Missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method

Abstract

The invention discloses a space-variant self-focusing imaging method for a missile-borne synthetic aperture radar sea surface moving target. The method comprises the following steps: acquiring a radar fundamental frequency echo signal; performing range pulse pressure and range migration correction on the radar fundamental frequency echo signal to obtain a correction signal, and further obtaining a coarse focusing radar image; extracting a single defocusing target image in the coarse focusing radar image, and inverting the single defocusing target image to an echo data domain to obtain data of single target energy; performing correction to obtain data after correction of the residual range walk; selecting a part of distance units from the data after the residual range walk is corrected, performing Doppler frequency modulation rate estimation on the selected part of distance units by adopting fractional Fourier transform, fitting the estimated Doppler frequency modulation rate by adopting a space-variant phase error model, and constructing a space-variant phase error compensation function of the target; and compensating the data after the correction of the residual range walk, and imaging. According to the invention, the refocusing effect of the moving ship target can be improved.

Description

Technical Field

[0001] The invention belongs to the technical field of digital signal processing, and in particular relates to a method for space-variable self-focusing imaging of sea surface moving targets by missile-borne synthetic aperture radar. Background Art

[0002] Marine monitoring is an important means of maintaining maritime order and ensuring marine safety. Ships are important carriers for human marine activities, an important part of the maritime battlefield, and an important target for marine monitoring. It is of great significance to obtain high-quality images of ship targets. Compared with optical images, Synthetic Aperture Radar (SAR), as an active microwave active sensor, can image marine ship targets at all times, all weather, and long distances, and is a powerful tool for monitoring the ocean.

[0003] Due to the influence of waves and other factors, in addition to the two-dimensional translational motion of the ship target sailing on the sea level, it also includes six degrees of freedom of swaying motion, namely three-dimensional swaying (roll, pitch, bow) motion and three-dimensional oscillation (sway, pitch, heave) motion, which makes the movement of the ship very complex. When imaging moving ship targets, traditional SAR imaging methods will cause defocusing and other phenomena, which has a serious impact on the subsequent detection, recognition and other applications of ship targets. Therefore, it is very important to image ship targets under complex motion conditions.

[0004] The ship is a rigid body. When it performs two-dimensional translational motion and three-dimensional oscillatory motion, the scattering points on the ship have the same motion state and the same impact on SAR imaging. Therefore, the existing SAR autofocus algorithm can be used for compensation. Traditional SAR image autofocus algorithms, such as the Map Drift (MD) algorithm and the Phase Gradient Autofocus (PGA) algorithm, usually assume that the phase error is non-space-variant, that is, the entire scene can be corrected using a unified phase error compensation function. When the ship target performs three-dimensional swaying motion, although the amplitude and period of the swaying angle of each scattering point on the ship target are the same, the distance of the swaying motion is proportional to its distance to the swaying axis, so the motion forms of each scattering point are different, resulting in the phase error of its radar echo being space-variant. Therefore, the traditional autofocus algorithm cannot meet the requirements of high-resolution imaging of ship targets under complex motion conditions. Summary of the invention

[0005] In order to solve the above problems existing in the prior art, the present invention provides a method for space-variable self-focusing imaging of sea surface moving targets by missile-borne synthetic aperture radar. The technical problem to be solved by the present invention is achieved by the following technical solutions:

[0006] In a first aspect, the present invention provides a method for space-variable self-focusing imaging of sea surface moving targets by missile-borne synthetic aperture radar, comprising:

[0007] According to the imaging scene information, the imaging space geometric model of the radar and the target is constructed, the instantaneous slant range model from the radar beam to any scattering point on the target is obtained, and the radar baseband echo signal is obtained;

[0008] Perform range pulse pressure and range migration correction on the radar baseband echo signal to obtain a correction signal; perform preprocessing on the correction signal to obtain a coarse focusing radar image;

[0009] Extract a single defocused target image from the coarsely focused radar image, and invert the single defocused target image into the echo data domain to obtain the data of the single target energy;

[0010] The data of single target energy is corrected by keystone transformation to obtain the data after correcting the residual distance movement;

[0011] Based on the maximum energy criterion, some range units are selected from the data after correcting the residual range movement, and the Doppler modulation rate of the selected range units is estimated by using fractional Fourier transform. The estimated Doppler modulation rate is fitted by using the space-varying phase error model, and the space-varying phase error compensation function of the target is constructed.

