CN115586495A - MR-FDA-MIMO radar interference suppression method - Google Patents

Abstract

The invention provides an MR-FDA-MIMO radar interference suppression method, which comprises the steps of transmitting signals according to a signal transmission model by using a transmitting array element, and acquiring multiple times of snapshot data received by a receiving array element; compensating the snapshot data to obtain compensated snapshot data; suppressing side lobe suppression type interference on the compensated snapshot data in a receiving dimension by utilizing a generalized side lobe cancellation GSC (generalized minimum cost) method to obtain snapshot data after side lobe interference suppression; solving a covariance matrix for the equivalent emission dimension snapshot data after sidelobe interference suppression, expanding the virtual snapshot freedom degree by utilizing the idea of a difference common matrix, and then suppressing multi-main lobe interference by utilizing a non-adaptive method to obtain a true target. Compared with the prior art, the invention has the advantages that the deception interference with the number higher than that of the transmitting array elements can be inhibited under the condition that the transmitting array elements and the receiving array elements are limited, the number of the inhibited interference is effectively increased, and the capacity of the frequency diversity array for inhibiting the number of the interference is improved.

Description

MR-FDA-MIMO radar interference suppression method

Technical Field

The invention belongs to the technical field of radar detection, and particularly relates to an MR-FDA-MIMO radar interference suppression method.

Background

With the development of information technology, the electromagnetic environment in a battlefield is more and more complex, the types and the number of electronic interferences are increased all the time, especially main lobe deceptive interferences, and the deceptive interferences radiate electromagnetic waves similar to target echoes to induce a radar system to treat false targets as true targets, so that the parameter estimation and tracking of the false targets on the true targets are influenced, and the battlefield viability of the radar is greatly threatened.

Indeed, conventional radars lack effective system freedom to distinguish true targets from false targets in the main lobe direction. Therefore, how to combat the deceptive jamming, especially the active deceptive jamming entering from the main lobe of the radar antenna, has become an urgent issue to be solved. Unlike a conventional phased array, a Frequency Diversity Array (FDA) radar uses small frequency increments in array elements to increase the degree of freedom in the distance dimension. In order to fully utilize the distance dimension information, FDA and Multiple Input Multiple Output (MIMO) technology are combined, and the method is favorable for always-mainlobe deceptive interference. In general, the number of main lobe deception jamming suppressions is fundamentally limited by the number of radar transmitting array elements.

In the prior art, the distance dimension degree of freedom of the FDA is utilized, a true target and deceptive interference are distinguished in a transmitting airspace frequency domain, and meanwhile, a robust distance angle two-dimensional beam forming method based on a direct data domain is provided. Likewise, the number of spoofed interference suppressions for multiple-input multiple-output (MIMO) radar is limited by the number of its transmitting elements.

Disclosure of Invention

In order to solve the problems in the prior art, the invention provides an MR-FDA-MIMO radar interference suppression method. The technical problem to be solved by the invention is realized by the following technical scheme:

the invention provides an MR-FDA-MIMO radar interference suppression method, which comprises the following steps:

step 1: establishing a signal transmitting model;

step 2: transmitting signals by using the transmitting array elements according to the signal transmitting model, and acquiring multiple times of snapshot data received by the receiving array elements;

the multi-time snapshot data comprises snapshot data of a true target, sidelobe pressing mode interference which is not greater than the number of the receiving array elements and main lobe deception interference which is greater than the number of the transmitting array elements;

and step 3: compensating the snapshot data to obtain compensated snapshot data;

and 4, step 4: suppressing side lobe suppression type interference on the compensated snapshot data in a receiving dimension by using a generalized side lobe cancellation GSC (generalized side lobe cancellation) method to obtain the snapshot data after side lobe interference suppression;

and 5: and (3) suppressing main lobe deceptive jamming on the snapshot data after the side lobe jamming is suppressed in an equivalent emission dimension by using a non-adaptive method, and obtaining virtual snapshot data of a real target.

