Missile-borne radar space-time interval adaptive clutter suppression method based on sum-difference channel

Abstract

According to the space-time interval adaptive clutter suppression method based on the sum-difference channel, sum-difference beams are utilized, the sum-difference channel is formed in a space domain, and target detection is facilitated while dimension reduction is carried out. A distance domain is utilized to form a distance dimension steering vector, a traditional space-time steering vector is expanded, space-time interval (STRAP) three-dimensional self-adaption is formed, a sum-difference channel is combined to complete the dimension reduction clutter suppression method, and the method can be used for missile-borne radar to achieve clutter suppression and target detection. Compared with a traditional dimensionality reduction STAP method, the method can effectively solve the problem that range ambiguity and errors affect clutter suppression performance, and has good clutter suppression performance.

Description

Technical Field

[0001] The present invention belongs to the field of signal processing technology, and further relates to a clutter suppression technology using sum-difference space-time range (STRAP) adaptively in the field of radar signal processing technology. The present invention can be used to effectively alleviate the STAP performance degradation caused by the estimation error of the clutter covariance matrix of the missile-borne radar. Background Art

[0002] When the missile-borne radar seeker is in the downward-looking working mode, it will face strong ground and sea clutter. Among them, the internal movement of the clutter will cause the amplitude and phase of the clutter signal to change randomly; the high-speed movement of the missile will cause the clutter spectrum to be broadened and the clutter Doppler blur is serious. At the same time, the missile-borne platform is different from the airborne platform. It not only has level flight movement, but also dives when attacking low-altitude targets, which will change the distribution of the clutter spectrum; furthermore, the clutter environment faced by the forward-looking array radar is different from that of the positive and side-looking array, and the clutter echo signals of the pulse radar are correlated, causing amplitude and phase errors, registration errors and channel errors, etc. These factors will affect the correct estimation of the clutter covariance matrix, and ultimately affect the clutter suppression capability of the radar.

[0003] In order to solve the above problems, clutter suppression is mainly performed through the STAP method. Considering the complexity of the clutter covariance matrix and the requirements for real-time calculation, the dimension reduction STAP method is mostly used. The resources of the missile-borne radar system are limited, and STAP must be processed by dimension reduction to meet the real-time requirements of the missile-borne system. In addition, the spatial degrees of freedom of the sum-difference STAP are only two channels, sum and difference, and it is consistent with the characteristics that missile-borne radars usually only have analog sum-difference antennas. In addition, missile-borne radars are usually configured with forward-looking arrays. At this time, the spatial and temporal distribution characteristics of clutter, especially the distribution of short-range clutter, have serious distance dependence, so that the range unit samples no longer meet the IID conditions, resulting in estimation errors of the clutter covariance matrix, which seriously affects the performance of the STAP filter. Summary of the invention

[0004] In order to solve the above problems existing in the prior art, the present invention provides a space-time adaptive clutter suppression method for missile-borne radar based on sum-difference channels. The technical problem to be solved by the present invention is achieved through the following technical solutions:

[0005] A space-time adaptive clutter suppression method for missile-borne radar based on sum-difference channels includes:

[0006] S100, receiving an echo signal by using a radar; the echo signal includes a target signal and a clutter signal;

[0007] S200, generating a space-time domain composite vector using the weights corresponding to the sum and difference channels;

[0008] S300. Construct a spatio-temporal-range three-dimensional steering vector, where the spatio-temporal-range three-dimensional steering vector comprises steering vectors in the spatial domain, temporal domain, and range domain.

[0009] S400. Replace the spatial-domain steering vector with the composite vector to obtain a redesigned spatial-domain steering vector, and substitute it into the spatio-temporal-range three-dimensional steering vector to obtain a new spatio-temporal-range three-dimensional steering vector.

[0010] S500. Concatenate the spatio-temporal composite vectors in sequence according to the range gate and Doppler channel order to obtain a concatenated composite vector; solve the covariance matrix of the concatenated composite vector; and calculate the clutter suppression weights in combination with the new spatio-temporal-range three-dimensional steering vector.

