CN117054976A - Method for eliminating strong sidelobe clutter of airborne multi-area array radar - Google Patents
Method for eliminating strong sidelobe clutter of airborne multi-area array radar Download PDFInfo
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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
- G01S7/36—Means for anti-jamming, e.g. ECCM, i.e. electronic counter-counter measures
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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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/933—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of aircraft or spacecraft
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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
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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
- G01S7/414—Discriminating targets with respect to background clutter
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Abstract
The invention belongs to the technical field of airborne distributed array signal processing, and particularly relates to an airborne multi-array radar strong sidelobe clutter rejection method; according to the layout of the multi-area array radar, the directional diagram of the multi-area array under the sine space is simulated when the multi-area array points at a large angle; then determining the relative positions of the strong side lobes and the main lobe and the range of the strong side lobes in a sine space; and finally, mapping the sine space position of the strong side lobe to a range Doppler position in a radar frequency spectrum, thereby removing the detected clutter false alarm. The method can rapidly and accurately estimate the position of the strong side lobe clutter in the radar spectrum, effectively eliminates the false alarm target caused by the strong side lobe clutter, and improves the target detection performance.
Description
Technical Field
The invention belongs to the technical field of airborne distributed array signal processing, and particularly relates to an airborne multi-array radar strong sidelobe clutter rejection method.
Background
The airborne multi-area array radar realizes the detection of an omnidirectional airspace by distributing a plurality of radar array planes around a fuselage. When the coherent combination is carried out on a plurality of radar array surfaces in the same plane, due to the influence of distributed layout, a directional diagram can generate serious side lobes and even grating lobes, so that side lobe clutter with high power is generated. The strong sidelobe clutter of the airborne radar can reduce the target detection performance or generate false alarms, and seriously affect the radar performance.
The existing organic active phased array radar realizes low sidelobe of the directional diagram mainly through array weighting, so that the sidelobe power is suppressed. The low side lobes commonly used at present comprise traditional taylor weights, chebyshev weights, optimization weights obtained by an optimization algorithm, and the like. On the other hand, the protection channel can be utilized to carry out side lobe hiding and eliminating side lobe clutter.
The existing sidelobe clutter suppression method mainly has the following problems: 1) Under a multi-face array radar layout, classical low side lobe weighting fails; 2) When the side lobe of the direction diagram is higher, the side lobe hiding of the protection channel is invalid, so that a false alarm is generated; 3) The low side lobe weight obtained through the intelligent optimization algorithm is limited by the influence of the phase shifter and the attenuator, the effect is limited in the actual engineering, and main lobe distortion is easily caused, so that the detection power and the angle measurement performance are influenced.
Disclosure of Invention
In view of the above, the invention provides a method for eliminating strong sidelobe clutter of an airborne multi-area array radar, which can rapidly and accurately estimate the position of the strong sidelobe clutter in radar frequency spectrum, effectively eliminates false alarm targets caused by the strong sidelobe clutter and improves target detection performance.
In order to achieve the technical purpose, the invention adopts the following specific technical scheme:
an airborne multi-array radar strong sidelobe clutter rejection method comprises the following steps:
s101: according to the array surface layout of the multi-surface array radar, calculating a directional diagram of the multi-surface array in a sine space at a preset angle;
s102: obtaining angle information of a strong side lobe in the directional diagram based on the directional diagram;
s103: based on the angle information, converting the strong side lobe into a spectrogram;
s104: removing the strong side lobe based on Doppler information and distance information of the Jiang Bangban in the spectrogram;
wherein: the 102 further comprises: obtaining the relative position between the strong side lobe and the main lobe;
when the preset angle in S101 is changed, the angle information is directly obtained based on the relative position and the changed preset angle.
Further, the method for calculating the pattern comprises the following steps:
according to the array structure of the multi-face array, calculating an array preset angle pattern F (u, v) under a sine space:
F(u,v)＝(a(u set ,v set )) H *a(u,v)
a (u, v) is a signal steering vector, expressed as:
wherein λ is the wavelength;
pos_array is the array plane coordinate of the multi-plane array;
u set ＝sin(phi set )*cos(theta set )；
v set ＝sin(theta set )；
phi set and theta set Respectively presetting azimuth angles and pitch angles for radar systems of the multi-area array;
u＝sin(phi)*cos(theta)；
v＝sin(theta)；
phi E [ -90,90] and theta E [ -90,90] are the azimuth and pitch angles, respectively, of the radar system.
