Terahertz ISAR (Inverse Synthetic Aperture Radar) imaging joint compensation method, device, equipment and medium

Abstract

The invention relates to a terahertz ISAR (Inverse Synthetic Aperture Radar) imaging joint compensation method, device and equipment and a medium. The method comprises the following steps: carrying out fractional order Fourier transform on extracted echo data, and then carrying out abrupt change error elimination and least square fitting to obtain a coarse estimation motion parameter; solving a radial displacement difference between adjacent echoes based on the coarse estimation motion parameters; then calculating a rough joint compensation function; performing coarse joint compensation on the target echo data through the coarse joint compensation function to obtain coarse compensation echo data; solving a synthetic waveform entropy based on the coarse compensation echo data; then taking the coarse estimation motion parameter as an iterative initial value, taking the synthetic waveform entropy as a fitness function, and performing iterative optimization solution through a GWO algorithm to obtain fine compensation echo data; and performing direction position Fourier transform on the fine compensation echo data, and outputting a final two-dimensional ISAR image. According to the invention, adverse effects such as frequency offset and defocusing caused by target motion can be effectively eliminated, and the compensation precision is high.

Description

Technical Field

[0001] The present invention relates to the technical field of radar signal processing, and particularly to a terahertz ISAR imaging joint compensation method, device, equipment and medium. Background Art

[0002] Inverse Synthetic Aperture Radar (ISAR) is proposed relative to Synthetic Aperture Radar (SAR), mainly for imaging non-cooperative targets such as ships, aircraft, satellites, etc., and has the characteristics of obtaining high-resolution imaging of targets all-weather, all-day and at long distances. The key step in ISAR imaging lies in translational compensation, that is, compensating for the radial motion of the target relative to the Radar Line of Sight (RLOS), so that the target only rotates around the equivalent rotation center relative to the radar.

[0003] Slow targets in traditional scenarios are usually imaged using a stop-and-go model, that is, considering that the target is stationary relative to the radar within the time of a single pulse emitted by the radar, and there is only range migration between different pulses emitted by the radar. For high-speed space targets such as satellites, the stop-and-go model is no longer applicable. In addition to inter-pulse compensation, intra-pulse compensation of the echo also needs to be considered, otherwise it will greatly affect the ISAR imaging quality.

[0004] Terahertz (THz) waves refer to electromagnetic waves with a frequency range between 0.1 THz and 10 THz, located between microwaves and infrared, and in the transition frequency band from electronics to photonics. Compared with infrared and lasers, terahertz waves have advantages such as good smoke and dust penetration and low sensitivity to aero-optical effects, and can be used for combat in complex environments and space target detection. At the same time, compared with the microwave frequency band, terahertz waves have a shorter wavelength and a larger bandwidth, and have important application values in the application scenarios of radar high-resolution imaging. However, at the same time, compared with radars in the microwave frequency band, when terahertz radars perform ISAR imaging, their higher range resolution also leads to more serious intra-pulse Doppler phenomena caused by the high-speed movement of the imaging target. Severe intra-pulse Doppler modulation will cause frequency offset and defocusing in the range image, affecting the subsequent imaging effect. Summary of the Invention

[0005] Based on this, it is necessary to provide a terahertz ISAR imaging joint compensation method, device, equipment and medium that can solve problems such as frequency offset and defocusing in the range image and low imaging accuracy for the above technical problems.

[0006] A terahertz ISAR imaging joint compensation method, the method comprising: Obtaining echo data of a target; Extract the echo data, then perform fractional Fourier transform on the extracted echo data, and then perform mutation error elimination and least squares fitting to obtain the rough estimated motion parameters; Solve the radial displacement difference between adjacent echoes caused by translational motion based on the rough estimated motion parameters; then calculate the rough joint compensation function according to the rough estimated motion parameters and the radial displacement difference; Perform rough joint compensation on the target echo data through the rough joint compensation function to obtain the roughly compensated echo data; Solve the synthetic waveform entropy based on the roughly compensated echo data; then use the rough estimated motion parameters as the iterative initial value and the synthetic waveform entropy as the fitness function, and perform iterative optimization through the GWO algorithm to obtain the precisely compensated echo data; Perform azimuth Fourier transform on the precisely compensated echo data and output the final two-dimensional ISAR image.