The invention has the beneficial effects that:

the invention provides an MR-FDA-MIMO radar interference suppression method, which comprises the steps of transmitting signals according to a signal transmission model by using a transmitting array element, and acquiring multiple times of snapshot data received by a receiving array element; compensating the snapshot data to obtain compensated snapshot data; suppressing side lobe suppression type interference on the compensated snapshot data in a receiving dimension by using a generalized side lobe cancellation GSC (generalized side lobe cancellation) method to obtain the snapshot data after side lobe interference suppression;

and by using a non-adaptive method, the virtual degree of freedom of the transmission dimension is expanded, main lobe deceptive interference of the snapshot data after the sidelobe interference suppression is suppressed in the receiving dimension, and a true target is obtained. Compared with the prior art, the invention has the advantages that the deception interference with the number higher than that of the transmitting array elements can be inhibited under the condition that the transmitting array elements and the receiving array elements are limited, the number of the inhibited interference is effectively increased, and the capacity of the frequency diversity array for inhibiting the number of the interference is improved.

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 an MR-FDA-MIMO radar interference suppression method according to an embodiment of the present invention;

FIG. 2 is a diagram showing 4 array elements;

FIG. 3 is a MR-FDA-MIMO radar target and interference power spectrum;

FIG. 4 is a graph showing the results of side lobe interference suppression;

FIG. 5 is a graph of output signal-to-noise ratio (SINR) versus input signal-to-noise ratio (SNR) after 300 Monte Carlo tests;

FIG. 6 is a graph of multi-mainlobe deception jamming suppression results comparing a 7-array element Minimum Variance Distortionless Response (MVDR), a virtual array adaptive approach, and a virtual array non-adaptive approach;

FIG. 7 is a graph of signal-to-noise ratio for multiple spoofing interference;

FIG. 8 is a graph of the SNR loss performance of the 7-element Minimum Variance Distortionless Response (MVDR) method compared to the virtual array non-adaptive method for multiple decoy cases.

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.

As shown in fig. 1, an MR-FDA-MIMO radar interference suppression method provided by the present invention includes:

step 1: establishing a signal transmitting model;

wherein, the signal emission model is:

where E is the transmit energy, M is the number of transmit array elements, T _P Is the pulse width, f _m ＝f ₀ +ΔfD _m Is the carrier frequency of the m-th antenna element, D _m The position corresponding to the array element of the minimum redundant array is shown, and delta f < f ₀ Phi is the envelope of the transmitted signal, the envelope of the transmitted signal satisfying

M '=1,2, \ 8230, M ≠ M', τ isTime delay, m is the mth transmit array element, and m' is the mth transmit array element.

Step 2: transmitting signals by using the transmitting array elements according to the signal transmitting model, and acquiring multiple times of snapshot data received by the receiving array elements;

the multi-time snapshot data comprise snapshot data of a true target, sidelobe pressing mode interference which is not greater than the number of the receiving array elements and main lobe deception interference which is greater than the number of the transmitting array elements;

for a position in the far field (R) ₀ ,θ ₀ ) The echo received by the nth receiving array element can be expressed as

Under the assumption of narrow band,. Phi _m (t-τ _m,n )≈Φ _m (t-τ ₀ ) Beta is the scattering coefficient of the point target, tau _m,n The time delay of the signal transmitted by the mth antenna and received by the nth array element can be written as

Wherein is d _R Spacing of receiving elements, τ ₀ ＝2R ₀ And c is the common delay time and c is the speed of light.

The signal is down-converted, matched filtered in the receiver. After the three signal processing flows, the received data can be expressed as the following parts:

wherein

λ ₀ ＝c/f ₀ Is the reference wavelength.