Further, the method for obtaining the angle information and the relative position includes:
according to the pattern, in a sinusoidal space (u.ltoreq.u 0 )∩(v≤v 0 ) And (3) selecting each strong side lobe point, and calculating the sine difference value of each strong side lobe point relative to the preset angle:
wherein:respectively sine values corresponding to the nth strong sidelobes; deltau n And Deltav n Is the sine difference.
Further, the manner of obtaining the angle information of the strong sidelobes in the actual flight situation is as follows:
calculating strong sidelobe clutter direction under actual flight situation
Azimuth beam phi according to radar system 0 And elevation beam pointing theta 0 Calculating a corresponding sine value;
u 0 ＝sin(phi 0 )*cos(theta 0 )
v 0 ＝sin(theta 0 )
setting a clutter protection range Pr, and calculating sine values [ U ] corresponding to all strong side lobe boundary points side ，V side ]
[U side ,V side ]＝{[u 0 ±Δu n ±Pr,v 0 ±Δv n ±Pr],n＝1,2,...N}
Further, the method for converting the angle information of the strong side lobe under the actual flight situation into the spectrogram comprises the following steps:
calculating the radar system angle [ phi ] corresponding to the angle information of each group of strong side lobes side 、theta side ]
theta side ＝arcsin(V side )
phi side ＝arcsin(U side /cos(theta side ))
Radar is tied according to inertial navigation information of the carrier of the multi-area arrayAngle [ phi ] side 、theta side ]Conversion to geographic system Az_G_Side0, el_G_Side0]The method comprises the steps of carrying out a first treatment on the surface of the Setting a strong clutter pitch angle threshold El_max, and selecting a strong clutter boundary point:
[AZ_G,El_G]＝{[AZ_G_side0,El_G_side0]|El_G_side0＜El_max}
calculating the speed V_c of each strong clutter boundary point according to the three-way speed of the carrier:
V_c＝[V_North,V_East,V_Down]
*[cos(Az_G)*cos(El_G)；sin(Az_G)*cos(El_G)；-sin(El_G)]
wherein [ V_North, V_east, V_Down ] are the carrier North speed, east speed and earth speed respectively;
calculating the distance R_c of each strong clutter boundary point according to the height of the carrier, the radius of the earth and the geographic pitch angle El_G;
and according to the strong clutter distance R_c, the speed V_c and the radar working waveform parameters, calculating a distance gate Nr_c and a Doppler gate Nf_c corresponding to the strong clutter boundary point in the frequency spectrum.
Further, the method for eliminating the strong side lobe comprises the following steps:
according to the boundary points of the strong clutter, determining the protection range of the strong clutter:
Pr_Nr∈[Nr_c_min,Nr_c_max]
Pr_Nf∈[Nf_c_min,Nf_c_max]
and eliminating clutter false alarms in the protection range.
By adopting the technical scheme, the invention has the following beneficial effects:
(1) The method is suitable for any sidelobe clutter suppression problem caused by the sidelobe degradation of the directional diagram due to distributed layout, irregular layout, diluted layout and the like, and has the advantages of high accuracy in sidelobe clutter position estimation, small calculated amount and easiness in engineering realization.
(2) The method can not influence the main lobe performance of the directional diagram, can ensure the detection power and the angle measurement performance of the targets in the main lobe, and can be simultaneously suitable for estimating the main lobe clutter.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings may be obtained according to these drawings without inventive effort to a person of ordinary skill in the art.
FIG. 1 is a sinusoidal spatial pattern in an embodiment of the present invention;
fig. 2 is a diagram of a radar spectrum in an embodiment of the invention.
Detailed Description
Embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.
