CN114265018B - Short-range clutter suppression method based on multi-frequency split radar - Google Patents

Short-range clutter suppression method based on multi-frequency split radar Download PDF

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CN114265018B
CN114265018B CN202210184291.9A CN202210184291A CN114265018B CN 114265018 B CN114265018 B CN 114265018B CN 202210184291 A CN202210184291 A CN 202210184291A CN 114265018 B CN114265018 B CN 114265018B
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王华柯
刘成
全英汇
廖桂生
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Xi'an Hesai Electronic Technology Co ltd
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Xidian University
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Abstract

The invention discloses a short-range clutter suppression method based on a multi-frequency split radar, which comprises the following steps: obtaining clutter echo data based on a radar system of superposition step frequency; analyzing two-dimensional distribution according to the receiving space frequency and the Doppler frequency in the clutter echo data; finding out the relation between the emission space frequency and the fuzzy area; constructing a principal value distance compensation vector based on the relation between the emission space frequency and the fuzzy region to obtain compensated clutter echo data; constructing a blocking vector according to the compensated clutter echo data to obtain the blocked data of each fuzzy area; and (4) carrying out simultaneous equations on expressions of the blocked data of each fuzzy region to obtain clutter data of each fuzzy region. The transmitting array element number of the invention is only one, thus saving the cost of hardware, having low computation complexity, being easy to realize, having low requirement on system parameters, not considering the fuzzy condition of transmitting spatial frequency, having good clutter separation and inhibiting effect.

Description

Short-range clutter suppression method based on multi-frequency split radar
Technical Field
The invention belongs to the technical field of radar signal processing, and particularly relates to a short-range clutter suppression method based on a multi-frequency split system radar.
Background
The airborne radar is usually in downward-looking work and has strong clutter, and due to the high-speed motion of the platform, the clutter has certain relative speed, the relative speed in different directions is different, and weak low-speed targets are submerged in the strong clutter, so that the performance of the radar is greatly reduced. Ground clutter echoes show correlation in both space and time dimensions, while interference is mainly correlated in angle, and signal to noise ratio (SCNR) can be effectively maximized by using space-time freedom. Space-time adaptive processing (STAP) involves adaptively adjusting a two-dimensional space-time filter response to maximize the output signal-to-noise ratio. By introducing the STAP algorithm into the airborne radar, the radar detection performance is improved.
In an airborne radar, clutter Doppler spread is serious, in order to avoid Doppler ambiguity as far as possible, a signal with a higher pulse repetition frequency is generally transmitted, but as is well known, the maximum unambiguous distance and the pulse repetition frequency are in inverse proportion, the higher pulse repetition frequency can bring a serious distance ambiguity problem, clutter in different ambiguity intervals can be superposed together at the moment, echo data of the clutter can not meet the independent and same-distribution condition any more, the direct application of the STAP can also suppress the notch broadening of the clutter factor, and the suppression performance of the STAP on the clutter can be remarkably reduced. For a non-positive side array, the distribution of the clutter has dependence on distance, the dependence of the short-range clutter on the distance is very serious, and the dependence of the long-range clutter on the distance is lighter.
Although some existing clutter compensation methods can reduce the distance dependency by compensating clutter data, when distance ambiguity is involved, the enhancement effect of the compensation methods on the STAP of the non-positive side array is not obvious due to different distance dependencies of different fuzzy areas.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a short-range clutter suppression method based on a multi-frequency split system radar. The technical problem to be solved by the invention is realized by the following technical scheme:
a short-range clutter suppression method based on a multi-frequency division radar, the short-range clutter suppression method comprising:
step 1, obtaining clutter echo data based on a radar system with superposed step frequency;
step 2, analyzing two-dimensional distribution of the clutter echo data on the receiving space frequency and the Doppler frequency according to the receiving space frequency and the Doppler frequency in the clutter echo data;
step 3, obtaining the relation between the transmitting space frequency and the distance according to the transmitting space frequency of the clutter echo data so as to find out the relation between the transmitting space frequency and the fuzzy area;
step 4, constructing a principal value distance compensation vector based on the relation between the emission space frequency and the fuzzy area to obtain compensated clutter echo data;
step 5, constructing a blocking vector according to the compensated clutter echo data to obtain the blocked data of each fuzzy area;
and 6, establishing a simultaneous equation set for the expressions of the blocked data of the fuzzy areas to obtain the clutter data of each fuzzy area.
