CN114578311B - Clutter and interference resisting method and device for sky wave over-the-horizon radar characteristic domain - Google Patents

Clutter and interference resisting method and device for sky wave over-the-horizon radar characteristic domain Download PDF

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CN114578311B
CN114578311B CN202210495840.4A CN202210495840A CN114578311B CN 114578311 B CN114578311 B CN 114578311B CN 202210495840 A CN202210495840 A CN 202210495840A CN 114578311 B CN114578311 B CN 114578311B
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clutter
interference
data
sky
domain
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CN114578311A (en
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陈辉
刘维建
李槟槟
周必雷
张昭建
陈浩
王永良
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Air Force Early Warning Academy
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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
    • 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
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • 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
    • 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
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/414—Discriminating targets with respect to background clutter
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

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  • Computer Networks & Wireless Communication (AREA)
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Abstract

The invention provides a clutter and interference resisting method for sky wave over-the-horizon radar characteristic domain, which comprises a receiving channel, beam forming, pulse compression, a clutter interference space, beam transformation, beam data extraction, filtering and detection, wherein the receiving channel acquires multi-channel data in the embodiment; forming different azimuth beams by the beams; pulse compression performs time domain accumulation on each beam data; the clutter interference space finishes the extraction of the clutter interference space of all the beam data; the wave beam transformation obtains data of the same direction and different dimensions; extracting beam data to complete dimension measurement of clutter and interference data, and extracting required beam data; and the filtering and the detection realize Doppler filtering and target detection of the extracted data. The invention adopts the characteristic domain information to perform anti-interference processing, can inhibit clutter and multi-style interference to the maximum extent, and has stronger interference adaptability. The invention also provides a corresponding clutter and interference resisting device for the characteristic domain of the sky-wave over-the-horizon radar.

Description

Clutter and interference resisting method and device for sky wave over-the-horizon radar characteristic domain
Technical Field
The invention belongs to the technical field of radars, and particularly relates to a clutter and interference resisting method and device for a characteristic domain of an sky-wave over-the-horizon radar, which are suitable for a large-scale sky-wave over-the-horizon radar system and can also be used for various phased array radar systems such as ground information, guidance, battlefield monitoring and the like.
Background
The sky-wave over-the-horizon radar is used as a type in homeland air defense equipment, has high comprehensive cost performance and irreplaceable effect. As a large phased array, the array is characterized by multiple array elements and reconfigurability, and beam channels can be customized easily according to functional requirements, so that multiple functions are realized.
However, the traditional sky-wave over-the-horizon radar has low working frequency, narrow working bandwidth, large transmitting power and high noise floor, so that the traditional sky-wave over-the-horizon radar is easily influenced by various interferences and loses targets in the practical application process. The interference comprises passive interference such as ionosphere disturbance, lightning in an observation area, meteor entering the atmosphere and the like, and also comprises active interference such as a large number of civil amplitude modulation broadcasting stations, short-wave communication, intentional electronic interference and the like. The interference always causes interference to the observation task of the sky-wave over-the-horizon radar in the whole observation window, the existing anti-interference method is usually only effective to one or more types of interference, such as the radar and meteor are usually filtered by a time domain method, the radio station and communication interference is filtered by a frequency domain method, and the intentional interference suppression interference is usually filtered by a space domain method. However, in the actual processing process, interference often exists at the same time, and at this time, the single method has a great defect, and if a combined anti-interference method is adopted, the operation amount is greatly increased, and meanwhile, many anti-interference methods put forward high requirements on the system, and the system is often required to have feedbackability, certain intelligence of the algorithm, certain fault tolerance of the decision and the like. From the above analysis, it can be seen that in the practical application process of the sky-wave over-the-horizon radar, the interference is large, the sky-wave over-the-horizon radar is complex and changeable, the combination modes are various, and the problem can be solved comprehensively by using one method.
