Moving target rapid imaging method based on KT transformation

Abstract

The invention discloses a KT transform-based moving target rapid imaging method. The method comprises the following steps of: receiving a moving target echo signal by a radar; performing distance compression processing, consistent compensation and slow time reversal processing on the moving target echo signal; carrying out distance azimuth decoupling on the echo signal by using KT transform, and then carrying out azimuth fast Fourier transform to obtain an estimated monomial coefficient; performing de-walking processing on the compensated echo signal by using the estimated monomial coefficient, performing correction by using SOKT transform, and extracting the corrected echo signal to perform mWVD transform so as to obtain an estimated Doppler frequency modulation rate; and azimuth focusing processing is carried out on the corrected echo signal by using a Doppler frequency modulation rate to obtain a focused echo signal, and a moving target imaging result is obtained. According to the invention, the efficiency of moving target imaging is remarkably improved, and a good real-time effect can be ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of signal processing and relates to a moving target fast imaging method based on KT transformation. Background Art

[0002] Synthetic aperture imaging (SAR) technology can image static scenes with high resolution, and has the advantages of all-day, all-weather, and high resolution. However, for moving targets in ground / sea scenes, such as vehicles speeding on the road, highly maneuverable weapons and equipment on the battlefield, and fast-moving speedboats on the sea, their motion parameters are unknown. If the motion parameters of static scenes are directly used for phase matching, their range and Doppler migration cannot be accurately compensated, and the mismatch of the matching function will cause the image of the moving target to be defocused and misplaced. These moving targets have the characteristics of high value and high threat, and their detection and imaging are of great significance in applications such as battlefield situation assessment, traffic monitoring, and sea anti-terrorism.

[0003] However, traditional moving target imaging methods for phase estimation mostly include search-based estimation methods, and the accuracy of the search is closely related to the size of the step, which leads to extremely high computational complexity and high time consumption of such methods, which is not conducive to the implementation of the algorithm.

[0004] Patent CN 113109810 A discloses a SAR moving target imaging method and system based on LVD, which includes: compressing echo signals in range, correcting range curvature, correcting range movement, estimating Doppler modulation frequency parameters using LVD method, and compressing azimuth signal imaging. However, this method only considers the range curvature caused by platform movement and ignores the range curvature caused by target movement when compensating for range curvature, resulting in insufficient compensation for movement, especially in the case of squint, where the range-azimuth coupling is more serious; at the same time, this method estimates the range movement using a spatial search method using Radon transform, and this search step is slow, resulting in poor imaging efficiency. Summary of the invention

[0005] The present invention aims to solve the technical problem of poor efficiency in moving target imaging. The present invention provides a moving target fast imaging method based on KT transformation. The technical solution adopted is:

[0006] A moving target rapid imaging method based on KT transformation comprises the following steps:

[0007] S1, radar receives the echo signal of moving target;

[0008] S2, performing distance compression processing on the moving target echo signal to obtain a compressed echo signal;

[0009] S3, performing consistent compensation on the compressed echo signal to obtain a compensated echo signal;

[0010] S4, performing slow time inversion processing on the compensated echo signal to obtain an inverted echo signal;

[0011] S5, using KT transformation to decouple the distance and azimuth of the inverted echo signal to obtain a decoupled echo signal;

[0012] S6, performing a fast Fourier transform in azimuth on the decoupled echo signal to obtain an estimated first-order coefficient;

[0013] S7, performing a de-motion processing on the compensated echo signal using the estimated first-order term coefficient to obtain a de-motion echo signal;

[0014] S8, correcting the echo signal after removing the movement by using SOKT transformation to obtain a corrected echo signal;

[0015] S9, extracting the corrected echo signal and performing mWVD transformation to obtain an estimated Doppler modulation rate;

[0016] S10, performing azimuth focusing processing on the corrected echo signal using the Doppler frequency modulation rate to obtain a focused echo signal and obtain a moving target imaging result.