[0012] The target's space-variable phase error compensation function is used to compensate the data after correcting the remaining distance movement and image it.

[0013] Beneficial effects of the present invention:

[0014] 1. The present invention first obtains coarse focusing imaging, then detects and extracts the energy of a single defocused moving ship target, and finally performs fine focusing processing on the defocused moving ship target. This scheme can effectively eliminate the mutual influence between multiple ship targets with different motion states on the sea surface, which is beneficial to improving the refocusing effect of the moving ship target.

[0015] 2. The present invention selects some distance units containing the energy of moving ship targets for fractional Fourier transform processing based on the maximum energy criterion to estimate their Doppler modulation rate, which can effectively reduce the amount of calculation; by fitting the Doppler modulation rate estimated by the fractional Fourier transform, a space-varying phase error compensation function of the moving ship target is constructed, which can solve the problem that the traditional self-focusing algorithm cannot handle the space-varying phase error caused by the ship target performing three-dimensional swaying motion, and the focusing effect of the obtained complex moving ship target image is better.

[0016] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of a method for space-variable self-focusing imaging of sea surface moving targets by missile-borne synthetic aperture radar provided by an embodiment of the present invention;

[0018] Figure 2 It is a schematic diagram of an imaging space geometric model of a radar and a target provided by an embodiment of the present invention;

[0019] Figure 3 is a schematic diagram of a ship target scattering point model provided by an embodiment of the present invention;

[0020] Figure 4 It is a schematic diagram of a coarse focusing imaging result of a single moving ship target detected by SP-CFAR provided by an embodiment of the present invention;

[0021] FIG5( a ) is a schematic diagram of a phase error compensation function estimated by an existing PGA algorithm;

[0022] FIG5( b ) is a schematic diagram of a phase error compensation function estimated by an algorithm provided in an embodiment of the present invention;

[0023] Figure 6 It is a schematic diagram of the result of refocusing a single defocused moving ship target image by the existing PGA algorithm;

[0024] Figure 7 It is a schematic diagram of the result of refocusing a single defocused moving ship target image by the algorithm provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0026] See also Figure 1 , Figure 1 The present invention provides a flowchart of a method for space-varying self-focusing imaging of a sea surface moving target by a missile-borne synthetic aperture radar, which comprises:

[0027] S101. Construct an imaging space geometric model of the radar and the target according to the imaging scene information, obtain an instantaneous slant range model from the radar beam to any scattering point on the target, and obtain a radar baseband echo signal.

[0028] Specifically, in this embodiment, see Figure 2 , Figure 2 : is a schematic diagram of an imaging space geometric model of a radar and a target provided by an embodiment of the present invention. Constructing an imaging space geometric model of a radar and a target includes:

[0029] With the point O vertically below the radar as the origin, establish the radar three-dimensional imaging coordinate system OXYZ. The radar can be a missile-borne synthetic aperture radar. The radar moves in a uniform straight line along the heading at a constant speed v, the front oblique angle is θ, and the front oblique angle of the sea is θ g , the distance from the center of the radar beam to the center of the imaging scene is R S , the distance between point O vertically below the radar and the target is R B , the radar height from the sea surface is H, and

[0030] See also Figure 3 , Figure 3 is a schematic diagram of a ship target scattering point model provided by an embodiment of the present invention. With the target gravity center o as the origin, a target fixed coordinate system oxyz is established. The target may be a ship target. The target speed along the course is v x , tangential velocity is v y , and three-dimensional swaying motion. The three-dimensional swaying motion of the ship target can be equivalent to the superposition of a series of sinusoidal functions. In order to simplify the analysis, each dimensional swaying motion of the target can be equivalent to a single-frequency sinusoidal motion. When any scattering point (x n ,y n ,z n ) performs three-dimensional swing motion, the coordinates of the scattering point are updated to Its expression is:

[0031]

[0032] Among them, t a represents the azimuth slow time, θ y (t a ),θ p (t a ) and θ r (t a ) represent the yaw, pitch and roll angles respectively, and their expressions are as follows:

[0033]

[0034] Among them, A y , A p , A r Respectively represent the amplitude of the heading angle, pitch angle and roll angle, T y , T p , T r denote the periods of the heading angle, pitch angle and roll angle, respectively, φ y ,φ p ,φ r They represent the initial phases of the heading angle, pitch angle and roll angle respectively;

[0035] When the scattering point moves in a two-dimensional plane, the coordinates are updated to (x n ′,y n ′,z n ′), its expression is:

[0036]

[0037] in,

[0038] t a Indicates slow time of direction.

