Method for determining sea clutter sparseness of small-array shipborne ground wave radar and application

Abstract

The invention discloses a small-array shipborne ground wave radar sea clutter sparseness determination method and application. The method comprises the following steps: constructing a small-array shipborne ground wave radar signal model; extracting a sea clutter area of the small-array shipborne ground wave radar; the navigation condition of the shipborne platform is judged through inertial navigation data; extracting a sea clutter ridge of the small-array shipborne ground wave radar; a sea clutter characteristic spectrum is constructed, the rank of a sea clutter covariance matrix of the small-array shipborne ground wave radar is calculated, the size of the rank of the sea clutter covariance matrix is determined based on the Brench law under the condition that no yaw phenomenon exists, and the clutter rank is doubled under the condition that the yaw phenomenon exists; and determining the sparseness of the small-array shipborne ground wave radar. The method is applied to ship-borne ground wave radar sea clutter suppression. According to the method, the defect that the performance of a sparse recovery algorithm is limited due to the fact that the sparseness of an existing ground wave radar is uncertain is overcome, the influence of the ship speed, the yaw angle, the back lobe balance and other factors on the sea clutter sparseness is comprehensively analyzed, and effective determination of the sea clutter sparseness of the small-array shipborne ground wave radar is achieved.

Description

Technical Field

[0001] The invention relates to a method for determining sea clutter sparsity of a shipborne ground wave radar, and in particular to a method for determining sea clutter sparsity of a small array shipborne ground wave radar and an application thereof, belonging to the technical field of shipborne radars. Background Art

[0002] Ground wave radar, also known as high-frequency surface wave radar, operates in the high-frequency (3-30MHz) frequency band. It uses the diffraction propagation characteristics of vertically polarized high-frequency electromagnetic waves along the coastal surface to detect targets beyond the line of sight. Compared with other marine monitoring equipment, ground wave radar has the advantages of long observation distance, large coverage area, and all-weather continuous operation. It plays an important role in monitoring my country's exclusive economic zone, safeguarding national rights and interests, and protecting the marine environment. Ground wave radar is divided into shore-based ground wave radar and ship-borne ground wave radar according to the platform where the radar system is deployed. Compared with shore-based ground wave radar, ship-borne ground wave radar is flexible and maneuverable, and has a larger detection range. On this basis, the small array ship-borne ground wave radar uses a small array of less than 100 meters, which overcomes the problem of shortage of land and marine resources and expands the scope of application of ship-borne ground wave radar.

[0003] Although the small array shipborne ground wave radar has outstanding advantages, compared with the shore-based ground wave radar, the small array shipborne ground wave radar faces two challenges in sea clutter suppression: First, due to the size of the shipborne platform, the receiving antenna arranged on the shipborne platform is limited, resulting in a small radar array aperture and poor spatial resolution; second, due to the movement of the shipborne platform, the first-order sea clutter (hereinafter referred to as sea clutter) spectrum is broadened, and the greater the speed of the shipborne platform, the greater the broadening range, and a large number of slow-moving ship targets fall into the sea clutter spectrum, resulting in a low target signal-to-noise ratio, which seriously affects the sea clutter suppression performance of the small array shipborne ground wave radar. Therefore, the sea clutter suppression of the small array shipborne ground wave radar is more difficult, making it impossible to accurately carry out subsequent target detection.

[0004] The sea clutter suppression method of shore-based ground wave radar relies on signal differences in the time domain, frequency domain or spatial domain to achieve sea clutter suppression, but when the target is submerged by the broadened sea clutter, the frequency, distance and amplitude of the target and the sea clutter are consistent and cannot be detected. In order to solve the problem of sea clutter suppression of small array shipborne ground wave radar, some research has been carried out at home and abroad, with two representative ideas: spatial filtering and space-time joint. Considering that sea clutter has space-time coupling, the sea clutter suppression results obtained from a single airspace are not ideal. Therefore, the space-time adaptive processing (STAP) technology is used to suppress sea clutter to obtain better results. However, the performance of STAP depends on the accuracy of the clutter covariance matrix (CCM) estimated using sample data. In fact, the CCM of the target unit is difficult to obtain directly, and it needs to be estimated through training samples that meet the independent and identically distributed (IID) conditions. However, the array aperture of the small array shipborne platform is small, so the distance unit of the adjacent target unit does not meet the IID condition, resulting in the problem of insufficient uniform samples. Therefore, how to improve the sea clutter suppression performance of the small array shipborne ground wave radar under small sample conditions is the key to restricting the development of STAP technology. Sparse Recovery STAP (SR-STAP) can improve the performance of STAP technology under small sample conditions and has become a research hotspot. Sparsity is the basis and prerequisite of SR-STAP theory and method. The study of sea clutter sparsity analysis and sparsity determination is crucial for the application of SR-STAP method, which has important theoretical significance and practical application value. However, the existing literature does not give specific solution steps for the sparsity of clutter, especially the lack of sea clutter sparsity determination method under the small array shipborne ground wave radar system. Summary of the invention