Disclosure of Invention
The present invention is directed to the above-mentioned deficiencies in the prior art. The method can realize the simultaneous inhibition of clutter and interference under the strong sea clutter by fully utilizing the wave beam domain data of the phased array radar and learning the characteristics, thereby realizing the effective detection of the target. Firstly, obtaining multi-array metadata by using a receiving channel of a phased array radar; obtaining channel data by using a beam forming technology; realizing time domain accumulation of data of each channel through pulse compression; performing characteristic decomposition on each channel data to obtain a clutter interference space; obtaining a plurality of beams in the same direction by a beam transformation algorithm of a clutter interference space; filtering the far-range Doppler channel of each beam data, and determining an output beam through the change of the noise level; and then the Doppler filter is used for filtering the output wave beam, and the detector is used for effective detection. The method of the invention makes full use of the characteristic difference of multi-channel data, so that the radar can simultaneously inhibit various interferences and clutter, and the algorithm does not need to change the system structure, only needs to adjust the signal processing algorithm, and is convenient for engineering realization. The technology of the invention can be used for various large phased array radar systems, is simple to realize and has wide application prospect.
In order to achieve the above object, according to one aspect of the present invention, there is provided a method for clutter and interference resistance of a characteristic region of an sky-wave beyond visual range radar, comprising the following steps:
(1) obtaining multi-array metadata using a receive channel of a phased array radar
Figure 230095DEST_PATH_IMAGE001
Wherein
Figure 51289DEST_PATH_IMAGE002
Is the array element number;
(2) obtaining multi-channel data using beamforming techniques
Figure 86241DEST_PATH_IMAGE003
The calculation formula is as follows
Figure 856751DEST_PATH_IMAGE004
Wherein the weighting matrix
Figure 482905DEST_PATH_IMAGE005
Is that
Figure 593992DEST_PATH_IMAGE006
The dimension matrix is a matrix of dimensions,
Figure 432635DEST_PATH_IMAGE007
the number of the channels is the number of the channels,
Figure 526493DEST_PATH_IMAGE008
each column of (a) is a conventional directional beam weighting,
Figure 792389DEST_PATH_IMAGE009
representing taking conjugate transpose;
(3) implementation of multi-channel data by pulse compression
Figure 119334DEST_PATH_IMAGE010
Is accumulated in the time domain to obtain
Figure 558406DEST_PATH_IMAGE011
Data;
(4) performing characteristic decomposition on each channel data to obtain clutter interference space
Figure 37929DEST_PATH_IMAGE012
The calculation formula is as follows
Figure 474726DEST_PATH_IMAGE013
Wherein the content of the first and second substances,
Figure 774121DEST_PATH_IMAGE014
in the formula (I), the compound is shown in the specification,
Figure 203834DEST_PATH_IMAGE015
as a characteristic value
Figure 334601DEST_PATH_IMAGE016
The formed diagonal matrix has characteristic values arranged from large to small,
Figure 942300DEST_PATH_IMAGE017
for the corresponding feature vector, take
Figure 728990DEST_PATH_IMAGE018
In the formula (I), wherein,
Figure 447547DEST_PATH_IMAGE019
is a large eigenvalue number;
(5) obtaining a plurality of beams with the same direction by a beam transformation algorithm of a clutter interference space, wherein the calculation formula is as follows
Figure 150930DEST_PATH_IMAGE020
In the formula, a beam transformation matrix
Figure 929530DEST_PATH_IMAGE021
Has a dimension of
Figure 265834DEST_PATH_IMAGE022
Wherein the beamforming vector
Figure 788082DEST_PATH_IMAGE023
And is
Figure 831124DEST_PATH_IMAGE024
Fixed beam pointing in dimension
Figure 29893DEST_PATH_IMAGE025
The guide vector of (2);
(6) filtering only the far-range Doppler channel of each beam data, averaging after taking the absolute value of the filtered result, and obtaining the total value
Figure 791176DEST_PATH_IMAGE026
Value of
Figure 913853DEST_PATH_IMAGE027
Will this
Figure 76981DEST_PATH_IMAGE028
Value of
Figure 197384DEST_PATH_IMAGE029
And the conventional noise level
Figure 695230DEST_PATH_IMAGE030
Making a comparison, closest
Figure 559281DEST_PATH_IMAGE030
Number of values
Figure 576915DEST_PATH_IMAGE031
As output beam number, i.e. selection
Figure 930536DEST_PATH_IMAGE032
Then, the beam forming is performed to the beam domain data
Figure 666411DEST_PATH_IMAGE033
In the formula
Figure 317841DEST_PATH_IMAGE034
I.e. the determined output beam;
(7) and filtering the output wave beam by using a Doppler filter, and effectively detecting the filtered data by using a detector to obtain a target detection result.