[0011] S600. Suppress the clutter signal in the echo signal by using the clutter suppression weights.

[0012] Advantageous effects:

[0013] The present invention proposes a spatio-temporal-range adaptive clutter suppression method based on sum-difference channels. By using sum-difference beams, sum-difference channels are formed in the spatial domain, which is beneficial for target detection while reducing the dimension. A range-dimensional steering vector is formed in the range domain to expand the traditional spatio-temporal steering vector, forming a spatio-temporal-range (STRAP) three-dimensional adaptivity, and combining with sum-difference channels to complete the clutter suppression method with dimension reduction. It can be used in airborne radars to achieve clutter suppression and target detection. Compared with the traditional dimension reduction STAP method, this method can effectively solve the problems of range ambiguity and error affecting the clutter suppression performance, and has good clutter suppression performance. The following will further elaborate on the present invention in conjunction with the drawings and embodiments. Description of the drawings

[0014] Figure 1 is a flowchart of an airborne radar spatio-temporal-range adaptive clutter suppression method based on sum-difference channels provided by the present invention;

[0015] Figure 2 is the range-Doppler channel spectrogram of clutter + target in the simulation of the present invention;

[0016] Figure 3 is the amplitude-phase error and registration error added in the simulation of the present invention;

[0017] Figure 4 is the array sum-difference beam pattern in the simulation of the present invention;

[0018] Figure 5 is the clutter suppression result of the 3DT sum-difference spatio-temporal adaptive method in the simulation of the present invention;

[0019] Figure 6 is the clutter suppression result of the spatio-temporal-range sum-difference spatio-temporal adaptive method in the simulation of the present invention. Specific Embodiments

[0020] The following further describes the present invention in detail with reference to specific embodiments, but the implementation manners of the present invention are not limited thereto.

[0021] The technical concept of the present invention is as follows: First, construct sum and difference channels, form sum and difference channels through an azimuth array, and obtain echo data reconstructed by the sum and difference channels; then adopt joint subspace partitioning in the spatial domain - time domain - range dimension. First, through joint processing of local Doppler channels, i.e., 3DT, reduce the computational dimension; finally, construct an extended spatio - temporal - range three - dimensional steering vector Sr, and calculate the optimal weight using the covariance matrix inversion method to achieve clutter suppression.

[0022] As Figure 1 shown, the present invention provides a method for airborne radar spatio - temporal - range adaptive clutter suppression based on sum and difference channels, including:

[0023] S100, utilize the radar to receive echo signals; the echo signals include target signals and clutter signals;

[0024] Suppose the airborne radar platform moves at a speed of Va, the altitude of the carrier aircraft is H, the radar operating wavelength is λ, the array is an N - element uniform linear array (ULA), and the element spacing d = λ / 2. The distribution of ground clutter scattering points satisfies the following geometric relationship:

[0025] The slant range from the target to the radar is: R(i) = R0 + ΔR·i (i = 1, 2,..., L). Where R0 is the reference slant range, ΔR is the range gate interval, and L is the total number of range gates. The elevation angle irradiated by the radar is: The azimuth angle distribution is θ ∈ [0, π].[[]END]]

[0026] To obtain the expression form of the clutter signal, it is necessary to construct its data model. Specifically, first generate the clutter reflection coefficient, then calculate the joint steering vector of the clutter, and finally obtain the clutter signal at the i - th range gate, the n - th element, and the k - th pulse.

[0027] Specifically, the clutter reflection coefficient corresponding to each azimuth angle is expressed as:

[0028]

[0029] In the formula, B c (θ) represents the clutter reflection coefficient corresponding to the azimuth angle θ, σ c (θ) represents a complex Gaussian random variable subject to a complex Gaussian distribution which describes the amplitude characteristic of the clutter reflection coefficient, and φ c represents a random phase subject to a uniform distribution. represents a uniform distribution on the interval (0, 2π);

[0030] For the i-th range gate, the spatial response of the array at azimuth angle θ is:

[0031]

[0032] where (θ0, φ0) is the center direction of the main lobe of the beam pointing.