[0017] In one embodiment of the present invention, step S2 comprises:

[0018] S21: performing a range dimension fast Fourier transform on the received two-dimensional time domain echo signal of the moving target to obtain an echo signal with a range dimension in the frequency domain and an azimuth dimension in the time domain;

[0019] The moving target echo signal is expressed as:

[0020]

[0021] Where rect(·) represents the window function, t represents the fast time variable, and t a represents the azimuth slow time variable, T p is the pulse width, λ is the wavelength of the transmitted signal, τ is the delay time of the received signal, c is the speed of light, μ is the distance bandwidth, exp is the exponential operation with the natural constant e as the base, R(t a ) is the instantaneous slant distance;

[0022] The echo signal with distance dimension in frequency domain and azimuth dimension in time domain is expressed as:

[0023]

[0024] Among them, f r is the distance frequency variable, fc is the carrier frequency;

[0025] S22: In the range frequency domain, azimuth time domain, multiply the echo signal with the range compression function to obtain the compressed echo signal, and calculate the slant range R(t a ) at t a = 0, expand the Taylor formula and keep the second-order term, which is expressed as:

[0026]

[0027] Among them, H rcom is the distance compression function, which is expressed as R s is the reference slant distance, which indicates the distance between the beam center and the platform, are the phase first-order coefficient and phase second-order coefficient respectively, θ 0 is the oblique angle, v represents the platform speed, v x 、v y Represents the velocity component of the target.

[0028] In one embodiment of the present invention, step S3 comprises:

[0029] S31: In the squint mode, the compressed echo signal has range-azimuth coupling. The compressed echo signal is first uniformly corrected for range movement and range curvature to construct a consistent compensation function, which is expressed as:

[0030]

[0031] Among them, H un is the consistent compensation function, ρ 10 =-vsinθ 0 , are the distance travel and distance bending coefficients caused by platform motion, respectively;

[0032] S32: The consistent compensation function and s 2 (f r ,t a ) are multiplied to obtain a compensated echo signal, and the compensated echo signal is expressed as:

[0033]

[0034] Among them, c 1 =ρ 1 -ρ 10 , c 2 =ρ 2 -ρ 20 .

[0035] In one embodiment of the present invention, step S4 comprises:

[0036] S41: Using the time reversal conversion method, the compensated echo signal is converted, which is expressed as:

[0037]

[0038] in, represents the slow time-reversal conjugate transform;

[0039] S42: With s 3 (f r ,t a ) are multiplied to obtain an inverted echo signal, which is expressed as:

[0040]

[0041] In one embodiment of the present invention, step S5 comprises:

[0042] Perform KT transformation on the inverted echo signal to achieve range and azimuth decoupling. The transformation method is expressed as:

[0043]

[0044] Among them, τ a is the transformed slow time variable;

[0045] The decoupled echo signal is obtained, and the decoupled echo signal is expressed as:

[0046]

[0047] In one embodiment of the present invention, step S6 comprises:

[0048] S61: Performing a fast Fourier transform in azimuth on the decoupled echo signal, expressed as:

[0049]

[0050] Among them, δ(·) is the impulse function, and the impulse appears at Department;

[0051] S62: Obtain the estimated linear term coefficient according to the position of the impulse function peak, expressed as:

[0052]

[0053] The peak(·) function represents the position of the peak value of the impulse function. represents the estimated linear coefficient.

[0054] In one embodiment of the present invention, step S7 includes:

[0055] S71: Construct the de-walking function, expressed as:

[0056]

[0057] Among them, H LRC is the distance movement function, used to correct the first-order phase term;

[0058] S72: The walking function H LRC The compensated echo signal s 3 (f r ,t a ) to obtain the echo signal after walking is removed. The echo signal after walking is expressed as:

[0059]

[0060] In one embodiment of the present invention, step S8 comprises:

[0061] S81: Use SOKT transformation to correct the distance bending term, expressed as:

[0062]

[0063] Among them, η a is the new slow time variable;

[0064] S82: Obtain a corrected echo signal, wherein the corrected echo signal is expressed as:

[0065]

[0066] In one embodiment of the present invention, step S9 includes:

[0067] S91: Perform inverse fast Fourier transform of the distance, extract the distance row after migration correction, and perform the inverse fast Fourier transform of the distance to the one-dimensional signal s p (η a ) is transformed into mWVD, which is expressed as:

[0068]

[0069] Among them, t 0 For a fixed delay, take

[0070] S92: Slow-time inverse Fourier transform to obtain an estimate of the Doppler modulation rate

[0071] In one embodiment of the present invention, step S10 includes:

[0072] S101: Fast Fourier transform along the azimuth direction to transfer to the range, time domain, azimuth and frequency domain;

[0073] S102: constructing an azimuth pulse pressure function using the Doppler frequency modulation rate, expressed as:

[0074]

[0075] S103: multiplying the azimuth pulse pressure function by the corrected echo signal to obtain a focused echo signal, wherein the focused echo signal is expressed as:

[0076]

[0077] S104: Perform inverse fast Fourier transform along the azimuth direction, convert to the range time domain and azimuth time domain, and obtain a focused image.