[0005] The purpose of the present invention is to provide a method and application for determining the sparsity of a small array shipborne ground wave radar based on the sparsity of sea clutter, so as to solve the problem that the performance of a sparse recovery algorithm is limited due to the uncertainty of sparsity, and to provide a theoretical basis and parameter basis for subsequent sea clutter suppression algorithms.

[0006] This method extracts the sea clutter area based on the signal model of the small array shipborne ground wave radar. Considering that the shipborne platform is greatly affected by wind and waves in the actual marine environment, which will cause yaw, the inertial navigation data is used to judge the navigation status of the shipborne platform. The sparsity analysis under the airborne radar system is used to extract the sea clutter ridge of the small array shipborne ground wave radar, and the rank of the sea clutter covariance matrix is ​​calculated. The influence of different ship speeds, yaw angles, and back lobe balances on the sparsity of sea clutter is analyzed to achieve real-time estimation of the sparsity of the small array shipborne ground wave radar.

[0007] The method for determining the sea clutter sparsity of a small array shipborne ground wave radar is characterized by comprising the following steps: Step 1: Construct a small array shipborne ground wave radar signal model.

[0008] Step 2: Extract the sea clutter region of the small array shipborne ground wave radar: Position A single clutter unit, let is the unit vector pointing from the shipborne platform to the clutter unit. If the velocity vector is aligned with the array axis, there is no yaw phenomenon. , the Doppler frequency of the clutter unit is defined as , in, is the moving speed of the shipborne platform, is the movement speed of the shipborne platform, is the X-axis unit vector of the Cartesian coordinate system, is the radar wavelength, is the first-order Bragg scattering frequency.

[0009] Step 3: Use inertial navigation data to determine the navigation status of the ship-borne platform: Assume the yaw angle is ,when ° is considered to have no yaw phenomenon, on the contrary, °, it is a yaw situation.

[0010] Step 4: Extract sea clutter ridges of small array shipborne ground wave radar: The clutter spatial frequency is , For the case of no deviation, the Doppler frequency can be obtained from the first two equations. With spatial frequency There is the following relationship, , in, is the coherent accumulation period, let is the slope of the clutter line, indicating the number of half-element spacings that the platform passes through during one PRI. It can be seen that the normalized Doppler is linear in spatial frequency; The above equation defines the angle-Doppler trajectory in the presence of clutter in the non-yaw condition, which is called the “clutter ridge”; The clutter spatial frequency remains unchanged during yaw, and the clutter normalized Doppler frequency becomes , It has a long axis Axis and minor axis The ellipse of the axis first follows The axis is translated and then rotated around the origin.

[0011] Step 5: Construct the sea clutter characteristic spectrum and calculate the rank of the sea clutter covariance matrix of the small array shipborne ground wave radar: Covariance matrix Perform eigendecomposition , in is the eigenvalue The diagonal matrix of is decomposed into eigenvectors and eigenvalues, and the eigenvalues ​​are arranged in order from large to small to obtain the characteristic spectrum. The characteristic spectrum is composed of the eigenvalues ​​of interference and noise, where the effective rank is the number of eigenvalues ​​greater than the noise power; For the case of no yaw phenomenon, the rank of the sea clutter covariance matrix is ​​derived based on Brennan's law. At this time, the clutter rank is expressed as: , in, ; For the yaw phenomenon, the Doppler and spatial frequency are no longer in a linear relationship, and the Brennan law is no longer applicable; severe yaw will reduce the Doppler domain that can be used to detect targets, resulting in the number of potential interference clutter units doubling, requiring more degrees of freedom to effectively suppress clutter. At this time, the number of potential clutter resolution units increases, and the clutter rank increases by about one-fold, as shown in the following formula: .