In one embodiment of the present invention, in the weighting matrix in step (2), the column vector is phase weighted while adding amplitude weighting, and the weighting coefficient is a hamming window or a hamming window.
In an embodiment of the present invention, there are two ways to realize the time domain accumulation in step (3), which can be realized by time domain pulse compression or frequency domain pulse compression.
In one embodiment of the present invention, in the step (4), the
Figure 189982DEST_PATH_IMAGE035
The selection of (2) is obtained by calculating a statistical value when no interference exists for a long time.
In one embodiment of the present invention, in the step (4), the
Figure 917767DEST_PATH_IMAGE036
The selection of (2) is obtained by calculating large characteristic values by using AIC and MDL algorithms.
In one embodiment of the present invention, in the step (6), when filtering the far-range doppler channel, the filtering weight of each beam is the same, only channels within 5 of the doppler channel edge far from the center of the main clutter are taken, and chebyshev weights below-60 are required to be added.
In one embodiment of the present invention, when the doppler filter is used for filtering in step (7), the chebyshev weight below-60 needs to be added to ensure good doppler side lobe clutter suppression.
In one embodiment of the present invention, in the target detection in step (7), when the target is close to the main clutter region, the distance is selected to be equal to the CFAR (Constant False Alarm Rate) or the CFAR algorithm is selected to be larger.
In one embodiment of the present invention, in the target detection in step (7), when the target is far away from the main clutter region, the selection unit selects the CFAR average, CFAR small, or CFAR cross range doppler algorithm.
According to another aspect of the invention, an anti-clutter and anti-interference device for characteristic domains of sky-wave over-the-horizon radar is also provided: the system comprises at least one processor and a memory, wherein the at least one processor and the memory are connected through a data bus, and the memory stores instructions capable of being executed by the at least one processor, and the instructions are used for completing the clutter and interference resisting method for the characteristic domain of the sky-wave over-the-horizon radar after being executed by the processor.
Generally, compared with the prior art, the technical scheme of the invention has the following beneficial effects:
(1) due to the fact that the characteristic domain information is adopted for anti-interference processing, clutter and multi-pattern interference can be suppressed to the maximum extent, and the adaptability of the interference is high;
(2) the dimensionality of the characteristic domain adopts a characteristic learning mechanism, so that the target can be retained to the maximum extent, interference and clutter are suppressed, and the algorithm has self-adaptive adjustment capability;
(3) the method only relates to the signal processing flow, namely only a processing system and software need to be upgraded, other system structures are not changed, and the method has popularization and application values.
Drawings
FIG. 1 is a flow chart of a method for clutter and interference rejection of a characteristic domain of a sky-wave over-the-horizon radar in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in FIG. 1, the invention provides an anti-clutter and anti-interference method for a sky-wave over-the-horizon radar feature domain, an embodiment of the invention is composed of a receiving channel 1, a beam forming 2, a pulse compression 3, a clutter interference space 4, a beam transformation 5, a beam data extraction 6, a filtering and a detection 7, wherein the receiving channel 1 acquires multi-channel data; beam forming 2 forms beams in different azimuth angles; pulse compression 3 performs time domain accumulation on each beam data; the clutter interference space 4 completes clutter interference space extraction of all beam data; the wave beam transformation 5 obtains data of the same direction and different dimensions; extracting beam data 6 to complete dimension measurement of clutter and interference data, and extracting required beam data; the filtering and detection 7 enables doppler filtering and target detection of the extracted data.
