CN110967673A - Multi-domain joint main lobe interference resisting method - Google Patents

Multi-domain joint main lobe interference resisting method Download PDF

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CN110967673A
CN110967673A CN201911225402.0A CN201911225402A CN110967673A CN 110967673 A CN110967673 A CN 110967673A CN 201911225402 A CN201911225402 A CN 201911225402A CN 110967673 A CN110967673 A CN 110967673A
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陈辉
倪萌钰
王永良
周必雷
倪柳柳
唐瑭
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Air Force Early Warning Academy
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Abstract

The invention discloses a multi-domain joint main lobe interference resisting method. The method comprises the steps of firstly carrying out pulse compression processing on multi-channel data of the phased array radar, then dividing the multi-channel into three space processing domains and a time processing domain, carrying out interference cancellation processing on the four domains by adopting different methods, then carrying out constant false alarm detection on the data after the interference of the multi-domain is suppressed, then carrying out secondary detection on the result after the multi-domain detection to obtain real target information, and finally utilizing the target information to realize the measurement of the distance and the angle of the real target. The technology of the invention adopts a spatial and temporal multi-domain combined processing mode, thereby reducing the false alarm rate of target detection while reducing the detection threshold, and simultaneously solving the problem of target angle measurement under the condition of self-adaptive mainlobe distortion. The invention can be widely used for phased array radars, and has the characteristics of easy upgrading and reconstruction, convenient realization and popularization, and the like.

Description

Multi-domain joint main lobe interference resisting method
Technical Field
The invention relates to a multi-domain joint main lobe interference resisting method in the field of radar signal processing, which is suitable for a signal processing system of a phased array radar for resisting concomitant main lobe slice forwarding interference and can also be used in signal processing systems of various multi-channel ground information radars, guidance radars and the like.
Background
Phased array radar is used as a symbolic result in the field of modern radar, is widely applied to various fields of military and civil use, and has the characteristics of multiple channels, multiple beams and multiple functions compared with the traditional radar. Phased array radars have a congenital advantage in anti-sidelobe interference, especially in interference environments.
However, in modern war, besides sidelobe interference, main lobe interference technology is widely used, which faces a serious challenge for phased array radar that relies solely on spatial domain interference resistance. From the perspective of radar countermeasure, most of main lobe interference can be countered by several means, for example, main lobe suppression interference can adopt a frequency hopping technology, main lobe deception interference can adopt a waveform agility technology, main lobe self-defense interference can adopt an active/passive fusion technology, and the like to realize anti-interference. At present, one type of adjoint main lobe slice forwarding interference in main lobe interference is difficult to resist, and the adjoint main lobe slice forwarding interference is mainly characterized in that an interference waveform is a radar waveform forwarded in real time, and the forwarding time is generally 3-5us or even shorter. Therefore, the radar fails to adopt a frequency hopping technology, an active/passive fusion technology and a waveform agility anti-main lobe interference method, and no effective method for inhibiting the interference exists at present. More serious, for the phased array radar, if the spatial domain adaptive processing is directly adopted, because the main lobe interference is close to the target angle, the target loss is large while the main lobe interference is suppressed, and the target signal-to-noise ratio is low while the interference is suppressed, so that the target cannot be detected due to the fact that the target signal-to-noise ratio does not meet the detection condition. In addition, even if part of the target is detected after the spatial domain adaptive processing, the detected target cannot measure the angle because the main lobe is seriously distorted.