[0039] In this embodiment, considering that the ship target has not only two-dimensional translational motion on the sea level but also three-dimensional swaying motion, the instantaneous slant range model from the radar beam to any scattering point on the target is obtained, including:

[0040] According to the imaging space geometric model, the instantaneous slant range model R(t a ), whose expression is:

[0041]

[0042] Since the coherent processing time of missile-borne SAR is less than the period of three-dimensional swing motion, the three-dimensional swing motion with sinusoidal variation can be approximated as three-dimensional nonlinear motion, which can be described by Taylor expansion formula. The instantaneous slant range model R(t a ) is Taylor expanded, and the third-order and higher-order terms are discarded, and updated to:

[0043]

[0044] in,

[0045] in,

[0046]

[0047] In formula (6), α 1 and α 2 Caused by radar motion, usually compensated in SAR imaging processing; β 1 and β 2 It is caused by the two-dimensional translational motion of the ship target. If it is not compensated, the imaging result will be defocused, but the phase error caused by it is non-space-varying; γ 1 and γ 2 It is caused by the three-dimensional swaying motion of the ship target, and the phase error caused by it is spatially variable.

[0048] In this embodiment, the missile-borne SAR usually transmits a linear frequency modulation signal with a fixed pulse repetition frequency. Where rect(·) is the rectangular window function, T p is the pulse width, f c is the carrier frequency, K r is the range modulation frequency. By removing the carrier frequency of the radar echo signal, the missile-borne forward squint SAR baseband echo signal s(t r ,t a ), whose expression is:

[0049]

[0050] Among them, w r (·) represents the distance window function, w a (·) represents the azimuth window function, t r represents the distance-to-time, c represents the speed of light, K r represents the distance modulation frequency, λ represents the wavelength, R(t a ) represents the instantaneous slant range model from the radar beam to any scattering point on the target.

[0051] S102, performing range pulse pressure and range migration correction on the radar baseband echo signal to obtain a correction signal; and preprocessing the correction signal to obtain a coarse focusing radar image.

[0052] Specifically, in this embodiment, the radar baseband echo signal is corrected for range pulse pressure and range migration to obtain a correction signal; and the correction signal is preprocessed to obtain a coarsely focused radar image, including:

[0053] Since the motion form of the ship target is unknown, β in the slant range model 1 , β 2 , γ 1 and γ 2 It cannot be obtained directly. According to the radar baseband echo signal, the range matched filter function and the range migration correction phase factor function are constructed, and their expressions are:

[0054]

[0055] Among them, H r1 (t r ) represents the distance matched filter function, H r2 (t r ,t a ) represents the range migration correction phase factor function;

[0056] According to the range matched filter function and the range migration correction phase factor function, the radar baseband echo signal is corrected for range pulse pressure and range migration to obtain the correction signal s 1 (t r ,t a ), whose expression is:

[0057]

[0058] Where B represents the signal bandwidth, That is, the range migration component caused by the radar movement is corrected, while the remaining range migration caused by the ship target movement is not corrected, which will affect the focusing effect of the moving target;

[0059] According to the radar baseband echo signal, the azimuth matched filter function H is constructed. a1 (t a ), whose expression is:

[0060]

[0061] The azimuth matched filter function is multiplied with the correction signal, and the multiplication result is subjected to azimuth Fourier transform (FFT) to obtain the coarse focusing radar image s 2 (t r ,f a ). The phase error caused by the ship target motion will lead to the azimuth matched filter function H a1 (t a ) mismatch, resulting in azimuth defocusing of the coarsely focused image of the ship target, and the defocusing forms of ship targets in different motion states are also different.

