor obtained by the fast Fourier transform processing of the weight coefficient needs to be corrected to obtain the array factor of the next iteration approximation, thereby defining the array factor correction projection subset PpattComprises the following steps:
Figure BDA0002315581650000081
in the formula (I), the compound is shown in the specification,
Figure BDA0002315581650000082
f (u, v) is the array factor obtained in the current iteration, omegaMDenotes a shaped region, ML、MUThe lower and upper bounds of the gain allowed by the desired array factor shaping region, respectively. The expected array factor sidelobe is set to be 0 so as to simplify the operation amount of each iteration, because the lowest sidelobe level of the sidelobe area is influenced by various factors, an optimal value cannot be simply determined.
The matrix factor correction of the shaped area does not consider the phase characteristic and only considers the adjustment of the amplitude information. This is because in smart antenna systems we only relate to the corrected array antenna power pattern and therefore we do not have to be concerned with the phase characteristics of the array antenna pattern.
The projection method for the generation of interference null comprises the following steps:
defining an interference subspace orthogonal vector projection set PJ⊥The definition is as follows:
PJ⊥:Z＝(I-C(CHC)-1CH) (22)
in the formula, I represents an identity matrix, C represents a matrix composed of interference-oriented vectors, the dimension of the matrix is MN × L, and L represents the number of interferences, that is:
C＝[a(uJ1,vJ1),a(uJ2,vJ2),…a(uJL,vJL)] (23)
after the weight coefficient w is subjected to interference subspace orthogonal projection, an antenna directional diagram can generate deeper null in the interference direction, and the deeper null is applied to an expression of the weight coefficient of the array factor F (u, v) to carry out iteration of the next period.
The method has the space domain self-adaptive suppression capability of the burst pulse interference, and is suitable for various types of broadband and narrowband interference suppression.
The working process of the airspace real-time self-adaptive anti-interference system aiming at the short-time pulse interference mainly comprises the following steps:
and D array element baseband data are cached in a blocking mode by adopting an FIFO memory, the baseband data of two blocks are cached in total, and each baseband data block is sequentially marked, wherein the marks are replaced by 0 and 1. If the baseband data rate is fsIf the total duration of the two blocks of data is 2T, the storage depth of the FIFO memory is 2T × fs，T>TI+TQ. Wherein, TICalculating time, T, for a block interference space-time estimation moduleQTime is calculated for the null/static beamforming module.
The block interference space-time estimation module continuously uses the buffered block array element level original baseband data to perform interference detection and angle estimation in the whole coverage airspace. When the power of the interference source in the data block is smaller than a set threshold, giving an indication that the interference source does not exist in the data of the current block; and when the power of the interference source is greater than a set threshold, giving an interference existence indication, and simultaneously carrying out angle estimation on the interference source to give interference source information. The interference source information includes the interference number, the interference angle, and the label of the interfered data block.
And the null/static beam forming module immediately carries out corresponding processing according to the interference source information. Under the condition of no interference source, using the shaped beam obtained by optimization or directly calculating the static weight coefficient of the obtained spot beam; under the condition of an interference source, a zero-notch beamforming algorithm is utilized, and on the basis of a static weight coefficient, a weight coefficient of a zero-notch beam is obtained through fast optimization calculation according to interference source information. And storing the calculated weight coefficient, and storing the data block label corresponding to the weight coefficient.
Digital beam forming module according to fsAnd continuously reading out the cached baseband data, and performing beam forming by using the weight coefficient calculated by the null/static beam forming module. The baseband data block used by digital beam forming is matched and matched with the baseband data block corresponding to the weight coefficient calculation, that is, the data block labels of the baseband data and the weight coefficient are consistent. The ability of the module to form multiple digital beams simultaneously.
Example 1
In this embodiment, anti-interference processing is performed on a microwave signal received by a triangular grid hexagonal array antenna with an array element spacing of 0.6 λ and D ═ 19, as shown in fig. 2, the received microwave signal is subjected to amplification filtering, down-conversion, intermediate-frequency filtering, intermediate-frequency analog-to-digital conversion and digital down-conversion filtering processing of a radio frequency signal by a radio frequency circuit, an intermediate-frequency sampling circuit and a digital down-conversion circuit, so as to obtain a baseband signal.