Disclosure of Invention
The present invention is directed to the above-mentioned deficiencies in the prior art. The method inhibits slice forwarding type interference in the main lobe through three space self-adaptive beam forming processing domains and a time processing domain respectively, further inhibits false alarm by utilizing a space domain and time domain multi-domain combined technology, extracts distance and angle parameters of a target, and further realizes detection and parameter measurement of a moving target under the background of the concomitant main lobe interference. Firstly, pulse compression processing is carried out on multi-channel data of the phased array radar; then dividing the multi-channel into three spatial processing domains and a time processing domain; then, the four domains are subjected to interference cancellation processing of different methods; then, performing constant false alarm detection on the data subjected to multi-domain interference suppression; secondly, performing secondary detection on the result of the multi-domain detection to obtain real target information; and finally, measuring the distance and the angle of the real target by utilizing the target information. Because a multi-domain combination technology is adopted in the processing process, the false alarm rate of target detection is reduced while the detection threshold is reduced, and the problem of target angle measurement under the condition of self-adaptive main lobe distortion is solved. The invention can be widely used for phased array radars, and has the characteristics of easy upgrading and reconstruction, convenient realization and popularization, and the like.
In order to achieve the above object, the present invention provides a multi-domain joint anti-mainlobe interference method, which comprises the following steps:
(1) performing pulse compression processing on multi-channel data of the phased array radar to obtain compressed multi-channel data;
(2) multi-domain division is carried out on multi-channel data, four domains are totally divided, the four domains comprise a space self-adaptive processing domain, a space row self-adaptive processing domain, a space column self-adaptive processing domain and a time conventional processing domain, and the data of the four domains are respectively XS，XR，XC，XT；
(3) Fully adaptive processing is performed on the spatial adaptive processing domain to form fully adaptive processing and channel data
Figure BSA0000196610790000021
Wherein the content of the first and second substances,
Figure BSA0000196610790000022
is the steering vector of the spatial adaptive processing domain, theta is the azimuth,
Figure BSA0000196610790000023
is a pitch angle;
(4) the self-adaptive processing field of the space line is processed according to the line to obtain two blocks of self-adaptive output data of the line
Figure BSA0000196610790000024
Wherein, XR1And XR2Is to convert the data XRIs divided into an upper block and a lower block,
Figure BSA0000196610790000025
RR1and RR2Are each XR1And XR2Of the autocovariance matrix of aR1(theta) and aR2(theta) is an azimuth guide vector corresponding to the upper and lower two-block array, and then the self-adaptive outputs of the rows are synthesized to form self-adaptive row and channel and row difference channel
YRΣ＝YR1+YR2，YRΔ＝YR1-YR2
Wherein, YRΣBeing the output of a row and a channel, YRΔIs the output of the row difference channel;
(5) the self-adaptive processing domain of the spatial column is processed according to the column to obtain two block column self-adaptive output data
Figure BSA0000196610790000026
Wherein, XC1And XC2Is to convert the data XCIs divided into a left block and a right block,
Figure BSA0000196610790000027
RC1and RC2Are each XC1And XC2The auto-covariance matrix of (a) is,
Figure BSA0000196610790000028
and
Figure BSA0000196610790000029
synthesizing the column self-adaptive outputs for the pitching guide vectors corresponding to the left and right two arrays to form self-adaptive column sum channels and column difference channels
YCΣ＝YC1+YC2，YCΔ＝YC1-YC2
Wherein, YCΣIs the output of the column and channel, YCΔIs the output of the column difference channel;
(6) performing conventional sum and difference channel formation on the time conventional processing domain to obtain a sum channel Y of the time domainTΣChannel Y with azimuth differenceΔ1Sum pitch difference channel YΔ2；
(7) Sum channel data Y for four fields respectivelyS、YRΣ、YCΣAnd YTΣCarrying out constant false alarm rate detection;
(8) performing fusion detection on the detection results of the four domains to determine the distance of a real target;
(9) carrying out joint angle measurement by utilizing a multi-domain sum-difference channel;
(10) and integrating the information of the target, and integrating the information such as the measured distance and angle and the like and then outputting the integrated information.
2. The multi-domain joint mainlobe interference resisting method according to claim 1, wherein the pulse compression processing in step (1) can be processed by using a time domain algorithm and a frequency domain algorithm.
3. The multi-domain joint mainlobe interference rejection method of claim 1, wherein the adaptive process in step (3) can use a least square criterion and a least mean square criterion to calculate the optimal weight.