In an embodiment of the present invention, the transmitting antennas are configured to transmit M orthogonal signals, each of the orthogonal signals transmits K pulses, there are N receiving antennas in total, and there are P fuzzy areas in total, then the clutter data received by the ith distance unit is:
Figure GDA0003598841310000031
wherein, aT(Rp,l)、aR(θi)、at(v0) The transmitting space guide vector, the receiving space guide vector and the Doppler guide vector of the clutter echo data are respectively represented, and Nc represents the equivalent number of clutter sources in each range unit.
In one embodiment of the present invention, the two-dimensional distribution is:
Figure GDA0003598841310000032
Figure GDA0003598841310000033
wherein S isH(fRs,ft) Representing the received spatial frequency and the normalized Doppler frequency as fRs、ftSpace-time two-dimensional steering vector of RsAnd the method comprises the steps of representing a covariance matrix of clutter echo data, wherein L represents the total number of training samples, L represents the ith training sample, H represents conjugate transpose, and the training samples represent clutter echo data on the ith distance unit.
In one embodiment of the invention, the relationship between the transmit spatial frequency and the distance is:
Figure GDA0003598841310000034
R＝Rl+(P-1)Ru
wherein f isT(R) represents the received spatial frequency,. DELTA.f represents the frequency increment, c represents the speed of light, R represents the distance, R represents the frequency increment, andldenotes a principal value distance, P denotes the number of blurred regions, RuMaximum unambiguous distance.
In one embodiment of the present invention, the principal value distance compensation vector is:
bc(Rl)＝[1,e-j4πΔfR/c,…,e-j4πΔfR(M-1)/c]
where M is the number of transmit waveforms.
In one embodiment of the present invention, the compensated clutter echo data is:
Figure GDA0003598841310000041
wherein, INRepresenting an identity matrix of dimension N, IKRepresenting an identity matrix of dimension K.
In one embodiment of the present invention, the blur area includes a first blur area, a second blur area, a third blur area and a fourth blur area, wherein the step 4 includes:
step 4.1, compensating the dominant value distance of the first fuzzy area through the corresponding dominant value distance compensation vector to obtain clutter echo data after compensation in the first fuzzy area;
step 4.2, compensating the dominant value distance of the second fuzzy area through the corresponding dominant value distance compensation vector to obtain clutter echo data after compensation in the second fuzzy area;
4.3, compensating the dominant value distance of the third fuzzy area through the corresponding dominant value distance compensation vector to obtain clutter echo data after compensation in the third fuzzy area;
and 4.4, compensating the principal value distance of the fourth fuzzy area through the corresponding principal value distance compensation vector to obtain the clutter echo data after compensation in the fourth fuzzy area.
In one embodiment of the present invention, the step 5 comprises:
step 5.1, rearranging the compensated clutter echo data in the first fuzzy area, and constructing a first blocking vector to obtain data after the clutter echo data are blocked in the first fuzzy area;
step 5.2, rearranging the compensated clutter echo data in the second fuzzy area, and constructing a second blocking vector to obtain data after the clutter blocking in the second fuzzy area;
step 5.3, rearranging the compensated clutter echo data in the third fuzzy area, and constructing a third blocking vector to obtain data after the third fuzzy area blocks the clutter;
and 5.4, rearranging the compensated clutter echo data in the fourth fuzzy area, and constructing a fourth blocking vector to obtain data after the clutter blocking in the fourth fuzzy area.