[0062] S103, extracting a single defocused target image from the coarsely focused radar image, and inverting the single defocused target image into an echo data domain to obtain data of single target energy.

[0063] Specifically, see Figure 4 , Figure 4 FIG. 1 is a schematic diagram of a coarse focusing imaging result of a single moving ship target detected by SP-CFAR according to an embodiment of the present invention. In this embodiment, the SP-CFAR detection algorithm can be used to obtain the coarse focusing SAR image s 2 (t r ,f a ) to detect and extract a single defocused moving ship target image s 3 (t r ,f a ) to eliminate the influence of different moving ship targets on the subsequent refocusing process.

[0064] In this embodiment, a superpixel constant false alarm rate (SP-CFAR) detection algorithm is used to detect and extract a single defocused moving ship target image and invert it to the echo data domain to obtain a single defocused moving ship target data.

[0065] S104, using keystone transformation to correct the data of single target energy, to obtain corrected data of remaining distance movement.

[0066] Specifically, in this embodiment, a single defocused target image is inverted into the echo data domain to obtain data of a single target energy, including:

[0067] Invert a single defocused target image into the echo data domain to obtain data s 3 (t r ,t a ), whose expression is:

[0068]

[0069] It can be seen from equation (13) that the motion of the ship target will produce residual range migration in the range direction and phase error in the azimuth direction, causing serious defocusing of the imaging result.

[0070] For data 3 (t r ,t a ) performs distance Fourier transform to obtain the data s of single target energy 3 (f r ,t a ), whose expression is:

[0071]

[0072] Among them, f r Represents the distance frequency, f c Indicates the carrier frequency.

[0073] The second and third phase terms in equation (14) indicate that there is a coupling relationship between the distance dimension and the azimuth dimension, which will cause defocusing in the imaging results.

[0074] In this embodiment, virtual slow time is constructed by keystone transformation principle, and its expression is:

[0075]

[0076] In this embodiment, the keystone transform is a keystone transform (KT) algorithm.

[0077] Remove the linear coupling relationship between the distance dimension and the azimuth dimension, that is, the second phase term in equation (14), and substitute equation (15) into equation (14) to obtain s 3 (f r ,τ a ), since the transmitted signal bandwidth is much smaller than the carrier frequency, that is, fr <<f c ,f r ∈[-B / 2,B / 2], so there is an approximate relationship: f c / (f r +f c )≈1-f r / f c ;

[0078] Virtual slow time combines the data of single target energy and converts the data of single target energy into 3 (f r ,t a ) is updated to:

[0079]

[0080] From the second phase term of equation (16), it can be seen that the keystone transformation eliminates the linear coupling between the range dimension and the azimuth dimension, that is, corrects the linear range movement caused by the motion of the ship target. 3 (f r ,τ a ) to perform distance inverse Fourier transform (IFFT) processing to obtain the data s after correcting the remaining distance movement 4 (t r ,τ a ), whose expression is:

[0081]

[0082] In formula (17), since the carrier frequency f c Very large, the distance is fast, the second term of the time dimension can be ignored, and the data after correcting the remaining distance s 4 (t r ,τ a ) is simplified to:

[0083]

[0084] Among them, c represents the speed of light. After KT processing, the residual range movement caused by the movement of the ship target is corrected, and the energy of a single scattering point is located in one range unit.

[0085] S105. Based on the maximum energy criterion, select some distance units from the data after multiple corrections of the remaining distance movement, use Fractional Fourier Transform (FrFT) to estimate the Doppler frequency modulation rate of the selected distance units, use the space-varying phase error model to fit the estimated Doppler frequency modulation rate, and construct the space-varying phase error compensation function of the target.

[0086] In this embodiment, fractional Fourier transform is used to estimate the Doppler modulation rate of selected range units, including:

[0087] If the azimuth FFT processing is directly performed on equation (18), the SAR image of the ship target in the range Doppler domain can be obtained. However, since the phase error caused by the motion of the ship target is not compensated, the imaging result will be defocused in azimuth. Since the first-order phase error will only cause the displacement of the imaging result of the moving ship target and will not affect the SAR image quality, the first-order phase error is ignored and only the second-order phase error caused by the motion of the ship target is considered. In addition, due to the particularity of the three-dimensional swaying motion of the ship target, the distance from the scattering point to the swaying axis is different, and its motion state is also different, which leads to the phase error having spatial variation and cannot be processed using the traditional self-focusing algorithm.