[0007] A terahertz ISAR imaging joint compensation device, the device includes: An echo data acquisition module for acquiring the echo data of the target; A rough estimated motion parameter acquisition module for extracting the echo data, then performing fractional Fourier transform on the extracted echo data, and then performing mutation error elimination and least squares fitting to obtain the rough estimated motion parameters; A rough joint compensation function acquisition module for solving the radial displacement difference between adjacent echoes caused by translational motion based on the rough estimated motion parameters; then calculating the rough joint compensation function according to the rough estimated motion parameters and the radial displacement difference; A roughly compensated echo data calculation module for performing rough joint compensation on the target echo data through the rough joint compensation function to obtain the roughly compensated echo data; Precisely compensated echo data calculation, for solving the synthetic waveform entropy based on the roughly compensated echo data; then using the rough estimated motion parameters as the iterative initial value and the synthetic waveform entropy as the fitness function, and performing iterative optimization through the GWO algorithm to obtain the precisely compensated echo data; A two-dimensional ISAR image generation module for performing azimuth Fourier transform on the precisely compensated echo data and outputting the final two-dimensional ISAR image.

[0008] A computer device includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the steps of the terahertz ISAR imaging joint compensation method are implemented.

[0009] A computer-readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, the steps of the terahertz ISAR imaging joint compensation method are implemented.

[0010] The above-mentioned terahertz ISAR imaging joint compensation method, device, equipment and medium obtain echo data of a target; extract the echo data, then perform fractional Fourier transform on the extracted echo data, and then perform mutation error elimination and least square fitting to obtain a rough estimated motion parameter; solve the radial displacement difference between adjacent echoes caused by translational motion based on the rough estimated motion parameter; then calculate a rough joint compensation function according to the rough estimated motion parameter and the radial displacement difference; perform rough joint compensation on the target echo data through the rough joint compensation function to obtain roughly compensated echo data; solve the synthetic waveform entropy based on the roughly compensated echo data; then use the rough estimated motion parameter as the iterative initial value and the synthetic waveform entropy as the fitness function, and perform iterative optimization through the GWO algorithm to obtain precisely compensated echo data; perform direction Fourier transform on the precisely compensated echo data and output the final two-dimensional ISAR image.

[0011] The beneficial effects of the present invention are as follows: Through the two-step compensation strategy of rough compensation and precise compensation, it can effectively eliminate the adverse effects such as frequency offset and defocus caused by target motion, and the compensation accuracy is higher, so that the target can be more accurately focused during final imaging, improving the image resolution and clarity. Among them, in the rough compensation stage, using the extracted echo data for fractional Fourier transform can reduce the data processing time; using mutation error elimination and least square fitting can effectively remove interference data and obtain more accurate rough estimated motion parameters; calculating the rough joint compensation function through the rough estimated motion parameter and the radial displacement difference can initially correct the echo distortion caused by target motion and make the echo data more conducive to subsequent processing. In the precise compensation stage, using the rough estimated motion parameter as the iterative initial value and the synthetic waveform entropy as the fitness function can not only greatly improve the accuracy of motion parameter estimation, but also limit the parameter search range in precise compensation, accelerate the convergence of the GWO algorithm, have higher calculation efficiency, can achieve more accurate motion compensation in a shorter time, and have better adaptability and robustness. Description of the Drawings

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for description in the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on the structures shown in these drawings without creative efforts.