In one embodiment of the present invention, the first occlusion vector is:
Figure GDA0003598841310000042
the second occlusion vector is:
Figure GDA0003598841310000051
the third occlusion vector is:
Figure GDA0003598841310000052
the fourth occlusion vector is:
Figure GDA0003598841310000053
the data after the clutter is blocked in the first fuzzy region is data;
B1yc1,l＝(a1,1-a2,1)C1+(a1,2-a2,2)C2+(a1,3-a2,3)C3+(a1,4-a2,4)C4
the data after the clutter blocking of the second fuzzy region is data;
B2yc2,l＝(a3,0-a4,0)C1+(a3,1-a4,1)C2+(a3,2-a4,2)C3+(a3,3-a4,3)C4
the data after the third fuzzy region blocks the clutter is;
B3yc3,l＝(a5,-1-a6,-1)C1+(a5,.0-a6,0)C2+(a5,1-a6,1)C3+(a5,2-a6,2)C4
the data after the fourth fuzzy region blocks the clutter is;
B4yc4,l＝(a7,-2-a8,-2)C1+(a7,-1-a8,-1)C2+(a7,0-a8,0)C3+(a7,1-a8,1)C4
wherein,
Figure GDA0003598841310000054
representing the matrix dimension, C1, C2, C3 and C4 respectively correspond to the kronecker product, a, of the received space steering vector and the Doppler steering vector of different fuzzy areasm,pExp (-j4 pi (m-1) (p-1) Ru × Δ f/c), m denotes the mth emission waveform, and p denotes the number of blurred regions.
In an embodiment of the present invention, after the step 6, the method further includes:
and processing clutter data of the first fuzzy area by adopting a Doppler frequency shift compensation method, and then processing the clutter data compensated by the Doppler frequency shift compensation method in the first fuzzy area and the clutter data of the second fuzzy area, the third fuzzy area and the fourth fuzzy area by adopting a STAP algorithm so as to eliminate the clutter data of each fuzzy area.
The invention has the beneficial effects that:
the invention has the advantages of only one transmitting array element, low hardware cost, low calculation complexity, easy realization, low requirement on system parameters, no need of considering the fuzzy condition of transmitting spatial frequency, good clutter separation and good inhibition effect.
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Drawings
Fig. 1 is a schematic flowchart of a short-range clutter suppression method based on a multi-frequency diversity radar according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of another short-range clutter suppression method based on a multi-frequency diversity radar according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating the relationship between the transmission spatial frequency and the distance after the first blurring region compensation is performed according to an embodiment of the present invention;
FIG. 4a is a schematic diagram of the power spectrum distribution of clutter in the first fuzzy region after mixed clutter data separation according to an embodiment of the present invention;
FIG. 4b is a schematic diagram illustrating a power spectrum distribution of clutter of the second fuzzy region after mixed clutter data separation according to an embodiment of the present invention;
FIG. 4c is a schematic diagram of the power spectrum distribution of clutter in the third fuzzy region after mixed clutter data separation according to an embodiment of the present invention;
FIG. 4d is a schematic diagram of the power spectrum distribution of clutter in the fourth fuzzy region after mixed clutter data separation according to an embodiment of the present invention;
FIG. 5a is a diagram illustrating the relationship between the improvement factor and the normalized Doppler frequency after STAP is performed on the data of the first blurred region after separation according to an embodiment of the present invention;
FIG. 5b is a diagram illustrating the relationship between the improvement factor and the normalized Doppler frequency after STAP is performed on the data of the second blurred region after separation according to the embodiment of the present invention;
FIG. 5c is a diagram illustrating the relationship between the improvement factor and the normalized Doppler frequency after STAP is performed on the data of the third blurred region directly after separation according to an embodiment of the present invention;
FIG. 5d is a diagram illustrating the relationship between the improvement factor and the normalized Doppler frequency after STAP is directly performed on the data of the fourth blurred region after separation according to the embodiment of the present invention;
fig. 6 is a schematic diagram of a clutter power spectrum distribution of the first blurred region after doppler shift compensation is performed on the first blurred region according to an embodiment of the present invention;
fig. 7 is a comparison graph of the relationship between the normalized doppler frequency and the improvement factor of the STAP performed after the first blurred region is compensated, and the STAP performed directly in the past.