[0012] Step 6: Determine the sparsity of the small array shipborne ground wave radar: The sparsity of sea clutter of small array shipborne ground wave radar is approximately equal to the rank of the covariance matrix. For the case of no yaw, the sparsity ; For the case of yaw, the corresponding sparsity will also increase with the increase of rank. .

[0013] The step 1: constructing a small array shipborne ground wave radar signal model is as follows: The shipborne platform moves at a constant velocity vector Movement, the true azimuth is expressed as an angle variable indicate, point to A unit vector in the direction Given by the formula , in , is the X-axis and Y-axis unit vector of the Cartesian coordinate system. Assume that the receiving array direction of the uniform linear array is determined by the position vector between the array elements. Specify the number of array elements. , the distance between adjacent antennas is , when the antenna is placed horizontally, ; Shipborne ground wave radar The channels are in the coherent accumulation period Received A pulse signal is obtained after sampling and distance processing. A three-dimensional data matrix block, Indicates distance, , No. Distance unit The data matrix is , At a certain point in time The array data at is , stands for transpose; Will According to the slow time dimension, it is stacked Column vector of , which is a space-time snapshot, Expressed as , Among them, the received target signal is expressed as the amplitude of the target and the target space-time guidance vector The product form of and denote sea clutter and noise respectively, and the target space-time guidance vector Expressed as , , , In the formula, is the target time orientation vector, is the target space steering vector, represents the target Doppler frequency, Indicates the angle of the target relative to the main axis of the shipborne radar, represents the Kronecker product.

[0014] The method for determining the sea clutter sparsity of a small array shipborne ground wave radar is applied in suppressing sea clutter of the shipborne ground wave radar.

[0015] The application of the method for determining the sparseness of sea clutter of a small array shipborne ground wave radar is characterized in that a sparse recovery algorithm is performed on the sea clutter of the shipborne ground wave radar.

[0016] The method for determining the sparseness of sea clutter in a small array shipborne ground wave radar is applied, wherein the sparse recovery algorithm includes an orthogonal matching pursuit OMP, which sets the condition for the end of iteration. When the rank of clutter in the radar system can be estimated more accurately, that is, the sparsity is known, as an appropriate number of iterations for the algorithm.

[0017] After a lot of derivation and analysis, it is found that the sparsity of small array shipborne ground wave radar is affected by factors such as ship speed, yaw, back lobe horizon, etc. Based on the influence of the above factors, the present invention proposes a sparsity determination method for sea clutter of small array shipborne ground wave radar based on sparsity, which solves the problem of limited performance of sparse recovery algorithm caused by uncertainty of sparsity. In particular, the method systematically explains the sparsity of sea clutter of small array shipborne ground wave radar.

[0018] Therefore, in view of the above reasons, the innovation of the present invention compared with the prior art is embodied in the following aspects: 1. By constructing a small array shipborne ground wave radar sea clutter signal model, the sea clutter area and sea clutter ridge are extracted, and the influence of the shipborne platform speed on the sea clutter ridge is given, which is not done in conventional sea clutter characteristic analysis.

[0019] 2. The inertial navigation data is used to judge the different navigation states of the shipborne platform, and the sea clutter sparsity analysis and sparsity estimation are divided into two typical cases to achieve sparsity estimation that is more in line with the actual situation.

[0020] 3. Based on the Brennan law of ground clutter of airborne radar, the rank of the sea clutter covariance matrix of small array shipborne ground wave radar is theoretically derived. The traditional clutter rank needs to be empirically judged by constructing the sea clutter characteristic spectrum, which is complicated and inaccurate.

[0021] 4. In the theoretical derivation of the covariance matrix rank of sea clutter for small array shipborne ground wave radar, the influence of the backlobe balance on the clutter rank is added. However, in the conventional sea clutter characteristic analysis, only the radar forward direction, that is, the azimuth direction, is considered. of clutter.

