Space-Varied Self-Focusing Imaging Method for Sea Surface Moving Targets Using Missile-Borne Synthetic Aperture Radar

Abstract

The present invention discloses a space-variant self-focusing imaging method for a missile-borne synthetic aperture radar (SAR) sea surface moving target, comprising the steps of: obtaining a radar baseband echo signal; performing range pulse pressure and range migration correction on the radar baseband echo signal to obtain a correction signal, and further obtaining a coarse-focused radar image; extracting a single defocused target image from the coarse-focused radar image, and inverting the single defocused target image into the echo data domain to obtain data of the single target energy; performing correction to obtain data corrected for residual range movement; selecting some range units from the data corrected for residual range movement, using fractional Fourier transform to estimate Doppler frequency modulation for the selected range units, fitting the estimated Doppler frequency modulation using a space-variant phase error model, constructing a space-variant phase error compensation function for the target, compensating the data corrected for residual range movement, and finally imaging. The present invention is advantageous in improving the refocusing effect of a moving ship target.

Description

Technical Field

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

[0002] Maritime surveillance is a crucial means of maintaining maritime order and ensuring marine security. Ships are essential vehicles for human marine activities, a crucial component of the maritime battlefield, and crucial targets for maritime surveillance. Acquiring high-quality images of ship targets is crucial. Compared to optical imagery, Synthetic Aperture Radar (SAR), an active microwave sensor, can image maritime ship targets at any time of day, in all weather conditions, and at long distances, making it a powerful tool for ocean surveillance.

[0003] Due to the influence of waves and other factors, ships, in addition to their two-dimensional translational motion on the sea surface, also experience six degrees of freedom of oscillation: three-dimensional sway (roll, pitch, and bow) and three-dimensional oscillation (surge, surge, and heave). This makes ship motion very complex. Traditional SAR imaging methods can suffer from defocusing when imaging moving ships, severely impacting subsequent detection, recognition, and other applications. Therefore, imaging ships under complex motion conditions is crucial.

[0004] A ship is a rigid body. When it undergoes two-dimensional translational motion and three-dimensional oscillatory motion, each scattering point on the ship has the same motion state and therefore has the same impact on SAR imaging. Therefore, existing SAR autofocus algorithms can be used to compensate for this. Traditional SAR image autofocus algorithms, such as the Map Drift (MD) algorithm and the Phase Gradient Autofocus (PGA) algorithm, typically assume that the phase error is non-space-variant, meaning that a unified phase error compensation function can be used to correct the entire scene. When a ship target undergoes three-dimensional oscillation, although the amplitude and period of the oscillation angle of each scattering point on the ship target are the same, the oscillation distance is proportional to its distance from the oscillation axis. Therefore, each scattering point has different motion patterns, resulting in space-variant phase errors in its radar echo. Consequently, traditional autofocus algorithms cannot meet the requirements for high-resolution imaging of ship targets under complex motion conditions. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, the present invention provides a method for space-variable self-focusing imaging of sea-surface moving targets using missile-borne synthetic aperture radar. The technical problems to be solved by the present invention are achieved through the following technical solutions:

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

[0007] Based on 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 fundamental frequency echo signal is obtained;

[0008] Perform range pulse pressure and range migration correction on the radar baseband echo signal to obtain a correction signal; pre-process the correction signal to obtain a coarse-focus 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 cells are selected from the data after correcting the residual range movement. The Doppler frequency modulation rate of the selected range cells is estimated using fractional Fourier transform. The estimated Doppler frequency modulation rate is fitted with a space-varying phase error model to construct the target's space-varying phase error compensation function.

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

[0013] Beneficial effects of the present invention:

[0014] 1. The present invention first obtains a coarse focus image, 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 solution can effectively eliminate the mutual influence between multiple ship targets with different motion states on the sea surface, which is conducive 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 based on the maximum energy criterion for fractional Fourier transform processing to estimate their Doppler frequency modulation, which can effectively reduce the amount of calculation; by fitting the Doppler frequency modulation estimated by fractional Fourier transform, a space-varying phase error compensation function of the moving ship target is constructed, which can solve the problem that traditional autofocus algorithms cannot handle the space-varying phase error caused by the three-dimensional swinging motion of ship targets, and the obtained complex moving ship target image has a better focusing effect.