4. The multi-domain joint main lobe interference resisting method according to claim 1, wherein the constant false alarm processing in step (7) may adopt algorithms such as unit average CFAR, large CFAR, small CFAR, and ordered CFAR.
5. The multi-domain joint mainlobe interference resisting method as claimed in claim 1, wherein the fusion detection in step (8) can adopt 3/4 detection or 4/4 detection according to the signal-to-noise ratio of the target.
6. The multi-domain joint mainlobe interference resisting method as claimed in claim 1, wherein Y is adopted in the joint angle measurement in step (9)T∑And YΔ1Carrying out azimuth measurement by adopting YTΣAnd YΔ2For pitch angle measurements, Y can also be usedC∑And YCΔCarrying out azimuth measurement by adopting YRΣAnd YRΔA pitch angle measurement is made.
The invention has the advantages that:
(1) because all the subarrays are selected in the spatial adaptive processing domain, the suppression performance of the adaptive processing on interference is the best, the loss of the target is relatively small, and the target can be detected only by reducing the detection threshold, so that the target processed in the spatial domain can be detected.
(2) The time domain processing carries out time domain elimination processing on the interference with large intensity to the maximum extent, thereby effectively inhibiting the main lobe interference of the areas, and ensuring that the target is not missed although loss is brought to the signal-to-noise ratio of the target.
(3) Although the spatial row adaptive processing domain and the spatial column adaptive processing domain only perform one-dimensional adaptive processing, the performance of the spatial row adaptive processing domain and the spatial column adaptive processing domain is poor than that of the spatial adaptive processing, a sum channel and a difference channel formed by the spatial row adaptive processing domain and the spatial column adaptive processing domain can realize angle measurement on a target, so that the angle measurement under the condition that no target information is output in a time domain channel is ensured.
(4) The target angle measurement adopts target information after multi-domain fusion, if the time domain has target output, the sum-difference ratio curve of the original system is not changed, the angle measurement precision is high, and the realization is easy.
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Fig. 1 is a block diagram of the structure of an embodiment of the present invention.
Referring to fig. 1, the embodiment of the present invention is composed of a pulse compression 1, a multi-domain division 2, a spatial adaptive processing domain 3, a spatial row adaptive processing domain 4, a spatial column adaptive processing domain 5, a temporal conventional processing domain 6, a constant false alarm processing 7, a multi-domain joint detection 8, a joint angle measurement 9, and a target information synthesis 10.
In the embodiment, subarray data of a radar antenna is processed by pulse compression 1; dividing the subarray data into four domains by multi-domain division 2, including: a space self-adaptive processing domain 3, a space row self-adaptive processing domain 4, a space column self-adaptive processing domain 5 and a time conventional processing domain 6; the space self-adaptive processing domain 3 carries out self-adaptive processing on all the sub-arrays; the space row self-adaptive processing domain 4 carries out self-adaptive processing on the subarrays according to rows and forms a row self-adaptive sum channel and a difference channel; the space array self-adaptive processing domain 5 carries out self-adaptive processing on the subarrays according to the array and forms a sum channel and a difference channel which are self-adaptive to the array; the time conventional processing domain 6 forms a conventional sum channel, an azimuth difference channel and a pitch difference channel; the constant false alarm processing 7 detects all the sum channel data; performing secondary detection on the target by multi-domain joint detection 8; the angle measurement 9 is combined to realize the angle measurement of the real target; finally, the target information integration 10 reports the integrated information of the target distance, angle, etc.
Detailed Description
The principle of implementing the invention is as follows: firstly, pulse compression processing is carried out on multi-channel data of the phased array radar; then dividing the multi-channel into three spatial processing domains and a time processing domain; then, the four domains are subjected to interference cancellation processing of different methods; then, performing constant false alarm detection on the data subjected to multi-domain interference suppression; secondly, performing secondary detection on the result of the multi-domain detection to obtain real target information; and finally, measuring the distance and the angle of the real target by utilizing the target information, and further detecting and measuring parameters of the moving target under the main lobe slice forwarding type interference background.
