Terahertz ISAR Imaging Sidelobe Suppression Method, Device, Equipment and Medium

Abstract

The present invention relates to a method, device, equipment and medium for suppressing sidelobes in terahertz ISAR imaging. The method includes: obtaining the ISAR focused imaging result in the terahertz frequency band; using the Newton iteration method to estimate the ISAR focused imaging result to obtain the rotational angular velocity and rotation center of the target; selecting two sub-aperture images from the ISAR focused imaging result, and based on the rotational angular velocity and rotation center, matching the two sub-aperture images to obtain a matched imaging result; performing sum-difference operation on the matched imaging result to obtain the final result after sidelobe suppression. The present invention can effectively separate the main lobe and the sidelobe, significantly suppress non-orthogonal sidelobes, greatly improve the imaging clarity, avoid problems such as image blurring, artifact enhancement and weak target masking, and has strong practicability and reliability.

Description

Technical Field

[0001] The present invention relates to the field of radar imaging technology, and in particular to a terahertz ISAR imaging sidelobe suppression method, device, equipment and medium. Background Art

[0002] Terahertz radar technology has been widely used in the field of imaging detection due to its significant advantages such as large bandwidth and high resolution. Electromagnetic waves in the terahertz frequency band can penetrate a variety of non-conductive materials and provide high-precision target imaging capabilities, so it shows great application potential in security inspections, medical imaging, and non-destructive testing. However, although terahertz radar has excellent performance in theory, it still faces many technical challenges in practical applications, especially in terms of imaging quality.

[0003] One of the main issues is the impact of system non-ideality and target scattering characteristics on imaging results. These factors will lead to the generation of non-orthogonal sidelobes, which will interfere with imaging. The existence of non-orthogonal sidelobes will cause problems such as image blur, artifact enhancement, and masking of weak targets, which seriously reduces the clarity of imaging and the accuracy of target recognition. Especially in the terahertz frequency band, due to its high Doppler sensitivity and large bandwidth, the interference of non-orthogonal sidelobes on imaging is particularly significant. In addition, the distribution of non-orthogonal sidelobes in the terahertz frequency band is usually irregular, and traditional sidelobe suppression methods are difficult to deal with effectively, resulting in further deterioration of imaging quality.

[0004] In addition, the existing sidelobe suppression technology is mainly designed for low-frequency radar systems, and these methods have limited applicability in the terahertz band. For example, although the traditional frequency domain windowing method can suppress sidelobes to a certain extent, it will introduce the problems of main lobe broadening and resolution loss, which is particularly unfavorable for high-precision imaging requirements. Although the nonlinear weighted algorithm (SVA) directly suppresses sidelobes in the image domain, the nonlinear weighted algorithm is mainly designed for orthogonal sidelobes, and the suppression effect of non-orthogonal sidelobes is poor. Its main means is to perform weighted processing on each pixel, which has high computational complexity and the risk of weak target loss in the process of suppressing sidelobes. The CLEAN algorithm mainly reconstructs the target image by iteratively subtracting the scattering center, but it is highly dependent on the accuracy of the initial scattering center model, and the imaging effect for extended targets or complex target structures is poor. The SRSR method mainly separates the main lobe and sidelobes by changing the shape of the spectrum support area. However, this method requires accurate estimation of the spectrum support area. If the estimation is inaccurate, it may lead to failure of sidelobe suppression or loss of main lobe energy. Moreover, the spectrum support area can only affect the distribution of orthogonal side lobes. Therefore, the SRSR method can only suppress orthogonal side lobes, but has limited suppression effect on non-orthogonal side lobes, especially in the terahertz frequency band, where the side lobe distribution is complex and irregular. Summary of the invention

[0005] Based on this, it is necessary to provide a Terahertz ISAR imaging sidelobe suppression method, device, equipment and medium that can effectively suppress non-orthogonal sidelobes, improve imaging quality, and solve problems such as image blurring, artifact enhancement, and weak target masking for the above technical problems.