[0013] Figure 1Schematic diagram of the process of the terahertz ISAR imaging joint compensation method in an embodiment; Figure 2 Schematic diagram of the satellite scatter point model in an embodiment; Figure 3 Schematic diagram of the one-dimensional range profile after coarse compensation in an embodiment, where, Figure 3 (a) Schematic diagram of the coarse-compensated one-dimensional range profile, Figure 3 (b) Local magnification schematic diagram; Figure 4 Schematic diagram of the comparison between the method proposed in the present invention and the PSO algorithm in an embodiment; Figure 5 Schematic diagram of the one-dimensional range profile after fine compensation in an embodiment, where, Figure 5 (a) Schematic diagram of the fine-compensated one-dimensional range profile, Figure 5 (b) Local magnification schematic diagram; Figure 6 Schematic diagram of the comparison of two-dimensional ISAR image results in an embodiment, where, Figure 6 (a) Schematic diagram of the PSO algorithm imaging, Figure 6 (b) Schematic diagram of the GWO algorithm imaging; Figure 7 Schematic block diagram of the terahertz ISAR imaging joint compensation device in an embodiment; Figure 8 Internal structure diagram of a computer device in an embodiment.

[0014] The realization of the object, functional features and advantages of the present invention will be further described with reference to the embodiments and the accompanying drawings. Detailed implementation manners

[0015] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0016] It can be understood that the technical solutions between the various embodiments of the present invention can be combined with each other, but it must be based on the fact that those of ordinary skill in the art can implement it. When the combination of technical solutions conflicts with each other or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the protection scope required by the present invention.

[0017] Next, the embodiments of the present invention will be described in detail with reference to the accompanying drawings in the embodiments of the present invention.

[0018] Embodiment 1 This embodiment discloses a joint compensation method for terahertz ISAR imaging. Through a two-step compensation strategy of coarse compensation and fine compensation, it can effectively eliminate the adverse effects such as frequency offset and defocus caused by target motion, with higher compensation accuracy. As a result, when finally imaging, the target can be focused more accurately, improving the image resolution and clarity. Among them, in the coarse compensation stage, the fractional Fourier transform is performed on the extracted echo data, which can reduce the data processing time; the mutation error elimination and least squares fitting are used, which can effectively remove the interference data and obtain more accurate rough estimated motion parameters; by calculating the coarse joint compensation function through the rough estimated motion parameters and the radial displacement difference, the echo distortion caused by target motion can be preliminarily corrected, making the echo data more conducive to subsequent processing. In the fine compensation stage, taking the rough estimated motion parameters as the iterative initial value and the synthetic waveform entropy as the fitness function, not only can the accuracy of motion parameter estimation be greatly improved, but also the parameter search range in the fine compensation can be restricted, accelerating the convergence of the GWO algorithm, with higher calculation efficiency, enabling more accurate motion compensation to be completed in a shorter time, and having better adaptability and robustness.

[0019] Specifically, as Figure 1 shown, the joint compensation method for terahertz ISAR imaging provided in this embodiment includes the following steps: Step 201, obtain the echo data of the target.

[0020] Step 202, extract the echo data, then perform the fractional Fourier transform on the extracted echo data, and then perform mutation error elimination and least squares fitting to obtain the rough estimated motion parameters.

[0021] Step 203, solve the radial displacement difference between adjacent echoes caused by translational motion based on the rough estimated motion parameters; then calculate the coarse joint compensation function according to the rough estimated motion parameters and the radial displacement difference.

[0022] Step 204, perform coarse joint compensation on the target echo data through the coarse joint compensation function to obtain the coarsely compensated echo data.

[0023] Step 205, solve the synthetic waveform entropy based on the coarsely compensated echo data; then take the rough estimated motion parameters as the iterative initial value and the synthetic waveform entropy as the fitness function, and perform iterative optimization through the GWO algorithm to obtain the finely compensated echo data.

[0024] Step 206, perform the azimuth Fourier transform on the finely compensated echo data and output the final two-dimensional ISAR image.