Other advantages and effects of the present disclosure will become readily apparent to those skilled in the art from the following disclosure, which describes embodiments of the present disclosure by way of specific examples. It will be apparent that the described embodiments are merely some, but not all embodiments of the present disclosure. The disclosure may be embodied or practiced in other different specific embodiments, and details within the subject specification may be modified or changed from various points of view and applications without departing from the spirit of the disclosure. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict. All other embodiments, which can be made by one of ordinary skill in the art without inventive effort, based on the embodiments in this disclosure are intended to be within the scope of this disclosure.
It is noted that various aspects of the embodiments are described below within the scope of the following claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the present disclosure, one skilled in the art will appreciate that one aspect described herein may be implemented independently of any other aspect, and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method practiced using any number of the aspects set forth herein. In addition, such apparatus may be implemented and/or such methods practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.
It should also be noted that the illustrations provided in the following embodiments merely illustrate the basic concepts of the disclosure by way of illustration, and only the components related to the disclosure are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
In addition, in the following description, specific details are provided in order to provide a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects may be practiced without these specific details.
In one embodiment of the invention, the method for eliminating the strong sidelobe clutter of the airborne multi-array radar comprises the following steps:
s101: according to the array surface layout of the multi-surface array radar, calculating a directional diagram of the multi-surface array in a sine space at a preset angle;
s102: obtaining angle information of a strong side lobe in the directional diagram based on the directional diagram;
s103: based on the angle information, converting the strong side lobe into a spectrogram;
s104: removing the strong side lobe based on Doppler information and distance information of the Jiang Bangban in the spectrogram;
wherein: the 102 further comprises: obtaining the relative position between the strong side lobe and the main lobe;
when the preset angle in S101 is changed, the angle information is directly obtained based on the relative position and the changed preset angle.
In this embodiment, the method for calculating the pattern includes:
according to the array structure of the multi-face array, calculating an array preset angle pattern F (u, v) under a sine space:
F(u,v)＝(a(u set ,v set )) H *a(u,v)
a (u, v) is a signal steering vector, expressed as:
wherein λ is the wavelength;
pos_array is the array plane coordinate of the multi-plane array;
u set ＝sin(phi set )*cos(theta set )；
v set ＝sin(theta set )；
phi set and theta set Respectively presetting azimuth angles and pitch angles for radar systems of the multi-area array;
u＝sin(phi)*cos(theta)；
v＝sin(theta)；
phi E [ -90,90] and theta E [ -90,90] are the azimuth and pitch angles, respectively, of the radar system.
In this embodiment, the method for obtaining the angle information and the relative position includes:
according to the pattern, in a sinusoidal space (u.ltoreq.u 0 )∩(v≤v 0 ) And (3) selecting each strong side lobe point, and calculating the sine difference value of each strong side lobe point relative to the preset angle:
wherein:respectively sine values corresponding to the nth strong sidelobes; deltau n And Deltav n Is the sine difference.
In this embodiment, the manner of obtaining the angle information of the strong sidelobes in the actual flight situation is as follows:
calculating strong sidelobe clutter direction under actual flight situation
Azimuth beam phi according to radar system 0 And elevation beam pointing theta 0 Calculating a corresponding sine value;
u 0 ＝sin(phi 0 )*cos(theta 0 )
v 0 ＝sin(theta 0 )
setting a clutter protection range Pr, and calculating sine values [ U ] corresponding to all strong side lobe boundary points side ，V side ]
[U side ,V side ]＝{[u 0 ±Δu n ±Pr,v 0 ±Δv n ±Pr],n＝1,2,...N}
In this embodiment, the method for converting the angle information of the strong sidelobes under the actual flight situation into the spectrogram includes:
calculating the radar system angle [ phi ] corresponding to the angle information of each group of strong side lobes side 、theta side ]
theta side ＝arcsin(V side )
phi side ＝arcsin(U side /cos(theta side ))
According to inertial navigation information of the carrier of the multi-area array, radar system angle [ phi ] side 、theta side ]Conversion to geographic system Az_G_Side0, el_G_Side0]The method comprises the steps of carrying out a first treatment on the surface of the Setting a strong clutter pitch angle threshold El_max, and selecting a strong clutter boundary point:
[AZ_G,El_G]＝{[AZ_G_side0,El_G_side0]|El_G_side0＜El_max}
calculating the speed V_c of each strong clutter boundary point according to the three-way speed of the carrier:
V_c＝[V_North,V_East,V_Down]
*[cos(Az_G)*cos(El_G)；sin(Az_G)*cos(El_G)；-sin(El_G)]
wherein [ V_North, V_east, V_Down ] are the carrier North speed, east speed and earth speed respectively;
calculating the distance R_c of each strong clutter boundary point according to the height of the carrier, the radius of the earth and the geographic pitch angle El_G;
and according to the strong clutter distance R_c, the speed V_c and the radar working waveform parameters, calculating a distance gate Nr_c and a Doppler gate Nf_c corresponding to the strong clutter boundary point in the frequency spectrum.