[0022] 5. In the theoretical derivation of the covariance matrix rank of sea clutter of small array shipborne ground wave radar, the influence of yaw on clutter rank is added. By analyzing the influence of factors such as shipborne platform speed, yaw angle, back lobe horizon on the characteristic spectrum of sea clutter, it can be closer to the actual ocean environment and achieve more accurate sparsity estimation. It has been analyzed and verified by the measured data of small array shipborne ground wave radar. In addition, the estimated sparsity can provide an effective parameter basis for the subsequent sea clutter suppression algorithm.

[0023] The present invention overcomes the defect that the existing sparse recovery algorithm has limited performance due to the uncertainty of the sparsity of the existing ground wave radar. By constructing a small array shipborne ground wave radar signal model, the influence of factors such as ship speed, yaw angle, and back lobe horizon on the sparsity of sea clutter is comprehensively analyzed, and the effective determination of the sea clutter sparsity of the small array shipborne ground wave radar, that is, twice the theoretical value of Brennan's law, is achieved, providing a theoretical basis and parameter basis for the subsequent sea clutter suppression algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a basic flow chart of the present invention.

[0025] Figure 2 Schematic diagram of small array shipborne ground wave radar detection under the shipborne platform geometry.

[0026] Figure 3 Schematic diagram of small array shipborne ground wave radar detection to simplify the coordinate system.

[0027] Figure 4 Schematic diagram of small array shipborne ground wave radar detection during yaw.

[0028] Figure 5 is the sea clutter ridge of the small array shipborne ground wave radar at different ship speeds, Among them, (a) the ship speed is 0 m / s, (b) the ship speed is 2.5 m / s, (c) the ship speed is 5 m / s, and (d) the ship speed is 7.5 m / s.

[0029] Figure 6 is the sea clutter ridge of the small array shipborne ground wave radar at different yaw angles, Among them, (a) the yaw angle is 0 degrees, (b) the yaw angle is 5 degrees, (c) the yaw angle is 45 degrees, and (d) the yaw angle is 90 degrees.

[0030] Figure 7 This is the sea clutter ridge of a small array shipborne ground wave radar when yaw.

[0031] Figure 8 This is the element pattern of a small array shipborne ground wave radar.

[0032] Fig. 9 This is the characteristic spectrum of sea clutter at different ship speeds.

[0033] Fig.10 for Characteristic spectra of sea clutter under different back-lobe balances at .

[0034] Fig.11 It is the characteristic spectrum of sea clutter at different yaw angles.

[0035] Fig.12 for Characteristic spectra of sea clutter under different back-lobe balances at .

[0036] Fig.13 is the sea clutter characteristic spectrum of the measured data. DETAILED DESCRIPTION

[0037] The present invention provides a technical solution for determining the sparseness of sea clutter of a small array shipborne ground wave radar based on sparsity. The schematic diagram of the process based on sparsity determination is shown in FIG. Figure 1 , including the following steps: Step 1: Construct a small array shipborne ground wave radar signal model: Each ship target can be regarded as a point target in a single direction. The sea clutter is composed of a large number of independent clutter sources, which are evenly distributed in the azimuth around the radar. Motion. Angle variable Refers to the true azimuth, pointing to A unit vector in the direction Given by the formula: (1) in , is the X-axis and Y-axis unit vector of the Cartesian coordinate system. Assume that the receiving array direction of the uniform linear array is determined by the position vector between the array elements. Specify the number of array elements. , the distance between adjacent antennas is , when the antenna is placed horizontally, .

[0038] Shipborne ground wave radar The channels are in the coherent accumulation period Received A pulse signal is obtained after sampling and distance processing. A three-dimensional data matrix block, Indicates distance. Distance unit The data matrix is (2) At a certain point in time The array data at is , Represents transpose.

[0039] Will According to the slow time dimension, it is stacked Column vector of , which is a space-time snapshot. It can be expressed as (3) Among them, the received target signal can be expressed as the amplitude of the target and its space-time steering vector The product form of and represent sea clutter and noise respectively. Target space-time guidance vector Expressed as , (4) , (5) , (6) In the formula, is the target time orientation vector, is the target space steering vector, represents the target Doppler frequency, Indicates the angle of the target relative to the main axis of the shipborne radar, represents the Kronecker product.