[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 This is a flow chart of a method for space-varying 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 This is a schematic diagram of a geometric model of the imaging space of a radar and a target provided by an embodiment of the present invention;

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

[0020] Figure 4 This is a schematic diagram of the coarse focus imaging result of a single moving ship target detected by SP-CFAR according to 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 This is a schematic diagram of the result of refocusing a single defocused moving ship target image using the existing PGA algorithm;

[0024] Figure 7 The figure 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 will be further described in detail below with reference to specific examples, but the embodiments of the present invention are not limited thereto.

[0026] See Figure 1 , Figure 1 This is a flow chart of a method for space-varying self-focusing imaging of a moving target on a sea surface using a missile-borne synthetic aperture radar, provided by an embodiment of the present invention. The method comprises:

[0027] S101. Construct an imaging space geometric model of the radar and the target based on 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 fundamental frequency echo signal.

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

[0029] With 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. Among them, 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 Figure 3 , Figure 3 This 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 can be a ship target. The target speed along the course is v x , tangential velocity is v y , and three-dimensional swing motion. The three-dimensional swing motion of the ship target can be equivalent to the superposition of a series of sinusoidal functions. In order to simplify the analysis, each dimension of the target's swing motion 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:

[0033]

[0034] Among them, A y 、A p 、A r They represent the amplitudes of the heading angle, pitch angle and roll angle respectively, T y 、T p 、T r are the periods of the heading angle, pitch angle and roll angle, respectively, y 、φ p 、φ r 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 azimuth slow time.

[0039] In this embodiment, considering that the ship target has not only two-dimensional translation motion on the sea surface but also three-dimensional sway motion, obtaining the instantaneous slant range model from the radar beam to any scattering point on the target includes:

[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 sinusoidal three-dimensional swing motion can be approximated as a three-dimensional nonlinear motion, which can be described by the Taylor expansion formula. The instantaneous slant range model R(t a ) performs Taylor expansion and discards the third-order and higher-order terms, and updates to:

[0043]

[0044] in,

[0045] in,

[0046]

[0047] In equation (6), α1 and α2 are caused by radar motion and are usually compensated in the SAR imaging process; β1 and β2 are caused by the two-dimensional translational motion of the ship target. If not compensated, the imaging result will be defocused, but the phase error caused by them is non-space-variant; γ1 and γ2 are caused by the three-dimensional swaying motion of the ship target, and the phase error caused by them is space-variant.

[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 cis the carrier frequency, K r The 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 distance-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-focus radar image.

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

[0053] Since the motion form of the ship target is unknown, β1, β2, γ1 and γ2 in the slant range model cannot be directly obtained. According to the radar fundamental frequency echo signal, the range matched filter function and the range migration correction phase factor function are constructed. 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 s1(t r ,t a ), whose expression is:

[0057]

[0058] Where B represents the signal bandwidth, That is, the range migration component caused by radar motion is corrected, while the remaining range migration caused by ship target motion 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 by the correction signal, and the multiplication result is subjected to azimuth Fast Fourier Transform (FFT) to obtain the coarse focused radar image s2(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, the coarsely focused image of the ship target will be defocused in azimuth, and the defocus 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 single target energy data.

[0063] Specifically, see Figure 4 , Figure 4 This is a schematic diagram of the coarse focus 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 focus SAR image s2(t r ,f a ) to detect and extract a single defocused moving ship target image s3(t r ,f a ), eliminating the impact of different moving ship targets on subsequent refocusing processing.

[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 into the echo data domain to obtain single defocused moving ship target data.

[0065] S104: Correct the data of the single target energy using a keystone transformation to obtain corrected data of the remaining distance.

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

[0067] Invert the single defocused target image into the echo data domain to obtain data s3(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 results.

[0070] 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:

[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 range dimension and the azimuth dimension, which will lead to defocusing in the imaging results.