Thus, the snapshot data of true targets received in MR-FDA-MIMO is represented as

Wherein,

and

respectively, a transmit steering vector and a receive steering vector, respectively, denoted as

Wherein, y _MN The receiving array element receives the snapshot data of the real target after the Mth transmitting array element transmits signals,

in order to guide the vector for the distance,

an angle steering vector, \ indicates a Hadamard product, (R) ₀ ,θ ₀ ) Indicating the position of a true object in the far field, c is the speed of light, λ ₀ ＝c/f ₀ Is a reference wavelength, d _R The receive array element spacing, d the transmit element spacing, typically a half wavelength,

is a complex set.

The transmitting frequency and the receiving frequency corresponding to the true target are respectively

Suppose Q are from theta _q Q =1,2, \ 8230, and the interference signal in the Q direction has side-lobe suppression type interference of

Wherein ξ _q Is a uniform complex Gaussian random variable with a mean value of zero and a variance of

E {. Is the mathematical expectation operation;

and

respectively representing the transmit and receive steering vectors of the interference of the respective noise classes, n, due to the statistical nature and the obtrusiveness of the noise of the interference _T Satisfying a zero mean Gaussian noise distribution, i.e. n _T ～CN(0,I _M )；

Suppose that in the far field of space (R) _j ,θ _j ) The interference machine intercepts radar signals and delays and forwards one or more pulse periods to form a false target, and the interference radar identifies and tracks the true target. The main lobe deception jamming contained in the received echo signal of the n array element is

Wherein Q' is the number of decoys, beta _q′ Is Q ' (Q ' =1, 2., Q ') Scattering coefficient of a false target, tau _q′ Is the delay of the qth' th decoy, τ _j Is a two-way time delay, the jammer is located in the far field at (R) _j ,θ _j )，

The qth' th decoy can be expressed as

Wherein

The equivalent distance of the qth' th decoy is shown. The q' th decoy has a transmit and receive space-time frequency of

The snapshot data finally received by the receiving array element not only comprises the snapshot data of a true target, main lobe interference and side lobe interference, but also is expressed as

x＝x _s +x _J +x _I +x _n (16)

Wherein x is _n Is a mean of 0 and a variance of σ ² White gaussian noise.

And 3, step 3: compensating the snapshot data to obtain compensated snapshot data;

the emission space frequency of the invention is distance-dependent, which needs further compensation, and the compensated snapshot data is

Where p represents the number of false target delay pulses,

for the purpose of the transmit-receive joint compensation vector,

is a compensation vector of the emission domain, r _a Is the primary value distance.

The transmission frequencies of the true target and the false target after compensation are respectively

Wherein R is _u ＝c/(2f _r ) Is the maximum unambiguous distance.

And 4, step 4: suppressing side lobe suppression type interference on the compensated snapshot data in a receiving dimension by utilizing a generalized side lobe cancellation GSC (generalized minimum cost) method to obtain snapshot data after side lobe interference suppression;

the side lobe interference is different from the target angle, and is suppressed by a generalized side lobe cancellation (GSC) method in a receiving dimension. The receiving dimension is the number dimension of the receiving array elements, and the snapshot data after the sidelobe interference suppression is

Wherein w _R ＝w ₀ -w _a ，w _a ＝(C ^H RC) ^-1 (C ^H Rw ₀ )，

The covariance matrix is

x ^H _comp (l) Blocking matrix

|θ-θ ₀ | ≦ ε, θ is the range of the target that is likely to be in the main lobe, ε is the angle uncertainty parameter range.

And 5: and (3) suppressing main lobe deceptive jamming on the snapshot data after the side lobe jamming is suppressed in an equivalent emission dimension by using a non-adaptive method, and obtaining the snapshot data of the true target.