Detailed Description
The present invention will be described in further detail with reference to specific examples, but the embodiments of the present invention are not limited thereto.
Example one
Referring to fig. 1 and fig. 2, fig. 1 is a schematic flow chart of a short-range clutter suppression method based on a multi-frequency system radar according to an embodiment of the present invention, and fig. 2 is a schematic flow chart of another short-range clutter suppression method based on a multi-frequency system radar according to an embodiment of the present invention. The embodiment of the invention provides a short-range clutter suppression method based on a multi-frequency split radar, which comprises the following steps:
and step 1, obtaining clutter echo data based on a radar system of superposition step frequency.
Specifically, setting a transmitting antenna to transmit M orthogonal signals, each of which transmits K pulses, N receiving antennas in total and P fuzzy areas in total, and then receiving clutter data by the ith distance unit:
Figure GDA0003598841310000071
wherein, aT(Rp,l)、aR(θi)、at(v0) The transmitting space guide vector, the receiving space guide vector and the Doppler guide vector of the clutter echo data are respectively represented, and Nc represents the equivalent number of clutter sources in each range unit.
And 2, analyzing two-dimensional distribution of the clutter echo data on the receiving space frequency and the Doppler frequency according to the receiving space frequency and the Doppler frequency in the clutter echo data.
Specifically, the property of the clutter may be determined according to the two-dimensional distribution, which is used as a basis for the property change of the clutter before and after the back compensation, and the two-dimensional power spectrum distribution of the clutter echo data is:
Figure GDA0003598841310000081
Figure GDA0003598841310000082
wherein S isH(fRs,ft) Representing the received spatial frequency and the normalized Doppler frequency as fRs、ftSpace-time two-dimensional steering vector of RsAnd the method comprises the steps of representing a covariance matrix of clutter echo data, wherein L represents the total number of training samples, L represents the ith training sample, H represents conjugate transpose, and the training samples represent clutter echo data on the ith distance unit.
And 3, obtaining the relation between the transmitting space frequency and the distance according to the transmitting space frequency of the clutter echo data so as to find out the relation between the transmitting space frequency and the fuzzy area.
In this embodiment, the mth transmission signal of the transmission array element can be expressed as:
Figure GDA0003598841310000083
wherein,
Figure GDA0003598841310000084
representing the envelope of the transmitted signal, E representing the total power of the transmitted signal, T representing the duration of the transmitted pulse, T representing a time variable, fmRepresenting the carrier frequency of the mth transmitted signal. Assuming that the envelope of the transmitted signal satisfies the orthogonality condition, there are:
Figure GDA0003598841310000085
wherein τ represents an arbitrary time delay ()*It is indicated that the conjugate operation is performed,
Figure GDA0003598841310000086
representing the envelope of the signal.
Considering a far-field point source, the time delay for the nth unit to receive a signal transmitted via the far-field point source can be expressed as:
Figure GDA0003598841310000091
wherein, tau02R/c denotes the common time delay, R denotes the distance between the receiving array element and the far field point, c denotes the speed of light, τnRepresenting the time delay difference between cells, vaRepresenting the velocity of the platform and theta the angle of the far field point.
The kth pulse received by the nth unit can be expressed as:
Figure GDA0003598841310000092
where ρ represents the complex scattering coefficient of the point source. Taking into account the narrowband assumption, i.e.
Figure GDA0003598841310000093
Then the received signal is at
Figure GDA0003598841310000094
After matched filtering, it can be decomposed into:
Figure GDA0003598841310000095
where ξ ═ ρ exp { j2 π f0R}，f0Representing carrier frequency, d representing array element spacing, fDDenotes the doppler frequency of the point source, λ denotes the wavelength, and v denotes the point source velocity. The receive snapshots in frequency diversity array MIMO can therefore be expressed in vector form as:
Figure GDA0003598841310000096
wherein,
Figure GDA0003598841310000097
the superscript T is the transpose operator,
Figure GDA0003598841310000098
is the product of Kronecker.