In this embodiment, the center frequency of the intermediate frequency signal output by the radio frequency circuit is 5MHz, the sampling rate of analog-to-digital change is 80MHz, as shown in fig. 3, the intermediate frequency sampling and digital down-conversion circuit of each channel of 19 channels is provided, and the digital down-conversion NCO is 5 MHz; the decimation filter is implemented in two stages, including: after 3-level CIC filtering, 5-time extraction and 8-time extraction are finished, and finally the base band output data rate is fs＝2MHz。
As shown in fig. 1, in this embodiment, the airspace real-time adaptive anti-interference system for short-time pulse interference includes a baseband data caching module, a digital beam forming module, a blocking interference space-time estimation module, and a null/static beam forming module, where the baseband data caching module is configured to block baseband data according to time T and cache the baseband data according to blocks; the block interference space-time estimation module is used for carrying out block basebandPerforming pulse interference detection on the data block by block, and determining the interference quantity and angle of each block of baseband data; the null/static beam forming module is used for calculating the weight coefficient of the null beam according to the interference quantity and the interference angle when the block interference space-time estimation module detects the interference, otherwise, directly calculating the weight coefficient of the static beam; the digital beam forming module carries out beam forming processing according to the weight coefficient corresponding to the blocked baseband data to obtain an anti-interference digital beam, wherein T is>TI+TQ，TICalculating time, T, for a block interference space-time estimation moduleQTime is calculated for the corresponding null/static beamforming module.
A baseband data caching module: and caching two data blocks of the baseband data of 19 array elements according to the partitioned D, by adopting FIFO, and sequentially marking each baseband data block, wherein the marks are replaced by 0 and 1. Base band data rate of fs2MHz, the total time length of two blocks of data is 2T 2x16us, and the storage depth of FIFO memory is 2T x fs＝64。TI+TSIs slightly less than 16us, wherein TICalculating time, T, for a block interference space-time estimation moduleQTime is calculated for the null/static beamforming module.
The block interference space-time estimation module continuously uses the buffered block array element level original baseband data to perform pulse interference detection and angle estimation in the whole coverage airspace. When the power of the interference source in the data block is smaller than a set threshold, giving an indication that the interference source does not exist in the data of the current block; and when the power of the interference source is greater than a set threshold, giving an interference existence indication, and simultaneously carrying out angle estimation on the interference source to give interference source information. The interference source information includes the interference number, the interference angle, and the label of the interfered data block.
And the null/static beam forming module carries out corresponding processing according to the interference source information. Under the condition of no interference source, using the shaped beam obtained by optimization or directly calculating the static weight coefficient of the obtained spot beam; under the condition of an interference source, a zero-notch beamforming algorithm is utilized, and on the basis of a static weight coefficient, a weight coefficient of a zero-notch beam is obtained through fast optimization calculation according to interference source information. And storing the calculated weight coefficient, and storing the data block label corresponding to the weight coefficient.
And the digital beam forming module continuously reads out the cached baseband data according to the data rate of 2MHz and performs beam forming by using the weight coefficient calculated by the null/static beam forming module.
The digital beam forming module ensures that the baseband data and the data block of the weight coefficients are labeled identically.

Claims (4)

1. A space domain real-time self-adaptive anti-interference system aiming at short-time pulse interference is characterized by comprising a baseband data caching module, a digital beam forming module, a blocking interference space-time estimation module and a null/static beam forming module, wherein the baseband data caching module is used for blocking baseband data according to time T and caching the baseband data according to blocks; the block interference space-time estimation module is used for blocking the baseband data according to time T and detecting pulse interference according to blocks to determine the interference quantity and angle of each block of baseband data; the null/static beam forming module is used for calculating the weight coefficient of the null beam according to the interference quantity and the interference angle when the block interference space-time estimation module detects the interference, otherwise, directly calculating the weight coefficient of the static beam; the digital beam forming module carries out beam forming processing according to the weight coefficient corresponding to the partitioned baseband data to obtain an anti-interference digital beam, wherein T is more than TI+TQ，TICalculating time, T, for a block interference space-time estimation moduleQTime is calculated for the corresponding null/static beamforming module.