[0025] In the specific implementation process of step 201, the Dechirp echo data of the moving target can be expressed as: ; Let: ; ; ; Then the echo data can be simplified to: ; Furthermore, the second and third terms of the exponential term in the target dechirped received data do not contain fast time , and they are denoted as a constant exponential term , then the final expression of the echo data is: ; In the formula, represents the data form after Dechirp processing of a single scatter point and a single echo; represents the data of a single scatter point and a single echo; represents the conjugate form of the reference signal in the Dechirp process; represents the attenuation coefficient of the scatter point echo; represents the amplitude of the transmitted signal; represents the target's radial velocity relative to the radar at the time; represents the reference distance during Dechirp processing; represents the radar signal wavelength; represents the conjugate operation; represents the fast time; represents the slow time; represents the distance from the radar to the target at each pulse emission moment; represents the pulse repetition period; represents the imaginary unit; , , represent intermediate quantities; represents the constant exponential term; represents the speed of light; represents the chirp rate of the transmitted radar signal (LFM signal).

[0026] In the specific implementation process of step 202, in order to improve the operation efficiency, it is only necessary to extract a finite-length LFM signal for fractional Fourier transform (FrFT). Preferably, generally the first half of the echo is extracted for calculation.

[0027] Specifically, a rotation angle is preset; based on the rotation angle , the extracted echo data is subjected to fractional Fourier transform along the fast time domain, and the process expression is: ; Then, according to the relationship between the rotation angle and the chirp rate : ; ; a joint solution is carried out to obtain the radial motion velocity of the target.

[0028] In the formula, represents the result of the fractional Fourier transform; represents the fractional frequency domain; represents the normalization factor.

[0029] It can be seen that when a suitable rotation angle is selected for the FrFT, the influence of the chirp term is removed, so that a well-focused one-dimensional range image can be obtained.

[0030] Then, to solve the problem of large estimation error of the FrFT method, the method of "eliminating mutation error + least squares fitting" is adopted to improve the fitting accuracy of the target motion parameters.

[0031] Specifically, by eliminating the mutation error and performing least squares fitting on the radial motion velocity of the target, the rough estimated motion parameters are finally obtained, including: First, the mutation error of the radial motion velocity of the target is eliminated, including: For , the fractional Fourier transform is performed on the -th echo to solve the radial motion velocity of the target at the -th echo.

[0032] An empirical value is set. If there exists such that and , where , then let , and the error elimination is completed.

[0033] Then, the least squares fitting is performed on the radial motion velocity of the target after error elimination, including: For the discrete velocity-time observation sequence , assuming it follows the parametric model , then the target minimizes the sum of squared residuals to obtain the rough estimated motion parameters , , .

[0034] In the formula, represents the number of pulses within the coherent integration time (assumed to be even); represents the th radial velocity of the target at the th echo; represents the th radial velocity of the target at the th echo; represents the estimated velocity of the th echo; represents the coarsely estimated initial velocity; represents the coarsely estimated acceleration; represents the coarsely estimated jerk.

[0035] In the specific implementation process of step 203, based on the coarsely estimated motion parameters , , obtained in step 202, let: ; Based on this, the radial displacement difference between adjacent echoes caused solely by translational motion can be obtained, and the calculation expression is: ; In the formula, represents the radial displacement difference between adjacent echoes; represents the th slow time at the

[0036] Based on the above analysis, the first compensation function and the second compensation function required for intra-pulse compensation of the moving target can be obtained; Among them, the expression of the first compensation function is: ; The expression of the second compensation function is: ; In the formula, represents the distance from the radar to the target at the moment of each pulse emission; represents the chirp rate of the transmitted radar signal; represents the fast time; represents the radial velocity of the target relative to the radar at ; represents the speed of light; Since both intra-pulse and inter-pulse compensations rely on the estimation of target motion parameters, therefore, the required joint compensation function is denoted as a whole as Then, the target echo data is multiplied by the joint compensation function to complete the joint compensation in both intra-pulse and inter-pulse. That is, in the coarse compensation stage, based on the coarsely estimated motion parameters, the radial displacement difference, the first compensation function, and the second compensation function, the coarse joint compensation function for the target motion parameters is obtained and expressed as .

[0037] In the specific implementation process of step 204, the target echo data is coarsely jointly compensated by the coarse joint compensation function to obtain the coarsely compensated echo data, and the expression is: ; where, ; In the formula, represents the one-dimensional range profile after joint intra-pulse and inter-pulse coarse compensation; represents the one-dimensional range profile after intra-pulse coarse compensation; represents the displacement caused by the target translational motion; represents the frequency domain; represents the radial range walk caused by the target translational motion; represents the radial range walk caused by the target rotational motion.