False target suppression is carried out, and the method can be divided into two steps: (1) Expanding equivalent transmitting freedom according to the idea of difference common array; (2) Adopting a non-adaptive beam forming method to restrain a false target, specifically:

step 5-1: obtaining the covariance matrix R of the snapshot data after the sidelobe interference suppression in the equivalent transmission dimension _t ；

Wherein, covariance matrix R _t Is composed of

Wherein K is the number of information sources, L is the number of snapshots, x _t And (5) carrying out snapshot on equivalent transmission dimension data after sidelobe interference suppression. l is the first snapshot, a _k For the k-th source steering vector,

is the noise power, I _M Is an M-dimensional identity matrix.

The equivalent virtual signal of the minimum redundant array is constructed by the second order statistic calculated by equation (19). The minimum redundancy array is exemplified by four array elements, the covariance matrix R of which _t Is composed of

Thus the covariance matrix R _t The ith row and jth column elements of (1) are:

wherein i, j =1,2, \ 8230;, M, f _comp Is the transmission frequency after the true and false target compensation.

Second order statistic r _i,j The exponential function term in (1) can be regarded as a guide vector of an equivalent virtual array element, and the position of each element in the virtual array element is as follows:

then

Each individual element in (a) may be equivalently represented using a differential co-array of the lowermost redundant array,

namely:

the differential common array V of the minimum redundant array at least comprises 2D _M With M physical array elements, 2D can be obtained _M An equivalent virtual array element. Thus, for covariance matrix R _t Vectorization is carried out, and equivalent virtual signals corresponding to the virtual array V can be obtained.

Step 5-2: the covariance matrix R _t Each row of the virtual array signals is superposed into a vector to obtain an equivalent virtual array signal z;

wherein the virtual array signal z is

Wherein,

is a virtual steering vector matrix corresponding to the virtual domain V,

a virtual guide vector is generated by a virtual guide vector,

contains K sources, e = vec (I) _M )。

Step 5-3: utilizing the G matrix to remove redundancy and rearrange the virtual array signal z to obtain a rearranged virtual array signal

The values indicate that: the virtual array signal z contains redundancy, the data is subjected to redundancy removal and rearrangement by using the G matrix, and the rearranged virtual array signal

Is composed of

Wherein,

a matrix of virtual steering vectors is formed,

the virtual guide vector is a vector of the virtual guide,

according to the difference of the minimum redundant array element number, the structure of the selection matrix G is different according to the difference of the covariance matrix element position. Taking 4 array elements as an example, G can be expressed as

Step 5-4: predicting a mainlobe deceptive interference location in a transmit frequency dimension to construct a covariance matrix R containing only virtual interference and noise _v ；

Since the main lobe deceptive interference can be predicted in the transmit frequency dimension, a virtual interference can be constructed.

The covariance matrix thus constructed is expressed as

Covariance matrix R _v Is composed of

Wherein R is _N And R _I For the constructed noise covariance matrix and interference covariance matrix,

in order to be able to measure the power of the noise,

in order to be a virtual interference power,

and a steering vector corresponding to the q virtual interference.

Step 5-5: the covariance matrix R is calculated using the Minimum Variance Distortionless Response (MVDR) criterion _v A non-adaptive weight vector of (a);

according to the Minimum Variance Distortionless Response (MVDR) criterion, the non-adaptive weight vector is

Wherein,

a _v (θ ₀ )＝[exp(-j2πd sin(θ ₀ )D _M /λ ₀ ),…,1,…,exp(j2πd sin(θ ₀ )D _M /λ ₀ )]is a true targetA virtual steering vector;

and 5-6: using the non-adaptive weight vector to the rearranged virtual array signal

And carrying out self-adaptive main lobe deception jamming suppression in a receiving dimension to obtain virtual snapshot data of the true target.

Wherein the true target is

Where H denotes the transpose of the matrix.

Simulation experiments can further prove the beneficial effects of the invention.

Simulation experiment I:

first, table 1 provides the array element positions of the minimum redundant array, as shown in fig. 2, and is illustrated by taking 4 array elements as an example, for example, the array elements of the quaternary uniform array are located at {0,1,4,6} d, and the array elements of the quaternary MRA are located at {0,1,4,6} d, where d represents the unit pitch, typically half wavelength, and the array of the four-array element MRA is shown in fig. 1.