[0033] The spatial steering vector of clutter is:

[0034]

[0035] The temporal steering vector is:

[0036]

[0037] Using the spatial steering vector and temporal steering vector of clutter, the joint steering vector can be calculated, expressed as:

[0038]

[0039] In the formula, W s (n - 1) represents the spatial steering vector of clutter of the (n - 1)-th array element, and W t (k - 1) represents the temporal steering vector of clutter of the k-th pulse;

[0040] Using the clutter reflection coefficient, the spatial response of the array element at azimuth angle θ at the i-th range gate, and the joint steering vector, determine the clutter signal of the i-th range gate, the n-th array element, and the k-th pulse, expressed as:

[0041]

[0042] In the formula, F(θ, φ(i)) represents the spatial response of the array element at azimuth angle θ at the i-th range gate, (θ0, φ0) is the center direction of the main lobe of the beam pointing, and R(i) represents the slant range from the radar to the i-th range gate.

[0043] S200, generate the spatio-temporal composite vector using the weights corresponding to the sum and difference channels respectively;

[0044] This step includes S210, generating the sum channel response using the weights obtained by the Taylor window and generating the difference channel response using the two-stage weights; S220, generating the spatio-temporal composite vector using the responses of the sum and difference channels and their corresponding weights.

[0045] The sum and difference channel method enables the composite data vector to have higher dimensionality and resolution in space-time adaptive processing (STAP), thereby more effectively suppressing clutter and improving target detection performance.

[0046] The spatial frequency corresponding to the target direction is: The sum channel weight vector uses a pre-designed weighting window, where the Taylor window is used. The sum channel spatial steering vector is as follows:

[0047] s s = exp{jWs0[0, 1, …, N - 1] T} ⊙ w s

[0048] w s is the weight value obtained from the Taylor window. The difference channel uses a simple two-segment weight value. Let

[0049]

[0050] Construct the spatial steering vector of the difference channel as

[0051] s d = exp{jWs0[0, 1, …, N - 1] T} ⊙ w d

[0052] The responses of the sum channel and the difference channel are respectively:

[0053]

[0054] In the formula, s s represents the spatial steering vector of the sum channel, d represents the element spacing, λ represents the radar operating wavelength, ψ represents the beam elevation angle, N represents the number of array elements, and s d represents the spatial steering vector of the difference channel.

[0055] In each range cell (index i) and pulse (index k), when calculating the signal, the phase terms in the spatial and temporal domains are considered, and amplitude-phase errors, channel errors, and registration errors are added to simulate the error environment. Then, the sum channel and the difference channel are processed respectively, and then combined to form a composite data vector for subsequent space-time adaptive processing. In the sum channel output, for each range cell i,

[0056]

[0057] Similarly, for the difference channel, the output can be obtained as:

[0058]

[0059] Combine the two-channel outputs into a space-time domain composite vector:

[0060]

[0061] S300, construct a space-time-range three-dimensional steering vector; the space-time-range three-dimensional steering vector includes the steering vectors in the spatial domain, temporal domain, and range domain;

[0062] This step includes S310, extracting the spatial domain data vector of the range gate to be detected from the echo signal and performing Doppler filtering on it to obtain the spatially domain data vector after Doppler filtering; S320, using the 3DT method to perform dimensionality reduction processing on the spatially domain data vector after Doppler filtering to obtain the spatially domain data vector under the 3DT method; S330, combining the spatially domain data vectors of three adjacent range gates under the 3DT method to obtain a spatio-temporal-range three-dimensional steering vector; the spatio-temporal-range three-dimensional steering vector is composed of steering vectors in the spatial domain, temporal domain, and range domain.

[0063] The spatially domain data vector after Doppler filtering is expressed as:

[0064] x(r0,f0) = [x(1,r0,f0),x(2,r0,f0),x(3,r0,f0)...,x(N,r0,f0)] T

[0065] In the formula, r0 and f0 represent the range gate to be detected and the Doppler channel.