[0038] In the specific implementation process of step 205, first, the fine joint compensation function for the target motion parameters is determined.

[0039] According to the coarsely estimated motion parameters , , , the displacement caused by the target translational motion is obtained, and the expression is: ; According to the displacement caused by the target translational motion, the range-direction Fourier transform of the coarsely compensated echo data obtained in step 204 is performed, and it is expressed as: ; The above formula is discretized to obtain: ; For the convenience of expression, let: ; Then the simplified expression is: ; In the formula, represents the single scatter point and single echo data after joint compensation; represents the discretized ; represents the range-direction sampling rate; Indicates the number of sampling points in the distance direction; Indicates the distance to any sampling location; Indicates the pulse frequency of radar transmission signal; Indicates the azimuth sampling pulse.

[0040] This is the echo data format after intra-pulse and inter-pulse compensation for a single scattering point and a single echo. Scattering points, the storage format of echo data is expressed as: ; In the formula, express Scattering points, echo data within the coherent accumulation time; Indicates the number of received pulses.

[0041] Based on the above analysis, in the process of fine compensation, represents the one-dimensional range image after translation compensation, where Indicates taking the absolute value.

[0042] The estimated motion parameters to be estimated in the fine compensation process are expressed as: ; Then in the fine compensation process, the fine joint compensation function can be further written as , the one-dimensional range image after fine joint compensation can be expressed as .

[0043] Drawing on the concept of waveform entropy, the one-dimensional distance images of all pulses are synthesized and summed up row by row (in actual processing, the column direction is generally the distance direction, and the row direction is the azimuth direction), thereby synthesizing the entropy value of the waveform. If the broadening of the main lobe is corrected well during intra-pulse compensation, the peak is more prominent, and the envelope alignment is well done during inter-pulse compensation, the peaks will be superimposed on each other, and the synthesized waveform will be more "sharp", that is, the waveform entropy value is lower; on the contrary, if the intra-pulse and inter-pulse compensation is not done well, the peaks will be staggered, and the envelope of the synthesized waveform will be more "flat", that is, the waveform entropy value is higher. The synthesized waveform is recorded as ,but Should be a Column vector of , and for any sampling point of distance , the synthetic waveform has the following relationship: ; Assume that the resulting distance vector , normalize the value of the distance vector to , that is, the value of each unit after normalization is , and there is , at this time, it has the property of similar probability, and the synthetic waveform entropy can be expressed as: ; When solving for any element , in order to achieve the best estimation, it is necessary to make: ; In the formula, represents any sampling point in the range direction; represents the joint compensation function; takes values of , , .

[0044] When using the synthetic waveform entropy as the fitness function, the initial waveform entropy is solved based on the coarsely compensated echo data, and the joint compensation function is the coarse joint compensation function , and the initial waveform entropy is used as the initial fitness function for iteration; in the iterative optimization process, the synthetic waveform entropy is solved based on the finely compensated echo data, and the joint compensation function is the fine joint compensation function .

[0045] After obtaining the coarsely estimated motion parameters and the synthetic waveform entropy, using the coarsely estimated motion parameters as the initial iteration value and the synthetic waveform entropy as the fitness function, iterative optimization is performed through the GWO algorithm to obtain the finely compensated echo data.

[0046] It can be understood that in the GWO algorithm, in order to mathematically simulate the social hierarchy of wolves, the optimal solution is defined as for simulating the position of the leading wolf, the sub-optimal solution and the second sub-optimal solution are respectively named and , for simulating the positions of the second-order wolf and the third-order wolf. The remaining candidate solutions are assumed to be , for simulating the position of the subordinate wolf. In the GWO algorithm, the hunting (solving) is guided by wolf, wolf and wolf, and wolf follows these three wolves to change its own position. In this embodiment, the coarsely estimated motion parameters in the coarse compensation stage limit the search range of parameters in the iterative process, accelerate the convergence speed of GWO, and have higher compensation efficiency. In addition, iterative optimization through the GWO algorithm is a conventional technical means and will not be elaborated here. In the specific implementation process of step 206, before performing the azimuth Fourier transform on the finely compensated echo data, it is also necessary to perform phase fine calibration PGA on the finely compensated echo data to correct the phase error and achieve image autofocus.