[0078] Beneficial effects of the present invention:

[0079] The present invention is based on the KT (keystone) transform of the moving target rapid imaging method, firstly completes the consistent compensation processing of the static scene and the moving target according to the platform parameters in the range frequency domain, then extracts the single moving target echo information from the SAR image, uses slow time reversal, KT transform and SOKT (second order KT) transform to complete the range migration processing, and finally extracts the echo signal falling into the same range unit for azimuth focusing processing to obtain a two-dimensional high-resolution moving target image. The present invention is suitable for squint imaging, and does not require search estimation, significantly improves the efficiency of moving target imaging, and provides a good solution for fast imaging of moving targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 is a flow chart of a moving target rapid imaging method based on KT transform provided by an embodiment of the present invention;

[0081] Figure 2 is a result diagram after consistent compensation provided by an embodiment of the present invention;

[0082] Figure 3 is a result diagram of estimating linear term coefficients provided by an embodiment of the present invention;

[0083] Figure 4 is a result diagram after walking is removed provided by an embodiment of the present invention;

[0084] Figure 5 is a result diagram after SOKT provided by an embodiment of the present invention;

[0085] Figure 6 is a result diagram of the mWVD estimation phase quadratic term coefficient provided by an embodiment of the present invention;

[0086] Figure 7is a focusing result diagram after azimuth processing provided by an embodiment of the present invention;

[0087] Figure 8 for Figure 7 Detailed cross-section of the target in focus. DETAILED DESCRIPTION

[0088] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0089] The present invention provides a moving target fast imaging method based on KT transformation. Figure 1 The moving target rapid imaging method based on KT transform comprises the following steps:

[0090] S1, radar receives the echo signal of moving target;

[0091] S2, performing distance compression processing on the moving target echo signal to obtain a compressed echo signal;

[0092] S3, performing consistent compensation on the compressed echo signal to obtain a compensated echo signal;

[0093] S4, performing slow time inversion processing on the compensated echo signal to obtain an inverted echo signal;

[0094] S5. Decouple the range and azimuth of the inverted echo signal by using KT transformation to obtain a decoupled echo signal;

[0095] S6. Performing a fast Fourier transform in azimuth on the decoupled echo signal to obtain an estimated first-order coefficient;

[0096] S7, performing a motion-removal processing on the compensated echo signal using the estimated first-order term coefficient to obtain a motion-removed echo signal;

[0097] S8, using SOKT (Second-Order Keystone Transform) to correct the echo signal after the movement is eliminated to obtain a corrected echo signal;

[0098] S9, extract the corrected echo signal and perform mWVD transformation to obtain the estimated Doppler modulation rate;

[0099] S10, using Doppler frequency modulation to perform azimuth focusing processing on the corrected echo signal to obtain a focused echo signal and obtain a moving target imaging result.

[0100] The KT transform-based moving target rapid imaging method of the present invention is suitable for squint imaging and does not require search estimation, which significantly improves the efficiency of moving target imaging and provides a good solution for moving target rapid imaging.

[0101] In one embodiment of the present invention, the moving target echo signal is expressed as:

[0102]

[0103] In formula (1), rect(·) represents the window function, t represents the fast time variable, and t a represents the azimuth slow time variable, T p is the pulse width, λ is the wavelength of the transmitted signal, τ is the delay time of the received signal, c is the speed of light, μ is the distance bandwidth, exp is the exponential operation with the natural constant e as the base, R(t a ) is the instantaneous slant distance.

[0104] In model building, the echo model used in the present invention fully considers the strabismus situation, has strong adaptability, and can more accurately reflect the complex situations in practical applications.

[0105] Step S2 of the present invention comprises:

[0106] S21: Performing a range dimension fast Fourier transform on the received two-dimensional time domain moving target echo signal to obtain an echo signal with the range dimension in the frequency domain and the azimuth dimension in the time domain.