[0088] Fractional Fourier transform (FrFT) is a good time-frequency analysis tool. It can be understood as rotating the coordinate axis of the signal counterclockwise at an arbitrary angle α in the time-frequency plane with the origin as the center to the fractional Fourier domain, and defining the fractional Fourier domain as the u domain. The p-order FrFT of the function x(t) in the time domain is defined as:

[0089]

[0090] Among them, K p (u, t) is the kernel function of FrFT, that is:

[0091]

[0092] in, α=pπ / 2, α is the rotation angle, and p represents the order of FrFT.

[0093] As mentioned above, the phase error caused by the ship target motion only considers the second-order term, and for the signal s 4 (t r ,τ a ) performs FrFT, and ignores the distance dimension, constant phase term and first-order phase term, only retains the azimuth second-order phase term, and the p-order fractional Fourier transform result is S p (u), its expression is:

[0094]

[0095] Among them, A α represents the fractional Fourier transform coefficient, u represents the fractional Fourier domain, and α represents the rotation angle corresponding to the maximum peak point in the fractional Fourier transform;

[0096] The process is repeated until the Doppler modulation rate estimation value of the selected part of the range units is obtained.

[0097] In order to make the signal s 4 (t r ,τ a ) has the best energy concentration, and the final result should be the sinc function, that is, The coefficient should be 0, then we can get β 2 +γ 2 =λcotα / 4, where α is the rotation angle corresponding to the maximum peak point in the FrFT result, from which the signal s can be estimated 4 (t r ,τ a )’s Doppler modulation frequency.

[0098] Based on the above analysis, the signal s 4 (t r ,τ a ) Based on the maximum energy criterion, N distance units containing the ship target energy are selected, and the N distance units are processed by FrFT respectively to estimate the Doppler modulation frequency corresponding to the N distance units, which is recorded as K ai , the corresponding distance unit position is recorded as r i , where i=1,2,…,N.

[0099] In this embodiment, it is mentioned above that the phase error caused by the three-dimensional swaying motion of the ship target changes slowly with the position of the scattering point on the ship target, and the phase error here mainly refers to the second-order phase error. A linear model is used here to describe the space-varying phase error model, that is, K a =ar+b, a and b both represent unknown parameters, r represents the distance position; according to the Doppler modulation rate corresponding to the above-estimated partial distance unit, in order to solve the space-varying phase error model, it can be regarded as a linear regression problem. Since there is a certain random error ε between the estimated Doppler modulation rate and the actual Doppler modulation rate, in order to achieve the goal of minimizing ε, the least squares method is used for straight line fitting. The main idea of ​​the least squares method is to solve the unknown parameters so that the difference between the theoretical value and the observed value, that is, the sum of the squares of the errors, is minimized, that is:

[0100]

[0101] Let K = [K a1 K a2 …K aN ] T , A=[ab] T , the actual Doppler modulation frequency is obtained, and its expression is:

[0102] K = RA + E;

[0103] Where E represents the random error matrix, K represents the observed value, and RΑ represents the theoretical value.

[0104] According to the matrix form of the least squares method The coefficient matrix Α is obtained by solving the equation:

[0105] A=(R T R) -1 R T K;

[0106] in,(·) T Indicates the transpose of a matrix, (·) -1 It means to find the inverse of the matrix, ||·|| 2 represents the 2-norm of the matrix;

[0107] According to the coefficient matrix A and the target's distance unit position, the global Doppler modulation rate of the target is constructed to obtain the target's space-varying phase error compensation function H(t r ,t a ).

[0108] The target space-varying phase error compensation function H(t r ,t a ) is multiplied with the data after multiple corrections for the remaining distance movement, and the multiplication result is Fourier transformed to obtain a target fine-focus image.

[0109] S106, using the target's space-variant phase error compensation function to compensate for the multiple corrected residual distance movement data, and forming an image.

[0110] Specifically, in this embodiment, the target's space-varying phase error compensation function is multiplied by a plurality of corrected residual distance movement data, and the multiplication result is Fourier transformed to obtain a target fine-focus image.