[0040] Step 2: Extract the sea clutter region of the small array shipborne ground wave radar: In a small array shipborne ground wave radar, due to the movement of the radar platform, the Doppler frequency center of the sea clutter is no longer fixed, but will change with the speed of the platform and the azimuth of the antenna, which will cause the broadening of the clutter spectrum. For a small array shipborne ground wave radar, the movement of the shipborne platform causes the positive and negative first-order Bragg peaks to shift. Considering the position A single clutter unit, let is the unit vector pointing from the platform to the clutter unit. Assume that the velocity vector is aligned with the array axis, that is, there is no yaw phenomenon. The Doppler frequency of this clutter unit is defined as (7) in, is the moving speed of the shipborne platform, is the first-order Bragg scattering frequency. Equation (7) shows the space-time coupling relationship of sea clutter of small array shipborne ground wave radar, that is, the azimuth sine of sea clutter scatterer and sea clutter Doppler frequency There is a linear coupling relationship between them.

[0041] Sea waves in different directions have different first-order Bragg frequencies. Since the radar has a certain beam width, it introduces different offsets to clutter in different directions, resulting in spectrum broadening. From equation (7), we can see that under ideal conditions, platform motion will cause sea clutter to broaden from one frequency value to cover the Doppler domain. range.

[0042] Step 3: Use inertial navigation data to determine the navigation status of the ship-borne platform: In the actual marine environment, the ship-borne platform is often affected by wind and waves, resulting in yaw, which affects the sparsity of the small array ship-borne ground wave radar. Inertial navigation data is used to judge the different navigation states of the ship-borne platform. Assume the yaw angle is ,when ° is considered to have no yaw phenomenon, on the contrary, °, it is a yaw situation.

[0043] Step 4: Extract sea clutter ridges of small array shipborne ground wave radar: The clutter spatial frequency is (8) For the case of no yaw, the normalized Doppler frequency can be obtained from formulas (7) and (8): With spatial frequency There is the following relationship, (9) make is the slope of the clutter line, which indicates the number of half-element spacings that the platform passes through during one PRI. It can be seen that the normalized Doppler is linear in spatial frequency.

[0044] Equation (9) defines the trajectory in the angle-Doppler domain where clutter exists without yaw, which is called the “clutter ridge”. In general, the clutter ridge can span a part of the Doppler domain or the entire Doppler domain, depending on the platform speed, operating wavelength and radar PRF.

[0045] The clutter spatial frequency remains unchanged during yaw, and the clutter normalized Doppler frequency becomes (10) The yaw angle is When , we transform equation (10) to , and then process the above equation to get (11) Furthermore, formula (11) is converted into an ellipse form and expressed as (12) In the above formula, non-zero The existence of the term indicates that a major axis is Axis and minor axis The ellipse of the axis first follows The axis is translated and then rotated around the origin. According to the literature published by EW Swokowski, the rotation angle of this type of oblique ellipse is satisfy (13) The rotation angle from The shaft rotates counterclockwise. and are the lengths of the major and minor axes respectively. The coordinate rotation transformation formula can be used again to obtain the major and minor axis information of the ellipse: (14) in (15) Therefore, the clutter ridges in the yaw condition are along After the axis moves up and down, The standard ellipse equations of the two oblique ellipses with angular rotation are: (16) When the yaw angle When becomes non-zero, the back lobe of the clutter ridge becomes obvious; For example, there are essentially two clutter ridges, such as at the target angle When , there are clutter at two Doppler frequencies, one from the front lobe and the other from the back lobe. Therefore, in the subsequent analysis, not only the front lobe clutter but also the back lobe clutter should be considered.

[0046] Step 5: Construct the sea clutter characteristic spectrum and calculate the rank of the sea clutter covariance matrix of the small array shipborne ground wave radar: Covariance matrix Perform eigendecomposition (17) in is the eigenvalue The diagonal matrix of , after eigendecomposition, we can get the eigenvectors and eigenvalues, and arrange the eigenvalues ​​from large to small to get the characteristic spectrum, which is composed of the eigenvalues ​​of interference and noise. The size of the effective rank (the number of eigenvalues ​​greater than the noise power) determines the minimum degree of freedom and the minimum number of samples required by the filter. Therefore, it is necessary to calculate the rank of the sea clutter covariance matrix of the small array shipborne ground wave radar.