Figure GDA0003598841310000099
Figure GDA00035988413100000910
And
Figure GDA00035988413100000911
respectively representing transmit, receive steering vectors and time steering vectors, expressed as follows:
Figure GDA00035988413100000912
Figure GDA0003598841310000101
Figure GDA0003598841310000102
note here that:
Figure GDA0003598841310000103
for transmitting spatial frequencies, R ═ Rl+(P-1)RuΔ f denotes the frequency increment, c denotes the speed of light, R denotes the distance, R denoteslRepresenting principal value distance, P representing the number of fuzzy regions, RuMaximum unambiguous distance;
Figure GDA0003598841310000104
to accept spatial frequencies;
Figure GDA0003598841310000105
is the normalized doppler frequency.
And 4, constructing a principal value distance compensation vector based on the relation between the transmitting spatial frequency and the fuzzy region to obtain compensated clutter echo data, wherein fig. 3 is a schematic diagram of the relation between the transmitting spatial frequency and the distance after the first fuzzy region is compensated.
In this embodiment, the principal value distance compensation vector is:
bc(Rl)＝[1,e-j4πΔfR/c,…,e-j4πΔfR(M-1)/c]
where M is the number of transmit waveforms.
Preferably, the blur area includes a first blur area, a second blur area, a third blur area, and a fourth blur area. Then:
the principal value distance compensation vector of the first fuzzy area is as follows:
Figure GDA0003598841310000106
the principal value distance compensation vector of the second fuzzy area is as follows:
Figure GDA0003598841310000107
the principal value distance compensation vector of the third fuzzy area is as follows:
Figure GDA0003598841310000108
the principal value distance compensation vector of the fourth fuzzy area is as follows:
Figure GDA0003598841310000111
in a specific embodiment, step 4 may specifically include:
and 4.1, compensating the dominant value distance of the first fuzzy area through the corresponding dominant value distance compensation vector to obtain the clutter echo data compensated in the first fuzzy area.
Specifically, the dominant value distance of the first fuzzy region is compensated through the corresponding dominant value distance compensation vector, clutter echo data irrelevant to the dominant value distance are obtained, the clutter echo data at the moment are only relevant to the number of fuzzy regions, and the transmitting space frequency of the clutter of the first fuzzy region is a constant irrelevant to the number of channels.
And 4.2, compensating the dominant value distance of the second fuzzy area through the corresponding dominant value distance compensation vector to obtain the clutter echo data compensated in the second fuzzy area.
Specifically, the dominant value distance of the second fuzzy area is compensated through the corresponding dominant value distance compensation vector, and the transmitting spatial frequency of the clutter of the second fuzzy area is a constant independent of the number of channels.
And 4.3, compensating the dominant value distance of the third fuzzy area through the corresponding dominant value distance compensation vector to obtain the clutter echo data compensated in the third fuzzy area.
And 4.4, compensating the dominant value distance of the fourth fuzzy area through the corresponding dominant value distance compensation vector to obtain the clutter echo data compensated in the fourth fuzzy area.
In one embodiment, the clutter echo data after the dominant distance compensation is:
Figure GDA0003598841310000112
wherein, INRepresenting an identity matrix, I, of dimension NKRepresenting an identity matrix of dimension K.
And 5, constructing a blocking vector according to the compensated clutter echo data to obtain the blocked data of each fuzzy area.
In one embodiment, step 5 comprises:
and 5.1, rearranging the compensated clutter echo data in the first fuzzy area, and constructing a first blocking vector to obtain data after the clutter echo data are blocked in the first fuzzy area.
Specifically, one of the range units is selected, the clutter echo data is rearranged, a first blocking vector is constructed, and the clutter data of the first fuzzy area is eliminated from the clutter echo data.
After the principal distance compensation of the first fuzzy region, the clutter echo data can be represented again after being rearranged as:
Figure GDA0003598841310000121
wherein,
Figure GDA0003598841310000122
respectively, the transmission spatial frequencies of each of the four blurring regions after the first blurring region compensation.