Specifically, the clutter and interference resisting method for the sky wave over-the-horizon radar characteristic domain comprises the following technical steps:
(1) obtaining multi-array metadata using a receive channel of a phased array radar
Figure 937675DEST_PATH_IMAGE001
Wherein
Figure 143529DEST_PATH_IMAGE002
Is the array element number;
(2) obtaining multi-channel data using beamforming techniques
Figure 385023DEST_PATH_IMAGE003
The calculation formula is as follows
Figure 18130DEST_PATH_IMAGE004
Wherein the weighting matrix
Figure 463018DEST_PATH_IMAGE005
Is that
Figure 269300DEST_PATH_IMAGE006
The dimension matrix is a matrix of dimensions,
Figure 381612DEST_PATH_IMAGE007
the number of the channels is the number of the channels,
Figure 452466DEST_PATH_IMAGE008
each column of (a) is a conventional pointed-beam weighting,
Figure 384650DEST_PATH_IMAGE009
representing taking conjugate transpose;
in the weighting matrix in the step (2), amplitude weighting is added when the column vector carries out phase weighting; the weighting coefficients may be Hamming windows or may be Haining windows.
(3) Implementation of multi-channel data by pulse compression
Figure 932306DEST_PATH_IMAGE010
Is accumulated in the time domain to obtain
Figure 164704DEST_PATH_IMAGE011
Data;
the time domain accumulation in the step (3) has two realization ways, which can be realized by time domain pulse compression or frequency domain pulse compression;
(4) performing characteristic decomposition on each channel data to obtain clutter interference space
Figure 123301DEST_PATH_IMAGE012
The calculation formula is as follows
Figure 808361DEST_PATH_IMAGE013
Wherein the content of the first and second substances,
Figure 159708DEST_PATH_IMAGE014
in the formula (I), the compound is shown in the specification,
Figure 981033DEST_PATH_IMAGE015
as a characteristic value
Figure 189160DEST_PATH_IMAGE016
The formed diagonal matrix has characteristic values arranged from large to small,
Figure 345204DEST_PATH_IMAGE017
for the corresponding feature vector, take
Figure 969084DEST_PATH_IMAGE018
In the formula (I), wherein,
Figure 910495DEST_PATH_IMAGE019
is a large eigenvalue number;
in step (4)
Figure 227207DEST_PATH_IMAGE019
The selection of (2) is obtained by calculating a statistical value during long-time interference-free, and can also be obtained by calculating a large characteristic value by using AIC and MDL algorithms.
(5) Obtaining a plurality of beams with the same direction by a beam transformation algorithm of a clutter interference space, wherein the calculation formula is as follows
Figure 418016DEST_PATH_IMAGE020
In the formula, a beam transformation matrix
Figure 360434DEST_PATH_IMAGE021
Has a dimension of
Figure 156351DEST_PATH_IMAGE022
Wherein the beamforming vector
Figure 643964DEST_PATH_IMAGE023
And is
Figure 525333DEST_PATH_IMAGE024
Fixed beam pointing in dimension
Figure 553332DEST_PATH_IMAGE025
A steering vector of (a);
(6) filtering only the far-range Doppler channel of each beam data, averaging after taking the absolute value of the filtered result, and obtaining the total value
Figure 453023DEST_PATH_IMAGE026
Value of
Figure 377117DEST_PATH_IMAGE027
To make this
Figure 480202DEST_PATH_IMAGE028
Value of
Figure 515154DEST_PATH_IMAGE029
And the conventional noise level
Figure 816823DEST_PATH_IMAGE030
Making a comparison, closest
Figure 161085DEST_PATH_IMAGE030
Number of value
Figure 17046DEST_PATH_IMAGE031
As output beam number, i.e. selection
Figure 324530DEST_PATH_IMAGE032
Then, the beam forming is performed to the beam domain data
Figure 949547DEST_PATH_IMAGE033
In the formula
Figure 464711DEST_PATH_IMAGE034
I.e. the determined output beam;
when the far-range Doppler channels are filtered in the step (6), the filtering weight of each wave beam is the same, only channels within 5 of the Doppler channel edge far away from the center of the main clutter are taken, and Chebyshev weights below-60 are added;
(7) and filtering the output wave beam by using a Doppler filter, and effectively detecting the filtered data by using a detector to obtain a target detection result.