[0047] However, in actual situations, this rank is unknown. Based on Brennan’s law, we need to analyze the sparsity of the first-order sea clutter of the shipborne ground wave radar and derive the theoretical rank of the sea clutter covariance matrix. Assuming that the platform velocity vector Vector with antenna array axis Complete alignment, that is, no yaw phenomenon, the clutter rank is expressed as: (18) in, However, in the actual ocean environment, the ship-borne platform is often affected by wind and waves, and the direction of movement may be slightly offset from the array axis, resulting in yaw, which leads to a significant increase in the clutter rank, exceeding the clutter rank predicted by formula (18).

[0048] All the previous analyses leading to the clutter covariance matrix are still valid in the case of yaw, except that the normalized Doppler frequency of a single clutter resolution unit changes from (9) to (10), resulting in the normalized Doppler and spatial frequency no longer being in a linear relationship. The Brennan law relies on the linear relationship between Doppler and spatial frequency. When No longer applicable.

[0049] Severe backlobe clutter and yaw will reduce the Doppler domain that can be used to detect targets. That is, yaw causes the number of potential interference clutter units to double, and more degrees of freedom are required to effectively suppress clutter. At this time, the number of potential clutter resolution units increases, and the clutter rank increases by about one time, as shown in equation (19): (19).

[0050] Step 6: Determine the sparsity of the small array shipborne ground wave radar: The sparsity of sea clutter of small array shipborne ground wave radar is approximately equal to the rank of the covariance matrix. For the case of no yaw, the sparsity .

[0051] For the case of yaw, the corresponding sparsity will also increase with the increase of rank. .

[0052] In the subsequent sea clutter suppression, sparse recovery space-time adaptive processing is required, and sparse recovery algorithms, such as the orthogonal matching pursuit (OMP) algorithm, need to set the conditions for the end of iteration. When the rank of clutter in the radar system can be estimated more accurately, that is, the sparsity is known, the condition for the end of iteration can be set to the number of iterations being equal to or slightly greater than the sparsity. Therefore, it can be considered that is the appropriate number of iterations of the algorithm.

[0053] Example Step 1: Figure 2 , 3 This is a schematic diagram of small array shipborne ground wave radar detection. Figure 2 is the geometric shape of the shipborne platform, and 3 is the simplified coordinate system. The unit vector in the simplified coordinate system can be used to model the signal of the small array shipborne ground wave radar. The channels are in the coherent accumulation period Received A pulse signal is obtained after sampling and distance processing. A three-dimensional data matrix block, Indicates distance. Distance unit Data Matrix According to the slow time dimension, it is stacked Column vector of , which is a space-time snapshot. It can be expressed as the superposition of target signal, sea clutter signal and noise signal.

[0054] Step 2: Based on the constructed small array shipborne ground wave radar signal model, extract the sea clutter area of ​​the small array shipborne ground wave radar. For the small array shipborne ground wave radar, the Doppler frequency of the clutter unit without yaw phenomenon The platform movement will cause the sea clutter frequency to broaden. The sea clutter area is .

[0055] Step 3: Figure 4 The following is a schematic diagram of the detection of a small array shipborne ground wave radar under yaw. The navigation status of the shipborne platform is determined by using the inertial navigation data. The yaw angle is ,when ° is considered to have no yaw phenomenon, on the contrary, °, it is a yaw situation.