In this embodiment, the method for eliminating the strong side lobe includes:
according to the boundary points of the strong clutter, determining the protection range of the strong clutter:
Pr_Nr∈[Nr_c_min,Nr_c_max]
Pr_Nf∈[Nf_c_min,Nf_c_max]
and eliminating clutter false alarms in the protection range.
As a further explanation of the present invention,
according to the embodiment, firstly, according to the layout of the multi-area array radar, a directional diagram of the multi-area array under a sine space is simulated when the multi-area array points at a large angle; then determining the relative positions of the strong side lobes and the main lobe and the range of the strong side lobes in a sine space; and finally, mapping the sine space position of the strong side lobe to a range Doppler position in a radar frequency spectrum, thereby removing the detected clutter false alarm.
The method comprises the following specific steps:
(1) Calculating a multi-faceted array pattern
According to the array structure of the multi-face array, calculating an array large-angle directional diagram F (u, v) under the sine space:
F(u,v)＝(a(u max ,v max )) H *a(u,v)
a (u, v) is a signal steering vector, expressed as:
wherein lambda is wavelength, pos_array is array plane coordinate u of multi-surface array max ＝sin(phi max )*cos(theta max )，v max ＝sin(theta max )，phi max 、theta max The azimuth angle and the pitch angle of the maximum beam pointing of the radar system are respectively u=sin (phi) cos (theta), v=sin (theta), phi epsilon [ -90,90],theta∈[-90,90]The azimuth angle and the pitch angle of the radar system are respectively set.
Let phi max ＝60°、theta max =60° gives a sinusoidal spatial pattern with a large angle beam pointing downwards, as shown in fig. 1.
(2) Determining the relative position of strong side lobe and main lobe
According to the simulation result of the beam pointing direction diagram, in the sine space (u is not less than u 0 )∩(v≤v 0 ) Each strong sidelobe point is selected in the beam direction, and the sine difference value of the strong sidelobe points relative to the beam direction is calculated:
wherein the method comprises the steps ofAnd respectively sine values corresponding to the nth strong sidelobes.
(3) Calculating strong sidelobe clutter direction under actual flight situation
According to the azimuth and elevation beam direction phi of radar system 0 、theta 0 The corresponding sine value of the beam pointing direction is calculated.
u 0 ＝sin(phi 0 )*cos(theta 0 )
v 0 ＝sin(theta 0 )
Setting a clutter protection range Pr, and calculating sine values [ U ] corresponding to all strong side lobe boundary points side ，V side ]
[U side ,V side ]＝{[u 0 ±Δu n ±Pr,v 0 ±Δv n ±Pr],n＝1,2,...N}
As shown in fig. 1, each strong sidelobe corresponds to 4 clutter boundaries.
Calculating radar system azimuth [ phi ] corresponding to each group of strong sidelobe boundary points side 、theta side ]
theta side ＝arcsin(V side )
phi side ＝arcsin(U side /cos(theta side ))
According to inertial navigation information of the carrier, the radar system azimuth angle [ phi ] side 、theta side ]Conversion to geographic system Az_G_Side0, el_G_Side0]. Setting a strong clutter pitch angle threshold El_max, and selecting a strong clutter boundary point:
[AZ_G,El_G]＝{[AZ_G_side0,El_G_side0]|El_G_side0＜El_max}
(4) Calculating the position of a strong clutter boundary point in the radar spectrum
Calculating the speed V_c of each strong clutter boundary point according to the three-way speed of the carrier:
V_c＝[V_North,V_East,V_Down]
*[cos(Az_G)*cos(El_G)；sin(Az_G)*cos(El_G)；-sin(El_G)]
wherein [ V_North, V_east, V_Down ] are the carrier North speed, east speed, ground speed, respectively.