When the Doppler filter is used for filtering in the step (7), Chebyshev weights below-60 are added to ensure good Doppler sidelobe clutter suppression;
during target detection in the step (7), when a target approaches the main clutter area, selecting a distance average CFAR (constant False Alarm rate) or selecting a large CFAR algorithm; when the distance is far away from the main clutter area, the unit average CFAR, the small CFAR or the range-Doppler cross CFAR algorithm is selected.
The following detailed steps of the present invention are described in conjunction with the accompanying drawings and embodiments:
(1) obtaining multi-array metadata using a receive channel of a phased array radar
Figure 339126DEST_PATH_IMAGE001
Wherein
Figure 981460DEST_PATH_IMAGE002
Is the array element number;
in an embodiment, assuming there are 64 array elements receiving data, 128 pulses per array element, and 500 range bins per pulse, each array element
Figure 195403DEST_PATH_IMAGE037
Is that
Figure 632201DEST_PATH_IMAGE038
A 1-dimensional vector of elements.
(2) Obtaining multi-channel data using beamforming techniques
Figure 446442DEST_PATH_IMAGE003
The calculation formula is as follows
Figure 361308DEST_PATH_IMAGE004
Wherein the weighting matrix
Figure 960917DEST_PATH_IMAGE005
Is that
Figure 365353DEST_PATH_IMAGE006
The dimension matrix is a matrix of dimensions,
Figure 417623DEST_PATH_IMAGE007
the number of the channels is the number of the channels,
Figure 391307DEST_PATH_IMAGE008
each column of (a) is a conventional directional beam weighting,
Figure 579843DEST_PATH_IMAGE009
representing taking conjugate transpose;
in an embodiment of the present invention,
Figure 358443DEST_PATH_IMAGE039
for conventional beam weighting with pointing, assuming that 32 beams are formed,
Figure 898009DEST_PATH_IMAGE039
the dimension of the matrix is
Figure 216995DEST_PATH_IMAGE040
Then obtained
Figure 774884DEST_PATH_IMAGE041
The channel data is
Figure 724386DEST_PATH_IMAGE042
A 1-dimensional vector of elements.
(3) Implementation of multi-channel data by pulse compression
Figure 485668DEST_PATH_IMAGE010
Is accumulated in the time domain to obtain
Figure 811607DEST_PATH_IMAGE011
Data;
embodiment directly adopts pulse compression technology pair
Figure 224003DEST_PATH_IMAGE043
The multi-channel data is subjected to pulse compression, and the multi-channel data after pulse compression is
Figure 344406DEST_PATH_IMAGE044
Each channel data is also
Figure 61826DEST_PATH_IMAGE045
A 1-dimensional vector of elements.