2. The spatial domain real-time adaptive interference rejection system for short-time pulse interference according to claim 1, wherein said baseband data buffer module buffers data for a total duration of 2T.
3. The spatial domain real-time adaptive anti-interference system for short-time pulse interference according to claim 1, wherein the block interference space-time estimation module performs pulse interference detection on a block-by-block basis, and the specific method for determining the interference angle of each block of baseband data comprises: selecting a reference array element, and performing cross-correlation processing on each array element and the reference array element to obtain a virtual array element;
and constructing a space-time DOA matrix according to the virtual array elements, and acquiring angle information eigenvalues and eigenvectors contained in the space-time DOA matrix, namely the data angles of each baseband.
4. The spatial domain real-time adaptive anti-jamming system for short-time pulse interference according to claim 3, wherein the specific step of determining the jamming angle of each block of baseband data is:
selecting any 3 antenna units which are not in the same straight line as a guide array element, and respectively receiving data x by the guide array elementj(t) receiving data x with each array elementi(t) performing a correlation calculation, i being 1, 2.. D, j being 1,2,3, the calculation formula being:
Figure FDA0003159035550000011
wherein x isi(t) represents the output of the ith array element;
Figure FDA0003159035550000012
denotes the kth incoming wave sk(t) an autocorrelation function at time τ; a isikAs a guiding vector a for the kth source down arraykD is an array element planar array, and K is the number of irrelevant narrow-band information sources;
the vector expression is:
r1(τ)＝A·g(τ) r2(τ)＝A·Φ1·g(τ) r3(τ)＝A·Φ2·g(τ)
rj(τ)＝[r1j(τ),…rij(τ)…rDj(τ)]T j＝1,2,3
Figure FDA0003159035550000021
Figure FDA0003159035550000022
Figure FDA0003159035550000023
wherein A ═ a1,…aK]For an array flow matrix, diag {. cndot } represents a diagonal matrix, and the elements in parentheses are diagonal elements on the diagonal matrix;
for the correlation vector rjTaking L samples, (τ), j is 1,2,3, and obtaining a space-time correlation matrix as follows:
Figure FDA0003159035550000024
in the formula, TsIs the sampling interval;
the vector expression of the correlation matrix is as follows:
R1(τ)＝A·G R2(τ)＝A·Φ1·G R3(τ)＝A·Φ2·G
Figure FDA0003159035550000025
calculating a cross-correlation matrix:
RT1＝E[R1·R1 H]＝E[AG·GHAH]＝E[ARGGAH]
RT2＝E[R2·R1 H]＝E[AΦ1·GGH·AH]＝E[AΦ1·RGGAH]
RT3＝E[R3·R1 H]＝E[AΦ2·GGH·AH]＝E[AΦ2·RGGAH]
to matrix RT1The characteristic decomposition is carried out to obtain:
RT1＝VsΛsVs H
wherein, VsIs a DXD dimension matrix; lambdasIs a D-order diagonal matrix whose diagonal elements contain K large eigenvalues λiSelecting the eigenvectors v corresponding to the K large eigenvaluesiI 1, 2.., D, construct RT1Pseudo-inverse of (2):
Figure FDA0003159035550000026
constructing a spatio-temporal DOA matrix DTi1,2, D, in particular:
DTi＝RTi+1·RT1 #
for matrix DTiD, performing a feature decomposition with an eigenvalue and an eigenvector of Φ, respectively1And A1,Φ2And A2To phi1，Φ2Performing matching processing by A1、A2A permutation matrix can be obtained:
Figure FDA0003159035550000031
adjusting phi according to the matrix coordinate of the element with the maximum absolute value of each column in P2The positions of the elements on the middle diagonal are such that phi1、Φ2Matching with each other, calculating the cosine u of the incoming wave directionk，vk：
Figure FDA0003159035550000032
arg[·]Represents the argument principal value (cx)i,cyi) Representing the coordinates of the ith array element, from which the kth signal is derived by direction cosineThe incoming wave angle is as follows:
Figure FDA0003159035550000033
Figure FDA0003159035550000034
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