The first occlusion vector is:
Figure GDA0003598841310000123
the data after the clutter is blocked in the first fuzzy region is as follows;
B1yc1,l＝(a1,1-a2,1)C1+(a1,2-a2,2)C2+(a1,3-a2,3)C3+(a1,4-a2,4)C4
wherein, B1yc1,lRepresenting data after the first blurred region blocks clutter.
And 5.2, rearranging the compensated clutter echo data in the second fuzzy area, and constructing a second blocking vector to obtain data after the clutter is blocked in the second fuzzy area.
Specifically, the same distance unit is selected, clutter echo data are rearranged, a second blocking vector is constructed again, and clutter data in a second fuzzy area are eliminated from the clutter echo data.
Wherein the second occlusion vector is:
Figure GDA0003598841310000124
the data after the clutter is blocked in the second fuzzy region is as follows;
B2yc2,l＝(a3,0-a4,0)C1+(a3,1-a4,1)C2+(a3,2-a4,2)C3+(a3,3-a4,3)C4
wherein, B2yc2,lRepresenting data after the second blurred region blocks clutter.
And 5.3, rearranging the compensated clutter echo data in the third fuzzy area, and constructing a third blocking vector to obtain data after the third fuzzy area blocks the clutter.
Wherein the third occlusion vector is:
Figure GDA0003598841310000131
the data after the third fuzzy region blocks the clutter is;
B3yc3,l＝(a5,-1-a6,-1)C1+(a5,.0-a6,0)C2+(a5,1-a6,1)C3+(a5,2-a6,2)C4
wherein, B3yc3,lRepresenting data after the third blurred region blocks clutter.
And 5.4, rearranging the compensated clutter echo data in the fourth fuzzy area, and constructing a fourth blocking vector to obtain data after the clutter is blocked in the fourth fuzzy area.
Wherein the fourth occlusion vector is:
Figure GDA0003598841310000132
the data after the fourth fuzzy region blocks the clutter is;
B4yc4,l＝(a7,-2-a8,-2)C1+(a7,-1-a8,-1)C2+(a7,0-a8,0)C3+(a7,1-a8,1)C4
wherein, B4yc4,lRepresenting data after the fourth blurred region blocks clutter.
Wherein,
Figure GDA0003598841310000133
representing the matrix dimension, C1, C2, C3 and C4 respectively correspond to the kronecker product, a, of the received space steering vector and the Doppler steering vector of different fuzzy areasm,p＝exp(-j4π(m-1) (p-1) Ru × Δ f/c), m representing the mth emission waveform, and p representing the number of blur areas.
And 6, establishing a simultaneous equation set for expressions of the blocked data of each fuzzy region to obtain clutter data of each fuzzy region.
And 7, traversing all the distance units to obtain clutter data of all the fuzzy areas, processing the clutter data of the first fuzzy area by adopting a Doppler frequency shift compensation method, and then processing the clutter data compensated by the Doppler frequency shift compensation method in the first fuzzy area and the clutter data of the second fuzzy area, the third fuzzy area and the fourth fuzzy area by adopting an STAP algorithm to eliminate the clutter data of each fuzzy area.
Next, the effect of the method for suppressing short-range clutter by using a multi-frequency division radar according to the present embodiment is further described through a simulation experiment.