[0107] The echo signal with distance dimension in frequency domain and azimuth dimension in time domain is expressed as:

[0108]

[0109] In formula (2), f r is the distance frequency variable, f c For the carrier frequency.

[0110] S22: In the range frequency domain, azimuth time domain, multiply the echo signal with the range compression function to obtain the compressed echo signal, and calculate the slant range R(t a ) at t a = 0, expand the Taylor formula and keep the second-order term, which is expressed as:

[0111]

[0112] In formula (3), H rcom is the distance compression function, which can be expressed as R s is the reference slant distance, which indicates the distance between the beam center and the platform, are the phase first-order coefficient and phase second-order coefficient respectively, θ 0 is the oblique angle, v represents the platform speed, v x 、v y Represents the velocity component of the target.

[0113] Step S3 of the present invention comprises:

[0114] S31: In the squint mode, the echo signal after range compression has obvious range migration problem, of which the platform causes a large part. First, the range migration and range bending are uniformly corrected for the echo signal after compression, and a consistent compensation function is constructed, which is expressed as:

[0115]

[0116] In formula (4), H un is the consistent compensation function, ρ 10 =-vsinθ 0 , are the distance travel and distance bending coefficients caused by platform motion, respectively.

[0117] S32: Combine the consistent compensation function with s 2 (f r ,t a ) are multiplied to obtain the compensated echo signal, which can eliminate the influence of platform motion and effectively reduce the range of subsequent phase coefficient estimation.

[0118] The echo signal after compensation is expressed as:

[0119]

[0120] In formula (5), c 1 =ρ 1 -ρ 10 , c 2 =ρ 2 -ρ 20 .

[0121] Step S4 of the present invention comprises:

[0122] S41: According to the equidistant scattering sampling characteristics of the target signal in the slow time domain, a time reversal transformation (TRT) method without losing signal sampling data is used to compensate the echo signal conversion, which is expressed as:

[0123]

[0124] In formula (6), represents the slow time-reversal conjugate transform.

[0125] S42: With s 3 (f r ,t a ) is multiplied to obtain the inverted echo signal, which is expressed as:

[0126]

[0127] The slow time reversal processing utilizes the discrete equal interval characteristics of slow time and the phase parity to eliminate the influence of the phase quadratic term without estimation processing, which is more efficient than other algorithms.

[0128] The present invention first uses the platform motion information to make consistent compensation for the echo, and then uses slow time reversal and KT transformation to make residual compensation for the migration caused by the target, thereby achieving more precise phase compensation. It can be seen from formula (7) that at this time, the signal only has the first-order phase term, which is more convenient for the subsequent estimation of the first-order term coefficient.

[0129] Step S5 of the present invention comprises:

[0130] Perform KT (keystone) transformation on the inverted echo signal to achieve range and azimuth decoupling. The transformation method is expressed as:

[0131]

[0132] In formula (8), τ a is the transformed slow time variable.

[0133] The decoupled echo signal is obtained, and the decoupled echo signal is expressed as:

[0134]

[0135] From formula (9), it can be seen that at this time, the phase only has the slow time term (that is, the azimuth direction), and has no relationship with the range direction (f r ,t r ) phase of the coupling, that is, the distance travel term is eliminated.

[0136] Step S6 of the present invention comprises:

[0137] S61: Perform fast Fourier transform of the decoupled echo signal in azimuth, expressed as:

[0138]

[0139] In formula (10), δ(·) is the impulse function, and the impulse appears at Place.

[0140] S62: Obtain the estimated linear term coefficient according to the position of the impulse function peak, expressed as:

[0141]

[0142] In formula (11), the peak(·) function represents the position of the peak value of the impulse function. Represents the estimated first-order coefficient, which can be obtained by finding the position of the maximum value of the echo matrix.

[0143] Step S7 of the present invention comprises:

[0144] S71: Construct the de-walking function, expressed as:

[0145]

[0146] In formula (12), H LRC is the distance travel function, which is used to correct the first-order phase term.