TABLE 1 MRA array element distribution

The simulation sets that the number of the transmitting array elements and the number of the receiving array elements are 7, the target angle is 0 degrees, the SNR =20dB, the side lobe pressing type interference angles are 30 degrees, -30 degrees, the dry-to-noise ratio JNRn =40dB, the pulse repetition period PRF =10kHz, and the reference carrier frequency f ₀ =16GHz, wavelength λ ₀ =0.0187m, assuming there are 2 decoys, the dry-to-noise ratio INR =20db, INR =25db.

FIG. 3 is a MR-FDA-MIMO radar target and interference power spectrogram. As can be seen from the graph (b) in fig. 3, true and false targets can be distinguished in the transmit dimension, and false targets can be suppressed in the transmit dimension. As can be seen from the (c) diagram in fig. 3, the suppressed interference is distinguishable in the receiving dimension, and can be suppressed in the receiving dimension.

Fig. 4 is a diagram of a side lobe suppression result, which is distorted by a Minimum Variance Distortionless Response (MVDR) method because of a target signal component existing in snapshot sample data, and this greatly affects the performance of suppressing side lobe suppression interference. While the Generalized Sidelobe Canceling (GSC) method can effectively suppress the suppressed interference, with performance close to the ideal case with an accurate interference plus noise covariance matrix.

Fig. 5 shows a plot of output signal-to-noise ratio (SINR) versus input signal-to-noise ratio (SNR) after 300 monte carlo tests. As can be seen from the graph (a) in fig. 5, the Generalized Sidelobe Cancellation (GSC) method effectively suppresses sidelobe interference, and the performance approaches the upper bound in the case of a relatively small input signal-to-noise ratio. When the signal-to-noise ratio is greater than 20dB, the signal-to-noise ratio output of both generalized side lobe cancellation (GSC) and Minimum Variance Distortionless Response (MVDR) decreases due to the presence of the object in the sample. In particular, generalized Sidelobe Cancellation (GSC) performs better than Minimum Variance Distortionless Response (MVDR). As shown in fig. 5 (b), both the Generalized Sidelobe Cancellation (GSC) and Minimum Variance Distortionless Response (MVDR) methods are ineffective in the presence of mainlobe spoofing interference. Note that the Generalized Sidelobe Cancellation (GSC) curve differs from the ideal curve by approximately 27dB, which is exactly the sum of the dry-to-noise ratios of the two main lobe spoofing interferers.

A second simulation experiment: assuming that there are 14 decoys, the interference-to-noise ratio INR (1-7) =20db, INR (2-14) =25dB. The rest parameters are the same as those of the simulation experiment.

Fig. 6 compares the multi-mainlobe deception jamming suppression results of 7-array element Minimum Variance Distortionless Response (MVDR), virtual array adaptive method, and virtual array non-adaptive method. The 7-array Minimum Variance Distortionless Response (MVDR) method has only 7 array elements, so 14 decoys cannot be suppressed. The virtual array self-adaptive method is only

One snapshot sample data has errors in covariance estimation, and a plurality of false targets cannot be suppressed. The virtual array non-adaptive method is not influenced by the number of snapshot samplesWith sufficient degrees of freedom, multiple spurious objects can be suppressed.

In order to comprehensively evaluate the performance of the MR-FDA-MIMO radar, the variation curve of the output signal-to-interference-and-noise ratio with the input signal-to-noise ratio under the condition of multiple deceptive interferences is simulated. As can be seen from fig. 7, when there are 14 decoy targets, the output signal-to-noise ratio performance of the 7-element Minimum Variance Distortionless Response (MVDR) method is severely degraded, below the ideal curve of 32dB, because the number of spoofing interferers is greater than the number of transmitting elements. For a virtual array non-adaptive method, the degree of freedom is expanded, the number of virtual array elements is greater than the number of deception interferences, a plurality of interferences are completely inhibited, and the performance is close to an ideal curve.