The phased array radar is assumed to be a planar array, M array elements are arranged in the row direction, N array elements are arranged in the column direction, the number of formed sub-arrays is K, and the distance gate number of each pulse is L. In the examples, M is 32, N is 16, K is 8, and L is 100. The following detailed steps of the present invention are described in conjunction with the accompanying drawings and embodiments:
(1) performing pulse compression processing on multi-channel data of the phased array radar to obtain compressed multi-channel data;
in the embodiment, each 8 × 8 array elements are combined into one sub-array, and 8 sub-array channels are required to be subjected to pulse compression in total.
The pulse compression 1 unit feeds these processed data into the multi-domain division 2 unit.
(2) Multi-domain division is carried out on multi-channel data, four domains are totally divided, the four domains comprise a space self-adaptive processing domain, a space row self-adaptive processing domain, a space column self-adaptive processing domain and a time conventional processing domain, and the data of the four domains are respectively XS，XR，XC，XT；
In the example, the 8 sub-arrays are divided into four domains: spatially adaptive processing of domain data to XSThe spatial row self-adaptive processing domain data is XRThe spatial column adaptive processing domain data is XCTime-regular processing domain data is XT. The four data are identical in the example, all having dimensions 8 x 100.
The multi-domain division 2 unit respectively sends corresponding data into a space self-adaptive processing domain 3, a space row self-adaptive processing domain 4, a space column self-adaptive processing domain 5 and a time routine processing domain 6.
(3) Fully adaptive processing is performed on the spatial adaptive processing domain to form fully adaptive processing and channel data
Figure BSA0000196610790000041
Wherein the content of the first and second substances,
Figure BSA0000196610790000042
is the steering vector of the spatial adaptive processing domain, theta is the azimuth,
Figure BSA0000196610790000043
is a pitch angle;
in the embodiment, a full-adaptive processing algorithm is adopted for XSProcessing to obtain output sum channel data YSThe dimension is 1 × 100.
And the data of the spatial adaptive processing domain 3 unit is output to a constant false alarm processing 7 unit.
(4) The self-adaptive processing field of the space line is processed according to the line to obtain two blocks of self-adaptive output data of the line
Figure BSA0000196610790000044
Wherein, XR1And XR2Is to convert the data XRIs divided into an upper block and a lower block,
Figure BSA0000196610790000045
RR1and RR2Are each XR1And XR2Of the autocovariance matrix of aR1(theta) and aR2(theta) is an azimuth guide vector corresponding to the upper and lower two-block array, and then the self-adaptive outputs of the rows are synthesized to form self-adaptive row and channel and row difference channel
YRΣ＝YR1+YR2，YRΔ＝YR1-YR2
Wherein, YRΣBeing the output of a row and a channel, YRΔIs the output of the row difference channel;
in the embodiment, data XRThe device is divided into an upper block and a lower block: xR1And XR2The dimensions of the two are 4 multiplied by 100, and then the two times of self-adaptive processing are carried out to obtain YR1And YR2Then, the sum and difference of the two data are processed to form a row-adaptive sum channel YRΣSum row adaptive difference channel YRΔAnd they have dimensions of 1 × 100.
And the data of the spatial line adaptive processing domain 4 unit is output to a constant false alarm processing 7 unit.
(5) The self-adaptive processing domain of the spatial column is processed according to the column to obtain two block column self-adaptive output data
Figure BSA0000196610790000051
Wherein, XC1And XC2Is to convert the data XCIs divided into a left block and a right block,
Figure BSA0000196610790000052
RC1and RC2Are each XC1And XC2The auto-covariance matrix of (a) is,
Figure BSA0000196610790000053
and
Figure BSA0000196610790000054
synthesizing the column self-adaptive outputs for the pitching guide vectors corresponding to the left and right two arrays to form self-adaptive column sum channels and column difference channels
YCΣ＝YC1+YC2，YCΔ＝YC1-YC2
Wherein, YCΣIs the output of the column and channel, YCΔIs the output of the column difference channel;
in the embodiment, data XCThe device is divided into a left block and a right block: xC1And XC2The dimensions of which are 4 x 100, and then the second column adaptive processing is carried out to obtain YC1And YC2Then, the sum and difference of the two data are processed to form a column-adaptive sum channel YCΣSum column adaptive difference channel YCΔAnd they have dimensions of 1 × 100.