[0074] In this embodiment, virtual slow time is constructed by the 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 s3(f r ,τ a ), since the bandwidth of the transmitted signal is much smaller than the carrier frequency, that is, f r <<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 s3(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. r ,τ a ) is processed by distance inverse Fourier transform (IFFT) to obtain the data s4 (t r ,τ a ), whose expression is:

[0081]

[0082] In formula (17), since the carrier frequency f c The second term of the distance-time dimension can be ignored, and the data s4(t r ,τ a ) is simplified to:

[0083]

[0084] Where c represents the speed of light. After KT processing, the residual range movement caused by the motion 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 range units from the data after the correction of the residual range movement, use the Fractional Fourier Transform (FrFT) to estimate the Doppler frequency modulation rate of the selected range 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 frequency modulation rate of selected range units, including:

[0087] If Equation (18) is directly processed by azimuth FFT, a SAR image of the ship target in the range Doppler domain can be obtained. However, since the phase error caused by the ship target's motion is not compensated, the imaging result will be defocused in azimuth. Since the first-order phase error only causes displacement of the imaging result of the moving ship target and does not affect the SAR image quality, the first-order phase error is ignored and only the second-order phase error caused by the ship target's motion is considered. In addition, due to the particularity of the ship target's three-dimensional swaying motion, the distance from the scattering point to the sway axis is different, and its motion state is also different, resulting in the phase error being spatially variable and unable to be processed using the traditional autofocus algorithm.

[0088] The fractional Fourier transform (FrFT) is a very good time-frequency analysis tool. It can be understood as rotating the coordinate axis of the signal counterclockwise by 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 s4(t r ,τ a ) performs FrFT, and ignores the distance dimension, constant phase term and first-order phase term, retaining only the azimuth second-order phase term. 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] Repeat the process until the Doppler modulation rate estimation value of the selected part of the range units is obtained.

[0097] In order to make the signal s4(t r ,τ a) has the best energy concentration, and the final result should be the sinc function, that is, the integral of formula (21) The coefficient should be 0, then we can get β2+γ2=λcotα / 4, where α is the rotation angle corresponding to the maximum peak point in the FrFT result, from which we can estimate the signal s4(t r ,τ a )'s Doppler modulation frequency.

[0098] Based on the above analysis, the signal s4(t r ,τ a ) Based on the maximum energy criterion, N range cells containing ship target energy are selected, and FrFT processing is performed on these N range cells respectively to estimate the Doppler modulation frequency corresponding to the N range cells, 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, as mentioned above, 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, where a and b represent unknown parameters and r represents the range position. Based on the estimated Doppler modulation rates corresponding to some range units, solving the space-varying phase error model can be considered a linear regression problem. Because there is a certain random error ε between the estimated Doppler modulation rate and the actual Doppler modulation rate, to minimize ε, the least squares method is used for linear 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, namely:

[0100]

[0101] Let K = [K a1 K a2 …K aN ] T , A=[ab] T , we can get the actual Doppler modulation frequency, which is expressed as:

[0102] K = RA + E;

[0103] Among them, E represents the random error matrix, K represents the observed value, and RA represents the theoretical value.

[0104] According to the matrix form of the least squares method The coefficient matrix A is obtained by solving the equation, and its expression is:

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

[0106] in,(·) T Indicates the transpose of the matrix, (·) -1 Indicates the inverse of the matrix, ||·||2 indicates the 2-norm of the matrix;

[0107] According to the coefficient matrix A and the target's position in the range unit, 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's space-varying phase error compensation function H(t r ,t a ) is multiplied with the data after multiple corrections of the remaining distance movement, and the multiplication result is Fourier transformed to obtain the 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 finely focused image of the target.

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

[0112] 1. The present invention first obtains a coarse focus image, 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 solution can effectively eliminate the mutual influence between multiple ship targets with different motion states on the sea surface, which is conducive 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 based on the maximum energy criterion for fractional Fourier transform processing to estimate their Doppler frequency modulation, which can effectively reduce the amount of calculation; by fitting the Doppler frequency modulation estimated by fractional Fourier transform, a space-varying phase error compensation function of the moving ship target is constructed, which can solve the problem that traditional autofocus algorithms cannot handle the space-varying phase error caused by the three-dimensional swinging motion of ship targets, and the obtained complex moving ship target image has a better focusing effect.