Fig. 8 shows the signal to interference plus noise ratio (snr) loss performance comparison of the 7-array element Minimum Variance Distortionless Response (MVDR) method and the virtual array non-adaptive method for the multi-decoy case. It can be seen that the 7-array Minimum Variance Distortionless Response (MVDR) method loses robustness completely when the number of interferers is greater than the number of array elements. The virtual array non-adaptive method is not affected, a plurality of interferences are completely inhibited, and a performance curve is close to an ideal curve.

Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the 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.

While the present application has been described in connection with various embodiments, other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed application, from a review of the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the word "a" or "an" does not exclude a plurality.

The foregoing is a further detailed description of the invention in connection with specific preferred embodiments and it is not intended to limit the invention to the specific embodiments described. 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. An MR-FDA-MIMO radar interference suppression method, comprising:

step 1: establishing a signal transmitting model;

step 2: transmitting signals by using the transmitting array elements according to the signal transmitting model, and acquiring multiple times of snapshot data received by the receiving array elements;

the multi-time snapshot data comprise snapshot data of a true target, sidelobe pressing mode interference which is not greater than the number of the receiving array elements and main lobe deception interference which is greater than the number of the transmitting array elements;

and step 3: compensating the snapshot data to obtain compensated snapshot data;

and 4, step 4: suppressing side lobe suppression type interference on the compensated snapshot data in a receiving dimension by utilizing a generalized side lobe cancellation GSC (generalized minimum cost) method to obtain snapshot data after side lobe interference suppression;

and 5: and (3) suppressing main lobe deceptive jamming on the snapshot data after the side lobe jamming suppression in an equivalent transmission dimension by using a non-adaptive method, and obtaining virtual snapshot data of the true target.

2. The method of claim 1, wherein the signal transmission model in step 1 is:

where E is the transmit energy, M is the number of transmit array elements, T _P Is the pulse width, f _m ＝f ₀ +ΔfD _m Is the carrier frequency of the m-th antenna element, D _m The position corresponding to the array element of the minimum redundant array is shown, and delta f < f ₀ Phi is the envelope of the transmitted signal, the envelope of the transmitted signal satisfying

m′＝1,2, _… Mm ≠ m ', τ being the time delay, m being the mth transmitting array element, m' being the mth transmitting array element.

3. The MR-FDA-MIMO radar interference mitigation method according to claim 2, wherein the snapshot data of the true target is represented as

Wherein,

and

respectively, transmit and receive steering vectors, denoted as

Wherein, y _MN The receiving array element receives the snapshot data of the true target after the Mth transmitting array element transmits the signal,

in order to guide the vector for the distance,

is an angle steering vector, < i > represents a Hadamard product, < i > R ₀ ,θ ₀ ) Indicating the position of a true object in the far field, c is the speed of light, λ ₀ ＝c/f ₀ Is a reference wavelength, d _R The receive array element spacing, d the transmit element spacing, typically a half wavelength,

is a complex set;

the transmitting frequency and the receiving frequency corresponding to the true target are respectively

The side lobe suppression type interference is

Wherein ξ _q Is a uniform complex Gaussian random variable with a mean value of zero and a variance of

E {. Is the mathematical expectation operation;

and

respectively representing the transmit and receive steering vectors of the interference of the respective noise classes, n, due to the statistical nature and the obtrusiveness of the noise of the interference _T Satisfying zero mean value Gaussian noiseAcoustic distribution, i.e. n _T ～CN(0,I _M )；

The main lobe deceptive jamming is

Wherein Q' is the number of decoys, beta _q′ Is the scattering coefficient, τ, of the Q ' (Q ' =1, 2.., Q ') th false target _q 'is the delay of the q' th decoy, τ _j Is a two-way time delay, the jammer is located in the far field at (R) _j ,θ _j )，

The snapshot data in the step 2 is

x＝x _s +x _J +x _I +x _n

Wherein x is _n Is a mean of 0 and a variance of σ ² White gaussian noise.