(4) Performing characteristic decomposition on each channel data to obtain clutter interference space
Figure 175144DEST_PATH_IMAGE012
The calculation formula is as follows
Figure 192779DEST_PATH_IMAGE013
Wherein the content of the first and second substances,
Figure 749662DEST_PATH_IMAGE014
in the formula (I), the compound is shown in the specification,
Figure 751116DEST_PATH_IMAGE015
is a characteristic value
Figure 402546DEST_PATH_IMAGE016
The formed diagonal matrix has characteristic values arranged from large to small,
Figure 930480DEST_PATH_IMAGE017
for the corresponding feature vector, take
Figure 658264DEST_PATH_IMAGE018
In the formula (I), wherein,
Figure 412594DEST_PATH_IMAGE019
is a large eigenvalue number;
in an embodiment, a covariance matrix is formed for the multi-channel pulse compressed data with dimensions of
Figure 884026DEST_PATH_IMAGE046
Then, feature decomposition is performed, using the large number of feature values
Figure 876253DEST_PATH_IMAGE047
Constructing clutter and interference spaces
Figure 493048DEST_PATH_IMAGE048
Examples of the embodiments
Figure 203515DEST_PATH_IMAGE049
Then, then
Figure 9797DEST_PATH_IMAGE050
Has a dimension of
Figure 856530DEST_PATH_IMAGE051
。
(5) Obtaining a plurality of beams with the same direction by a beam transformation algorithm of a clutter interference space, wherein the calculation formula is as follows
Figure 926118DEST_PATH_IMAGE020
In the formula, a beam transformation matrix
Figure 107569DEST_PATH_IMAGE021
Has a dimension of
Figure 655225DEST_PATH_IMAGE022
Wherein the beamforming vector
Figure 622044DEST_PATH_IMAGE023
And is
Figure 596953DEST_PATH_IMAGE024
Fixed beam pointing in dimension
Figure 78750DEST_PATH_IMAGE025
A steering vector of (a);
in the examples, take
Figure 673505DEST_PATH_IMAGE052
There are 7 beam transformation matrices, respectively
Figure 494831DEST_PATH_IMAGE053
And 7 output vectors are obtained
Figure 375062DEST_PATH_IMAGE054
The dimension of each vector is
Figure 281838DEST_PATH_IMAGE055
。
(6) Filtering only the far-range Doppler channel of each beam data, averaging after taking the absolute value of the filtered result, and obtaining the total value
Figure 686144DEST_PATH_IMAGE026
Value of
Figure 158713DEST_PATH_IMAGE027
Will this
Figure 741004DEST_PATH_IMAGE028
Value of
Figure 135077DEST_PATH_IMAGE029
And the conventional noise level
Figure 562647DEST_PATH_IMAGE030
Making a comparison, closest
Figure 607832DEST_PATH_IMAGE030
Number of values
Figure 157762DEST_PATH_IMAGE031
As output beam number, i.e. selection
Figure 773551DEST_PATH_IMAGE032
Then, the beam forming is performed to the beam domain data
Figure 270392DEST_PATH_IMAGE033
In the formula
Figure 655237DEST_PATH_IMAGE034
I.e. the determined output beam;
in the embodiment, 7 vectors are directly paired
Figure 828598DEST_PATH_IMAGE056
Doppler filtering is carried out in a far area, absolute values of the filtered data are obtained and averaged to obtain
Figure 197262DEST_PATH_IMAGE057
These 7 values are compared to the conventional noise level
Figure 28952DEST_PATH_IMAGE058
Making a comparison, and selecting if the 5 th is the closest
Figure 533883DEST_PATH_IMAGE059
Is recycled and reused
Figure 363299DEST_PATH_IMAGE060
Obtaining a beam domain data
Figure 202947DEST_PATH_IMAGE061
It is also a one-dimensional vector and the dimension is
Figure 41590DEST_PATH_IMAGE062
。
(7) And filtering the output wave beam by using a Doppler filter, and effectively detecting the filtered data by using a detector to obtain a target detection result.
In the examples, the
Figure 463345DEST_PATH_IMAGE063
Are recombined into one
Figure 729241DEST_PATH_IMAGE064
And filtering by using a Doppler filter, detecting by using a detector, and finally obtaining a target detection result.
In addition, in the weighting matrix in step (2), the column vector may be phase weighted while amplitude weighting is added, and the weighting coefficient may be a hamming window, a chebyshev window, or the like. A haining window is used in the examples.