[0047] In one embodiment, a simulation experiment is carried out to verify the method provided by the present invention. As Figure 2 shown, the satellite model used in the experiment consists of 544 scattering points.

[0048] The simulation parameters used are shown in Table 1: Table 1 Radar and target simulation parameters:

[0049] In the experiment, 512 echoes are taken for processing. After the first-step coarse compensation, the one-dimensional range profile of the target is as Figure 3 shown.

[0050] It is found that the envelope alignment effect is poor and cannot meet the subsequent imaging requirements. Set the number of gray wolf populations to 30 and the number of iterations to 50 times. Based on the same roughly estimated motion parameters 、 、 Compare the Particle Swarm Optimizer (PSO) and the method proposed by the present invention. In the PSO algorithm, the number of particles is also set to 30 and the number of iterations is 50 times, and the search range control is the same. The comparison chart of the iterative optimization results of the two algorithms is as Figure 4 shown. It can be seen from the curves of the method proposed by the present invention and PSO that when iterating 5 times, there is a large change in the entropy value of the synthesized waveform of the one-dimensional range profile, but neither of them reaches the optimal value. When iterating to about the 8th time, the PSO algorithm tends to be flat but fails to reach the optimal solution; the method proposed by the present invention begins to tend to be flat at the 20th iteration and approaches the optimal value. It shows that compared with the two algorithms, the method proposed by the present invention can converge faster and has a better final convergence effect.

[0051] Use the refined joint compensation function after 50 iterations to complete the intra-pulse and inter-pulse joint compensation of the target. The one-dimensional range profile is as Figure 5 shown.

[0052] The two-dimensional ISAR imaging results of the echo data after the intra-pulse and inter-pulse compensation of the two algorithms are as Figure 6 shown. At the same time, record the operation time of the two algorithms iterating 50 times and the contrast of the final imaging results in Table 2.

[0053] Table 2 Comparison of algorithm effects

[0054] It can be seen that the method proposed by the present invention takes less time, has higher computational efficiency, and has higher contrast in the two-dimensional ISAR image and better compensation accuracy.

[0055] Although in this embodiment Figure 1The steps in [it] are sequentially shown according to the indication of the arrows, but these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless there is a clear description in the present invention, there is no strict order limit for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least a part of the steps in [it] may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same moment, but can be executed at different moments. The execution order of these sub-steps or stages is not necessarily sequential either, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0056] Embodiment 2 Based on the terahertz ISAR imaging joint compensation method in Embodiment 1, this embodiment discloses a terahertz ISAR imaging joint compensation device. As Figure 7 shown, the terahertz ISAR imaging joint compensation device includes: an echo data acquisition module 401, a rough estimation motion parameter acquisition module 402, a rough joint compensation function acquisition module 403, a rough compensation echo data calculation module 404, a fine compensation echo data calculation 405, and a two-dimensional ISAR image generation module 406, where: The echo data acquisition module 401 is used to acquire the echo data of the target.

[0057] The rough estimation motion parameter acquisition module 402 is used to extract the echo data, then perform a fractional Fourier transform on the extracted echo data, and then perform mutation error elimination and least squares fitting to obtain the rough estimation motion parameters.

[0058] The rough joint compensation function acquisition module 403 is used to solve the radial displacement gap between adjacent echoes caused by translational motion based on the rough estimation motion parameters; then calculate the rough joint compensation function according to the rough estimation motion parameters and the radial displacement gap.

[0059] The rough compensation echo data calculation module 404 is used to perform rough joint compensation on the target echo data through the rough joint compensation function to obtain the rough compensation echo data.