Simulation parameter table for suppressing short-range clutter of multi-frequency division system radar
Carrier frequency 1GHz Number of coherent pulses 20
Spacing of transmitting array elements 0.15m Duration of pulse 1us
Spacing of receiving array elements 0.15m Distance fuzzy number 4
Speed of platform movement 150m/s Distance resolution 20m
Height of platform 6km Frequency increment 2.5kHz
Pulse repetition frequency 2kHz Target distance 12km
Number of transmitting array elements 8 Target horizontal angle 90
Number of receiving array elements 8 Target pitch angle 30.0552
The power spectrum distribution of the clutter after the clutter is separated by the method of the invention is shown in fig. 4a-4d, as can be seen from fig. 4a-4d, the distance dependency of the short-range clutter is more serious, which causes the power spectrum distribution to spread, while the distance dependency of the clutter of the other fuzzy areas is smaller, and the clutter distributions of different distances are almost the same, which is also the reason that the notch of the improvement factor of the first fuzzy area is wider and the clutter suppression performance is poorer in fig. 5a-5d, while the notch of the improvement factor of the other fuzzy areas by directly using the STAP is narrower, so that the clutter of the areas can be directly suppressed by using the STAP. Fig. 6 shows the clutter power spectrum distribution after applying the doppler shift compensation algorithm to the clutter in the first blurred region, and it can be clearly seen that the distribution of the mainlobe clutter is more concentrated. Fig. 7 is an improved factor graph obtained by using the STAP algorithm after compensation, the notch is already obviously narrowed, and the suppression effect is improved.
The invention has the advantages of only one transmitting array element, low hardware cost, low calculation complexity, easy realization, low requirement on system parameters, no need of considering the fuzzy condition of transmitting spatial frequency, good clutter separation and good inhibition effect.
In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In the description of the present specification, reference to the description of "one embodiment," "some embodiments," "an example," "a specific example," or "some examples" or the like means that a particular feature, structure, material, or characteristic data point described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples described in this specification can be combined and combined by those skilled in the art.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.

Claims (10)

1. A short-range clutter suppression method based on a multi-frequency division radar is characterized by comprising the following steps:
step 1, obtaining clutter echo data based on a radar system with superposed step frequency;
step 2, analyzing two-dimensional distribution of the clutter echo data on the receiving space frequency and the Doppler frequency according to the receiving space frequency and the Doppler frequency in the clutter echo data;
step 3, obtaining the relation between the transmitting space frequency and the distance according to the transmitting space frequency of the clutter echo data so as to find out the relation between the transmitting space frequency and the fuzzy area;
step 4, constructing a principal value distance compensation vector based on the relation between the emission space frequency and the fuzzy area to obtain compensated clutter echo data;
step 5, constructing a blocking vector according to the compensated clutter echo data to obtain the blocked data of each fuzzy area;
and 6, establishing a simultaneous equation set for the expressions of the blocked data of the fuzzy areas to obtain the clutter data of each fuzzy area.
2. The short-range clutter suppression method based on multi-band radar of claim 1, wherein the transmit antenna is configured to transmit M orthogonal signals, each of the orthogonal signals transmits K pulses, there are N receive antennas in total, and there are P fuzzy areas in total, then the clutter data received by the ith distance unit is:
Figure FDA0003598841300000011
wherein, aT(Rp,l)、aR(θi)、at(v0) The transmitting space guide vector, the receiving space guide vector and the Doppler guide vector of the clutter echo data are respectively represented, and Nc represents the equivalent number of clutter sources in each range unit.
3. The short-range clutter suppression method based on multi-frequency division radar according to claim 1, wherein the two-dimensional distribution is:
Figure FDA0003598841300000021
Figure FDA0003598841300000022
wherein S isH(fRs,ft) Representing the received spatial frequency and the normalized Doppler frequency as fRs、ftSpace-time two-dimensional steering vector of RsAnd the method comprises the steps of representing a covariance matrix of clutter echo data, wherein L represents the total number of training samples, L represents the ith training sample, H represents conjugate transpose, and the training samples represent clutter echo data on the ith distance unit.
4. The short-range clutter suppression method based on multi-band radar according to claim 1, wherein the relationship between the transmit spatial frequency and the distance is:
Figure FDA0003598841300000023
R＝Rl+(P-1)Ru
wherein f isT(R) represents the received spatial frequency, Δ f TableFrequency increment, c light speed, R distance, RlRepresenting principal value distance, P representing the number of fuzzy regions, RuMaximum unambiguous distance.
5. The short-range clutter suppression method based on multi-frequency division radar according to claim 4, wherein the principal value distance compensation vector is:
bc(Rl)＝[1,e-j4πΔfR/c,…,e-j4πΔfR(M-1)/c]
where M is the number of transmit waveforms.