[0056] Step 4: Based on step 3, the sea clutter ridges are extracted for both the non-yaw and yaw conditions by combining the measured data peaks with the theoretical space-Doppler frequency. From formula 9 in step 4, we can get Figure 5 The results shown, Figure 5The sea clutter ridge of a small array shipborne ground wave radar at different ship speeds shows four examples with platform speeds of 0m / s, 2.5m / s, 5m / s, and 7.5m / s. As the main lobe clutter increases, it occupies a larger Doppler region. In this case, there may be multiple angles of sidelobe clutter that have the same Doppler as the target, making suppression more difficult. From formula 10 in step 4, we can get Figure 6 The results shown, Figure 6 The sea clutter ridge at different yaw angles is shown in Figure 1. The part of the ellipse corresponding to the front half space of the antenna is drawn with a blue solid line, and the part corresponding to the back lobe clutter is drawn with a yellow solid line. The aligned case is seen as a degenerate ellipse, where the front and back lobe parts are on top of each other. It can be seen that when the yaw angle When becomes non-zero, the back lobe becomes apparent. Figure 7 When yaw Part of the sea clutter ridge illustration, it can be seen that at the target angle There are clutter at two Doppler frequencies, one from the front lobe and one from the back lobe, that is, there are essentially two clutter ridges. Therefore, severe backlobe clutter and yaw will reduce the Doppler range available for detecting targets, that is, yaw doubles the number of potential interfering clutter elements. Figure 8 is the array element radiation pattern, which is cosine in azimuth. The black represents the front lobe area and the back lobe area is the nominal back lobe level. They are -10 dB, -25dB, -45 dB, -50 dB and -85 dB respectively.

[0057] Step 5: Based on step 3, the rank of the sea clutter covariance matrix is ​​calculated for both the non-yaw and yaw conditions. From formulas 17, 18, and 19 in step 5, we can get Figure 9-13 The results shown, where Fig. 9 The characteristic spectrum of sea clutter at different ship speeds, and the value obtained by Brennan's law is represented by the dotted line. It can be seen that the characteristic spectrum shows a gradually decreasing trend, and Brennan's law accurately predicts the inflection point in the characteristic spectrum. It can also be noted that as the platform speed increases, the rank becomes larger. Fig.10 for The characteristic spectrum of sea clutter at different backlobe levels at 3m / s. The speed of the ship-borne platform is 3m / s. It can be seen that the tail of the characteristic spectrum shows a level drop that is basically linear with the backlobe level. This part of the characteristic spectrum is entirely caused by the backlobe part of the clutter ridge. The different backlobe levels have a negligible effect without yaw, and the numerical level of clutter is approximately equal to the level predicted by Brennan's law. Fig.11 is the characteristic spectrum of sea clutter at different yaw angles, and the speed of the ship-borne platform is 3m / s. , the number of non-zero eigenvalues ​​is approximately twice as expected due to the presence of the backlobe clutter ridge. Fig.12 for The characteristic spectrum of sea clutter at different backlobe levels, with a yaw angle of 50° and a ship-borne platform speed of 3m / s. It can be seen that the tail of the characteristic spectrum shows a level drop that is basically linear with the backlobe level. This part of the characteristic spectrum is entirely caused by the backlobe part of the clutter ridge. In the case of very low backlobe levels, the numerical level of clutter is approximately equal to the level predicted by Brennan's law. If the backlobe level is larger, the clutter rank will increase by about one time. In addition, it can be seen that when the backlobe balance is less than -50dB, the sea clutter characteristic spectrum tends to be unified, and the influence of the backlobe area can be ignored at this time. Fig.13 The sea clutter characteristic spectrum of the measured data, the yaw angle is 3°, and the ship-borne platform speed is 4.4 m / s. It can be seen that the inflection point in the characteristic spectrum is at twice the level predicted by the Brennan law.

[0058] Step 6: Based on steps 4 and 5, the rank of the sea clutter covariance matrix of the small array shipborne ground wave radar is obtained. For the case of no yaw, the sparsity ; For the case of yaw, the corresponding sparsity will also increase with the increase of rank, making The sparsity of the small array shipborne ground wave radar was finally determined.