The data of the spatial column adaptive processing domain 5 unit is output to a constant false alarm processing 7 unit.
(6) Performing conventional sum and difference channel formation on the time conventional processing domain to obtain a sum channel Y of the time domainTΣChannel Y with azimuth differenceΔ1Sum pitch difference channel YΔ2；
In the embodiment, data XTDividing the sum into four blocks, and directly summing to obtain a sum channel Y of a time domainTΣAnd the sum of the upper two blocks and the sum of the lower two blocks are subjected to difference to obtain a pitch difference channel YΔ2And the sum of the left two blocks and the sum of the right two blocks are subjected to difference to obtain an azimuth difference channel YΔ1The dimensions of the three conventional channels are all 1 × 100.
The data of the time regular processing domain 6 unit is output to the constant false alarm processing 7 unit.
(7) Sum channel data Y for four fields respectivelyS、YRΣ、YC∑And YT∑Carrying out constant false alarm rate detection;
in the embodiment, four sum channel data Y are processedS、YRΣ、YC∑And YT∑And (4) calculating the amplitude, and then adopting a unit average CFAR algorithm to detect the target.
And the constant false alarm processing unit 7 sends the detected result to the multi-domain joint detection unit 8.
(8) Performing fusion detection on the detection results of the four domains to determine the distance of a real target;
in the embodiment, the two-level threshold fusion detection is performed on the four sum channel detection results, the 3/4 criterion is adopted, and the real distance information of the target is extracted.
And the multi-domain joint detection 8 sends the detected target information to a joint angle measurement 9 unit.
(9) Carrying out joint angle measurement by utilizing a multi-domain sum-difference channel;
in an embodiment, Y is directly extracted according to the distance information of the targetTΣ、YΔ1And YΔ2Then angle measurement is carried out by adopting a method of comparing amplitudes and measuring angles, and Y is utilizedT∑And YΔ1Carrying out azimuth measurement by adopting YTΣAnd YΔ2A pitch angle measurement is made.
The joint angle measurement 9 unit sends the angle measurement information of the target to the target information integration 10 unit.
(10) And integrating the information of the target, and integrating the information such as the measured distance and angle and the like and then outputting the integrated information.
In an embodiment, the information to be integrated includes a target distance, an azimuth angle, and a pitch angle.
In addition, the pulse compression processing in step (1) may be processed by using a time domain algorithm and a frequency domain algorithm. In the embodiment, a frequency domain algorithm is adopted for processing.
The adaptive processing in step (3) may use a least square criterion and a least mean square criterion to calculate the optimal weights. The minimum variance criterion is employed in the embodiments.
In the step (7), the constant false alarm processing may adopt algorithms such as unit average CFAR, large CFAR, small CFAR and sequencing CFAR. The embodiment adopts a unit average CFAR algorithm.
The fusion detection in the step (8) can adopt 3/4 detection or 4/4 detection according to the signal-to-noise ratio of the target. The 3/4 criterion was used in the examples.
Y can be adopted in the combined angle measurement in the step (9)TΣAnd YΔ1Carrying out azimuth measurement by adopting YTΣAnd YΔ2For pitch angle measurements, Y can also be usedC∑And YCΔCarrying out azimuth measurement by adopting YRΣAnd YRΔA pitch angle measurement is made. The former scheme is adopted in the examples.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various changes or modifications within the scope of the appended claims.