[0111] In summary, the present invention provides a method for space-variable self-focusing imaging of sea surface moving targets by missile-borne synthetic aperture radar, which has the following beneficial effects:

[0112] 1. The present invention first obtains coarse focusing imaging, then detects and extracts the energy of a single defocused moving ship target, and finally performs fine focusing processing on the defocused moving ship target. This scheme can effectively eliminate the mutual influence between multiple ship targets with different motion states on the sea surface, which is beneficial to improving the refocusing effect of the moving ship target.

[0113] 2. The present invention selects some distance units containing the energy of moving ship targets for fractional Fourier transform processing based on the maximum energy criterion to estimate their Doppler modulation rate, which can effectively reduce the amount of calculation; by fitting the Doppler modulation rate estimated by the fractional Fourier transform, a space-varying phase error compensation function of the moving ship target is constructed, which can solve the problem that the traditional self-focusing algorithm cannot handle the space-varying phase error caused by the ship target performing three-dimensional swaying motion, and the focusing effect of the obtained complex moving ship target image is better.

[0114] In an optional embodiment of the present invention, the effect of the space-varying self-focusing imaging method of sea surface moving target by missile-borne synthetic aperture radar provided in the above embodiment is verified by simulation experiments, specifically:

[0115] 1. Simulation conditions

[0116] Set the missile-borne forward-looking synthetic aperture radar system parameters as shown in Table 1.

[0117] Table 1 Missile-borne synthetic aperture radar system parameters

[0118] parameter Value parameter Value Carrier frequency (GHz) 16 Signal duration (μs) 20 Bandwidth (MHz) 100 Pulse repetition frequency (Hz) 12000 Sampling rate (MHz) 150 Subaperture time (s) 0.34 Front oblique angle (°) 30 Missile-borne radar speed (m / s) 3400 Center slant distance (km) 60 Height (km) 25

[0119] The three-dimensional swaying motion parameters of the destroyer under different sea conditions are shown in Table 2. The three-dimensional swaying motion parameters of the destroyer under level 5 sea conditions are used in the simulation experiment.

[0120] Table 2 Parameters of destroyer's three-dimensional swaying motion under different sea conditions

[0121]

[0122] The ship target scattering point model used in the simulation process is as follows: Figure 3 Its related parameters are shown in Table 3.

[0123] Table 3 Ship scattering point model parameters

[0124]

[0125]

[0126] In the simulation experiment, the PGA algorithm is used to compare with the algorithm of the present invention.

[0127] 2. Simulation content and result analysis

[0128] See also Figure 5(a) and 5(b) 5(a) is a schematic diagram of a phase error compensation function estimated by an existing PGA algorithm, and FIG. 5(b) is a schematic diagram of a phase error compensation function estimated by an algorithm provided in an embodiment of the present invention, Figure 6It is a schematic diagram of the result of refocusing a single defocused moving ship target image by the existing PGA algorithm. Figure 7 It is a schematic diagram of the result of refocusing a single defocused moving ship target image by the algorithm provided in an embodiment of the present invention.

[0129] Figure 4 It shows that due to the complexity of the ship target movement, the coarse focusing SAR imaging results of a single moving ship target have serious defocusing phenomenon; Figure 5 shows that the PGA algorithm can only estimate the non-space-varying phase error while the algorithm of the present invention can estimate the space-varying phase error, and the non-space-varying phase error estimated by the PGA algorithm is inaccurate due to the influence of the space-varying phase error; Figure 6 It shows that the PGA algorithm cannot solve the space-varying phase error caused by the rocking motion, resulting in severe defocusing in the azimuth direction of the imaging results. Figure 7 It shows that in the refocusing imaging results of the algorithm of the present invention, each scattering point on the moving ship target is well focused.

[0130] In order to further verify the treatment effect of the present invention, Figure 4 , Figure 6 and Figure 7 The image parameters of the image are compared, and the image parameters include the entropy and contrast of the image. The results are shown in Table 4. As can be seen from Table 4, the entropy value and contrast of the processing result of the algorithm of the present invention are significantly improved compared with the original image, wherein the lower the entropy value and the higher the contrast, the better the image focusing effect.