Claims

1. A method for determining the sparseness of sea clutter for a small array shipborne ground wave radar, characterized by: The following steps are involved: Step 1: Construct a small array shipborne ground wave radar signal model; Step 2: Extract the sea clutter region of the small array shipborne ground wave radar: Position A single clutter unit, let is the unit vector pointing from the shipborne platform to the clutter unit. If the velocity vector is aligned with the array axis, there is no yaw phenomenon. , the Doppler frequency of the clutter unit is defined as ， in, is the moving speed of the shipborne platform, is the movement speed of the shipborne platform, is the X-axis unit vector of the Cartesian coordinate system, is the radar wavelength, is the first-order Bragg scattering frequency; Step 3: Use inertial navigation data to determine the navigation status of the ship-borne platform: Assume the yaw angle is ,when ° is considered to have no yaw phenomenon, on the contrary, °, it is a yaw situation; Step 4: Extract sea clutter ridges of small array shipborne ground wave radar: The clutter spatial frequency is ， For the case of no deviation, the Doppler frequency can be obtained from the first two equations. With spatial frequency There is the following relationship, ， in, is the coherent accumulation period, let is the slope of the clutter line, indicating the number of half-element spacings that the platform passes through during one PRI. It can be seen that the normalized Doppler is linear in spatial frequency; The above equation defines the angle-Doppler trajectory of clutter in the absence of yaw, which is called the "clutter ridge"; The clutter spatial frequency remains unchanged during yaw, and the clutter normalized Doppler frequency becomes ， It has a long axis Axis and minor axis The ellipse of the axis first follows The axis is translated, and then rotated around the origin; Step 5: Construct the sea clutter characteristic spectrum and calculate the rank of the sea clutter covariance matrix of the small array shipborne ground wave radar: Covariance matrix Perform eigendecomposition ， in is the eigenvalue The diagonal matrix of is decomposed into eigenvectors and eigenvalues, and the eigenvalues ​​are arranged in order from large to small to obtain the characteristic spectrum. The characteristic spectrum is composed of the eigenvalues ​​of interference and noise, where the effective rank is the number of eigenvalues ​​greater than the noise power; For the case of no yaw phenomenon, the rank of the sea clutter covariance matrix is ​​derived based on Brennan's law. At this time, the clutter rank is expressed as: ， in, ; For the yaw phenomenon, the Doppler and spatial frequency are no longer in a linear relationship, and the Brennan law is no longer applicable; severe yaw will reduce the Doppler domain that can be used to detect targets, resulting in the number of potential interference clutter units doubling, requiring more degrees of freedom to effectively suppress clutter. At this time, the number of potential clutter resolution units increases, and the clutter rank increases by about one-fold, as shown in the following formula: ， Step 6: Determine the sparsity of the small array shipborne ground wave radar: The sparsity of sea clutter of small array shipborne ground wave radar is approximately equal to the rank of the covariance matrix. For the case of no yaw, the sparsity ; For the case of yaw, the corresponding sparsity will also increase with the increase of rank. 。 2. The method for determining sea clutter sparsity of a small array shipborne ground wave radar according to claim 1, wherein the step 1: constructing a small array shipborne ground wave radar signal model is specifically as follows: The shipborne platform moves at a constant velocity vector Movement, the true azimuth is expressed as an angle variable indicate, point to A unit vector in the direction Given by the formula ， in , is the X-axis and Y-axis unit vector of the Cartesian coordinate system. Assume that the receiving array direction of the uniform linear array is determined by the position vector between the array elements. Specify the number of array elements. , the distance between adjacent antennas is , when the antenna is placed horizontally, ; Shipborne ground wave radar The channels are in the coherent accumulation period Received A pulse signal is obtained after sampling and distance processing. A three-dimensional data matrix block, Indicates distance, , No. Distance unit The data matrix is ， in, At a certain point in time The array data at is , stands for transpose; Will According to the slow time dimension, it is stacked Column vector of , which is a space-time snapshot, Expressed as ， Among them, the received target signal is expressed as the amplitude of the target and the target space-time guidance vector The product form of and denote sea clutter and noise respectively, and the target space-time guidance vector Expressed as ， ， ， In the formula, is the target time orientation vector, is the target space steering vector, represents the target Doppler frequency, Indicates the angle of the target relative to the main axis of the shipborne radar, represents the Kronecker product.

3. Application of the method according to claim 1 or 2 in sea clutter suppression of shipborne ground wave radar.

4. The use according to claim 3, characterized in that The sparse recovery algorithm is used to process the sea clutter of shipborne ground wave radar.

5. The use according to claim 4, characterized in that The sparse recovery algorithm includes orthogonal matching pursuit (OMP). The algorithm needs to set the condition for the end of iteration. When the rank of clutter in the radar system can be estimated more accurately, that is, the sparsity is known, as an appropriate number of iterations for the algorithm.

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