6. The short-range clutter suppression method based on multi-frequency division radar according to claim 5, wherein the clutter echo data after compensation is:
Figure FDA0003598841300000024
wherein, INRepresenting an identity matrix of dimension N, IKRepresenting an identity matrix of dimension K.
7. The short-range clutter suppression method based on multi-frequency diversity radar according to claim 6, wherein the fuzzy areas comprise a first fuzzy area, a second fuzzy area, a third fuzzy area and a fourth fuzzy area, wherein said step 4 comprises:
step 4.1, compensating the dominant value distance of the first fuzzy area through the corresponding dominant value distance compensation vector to obtain clutter echo data after compensation in the first fuzzy area;
step 4.2, compensating the dominant value distance of the second fuzzy area through the corresponding dominant value distance compensation vector to obtain clutter echo data after compensation in the second fuzzy area;
4.3, compensating the dominant value distance of the third fuzzy area through the corresponding dominant value distance compensation vector to obtain clutter echo data after compensation in the third fuzzy area;
and 4.4, compensating the principal value distance of the fourth fuzzy area through the corresponding principal value distance compensation vector to obtain the clutter echo data after compensation in the fourth fuzzy area.
8. The short-range clutter suppression method based on multi-frequency division radar according to claim 6, wherein said step 5 comprises:
step 5.1, rearranging the compensated clutter echo data in the first fuzzy area, and constructing a first blocking vector to obtain data after the clutter echo data are blocked in the first fuzzy area;
step 5.2, rearranging the compensated clutter echo data in the second fuzzy area, and constructing a second blocking vector to obtain data after the clutter blocking in the second fuzzy area;
step 5.3, rearranging the compensated clutter echo data in the third fuzzy area, and constructing a third blocking vector to obtain data after the third fuzzy area blocks the clutter;
and 5.4, rearranging the compensated clutter echo data in the fourth fuzzy area, and constructing a fourth blocking vector to obtain data after the clutter blocking in the fourth fuzzy area.
9. The short-range clutter suppression method based on multi-band radar according to claim 8, wherein the first blocking vector is:
Figure FDA0003598841300000041
the second occlusion vector is:
Figure FDA0003598841300000042
the third occlusion vector is:
Figure FDA0003598841300000043
the fourth occlusion vector is:
Figure FDA0003598841300000044
the data after the clutter is blocked in the first fuzzy region is data;
B1yc1,l＝(a1,1-a2,1)C1+(a1,2-a2,2)C2+(a1,3-a2,3)C3+(a1,4-a2,4)C4
the data after the clutter blocking of the second fuzzy region is data;
B2yc2,l＝(a3,0-a4,0)C1+(a3,1-a4,1)C2+(a3,2-a4,2)C3+(a3,3-a4,3)C4
the data after the third fuzzy region blocks the clutter is;
B3yc3,l＝(a5,-1-a6,-1)C1+(a5,.0-a6,0)C2+(a5,1-a6,1)C3+(a5,2-a6,2)C4
the data after the fourth fuzzy region blocks the clutter is;
B4yc4,l＝(a7,-2-a8,-2)C1+(a7,-1-a8,-1)C2+(a7,0-a8,0)C3+(a7,1-a8,1)C4
wherein,
Figure FDA0003598841300000045
representing the matrix dimension, C1, C2, C3 and C4 respectively correspond to the kronecker product, a, of the received space steering vector and the Doppler steering vector of different fuzzy areasm,pExp (-j4 pi (m-1) (p-1) Ru × Δ f/c), m denotes the mth emission waveform, and p denotes the number of blur areas.
10. The short-range clutter suppression method based on multi-frequency division radar according to claim 7, further comprising, after said step 6:
and processing clutter data of the first fuzzy area by adopting a Doppler frequency shift compensation method, and then processing the clutter data compensated by the Doppler frequency shift compensation method in the first fuzzy area and the clutter data of the second fuzzy area, the third fuzzy area and the fourth fuzzy area by adopting a STAP algorithm so as to eliminate the clutter data of each fuzzy area.
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