The time domain accumulation in the step (3) has two realization ways, which can be realized by time domain pulse compression or frequency domain pulse compression. Frequency domain pulse compression is used in the embodiments.
In the step (4)
Figure 806918DEST_PATH_IMAGE035
The selection of (2) is obtained by calculating a statistical value during long-time interference-free, and can also be obtained by calculating a large characteristic value by using AIC and MDL algorithms. In the embodiment, the statistical value without interference is adopted.
When the far-range Doppler channels are filtered in the step (6), the filtering weight of each wave beam is the same, only channels within 5 of the Doppler channel edge far away from the center of the main clutter are taken, and Chebyshev weights below-60 are required to be added. In the example, 3 edge channels are taken and the-70 dB weighting is carried out.
And (4) when the Doppler filter is used for filtering in the step (7), Chebyshev weights below-60 are added to ensure good Doppler sidelobe clutter suppression. In the example a-70 dB weighting is used.
When the target is detected in the step (7), the distance direction average CFAR or the large CFAR is selected when the target is close to the clutter area, and the unit average CFAR, the small CFAR or the cross-shaped distance Doppler CFAR is adopted for the other CFAR. In the embodiment, the former adopts a large selection algorithm, and the latter adopts a cross CFAR algorithm.
Furthermore, the invention also provides an anti-clutter and interference device for the characteristic domain of the sky wave over-the-horizon radar, which comprises the following steps: the system comprises at least one processor and a memory, wherein the at least one processor and the memory are connected through a data bus, and the memory stores instructions capable of being executed by the at least one processor, and the instructions are used for completing the clutter and interference resisting method for the characteristic domain of the sky-wave over-the-horizon radar after being executed by the processor.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (10)

1. A clutter and interference resisting method for sky wave over-the-horizon radar feature domain is characterized by comprising the following technical steps:
(1) obtaining multi-array metadata using a receive channel of a phased array radar
Figure 736431DEST_PATH_IMAGE001
Wherein
Figure 371681DEST_PATH_IMAGE002
Is the array element number;
(2) obtaining multi-channel data using beamforming techniques
Figure 620260DEST_PATH_IMAGE003
The calculation formula is as follows
Figure 484310DEST_PATH_IMAGE004
Wherein the weighting matrix
Figure 767524DEST_PATH_IMAGE005
Is that
Figure 308096DEST_PATH_IMAGE006
The dimension matrix is a matrix of dimensions,
Figure 840708DEST_PATH_IMAGE007
the number of the channels is the number of the channels,
Figure 508450DEST_PATH_IMAGE008
each column of (a) is a conventional directional beam weighting,
Figure 380591DEST_PATH_IMAGE009
representing taking conjugate transpose;
(3) implementation of multi-channel data by pulse compression
Figure 842796DEST_PATH_IMAGE010
Is accumulated in the time domain to obtain
Figure 315235DEST_PATH_IMAGE011
Data;
(4) performing characteristic decomposition on each channel data to obtain clutter interference space
Figure 317826DEST_PATH_IMAGE012
The calculation formula is as follows
Figure 310053DEST_PATH_IMAGE013
Wherein the content of the first and second substances,
Figure 208739DEST_PATH_IMAGE014
in the formula (I), the compound is shown in the specification,
Figure 653627DEST_PATH_IMAGE015
is a characteristic value
Figure 646859DEST_PATH_IMAGE016
The formed diagonal matrix has characteristic values arranged from large to small,
Figure 759172DEST_PATH_IMAGE017
for the corresponding feature vector, take
Figure 563180DEST_PATH_IMAGE018
In the formula (I), wherein,
Figure 760943DEST_PATH_IMAGE019
is a large eigenvalue number;
(5) obtaining a plurality of beams with the same direction by a beam transformation algorithm of a clutter interference space, wherein the calculation formula is as follows
Figure 105336DEST_PATH_IMAGE020
In the formula, a beam transformation matrix
Figure 321423DEST_PATH_IMAGE021
Has a dimension of