[0060] The fine compensation echo data calculation 405 is used to solve the synthetic waveform entropy based on the rough compensation echo data; then use the rough estimation motion parameters as the iterative initial value and the synthetic waveform entropy as the fitness function, and perform iterative optimization through the GWO algorithm to obtain the fine compensation echo data.

[0061] The two-dimensional ISAR image generation module 406 is used to perform a direction Fourier transform on the fine compensation echo data and output the final two-dimensional ISAR image.

[0062] In this embodiment, the specific working processes and working principles of the echo data acquisition module 401, the rough joint compensation function acquisition module 403, the roughly compensated echo data calculation module 404, the finely compensated echo data calculation 405, and the two-dimensional ISAR image generation module 406 are the same as those of the method in Embodiment 1. Therefore, they will not be elaborated in this embodiment. Each of these unit modules can be implemented in whole or in part by software, hardware, or a combination thereof. Each unit module can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of these unit modules.

[0063] Embodiment 3 As Figure 8 shown, a terminal device disclosed in this embodiment includes a transmitter, a receiver, a memory, and a processor. Among them, the transmitter is used to send instructions and data, the receiver is used to receive instructions and data, the memory is used to store computer execution instructions, and the processor is used to execute the computer execution instructions stored in the memory to implement the method in Embodiment 1 above.

[0064] It should be noted that the above memory can be either independent or integrated with the processor. When the memory is set independently, the terminal device further includes a bus for connecting the memory and the processor.

[0065] Embodiment 4 This embodiment discloses a computer-readable storage medium in which computer execution instructions are stored. When the processor executes the computer execution instructions, the method in Embodiment 1 above is implemented.

[0066] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0067] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0068] The above-described embodiments merely represent several implementation manners of the present invention. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.

Claims

1. A terahertz ISAR imaging joint compensation method, characterized in that: The method comprises: Get the target's echo data; Extracting the echo data, then performing fractional Fourier transform on the extracted echo data, and then performing mutation error elimination and least square fitting to obtain a rough estimated motion parameter; Solving the radial displacement difference between adjacent echoes caused by translation based on the coarse estimated motion parameters; then calculating the coarse joint compensation function according to the coarse estimated motion parameters and the radial displacement difference; Performing coarse joint compensation on the target echo data by using the coarse joint compensation function to obtain coarse compensated echo data; Solving the synthetic waveform entropy based on the coarse compensation echo data; then taking the coarse estimated motion parameter as the iteration initial value and the synthetic waveform entropy as the fitness function, performing iterative optimization through the GWO algorithm to obtain the fine compensation echo data; The precision compensated echo data is subjected to directional Fourier transform to output a final two-dimensional ISAR image.

2. The terahertz ISAR imaging joint compensation method according to claim 1, characterized in that: The extracted echo data is subjected to fractional Fourier transform, and then mutation error elimination and least squares fitting are performed to obtain rough estimated motion parameters, including: Preset rotation angle ; Based on the rotation angle The extracted echo data is subjected to fractional Fourier transform in the fast time domain. The process expression is: ； According to the rotation angle Frequency The relationship between: ； ； Perform joint solution to obtain the radial motion speed of the target ; The radial velocity of the target Perform mutation error elimination and least squares fitting to finally obtain rough estimated motion parameters; In the formula, Represents the fractional Fourier transform result; represents the fractional frequency domain; Indicates slow time; Indicates the rotation angle; represents the normalization factor; Indicates the attenuation coefficient of the echo from the scattering point; Indicates the amplitude of the transmitted signal; represents the pulse repetition period; represents an imaginary unit; , , Indicates an intermediate quantity; Indicates the frequency modulation; represents a constant exponential term; Represents the speed of light.