[0066] The spatially domain data vector under the 3DT method is expressed as:

[0067] y(r0,f0) = [x T (r0,f -1 ),x T (r0,f0),x T (r0,f1)] T ;

[0068] In the formula, f -1 and f1 represent the Doppler channels adjacent to f0.

[0069] The spatially domain data vectors of three adjacent range gates under the 3DT method are expressed as:

[0070] z(r0,f0) = [y T (r -1 ,f0),y T (r0,f0),y T (r1,f0)] T ;

[0071] In the formula, r -1 and r1 represent the range gates adjacent to r0; y T (r -1 ,f0),y T (r1,f0) represent the data of adjacent range gates under the 3DT method. It can be easily obtained from the construction of the data vector that the spatio-temporal-range three-dimensional steering vector is expressed as:

[0072]

[0073] In the formula, r n represents the distance from the gate, f d represents the Doppler frequency, represents the azimuth angle of the target;

[0074] Among them, the spatial domain steering vector is:

[0075]

[0076] The time domain steering vector is expressed as:

[0077]

[0078] In the formula, w d is the two-stage weight value adopted by the difference channel, s(f d ) represents the frequency domain representation of the target signal at the Doppler frequency f d at.

[0079] The distance domain steering vector is expressed as:

[0080] Sr(r n ) = [g(r n-1 ), 1, g(r n+1 )] T

[0081] In the formula, g(r n-1 ) and g(r n-1 ) are the normalized compression gains at adjacent range gates. If the FFT weight is selected as the Doppler channel beamforming weight, and will become zero because the beamformers of the FFT are orthogonal to each other. g(r n ) is the distance beamforming gain, s r is the sampling value of the distance matching filter with length L, w r is the distance matching filtering function of the range gate r, h l represents the weighting coefficient in the range direction (such as the coefficient used for weighting processing such as window functions), s l represents the value of the transmitted signal at the l-th sampling point. In other words, considering an ideal point target at the gate r, the received signal vector s r diffuses along the range gate. When compressed with the matching filtering function w r , the energy of the target is concentrated. Therefore, g(r n-1 ) and g(r n-1 ) are the normalized compression gains at adjacent range gates and are independent of the range gate.

[0082] S400. Replace the spatial domain steering vector with the composite vector to obtain a redesigned spatial domain steering vector, and substitute it into the space-time-distance three-dimensional steering vector to obtain a new space-time-distance three-dimensional steering vector;

[0083] After combining the sum and difference channels, dimensionality reduction processing will be performed in the spatial domain, and the spatial domain steering vector will be reduced from the size of N*1 to 2*1. The redesigned spatial domain steering vector can be obtained as follows:

[0084] Ss = [Ss s Ss d

[0085] In the formula, Ss s is the product of the spatial domain vectors corresponding to the sum weights, and Ss d is the product of the spatial domain vectors corresponding to the difference weights.

[0086] S500. Concatenate the space-time domain composite vectors in sequence according to the range gate and Doppler channel order to obtain a concatenated composite vector; use it to solve the covariance matrix of the concatenated composite vector; and calculate the weights for clutter suppression in combination with the new space-time-distance three-dimensional steering vector;

[0087] Traverse the range gates from 2 to L-1 and the Doppler channels from 2 to K-1, concatenate the space-time composite vector x_vec, and calculate its covariance matrix to obtain:

[0088]

[0089] In the formula, x_vec i represents the space-time composite vector of the i-th range gate.

[0090] S600. Use the weights for clutter suppression to suppress the clutter signals in the echo signals.

[0091] According to the LCMV criterion, minimize the output power and constrain the target signal to be distortion-free, and the weights for clutter suppression can be expressed as:

[0092]

[0093] In the formula, S represents the space-time-distance steering vector of the sum and difference channels.