Figure 296332DEST_PATH_IMAGE022
Wherein the beamforming vector
Figure 715812DEST_PATH_IMAGE023
And is
Figure 332738DEST_PATH_IMAGE024
Fixed beam pointing in dimension
Figure 403331DEST_PATH_IMAGE025
A steering vector of (a);
(6) filtering only the far-range Doppler channel of each beam data, averaging after taking the absolute value of the filtered result, and obtaining the total value
Figure 814721DEST_PATH_IMAGE026
Value of
Figure 924760DEST_PATH_IMAGE027
Will this
Figure 610956DEST_PATH_IMAGE028
Value of
Figure 999038DEST_PATH_IMAGE029
And the conventional noise level
Figure 581329DEST_PATH_IMAGE030
Making a comparison, closest
Figure 975401DEST_PATH_IMAGE030
Number of values
Figure 917818DEST_PATH_IMAGE031
As output beam number, i.e. selection
Figure 448157DEST_PATH_IMAGE032
Then, the beam forming is performed to the beam domain data
Figure 201349DEST_PATH_IMAGE033
In the formula
Figure 82717DEST_PATH_IMAGE034
I.e. the determined output beam;
(7) and filtering the output wave beam by using a Doppler filter, and effectively detecting the filtered data by using a detector to obtain a target detection result.
2. The clutter and interference resisting method for sky-wave beyond visual range radar feature region according to claim 1, wherein the weighting matrix in step (2) is added with amplitude weighting when the column vector is weighted in phase, and the weighting coefficient is Hamming window or Hamming window.
3. The clutter and interference resisting method for sky-wave over-the-horizon radar feature domain according to claim 1 or 2, characterized in that the time domain accumulation in step (3) has two implementation ways, which can be realized by time domain pulse compression or frequency domain pulse compression.
4. The sky-wave beyond visual range radar feature domain clutter and interference resisting method according to claim 1 or 2, wherein in step (4), the method comprises
Figure 828825DEST_PATH_IMAGE035
The selection of (2) is obtained by calculating a statistical value when no interference exists for a long time.
5. The sky-wave beyond visual range radar feature domain clutter and interference resisting method according to claim 1 or 2, wherein in step (4), the method comprises
Figure 275987DEST_PATH_IMAGE035
The selection of (2) is obtained by calculating large characteristic values by using AIC and MDL algorithms.
6. The clutter and interference resisting method for sky-wave over-the-horizon radar feature domain according to claim 1, wherein in the step (6), when filtering the far doppler channel, the filtering weight of each beam is the same, only channels within 5 of the edge of the doppler channel far from the center of the main clutter are taken, and chebyshev weights below-60 are added.
7. The clutter and interference rejection method for sky-wave beyond-the-horizon radar feature domain according to claim 1 or 2, characterized in that when filtering with doppler filter in step (7), chebyshev's weight below-60 is added to ensure good doppler side lobe clutter rejection.
8. The clutter and interference resisting method for sky-wave beyond visual range radar feature domain according to claim 1 or 2, wherein in the step (7), when the target is detected and is close to the main clutter region, the distance is selected to be the average CFAR (Constant False Alarm Rate) or the large CFAR algorithm.
9. The sky-wave beyond visual range radar feature domain clutter and interference resisting method according to claim 1 or 2, wherein in the step (7), when the target is far away from the main clutter region, the selecting unit selects the average CFAR, the small CFAR or the range-doppler cross CFAR algorithm.
10. The utility model provides an sky wave beyond visual range radar characteristic field clutter rejection and interference killing device which characterized in that:
comprising at least one processor and a memory, said at least one processor and memory being connected by a data bus, said memory storing instructions executable by said at least one processor, said instructions upon execution by said processor, for performing the sky-wave beyond-the-horizon radar signature domain clutter and interference rejection method of any one of claims 1 to 9.
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