4. The MR-FDA-MIMO radar interference mitigation method according to claim 3, wherein the snapshot data compensated in step 3 is

Wherein p represents the number of false target delay pulses,

for the purpose of a transmit-receive joint compensation vector,

is a compensation vector of the emission domain, r _a The distance is a distance of a main value,

the transmission frequencies of the true target and the false target after compensation are respectively

Wherein R is _u ＝c/(2f _r ) Is the maximum unambiguous distance.

5. The MR-FDA-MIMO radar interference suppression method according to claim 4, wherein the snapshot data after sidelobe interference suppression in the step 4 is

Wherein w _R ＝w ₀ -w _a ，w _a ＝(C ^H RC) ^-1 (C ^H Rw ₀ )，

The covariance matrix is

Blocking matrix

Where | theta-theta ₀ | ≦ ε, θ is the range of the target that is likely to be in the main lobe, ε is the angle uncertainty parameter range.

6. The MR-FDA-MIMO radar interference suppression method according to claim 5, wherein the step 5 comprises:

step 5-1: obtaining the covariance matrix R of the snapshot data after the sidelobe interference suppression in the equivalent transmission dimension _t ；

Step 5-2: the covariance matrix R _t Are superimposed into a vectorObtaining an equivalent virtual array signal z;

step 5-3: utilizing the G matrix to remove redundancy and rearrange the virtual array signal z to obtain a rearranged virtual array signal

Step 5-4: predicting a mainlobe deceptive interference location in a transmit frequency dimension to construct a covariance matrix R containing only virtual interference and noise _v ；

Step 5-5: the covariance matrix R is calculated using the Minimum Variance Distortionless Response (MVDR) criterion _v A non-adaptive weight vector of (a);

and 5-6: using the non-adaptive weight vector to the rearranged virtual array signal

And carrying out self-adaptive main lobe deception jamming suppression in the emission dimension to obtain a true target.

7. The MR-FDA-MIMO radar interference mitigation method according to claim 6, wherein the covariance matrix R in step 5-1 _t Is composed of

Wherein K is the number of information sources, L is the number of snapshots, x _t For suppressing the number of the equivalent emission dimension snapshots after the side lobe interference system, l is the ith snapshot, a _k The steering vector of the k-th source,

is the power of the k-th source,

is the noise power, I _M Is an M-dimensional identity matrix.

8. The method of claim 7, wherein the method further comprises the step of,

the virtual array signal z in the step 5-2 is

Wherein,

is a virtual steering vector matrix corresponding to the virtual field V,

a virtual guide vector is generated by a virtual guide vector,

contains K sources, e = vec (I) _M )，

Is a real number set;

the rearranged virtual array signal in the step 5-3

Is composed of

Wherein,

a matrix of virtual steering vectors is formed,

virtual directorThe amount of the compound (A) is,

9. the method as claimed in claim 8, wherein the covariance matrix R in step 5-4 is _v Is composed of

Wherein R is _N And R _I For the constructed noise covariance matrix and interference covariance matrix,

in order to be able to measure the power of the noise,

in order to be a virtual interference power,

and a steering vector corresponding to the qth virtual interference.

10. The method of claim 9, wherein the non-adaptive weight vector in step 5-5 is

Wherein,

a _v (θ ₀ )＝[exp(-j2πd sin(θ ₀ )D _M /λ ₀ ),…,1,…,exp(j2πd sin(θ ₀ )D _M /λ ₀ )]a virtual steering vector that is a true target;

the true target in the step 5-6 is

Where H denotes the transpose of the matrix.

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