[0147] S72: Move function H LRC and the compensated echo signal s 3 (f r ,t a ) to obtain the echo signal after walking is removed. The echo signal after walking is expressed as:

[0148]

[0149] Here, the estimated first-order coefficient is used to perform distance movement correction processing on the original consistent compensated signal. The ultimate purpose of the above slow time reversal processing and KT transformation is to estimate the first-order coefficient of the phase. Therefore, this algorithm can perform KT transformation and SOKT transformation at the same time without affecting each other.

[0150] Step S8 of the present invention comprises:

[0151] S81: Use SOKT (Second-Order Keystone Transform) to correct the distance curvature, expressed as:

[0152]

[0153] In formula (14), η a is the new slow time variable.

[0154] The SOKT transform is used to correct the second-order range curvature. The traditional Keystone transform can only correct the linear range movement. The SOKT transform realizes the range curvature compensation through linear substitution without knowing the precise motion parameters of the moving target.

[0155] S82: Obtain a corrected echo signal, which is expressed as:

[0156]

[0157] Step S9 of the present invention comprises:

[0158] S91: Perform inverse fast Fourier transform of the distance, extract the distance row after migration correction, and perform the inverse fast Fourier transform of the distance to the one-dimensional signal s p(η a ) is used to perform mWVD transformation (Modified Wigner-Ville Distribution Transform), which is expressed as:

[0159]

[0160] In formula (16), t 0 For a fixed delay, take

[0161] The improved Wigner-Ville distribution transform consists of two WVD transform kernels, which can be regarded as the result of performing another WVD process on the first-order WVD signal along the delay time variable; the improved Wigner-Ville distribution transform introduces an adjustable parameter, which can be adjusted by changing the delay τ 0 , which enables the transform to adjust the time-frequency resolution more flexibly.

[0162] The present invention uses an improved mWVD function to estimate the Doppler modulation frequency and realizes two-dimensional refined imaging, which significantly improves the calculation efficiency of the algorithm compared with the traditional method.

[0163] S92: Slow time dimension IFFT (slow time dimension inverse Fourier transform, slow time dimension = azimuth dimension) to obtain the estimated value of Doppler modulation frequency

[0164] Step S10 of the present invention includes:

[0165] S101: Fast Fourier transform along the azimuth direction to transfer to the range, time domain, azimuth and frequency domain.

[0166] S102: Using the Doppler frequency modulation, construct an azimuth pulse pressure function, which is expressed as:

[0167]

[0168] S103: Multiply the azimuth pulse pressure function by the corrected echo signal to obtain a focused echo signal, which is expressed as:

[0169]

[0170] S104: Perform inverse fast Fourier transform along the azimuth direction, convert to the range time domain and azimuth time domain, and obtain a focused image.

[0171] The fast imaging method of moving targets based on KT transformation of the present invention estimates the first-order phase term by slow time reversal and KT transformation, and compensates the first-order phase term of the echo after consistent compensation by using the estimated first-order term coefficient, realizes the removal of walking processing and the removal of Doppler center offset processing, and then uniformly corrects the range bending term by SOKT transformation, and better suppresses the energy diffusion caused by range migration and Doppler migration. The present invention has no search steps, so it has low calculation complexity, thereby significantly improving the imaging efficiency and ensuring good real-time effect.

[0172] The effect of the moving target rapid imaging method based on KT transform of the present invention is described below through simulation experiments.

[0173] 1. The parameter settings of the simulation experiment in this example are shown in Table 1:

[0174] Table 1 Simulation test parameters

[0175]

[0176] 2. The target motion information of this example simulation experiment is shown in Table 2:

[0177] Table 2 Target motion information table of simulation experiment

[0178] X-axis speed (m / s) Y-axis speed (m / s) Target 7 10

[0179] 3. Results of simulation test:

[0180] The results of the simulation test are shown in the attached Figure 2 -Attached Figure 8 . Figure 2 represents the result after consistent compensation. Consistent compensation eliminates the range migration caused by platform motion. The remaining range migration in the figure is mainly caused by target motion. Figure 3 It is the result of azimuth-dimensional Fourier transform. A pulse will appear in the signal in the azimuth frequency domain. According to the position of the pulse, the first-order phase coefficient can be estimated. Figure 4 In order to use the estimated first-order coefficient to correct the result after range movement, the echo phase only has the range bending term, so the migration is symmetrically distributed; Figure 5 is the result after SOKT transformation. At this time, the range migration compensation is completed and the signals at all azimuth times fall in the same range unit; Figure 6 The result of extracting the range unit signal and performing mWVD transformation on it is obtained. The function of mWVD is to focus the one-dimensional linear frequency modulation signal into a pulse signal and obtain the Doppler modulation frequency according to the position of the pulse; Figure 7 The result of azimuth focusing on the signal is obtained by constructing the azimuth pulse pressure function using the estimated Doppler modulation rate. Figure 8 for Figure 7The refined cross-section of the target at the focal point shows that the focusing effect is good and there is no coupling deformation.