And calculating the distance R_c of each strong clutter boundary point according to the altitude of the carrier, the earth radius and the geographic pitch angle El_G.
And according to the strong clutter distance R_c, the speed V_c and the radar working waveform parameters, calculating a distance gate Nr_c and a Doppler gate Nf_c corresponding to the strong clutter boundary point in the frequency spectrum.
For a certain strong clutter block, determining the protection range of the strong clutter according to the boundary point of the clutter:
Pr_Nr∈[Nr_c_min,Nr_c_max]
Pr_Nf∈[Nf_c_min,Nf_c_max]
(5) Clutter rejection false alarm
After CFAR detection, false alarms belonging to the strong clutter boundary are rejected.
Further description:
(1) Calculating a multi-faceted array pattern
Let phi max ＝60°、theta max =60° gives a sinusoidal spatial pattern with a large angle beam pointing downwards, as shown in fig. 1.
(2) Determining the relative position of strong side lobe and main lobe
According to the simulation result of the beam pointing direction diagram, in the sine space (u is not less than u 0 )∩(v≤v 0 ) Each strong sidelobe point is selected in the beam direction, and the sine difference value of the strong sidelobe points relative to the beam direction is calculated:
Δu n ＝0.0646 0.0688 0.1252...
Δv n ＝0.0273 0.0088 0.0088...
(3) Calculating strong sidelobe clutter direction under actual flight situation
And calculating a sine value corresponding to the beam pointing direction according to the azimuth and pitching beam pointing direction 28.4 degrees and minus 60.6 degrees of the radar system.
u 0 ＝0.2335
v 0 ＝-0.8712
Calculating sine values [ U ] corresponding to all strong side lobe boundary points side ，V side ]
[U side ,V side ]＝{[0.2335±0.0646±0.026,-0.8712±0.0273±0.026]...}
Calculating radar system azimuth [ phi ] corresponding to each group of strong sidelobe boundary points side 、theta side ]
theta side ＝-54.9°...
phi side ＝34.3°...
The radar system azimuth angle [34.3 DEG, -54.9 DEG ] is converted into the geographic system [ -118.1 DEG, -21.3 DEG ] according to the inertial navigation information [136.7728,13.7461, -68.3593] of the carrier. Setting a strong clutter pitch angle threshold of-35 degrees, and selecting strong clutter boundary points:
[AZ_G,El_G]＝[-118.1°,-21.3°]...
(4) Calculating the position of a strong clutter boundary point in the radar spectrum
Calculating the speed V_c of each strong clutter boundary point according to the three-way speed of the carrier:
V_c＝[-145.2,-79.8,-15.2]
*[cos(-118.1°)*cos(-21.3°)；sin(-118.1°)*cos(-21.3°)；-sin(-21.3°)]...
and according to parameters such as the strong clutter distance R_c and the velocity V_c, calculating a distance gate Nr_c and a Doppler gate Nf_c corresponding to the strong clutter boundary point in the frequency spectrum.
For a certain strong clutter block, the protection range of the strong clutter is determined according to the boundary point of the clutter, as shown in fig. 2.
(5) Clutter rejection false alarm
After CFAR detection, false alarms belonging to the strong clutter boundary are rejected.
The foregoing is merely specific embodiments of the disclosure, but the protection scope of the disclosure is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the disclosure are intended to be covered by the protection scope of the disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
Claims (6)
1. The method for eliminating the strong sidelobe clutter of the airborne multi-array radar is characterized by comprising the following steps of:
s101: according to the array surface layout of the multi-surface array radar, calculating a directional diagram of the multi-surface array in a sine space at a preset angle;
s102: obtaining angle information of a strong side lobe in the directional diagram based on the directional diagram;
s103: based on the angle information, converting the strong side lobe into a spectrogram;
s104: removing the strong side lobe based on Doppler information and distance information of the Jiang Bangban in the spectrogram;
wherein: the 102 further comprises: obtaining the relative position between the strong side lobe and the main lobe;
when the preset angle in S101 is changed, the angle information is directly obtained based on the relative position and the changed preset angle.