[0094] The hardware platform for the simulation experiment of the present invention is: Intel(R) Core(TM) i5-8265U CPU@1.60GHz, with a frequency of 1.8GHz, and Nvidia GeForce MX250.

[0095] The software used for the simulation experiment of the present invention is matlab2016b.

[0096] The simulation parameters of the present invention:​

[0097] The main simulation parameters of the present invention are shown in Table 1. The clutter-to-noise ratio is 20 dB, the signal-to-noise ratio is 20 dB, and the number of training samples in the range cell is 128. It is assumed that the target is in the 20th range cell.

[0098] Table 1 List of simulation parameters

[0099]

[0100] 2. Simulation content and result analysis:

[0101] First, the clutter spectrum distribution of the forward-looking missile-borne radar with fast movement is as shown in the left figure in the middle. It can be seen that the clutter spectra in different range regions are indistinguishable. In addition, the clutter spectra in different range regions strongly depend on the range, which means that the IID condition is not satisfied. Note that the traditional clutter compensation program can only be executed when there is no range ambiguity. In the simulation, the high PRF causes the range ambiguity problem, and the traditional clutter compensation technology is no longer effective. Figure 2 The right figure in the middle shows the energy distribution on all range cells, and a false target is set on the 20th range cell. Figure 2 Figure 3 Figure 4 is the added amplitude-phase error and registration error. is the array response after generating the sum-difference channels.

[0102] Figure 5 Figure 5 Clutter suppression using the 3DT sum-difference channel method is given. As shown in the right figure in the middle, there is an obvious suppression effect on the main lobe of the clutter. As can be seen from the left figure in the middle, due to errors and range ambiguity, multiple targets appear in the Doppler channel of the target, and the clutter suppression effect is not good. Figure 5

[0103] Figure 6

[0104] To solve this problem, the space-time steering vector is modified based on the sum-difference channels, the range dimension steering vector is added, and the range dimension information is introduced, which can better solve the problem of poor suppression effect caused by range ambiguity and errors. At the same time, the reduced-dimension method with the size of three range cells is used for the steering vector in the range dimension, reducing the computational complexity. Figure 6 The clutter suppression result using the sum-difference channel space-time-range adaptive method is shown. After suppression, not only the main lobe of the clutter is significantly suppressed, but also the errors and false targets in the range direction have been suppressed, and there is a better clutter suppression effect.

[0104] It should be noted that the terms "first" and "second" in the present invention are only for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined.

[0105] Although the present application has been described in conjunction with various embodiments herein, however, in the process of implementing the claimed present application, those skilled in the art can understand and realize other variations of the disclosed embodiments by viewing the accompanying drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "one" does not exclude a plurality of cases.

[0106] The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention pertains, without departing from the concept of the present invention, several simple deductions or substitutions can be made, and all should be regarded as belonging to the protection scope of the present invention.

Claims

1. A method for airborne radar space-time range adaptive clutter suppression based on sum-difference channels, characterized in that Including: S100, receiving an echo signal using a radar; The echo signal includes a target signal and a clutter signal; S200, generating an air-time domain composite vector using the weights corresponding to the sum and difference channels respectively; S300, constructing an air-time-range three-dimensional steering vector; the air-time-range three-dimensional steering vector includes steering vectors in the spatial domain, time domain, and range domain; S400, replacing the spatial domain steering vector with the composite vector to obtain a redesigned spatial domain steering vector, and substituting it into the air-time-range three-dimensional steering vector to obtain a new air-time-range three-dimensional steering vector; S500, splicing the air-time domain composite vector in sequence according to the range gate and Doppler channel order to obtain a spliced composite vector; calculating the covariance matrix of the spliced composite vector; and calculating the weight for clutter suppression in combination with the new air-time-range three-dimensional steering vector; S600, suppressing the clutter signal in the echo signal using the weight for clutter suppression.