Claims (6)

1. A multi-domain joint main lobe interference resisting method comprises the following technical steps:
(1) performing pulse compression processing on multi-channel data of the phased array radar to obtain compressed multi-channel data;
(2) multi-domain division is carried out on multi-channel data, four domains are totally divided, the four domains comprise a space self-adaptive processing domain, a space row self-adaptive processing domain, a space column self-adaptive processing domain and a time conventional processing domain, and the data of the four domains are respectively XS，XR，XC，XT；
(3) Fully adaptive processing is performed on the spatial adaptive processing domain to form fully adaptive processing and channel data
Figure FSA0000196610780000011
Wherein the content of the first and second substances,
Figure FSA0000196610780000012
is the steering vector of the spatial adaptive processing domain, theta is the azimuth,
Figure FSA0000196610780000013
is a pitch angle;
(4) the self-adaptive processing field of the space line is processed according to the line to obtain two blocks of self-adaptive output data of the line
Figure FSA0000196610780000014
Wherein, XR1And XR2Is to convert the data XRIs divided into an upper block and a lower block,
Figure FSA0000196610780000015
RR1and RR2Are each XR1And XR2Of the autocovariance matrix of aR1(theta) and aR2(theta) is an azimuth guide vector corresponding to the upper and lower two-block array, and then the self-adaptive outputs of the rows are synthesized to form self-adaptive row and channel and row difference channel
YR∑＝YR1+YR2，YRΔ＝YR1-YR2
Wherein, YR∑Being the output of a row and a channel, YRΔIs the output of the row difference channel;
(5) the self-adaptive processing domain of the spatial column is processed according to the column to obtain two block column self-adaptive output data
Figure FSA0000196610780000016
Wherein, XC1And XC2Is to convert the data XCIs divided into a left block and a right block,
Figure FSA0000196610780000017
RC1and RC2Are respectively asXC1And XC2The auto-covariance matrix of (a) is,
Figure FSA0000196610780000018
and
Figure FSA0000196610780000019
synthesizing the column self-adaptive outputs for the pitching guide vectors corresponding to the left and right two arrays to form self-adaptive column sum channels and column difference channels
YC∑＝YC1+YC2，YCΔ＝YC1-YC2
Wherein, YC∑Is the output of the column and channel, YCΔIs the output of the column difference channel;
(6) performing conventional sum and difference channel formation on the time conventional processing domain to obtain a sum channel Y of the time domainT∑Channel Y with azimuth differenceΔ1Sum pitch difference channel YΔ2；
(7) Sum channel data Y for four fields respectivelyS、YR∑、YC∑And YT∑Carrying out constant false alarm rate detection;
(8) performing fusion detection on the detection results of the four domains to determine the distance of a real target;
(9) carrying out joint angle measurement by utilizing a multi-domain sum-difference channel;
(10) and integrating the information of the target, and integrating the information such as the measured distance and angle and the like and then outputting the integrated information.
2. The multi-domain joint mainlobe interference resisting method according to claim 1, wherein the pulse compression processing in step (1) can be processed by using a time domain algorithm and a frequency domain algorithm.
3. The multi-domain joint mainlobe interference rejection method of claim 1, wherein the adaptive process in step (3) can use a least square criterion and a least mean square criterion to calculate the optimal weight.
4. The multi-domain joint main lobe interference resisting method according to claim 1, wherein the constant false alarm processing in step (7) may adopt algorithms such as unit average CFAR, large CFAR, small CFAR, and ordered CFAR.
5. The multi-domain joint mainlobe interference resisting method as claimed in claim 1, wherein the fusion detection in step (8) can adopt 3/4 detection or 4/4 detection according to the signal-to-noise ratio of the target.
6. The multi-domain joint mainlobe interference resisting method as claimed in claim 1, wherein Y is adopted in the joint angle measurement in step (9)T∑And YΔ1Carrying out azimuth measurement by adopting YT∑And YΔ2For pitch angle measurements, Y can also be usedC∑And YCΔCarrying out azimuth measurement by adopting YR∑And YRΔA pitch angle measurement is made.
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