2. The method for eliminating strong sidelobe clutter of airborne multi-array radar according to claim 1, wherein the method for calculating the directional diagram is as follows:
according to the array structure of the multi-face array, calculating an array preset angle pattern F (u, v) under a sine space:
F(u,v)＝(a(u set ,v set )) H a(u,v)
a (u, v) is a signal steering vector, expressed as:
wherein λ is the wavelength;
pos_array is the array plane coordinate of the multi-plane array;
u set ＝sin(phi set )*cos(theta set )；
v set ＝sin(theta set )；
phi set and theta set Respectively presetting azimuth angles and pitch angles for radar systems of the multi-area array;
u＝sin(phi)*cos(theta)；
v＝sin(theta)；
phi E [ -90,90] and theta E [ -90,90] are the azimuth and pitch angles, respectively, of the radar system.
3. The method for eliminating strong sidelobe clutter of an airborne multi-array radar according to claim 2, wherein the method for obtaining the angle information and the relative position is as follows:
according to the pattern, in a sinusoidal space (u.ltoreq.u 0 )∩(v≤v 0 ) And (3) selecting each strong side lobe point, and calculating the sine difference value of each strong side lobe point relative to the preset angle:
wherein:respectively sine values corresponding to the nth strong sidelobes; deltau n And Deltav n Is the sine difference.
4. The method for eliminating strong sidelobe clutter of airborne multi-array radar according to claim 3, wherein the method for obtaining the angle information of the strong sidelobe in the actual flight situation is as follows:
calculating strong sidelobe clutter direction under actual flight situation
Azimuth beam phi according to radar system 0 And elevation beam pointing theta 0 Calculating a corresponding sine value;
u 0 ＝sin(phi 0 )*cos(theta 0 )
v 0 ＝sin(theta 0 )
setting a clutter protection range Pr, and calculating sine values [ U ] corresponding to all strong side lobe boundary points side ，V side ][U side ,V side ]＝{[u 0 ±Δu n ±Pr,v 0 ±Δv n ±Pr],n＝1,2,...N}
5. The method for eliminating strong sidelobe clutter of the airborne multi-array radar according to claim 4, wherein the method for converting the angle information of the strong sidelobe in the actual flight situation into a spectrogram is as follows:
calculating the radar system angle [ phi ] corresponding to the angle information of each group of strong side lobes side 、theta side ]
theta side ＝arcsin(V side )
phi side ＝arcsin(U side /cos(theta side ))
According to inertial navigation information of the carrier of the multi-area array, radar system angle [ phi ] side 、theta side ]Conversion to geographic system Az_G_Side0, el_G_Side0]The method comprises the steps of carrying out a first treatment on the surface of the Setting a strong clutter pitch angle threshold El_max, and selecting a strong clutter boundary point:
[AZ_G,El_G]＝{[AZ_G_side0,El_G_side0]|El_G_side0＜El_max}
calculating the speed V_c of each strong clutter boundary point according to the three-way speed of the carrier:
V_c＝[V_North,V_East,V_Down]
*[cos(Az_G)*cos(El_G)；sin(Az_G)*cos(El_G)；-sin(El_G)]
wherein [ V_North, V_east, V_Down ] are the carrier North speed, east speed and earth speed respectively;
calculating the distance R_c of each strong clutter boundary point according to the height of the carrier, the radius of the earth and the geographic pitch angle El_G;
and according to the strong clutter distance R_c, the speed V_c and the radar working waveform parameters, calculating a distance gate Nr_c and a Doppler gate Nf_c corresponding to the strong clutter boundary point in the frequency spectrum.
6. The method for eliminating strong sidelobe clutter of airborne multi-array radar according to claim 5, wherein the method for eliminating the strong sidelobes is as follows:
according to the boundary points of the strong clutter, determining the protection range of the strong clutter:
Pr_Nr_c_min, nr_c_max ] Pr_nf_e [ nf_c_min, and nf_c_max ] eliminates clutter false alarms in the protection range.
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