[0181] By attaching Figure 2 -Attached Figure 8 It can be seen that the moving target rapid imaging method based on KT transform of the present invention has a good moving target focusing effect.

[0182] The algorithm proposed in the present invention can be widely used in airborne and missile-borne synthetic aperture radar (SAR) imaging systems, especially in complex battlefield environments, for real-time acquisition and analysis of the motion status and position information of various military targets. The algorithm can effectively focus on dynamic targets on the battlefield, including but not limited to tanks, armored vehicles, military trucks, aircraft carriers, warships and other moving targets. Through the algorithm, refocusing of moving targets can be achieved in SAR images, that is, imaging of moving targets can be achieved during the target movement process, overcoming the blur and deviation caused by the target movement, thereby obtaining a clear and accurate target image.

[0183] At the same time, the present invention can not only improve the accuracy of parameter estimation of moving targets, but also maintain high-precision true positioning when the target moves at high speed, ensuring the real-time and reliability of battlefield situation perception, providing an efficient solution for airborne and missile-borne SAR systems, greatly enriching the functions and information acquisition capabilities of SAR systems, and is of great significance to military reconnaissance, target strikes, perception of battlefield situation, monitoring of surface ships, and detection of low-altitude targets.

[0184] Moreover, the present invention can monitor the moving vehicles and pedestrians on the ground, better implement traffic control, monitor the traffic flow and vehicle status on the road in real time, identify traffic violations such as speeding, running red lights, and driving in the wrong direction, and provide real-time alarms. This plays an important role in urban traffic management and rapid response to traffic accidents; in terms of intelligent driving simulation, moving target imaging can provide the automatic driving system with all-time and all-weather perception capabilities, especially in bad weather or night driving conditions, to ensure the safety and stability of the automatic driving vehicle; in the automated logistics system, moving target imaging can monitor the dynamic position of transportation tools (such as unmanned vehicles, robots, etc.), ensure the efficiency and safety of the cargo transportation process, and optimize the allocation of logistics resources. At the same time, it can also be applied to disaster monitoring, marine research, and resource exploration to achieve efficient scheduling and save manpower and material resources.

[0185] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A moving target rapid imaging method based on KT transform, characterized in that: Includes steps: S1, radar receives the echo signal of moving target; S2, performing distance compression processing on the moving target echo signal to obtain a compressed echo signal; S3, performing consistent compensation on the compressed echo signal to obtain a compensated echo signal; S4, performing slow time inversion processing on the compensated echo signal to obtain an inverted echo signal; S5, using KT transformation to decouple the distance and azimuth of the inverted echo signal to obtain a decoupled echo signal; S6, performing a fast Fourier transform in azimuth on the decoupled echo signal to obtain an estimated first-order coefficient; S7, performing a de-motion processing on the compensated echo signal using the estimated first-order term coefficient to obtain a de-motion echo signal; S8, correcting the echo signal after removing the movement by using SOKT transformation to obtain a corrected echo signal; S9, extracting the corrected echo signal and performing mWVD transformation to obtain an estimated Doppler modulation rate; S10, performing azimuth focusing processing on the corrected echo signal using the Doppler frequency modulation rate to obtain a focused echo signal and obtain a moving target imaging result.