[0131] Table 4 Comparison of image parameters of different processing algorithms

[0132] Image number Entropy Contrast Figure 4 3.21 2.81 Figure 6 3.03 2.87 Figure 7 2.25 4.55

[0133] In summary, the simulation experiment verifies the correctness, effectiveness and reliability of the present invention. The algorithm of the present invention can solve the problem of spatial variability of phase error that cannot be handled by the traditional self-focusing algorithm, so as to achieve a good refocusing effect of moving ship targets; compared with the existing moving target imaging algorithm, the steps of the present invention are relatively simple, the formula derivation is relatively concise, there is no large number of iterative operations, the amount of calculation is small, and the implementation is simple.

[0134] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the term "include", "comprise" or any other variant is intended to cover non-exclusive inclusion, so that the article or device including a series of elements includes not only those elements, but also other elements that are not explicitly listed. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the article or device including the elements. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The orientation or position relationship indicated by "up", "down", "left", "right", etc. is based on the orientation or position relationship shown in the accompanying drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention.

[0135] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification.

[0136] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the scope of protection of the present invention.

Claims

1. A missile-borne synthetic aperture radar space-variable self-focusing imaging method for sea surface moving targets, characterized in that: include: According to the imaging scene information, the imaging space geometric model of the radar and the target is constructed, the instantaneous slant range model from the radar beam to any scattering point on the target is obtained, and the radar baseband echo signal is obtained; Performing range pulse pressure and range migration correction on the radar baseband echo signal to obtain a correction signal; performing preprocessing on the correction signal to obtain a coarse focusing radar image; Extracting a single defocused target image from the coarsely focused radar image, and inverting the single defocused target image into an echo data domain to obtain data of a single target energy; The data of the single target energy is corrected by using a keystone transformation to obtain data after correcting the remaining distance movement; Based on the maximum energy criterion, some distance units are selected from the data after the corrected residual distance movement, the Doppler modulation rate of the selected distance units is estimated by using fractional Fourier transform, the estimated Doppler modulation rate is fitted by using a space-varying phase error model, and a space-varying phase error compensation function of the target is constructed; The space-variable phase error compensation function of the target is used to compensate the data after the correction of the remaining distance movement and to form an image.

2. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 1 is characterized in that: Construct the imaging space geometric model of radar and target, including: The radar three-dimensional imaging coordinate system OXYZ is established with the point O vertically below the radar as the origin; wherein the radar moves in a uniform straight line along the heading at a constant speed v, the front oblique angle is θ, and the front oblique angle of the sea is θ g , the distance from the center of the radar beam to the center of the imaging scene is R S , the distance between point O vertically below the radar and the target is R B , the radar height from the sea surface is H, and With the target center of gravity o as the origin, establish the target fixed coordinate system oxyz; where the target speed along the heading is v x , tangential velocity is v y , and three-dimensional swaying motion, each dimensional swaying motion of the target is equivalent to a single-frequency sinusoidal motion, when any scattering point (x n ,y n ,z n ) performs three-dimensional swing motion, the coordinates of the scattering point are updated to Its expression is: Among them, t a represents the azimuth slow time, θ y (t a ),θ p (t a ) and θ r (t a ) represent the yaw, pitch and roll angles respectively, and their expressions are as follows: Among them, A y , A p , A r Respectively represent the amplitude of the heading angle, pitch angle and roll angle, T y 、T p 、T r denote the periods of the heading angle, pitch angle and roll angle, respectively, φ y ,φ p ,φ r They represent the initial phases of the heading angle, pitch angle and roll angle respectively; When the scattering point moves in a two-dimensional plane, the coordinates are updated to (x n ′,y n ′,z n ′), its expression is: in, t a Indicates slow time of direction.

3. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 2 is characterized in that: Obtain the instantaneous slant range model from the radar beam to any scattering point on the target, including: According to the imaging space geometric model, an instantaneous slant range model R(t a ), whose expression is: The instantaneous slant range model R(t a ) is Taylor expanded, and the third-order and higher-order terms are discarded, and updated to: in, in, 4. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 1 is characterized in that: Get the radar baseband echo signal, including: According to the instantaneous slant range model from the radar beam to any scattering point on the target, the radar baseband echo signal s(t r ,t a ), whose expression is: Among them, w r (·) represents the distance window function, w a (·) represents the azimuth window function, t r represents the distance-to-time, c represents the speed of light, K r represents the distance modulation frequency, λ represents the wavelength, R(t a ) represents the instantaneous slant range model from the radar beam to any scattering point on the target.

5. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 1, characterized in that: Performing range pulse pressure and range migration correction on the radar baseband echo signal to obtain a correction signal; Preprocessing the correction signal to obtain a coarsely focused radar image includes: According to the radar baseband echo signal, a range matched filter function and a range migration correction phase factor function are constructed, and their expressions are: Among them, H r1 (t r ) represents the distance matched filter function, H r2 (t r ,t a ) represents the range migration correction phase factor function; According to the range matched filter function and the range migration correction phase factor function, the radar baseband echo signal is corrected for range pulse pressure and range migration to obtain a correction signal s1(t r ,t a ), whose expression is: Where B represents the signal bandwidth, According to the radar baseband echo signal, an azimuth matched filter function H is constructed. a1 (t a ), whose expression is: The azimuth matched filter function is multiplied by the correction signal, and the multiplication result is subjected to azimuth Fourier transform to obtain a coarse focusing radar image s2(t r ,f a ).

6. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 1, characterized in that: Inverting the single defocused target image into the echo data domain to obtain data of single target energy includes: The single defocused target image is inverted into the echo data domain to obtain data s3(t r ,t a ), whose expression is: For data s3(t r ,t a ) performs distance Fourier transform to obtain the single target energy data s3(f r ,t a ), whose expression is: Among them, f r Represents the distance frequency, f c Indicates the carrier frequency.

7. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 1 is characterized in that: The data of the single target energy is corrected by using a keystone transformation to obtain data after a single corrected remaining distance movement, including: The virtual slow time is constructed by the keystone transformation principle, and its expression is: The virtual slow time combines the data of the single target energy with the data of the single target energy s3 (f r ,t a ) is updated to: The updated single target energy data is inverse Fourier transformed to obtain the corrected remaining distance moving data s4(t r ,τ a ), whose expression is: The data s4(t r ,τ a ) is simplified to: Here, c represents the speed of light.

8. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 1 is characterized in that: The fractional Fourier transform is used to estimate the Doppler modulation rate of some selected range units, including: The fractional Fourier transform is used to estimate the Doppler modulation rate of a single range unit. The p-order fractional Fourier transform result is S p (u), its expression is: Among them, A α represents the fractional Fourier transform coefficient, u represents the fractional Fourier domain, and α represents the rotation angle corresponding to the maximum peak point in the fractional Fourier transform; The process is repeated until the Doppler modulation rate estimation value of the selected part of the range units is obtained.

9. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 1, characterized in that: The estimated Doppler modulation rate is fitted using the space-varying phase error model to construct the target's space-varying phase error compensation function, including: Get the space-variant phase error model K a , whose expression is: K a =ar+b; Among them, a and b represent unknown parameters, and r represents the distance position; The estimated Doppler modulation rate is fitted using a space-varying phase error model, and the problem is described as minimizing the sum of the squares of the difference between the estimated Doppler modulation rate and the actual Doppler modulation rate, that is: Let K = [K a1 K a2 … K aN ] T , A=[ab] T , the actual Doppler modulation frequency is obtained, and its expression is: K = RA + E; Where E represents the random error matrix, K represents the observed value, and RΑ represents the theoretical value. According to the matrix form of the least squares method The coefficient matrix Α is obtained by solving the equation: A=(R T R) -1 R T K; in,(·) T Indicates the transpose of a matrix, (·) -1 represents the inverse of the matrix, ||·||2 represents the 2-norm of the matrix; According to the coefficient matrix A and the target's distance unit position, the global Doppler modulation rate of the target is constructed to obtain the target's space-varying phase error compensation function H(t r ,t a ).

10. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 1, characterized in that: The space-variable phase error compensation function of the target is used to compensate the data after the correction of the remaining distance movement, and imaging is performed, including: The space-varying phase error compensation function of the target is multiplied by the data after the residual distance movement is corrected, and the multiplication result is Fourier transformed to obtain a fine-focus image of the target.

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