3. The terahertz ISAR imaging joint compensation method according to claim 2, characterized in that: The radial velocity of the target Perform mutation error elimination and least squares fitting to finally obtain rough estimated motion parameters, including: First, the radial velocity of the target Perform mutation error elimination, including: for , for Perform fractional Fourier transform on the echo and solve the The radial velocity of the target at the second echo ; Setting Experience Points , if exists , so that and ,in , then let , complete error elimination; Then, the radial motion speed of the target after error elimination is Perform a least squares fit, including: For discrete speed-time observation sequences , assuming that it obeys the parameterized model , then the objective is to minimize the residual sum of squares , get the rough estimated motion parameters , , ; In the formula, Indicates the number of pulses within the coherent accumulation time; Indicates The radial velocity of the target at the time of the second echo; Indicates The radial velocity of the target at the time of the second echo; represents the coefficient of the first-order term parameterized with respect to slow time; represents the coefficient of the parameterized quadratic term with respect to slow time; Indicates the estimated The speed of the secondary echo; represents a rough estimate of the initial velocity; represents a rough estimate of acceleration; Represents a rough estimate of jerk.

4. The terahertz ISAR imaging joint compensation method according to claim 3, characterized in that: Solving the radial displacement difference between adjacent echoes caused by translation based on the coarse estimated motion parameters includes: set up: ； Based on this solution, the radial displacement difference between adjacent echoes caused by translation is calculated as follows: ； In the formula, Indicates the radial displacement difference between adjacent echoes; Indicates Slow time during the second echo.

5. The terahertz ISAR imaging joint compensation method according to any one of claims 1 to 4, characterized in that: Calculating a rough joint compensation function according to the rough estimated motion parameter and the radial displacement difference includes: First, construct a first-order compensation function and a second-order compensation function; The primary compensation function expression is: ； The quadratic compensation function expression is: ； In the formula, Indicates the distance from the radar to the target at each pulse emission moment; Indicates the modulation rate of the transmitted radar signal; Indicates fast time; Indicates the target The radial velocity relative to the radar at time; represents the speed of light; Then, based on the rough estimated motion parameters, the radial displacement difference, the first compensation function and the second compensation function, a rough joint compensation function for the target motion parameters is obtained. .

6. The terahertz ISAR imaging joint compensation method according to claim 5, characterized in that: The target echo data is coarsely combined and compensated by the coarse joint compensation function to obtain coarse compensated echo data, which is expressed as: ； In the formula, It represents the one-dimensional distance image after the intra-pulse and inter-pulse joint coarse compensation; It represents the one-dimensional range image after intra-pulse coarseness compensation; Represents the displacement caused by the target translation; Indicates the wavelength of radar signal; represents the radial distance movement caused by the target translation; Indicates the radial distance movement caused by the target rotation; Indicates the reference distance during Dechirp processing.

7. The terahertz ISAR imaging joint compensation method according to claim 6, characterized in that: The calculation expression of the synthetic waveform entropy is: ； In the formula, Indicates the distance to any sampling location; represents the joint compensation function.

8. A terahertz ISAR imaging joint compensation device, characterized in that: The device comprises: An echo data acquisition module, used to acquire echo data of a target; A rough estimation motion parameter acquisition module is used to extract the echo data, then perform fractional Fourier transform on the extracted echo data, and then perform mutation error elimination and least square fitting to obtain rough estimation motion parameters; A coarse joint compensation function acquisition module is used to solve the radial displacement difference between adjacent echoes caused by translation based on the coarse estimated motion parameters; and then calculate the coarse joint compensation function according to the coarse estimated motion parameters and the radial displacement difference; A coarse compensation echo data calculation module, used for performing coarse joint compensation on the target echo data by using the coarse joint compensation function to obtain coarse compensation echo data; Fine compensation echo data calculation is used to solve the synthetic waveform entropy based on the coarse compensation echo data; then the coarse estimated motion parameter is used as the iteration initial value, the synthetic waveform entropy is used as the fitness function, and the GWO algorithm is used to perform iterative optimization and solve to obtain fine compensation echo data; The two-dimensional ISAR image generation module is used to perform directional Fourier transform on the precision compensated echo data and output a final two-dimensional ISAR image.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the terahertz ISAR imaging joint compensation method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the terahertz ISAR imaging joint compensation method according to any one of claims 1 to 7 are implemented.

Images