2. The method for airborne radar space-time range adaptive clutter suppression based on sum-difference channels according to claim 1, characterized in that S200 includes: S210, generating a sum channel response using the weights obtained by the Taylor window, and generating a difference channel response using two-stage weights; S220, generating an air-time domain composite vector using the responses of the sum and difference channels and their corresponding weights.

3. The method for airborne radar space-time range adaptive clutter suppression based on sum-difference channels according to claim 2, wherein The responses of the sum channel and difference channel in S210 are respectively: where s s represents the spatial steering vector of the sum channel, d represents the element spacing, λ represents the radar operating wavelength, ψ represents the beam elevation angle, N represents the number of array elements, and s d represents the spatial steering vector of the difference channel.

4. The airborne radar space-time range adaptive clutter suppression method based on sum-difference channels according to claim 1, wherein S300 includes: S310, extracting the spatial domain data vector of the range gate to be detected from the echo signal, and performing Doppler filtering on it to obtain the spatially domain data vector after Doppler filtering; S320, performing dimensionality reduction processing on the spatially domain data vector after Doppler filtering using the 3DT method to obtain the spatially domain data vector under the 3DT method; S330, combining the spatially domain data vectors of three adjacent range gates under the 3DT method to obtain an air-time-range three-dimensional steering vector; the air-time-range three-dimensional steering vector is composed of steering vectors in the spatial domain, time domain, and range domain.

5. The method for airborne radar space-time range adaptive clutter suppression based on sum-difference channels according to claim 4, characterized in that The spatially domain data vector after Doppler filtering in S310 is expressed as: x(r0,f0) = [x(1,r0,f0), x(2,r0,f0), x(3,r0,f0)..., x(N,r0,f0)] T where r0 and f0 represent the range gate to be detected and the Doppler channel.

6. The method for airborne radar space-time range adaptive clutter suppression based on sum-difference channels according to claim 5, characterized in that The spatially domain data vector under the 3DT method in S320 is expressed as: y(r0,f0) = [x T (r0,f -1 ), x T (r0,f0), x T (r0,f1)] T ; where f -1 and f1 denote the Doppler channels adjacent to f0.

7. The method for airborne radar space-time range adaptive clutter suppression based on sum-difference channels according to claim 5, characterized in that The spatially domain data vectors of three adjacent range gates under the 3DT method in S330 are expressed as: z(r0,f0) = [y T (r -1 ,f0), y T (r0,f0), y T (r1,f0)] T ; where r -1 and r1 denote range gates adjacent to r0; The air-time-range three-dimensional steering vector is expressed as: where r n represents the distance to the door, f d represents the Doppler frequency, represents the azimuth angle of the target; Among them, the spatial domain steering vector is: The time domain steering vector is expressed as: Wherein, w d is the two-stage weight value adopted by the difference channel, s(f d ) represents the frequency-domain representation of the target signal at the Doppler frequency f d . The range domain steering vector is expressed as: Sr(r n ) = [g(r n-1 ), 1, g(r n+1 )] T In the formula, g(r n-1 ) and g(r n-1 ) are the normalized compression gains at adjacent range gates, s r is the sampling value of the range matching filter with length L, w r is the range matching filter function for range gate r, h l represents the weighting coefficient in the range direction, s l represents the value of the transmitted signal at the l-th sampling point.

8. The method for airborne radar space-time range adaptive clutter suppression based on sum-difference channels according to claim 5, characterized in that The redesigned spatial domain steering vector in S400 is expressed as: Ss = [Ss s Ss d ​ where, Ss s is the spatial domain vector product corresponding to the weight value, and Ss d is the spatial domain vector product corresponding to the difference weight value.

9. The method for airborne radar space-time range adaptive clutter suppression based on sum-difference channels according to claim 8, characterized in that, The covariance matrix of the spliced composite vector in S400 is expressed as: where x_vec i represents the space-time composite vector of the i-th range gate.

10. The method for airborne radar space-time range adaptive clutter suppression based on sum-difference channels according to claim 9, characterized in that, The weight for clutter suppression in S500 is expressed as: where S represents the air-time-range steering vector of the sum and difference channels.

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