[0114] In an optional embodiment of the present invention, the effect of the space-varying self-focusing imaging method of sea surface moving targets provided by the missile-borne synthetic aperture radar provided in the above embodiment is verified through 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 Altitude (km) 25

[0119] The three-dimensional swing motion parameters of the destroyer under different sea conditions are shown in Table 2. The three-dimensional swing 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 Figure 5(a) and 5(b) FIG5(a) is a schematic diagram of a phase error compensation function estimated by an existing PGA algorithm, and FIG5(b) is a schematic diagram of a phase error compensation function estimated by an algorithm provided in an embodiment of the present invention. Figure 6 This is a schematic diagram of the result of refocusing a single defocused moving ship target image using the existing PGA algorithm. Figure 7 The figure 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 4It shows that due to the complexity of the ship target motion, the coarse-focused 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 resolve the space-varying phase error caused by the rocking motion, resulting in severe defocus 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 proposed algorithm are compared, including the entropy and contrast of the image, and the results are shown in Table 4. As can be seen from Table 4, the entropy and contrast of the processing results of the proposed algorithm are significantly improved compared with the original image, where the lower the entropy 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, simulation experiments have verified 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 traditional autofocus algorithms cannot handle, thereby achieving a good refocusing effect on moving ship targets. Compared with existing moving target imaging algorithms, the present invention has simpler steps and more concise formula derivations, does not require a large number of iterative operations, has a low computational load, and is simple to implement.

[0134] It should be noted that, in this document, relational terms such as first and second are used solely to distinguish one entity or operation from another, and do not necessarily require or imply any actual relationship or order between these entities or operations. Furthermore, the terms "comprise," "include," or any other variations thereof are intended to encompass non-exclusive inclusion, such that an article or device comprising a list of elements includes not only those elements but also other elements not explicitly listed. Without further limitation, an element defined by the phrase "comprising a..." does not preclude the presence of additional identical elements in the article or device comprising the element. Terms such as "connected" or "connected" are not limited to physical or mechanical connections but may include electrical connections, whether direct or indirect. References to orientations or positional relationships, such as "upper," "lower," "left," and "right," are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate description and simplify the description of the present invention. They do not indicate or imply that the device or element referred to must have, be constructed, or operate in a specific orientation, and are therefore not to be construed as limiting the present invention.

[0135] In the description of this specification, the reference terms "one embodiment," "some embodiments," "example," "specific example," or "some examples" mean 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 representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described can be combined in any suitable manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification.

[0136] The above is a further detailed description of the present invention in conjunction with specific preferred embodiments, and the specific implementation of the present invention should not be considered to be limited to these descriptions. For those skilled in the art of the present invention, without departing from the concept of the present invention, several simple deductions or substitutions can be made, which should be considered to fall within the scope of protection of the present invention.

Claims

1. A missile-borne synthetic aperture radar space-variant self-focusing imaging method for sea surface moving targets, characterized by: include: Based on 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 fundamental frequency echo signal is obtained; 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 coarse-focused 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 on single target energy; Correcting the data of the single target energy using a keystone transformation to obtain data after correcting the remaining distance movement; Based on the maximum energy criterion, some range units are selected from the data after the residual range movement correction, the Doppler frequency modulation rate of the selected range units is estimated using a fractional-order Fourier transform, the estimated Doppler frequency modulation rate is fitted using a space-varying phase error model, and a space-varying phase error compensation function of the target is constructed; The target's space-varying phase error compensation function is used to compensate the data after the correction of the remaining distance movement, and imaging is performed.

2. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 1, characterized in that: Construct the imaging space geometric model of the radar and the target, including: Take the point vertically below the radar As the origin, establish the radar three-dimensional imaging coordinate system ; Wherein, the radar is at a constant speed Do uniform linear motion along the heading, the forward oblique angle is , the oblique angle of view before the sea is , the distance from the center of the radar beam to the center of the imaging scene is , the point vertically below the radar The distance to the target is , the radar height from the sea surface is ,and , Indicates the distance between the origin and the target; Focus on the target As the origin, establish the target fixed coordinate system ; Wherein, the target speed along the course is The tangential velocity is , and three-dimensional swing motion, each dimension of the swing motion of the target is equivalent to a single frequency sinusoidal motion, when any scattering point in the target fixed coordinate system When performing three-dimensional rocking motion, the coordinates of the scattering point are updated to , whose expression is: ； in, Indicates the direction of slow time, 、 and They represent the yaw, pitch and roll angles respectively, and their expressions are: ； in, 、 、 denote the amplitudes of the heading angle, pitch angle and roll angle respectively, 、 、 denote the periods of the heading angle, pitch angle and roll angle respectively, 、 、 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 as follows: , whose expression is: ； in, ; Indicates azimuth slow time.

3. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 2, 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 of the radar beam to any scattering point on the target is constructed. , whose expression is: ； The instantaneous slant range model of the radar beam to any scattering point on the target Perform Taylor expansion and discard the third-order and higher-order terms to update to: ； in, ; ； ； in, 。 4. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 3, characterized in that: Get the radar baseband echo signal, including: The radar fundamental frequency echo signal is obtained according to the instantaneous slant range model from the radar beam to any scattering point on the target , whose expression is: ； in, represents the distance window function, represents the orientation window function, Indicates distance to fast time, represents the speed of light, Indicates the distance modulation frequency, represents the wavelength, 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 4, 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-direction matched filter function and a range migration correction phase factor function are constructed, and their expressions are: ； ； in, represents the distance matched filter function, 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 , whose expression is: ； in, represents the signal bandwidth, ; According to the radar baseband echo signal, an azimuth matched filter function is constructed. , whose expression is: ； Multiply the azimuth matched filter function with the correction signal, and perform azimuth Fourier transform on the multiplication result to obtain a coarse focused radar image. .

6. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 5, characterized in that: Inverting the single defocused target image into the echo data domain to obtain single target energy data includes: The single defocused target image is inverted into the echo data domain to obtain data , whose expression is: ； Data Perform distance Fourier transform to obtain single target energy data , whose expression is: ； in, represents the distance frequency, Indicates the carrier frequency.

7. The missile-borne synthetic aperture radar sea surface moving target space-variant self-focusing imaging method according to claim 6, characterized in that: The data of the single target energy is corrected 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. Updated to: ； Perform inverse Fourier transform on the updated single target energy data to obtain the data after correcting the remaining distance movement. , whose expression is: ； The data after the correction of the remaining distance Simplified to: ； in, 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 7, characterized in that: The Doppler modulation rate is estimated for some selected range cells using fractional Fourier transform, including: The fractional Fourier transform is used to estimate the Doppler frequency modulation rate of a single range unit. The result of the fractional Fourier transform is , whose expression is: ； in, represents the fractional Fourier transform coefficient, represents the fractional Fourier domain, Indicates the rotation angle corresponding to the maximum peak point in the fractional Fourier transform; Repeat the process 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 frequency modulation rate is fitted using the space-varying phase error model to construct the target's space-varying phase error compensation function, including: Obtaining the space-variant phase error model , whose expression is: ； in, and All represent unknown parameters. Indicates distance position; The estimated Doppler modulation rate is fitted using a space-varying phase error model. The problem is described as minimizing the sum of the squares of the differences between the estimated Doppler modulation rate and the actual Doppler modulation rate, that is: ； make , Indicates the index of the range cell containing the ship target energy, Indicates the number of range cells containing the ship target energy. , Indicates the The range cell location containing the ship target energy, , we can get the actual Doppler modulation frequency, which is expressed as: ； in, represents the random error matrix, represents the observed value, represents the theoretical value, According to the matrix form of the least squares method , solve to get the coefficient matrix , whose expression is: ； in, It means to find the transpose of the matrix. It means to find the inverse of the matrix. represents the 2-norm of the matrix; According to the coefficient matrix And the target's range unit position, construct the target's global Doppler modulation frequency, and obtain the target's space-varying phase error compensation function .

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

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