2. The moving target rapid imaging method based on KT transform according to claim 1, characterized in that: The step S2 comprises: S21: performing a range dimension fast Fourier transform on the received two-dimensional time domain echo signal of the moving target to obtain an echo signal with a range dimension in the frequency domain and an azimuth dimension in the time domain; The moving target echo signal is expressed as: Where rect(·) represents the window function, t represents the fast time variable, and t a represents the azimuth slow time variable, T p is the pulse width, λ is the wavelength of the transmitted signal, τ is the delay time of the received signal, c is the speed of light, μ is the distance bandwidth, exp is the exponential operation with the natural constant e as the base, R(t a ) is the instantaneous slant distance; The echo signal with distance dimension in frequency domain and azimuth dimension in time domain is expressed as: Among them, f r is the distance frequency variable, f c is the carrier frequency; S22: In the range frequency domain, azimuth time domain, multiply the echo signal with the range compression function to obtain the compressed echo signal, and calculate the slant range R(t a ) at t a = 0, expand the Taylor formula and keep the second-order term, which is expressed as: Among them, H rcom is the distance compression function, which is expressed as R s is the reference slant distance, which indicates the distance between the beam center and the platform, are the phase first-order coefficient and phase second-order coefficient respectively, θ0 is the oblique angle, v represents the platform speed, v x 、v y Represents the velocity component of the target.

3. The moving target rapid imaging method based on KT transform according to claim 2, characterized in that: The step S3 comprises: S31: In the squint mode, the compressed echo signal has range-azimuth coupling. The compressed echo signal is first uniformly corrected for range movement and range curvature to construct a consistent compensation function, which is expressed as: Among them, H un is the consistent compensation function, ρ 10 = -vsinθ0, are the distance travel and distance bending coefficients caused by platform motion, respectively; S32: The consistent compensation function is combined with s2(f r ,t a ) are multiplied to obtain a compensated echo signal, and the compensated echo signal is expressed as: Where, c1=ρ1-ρ 10 ,c2=ρ2-ρ 20 。 4. The moving target rapid imaging method based on KT transform according to claim 3, characterized in that: The step S4 comprises: S41: Using the time reversal conversion method, the compensated echo signal is converted, which is expressed as: in, represents the slow time-reversal conjugate transform; S42: With s3(f r ,t a ) are multiplied to obtain an inverted echo signal, which is expressed as:

5. The moving target rapid imaging method based on KT transform according to claim 4, characterized in that: The step S5 comprises: Perform KT transformation on the inverted echo signal to achieve range and azimuth decoupling. The transformation method is expressed as: Among them, τ a is the transformed slow time variable; The decoupled echo signal is obtained, and the decoupled echo signal is expressed as:

6. The moving target rapid imaging method based on KT transform according to claim 5, characterized in that: The step S6 comprises: S61: Performing a fast Fourier transform in azimuth on the decoupled echo signal, expressed as: Among them, δ(·) is the impulse function, and the impulse appears at Department; S62: Obtain the estimated linear term coefficient according to the position of the impulse function peak, expressed as: The peak(·) function represents the position of the peak value of the impulse function. represents the estimated linear coefficient.

7. The moving target rapid imaging method based on KT transform according to claim 6, characterized in that: The step S7 comprises: S71: Construct the de-walking function, expressed as: Among them, H LRC is the distance movement function, used to correct the first-order phase term; S72: The walking function H LRC and the compensated echo signal s3(f r ,t a ) to obtain the echo signal after walking is removed. The echo signal after walking is expressed as:

8. The moving target rapid imaging method based on KT transform according to claim 7, characterized in that: The step S8 comprises: S81: Use SOKT transformation to correct the distance bending term, expressed as: Among them, η a is the new slow time variable; S82: Obtain a corrected echo signal, wherein the corrected echo signal is expressed as:

9. The moving target rapid imaging method based on KT transform according to claim 8, characterized in that: The step S9 comprises: S91: Perform inverse fast Fourier transform of the distance, extract the distance row after motion correction, and perform the inverse fast Fourier transform of the distance to the one-dimensional signal s p (η a ) is transformed into mWVD, which is expressed as: Among them, t0 is a fixed delay, take S92: Slow-time inverse Fourier transform to obtain an estimate of the Doppler modulation rate 10. The moving target rapid imaging method based on KT transform according to claim 9, characterized in that: The step S10 comprises: S101: Fast Fourier transform along the azimuth direction to transfer to the range, time domain, azimuth and frequency domain; S102: constructing an azimuth pulse pressure function using the Doppler frequency modulation rate, expressed as: S103: multiplying the azimuth pulse pressure function by the corrected echo signal to obtain a focused echo signal, wherein the focused echo signal is expressed as: S104: Perform inverse fast Fourier transform along the azimuth direction, convert to the range time domain and azimuth time domain, and obtain a focused image.

Images