[0006] A Terahertz ISAR imaging sidelobe suppression method, the method comprising:

[0007] Obtain the ISAR focused imaging result in the Terahertz frequency band;

[0008] Use the Newton iteration method to estimate the ISAR focused imaging result to obtain the rotational angular velocity and rotation center of the target;

[0009] Select two sub-aperture images from the ISAR focused imaging result, and based on the rotational angular velocity and the rotation center, match the two sub-aperture images to obtain a matched imaging result;

[0010] Perform sum-difference operation on the matched imaging result to obtain the final result after sidelobe suppression.

[0011] A Terahertz ISAR imaging sidelobe suppression device, the device comprising:

[0012] An ISAR focused imaging result acquisition module, configured to obtain the ISAR focused imaging result in the Terahertz frequency band;

[0013] A rotational angular velocity and rotation center estimation module, configured to use the Newton iteration method to estimate the ISAR focused imaging result to obtain the rotational angular velocity and rotation center of the target;

[0014] A matching module, configured to select two sub-aperture images from the ISAR focused imaging result, and based on the rotational angular velocity and the rotation center, match the two sub-aperture images to obtain a matched imaging result;

[0015] A sidelobe suppression module, configured to perform sum-difference operation on the matched imaging result to obtain the final result after sidelobe suppression.

[0016] A computer device, comprising a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the Terahertz ISAR imaging sidelobe suppression method when executing the computer program.

[0017] A computer-readable storage medium, having a computer program stored thereon, and the computer program implementing the steps of the Terahertz ISAR imaging sidelobe suppression method when executed by a processor.

[0018] The above-mentioned terahertz ISAR imaging sidelobe suppression method, device, equipment and medium obtain the ISAR focused imaging result in the terahertz band; use the Newton iteration method to estimate the ISAR focused imaging result to obtain the rotational angular velocity and rotation center of the target; select two sub-aperture images from the ISAR focused imaging result, and based on the rotational angular velocity and rotation center, match the two sub-aperture images to obtain the matched imaging result; perform sum-difference operation on the matched imaging result to obtain the final result after sidelobe suppression.

[0019] Based on the ISAR focused imaging result in the terahertz band, the present invention selects two sub-aperture images. Based on the idea of separating the sidelobe and main lobe by spectrum rearrangement, one imaging result is matched with another imaging result to obtain an imaging result with the main lobes coinciding and the sidelobes not overlapping. This can effectively separate the main lobe and sidelobe, significantly suppress non-orthogonal sidelobes, greatly improve the imaging clarity, avoid problems such as image blurring, artifact enhancement, and weak target masking, and make the target details clearer and distinguishable. During the imaging process, the Newton iteration method is used to estimate the target rotational angular velocity and rotation center, which can obtain high-precision ISAR image quality and provide an important basis for subsequent motion state analysis and structural features. When performing sum-difference operation on the matched imaging result, it can achieve non-coherent superposition of the main lobe energy while suppressing the sidelobe. This enhances the main lobe signal intensity, further improves the prominence of the target in the image, and improves the detection accuracy of the target. The present invention can effectively solve the problem of sidelobe interference in terahertz ISAR imaging and has strong practicability and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] 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, without creative efforts, other drawings can be obtained based on the structures shown in these drawings.

[0021] Figure 1 It is a schematic flowchart of a terahertz ISAR imaging sidelobe suppression method in an embodiment;

[0022] Figure 2 It is a schematic diagram of the relative positions of the first sub-aperture image and the second sub-aperture image in an embodiment;

[0023] Figure 3 It is a schematic diagram of the relative positions of the sidelobes and main lobes of the third sub-aperture image and the fourth sub-aperture image in an embodiment;

[0024] Figure 4 It is a schematic diagram of the inverse imaging result of the rotation angle in an embodiment, whereFigure 4 (a) is a schematic diagram of the first sub-aperture imaging, Figure 4 (b) is a schematic diagram of the second sub-aperture imaging, Figure 4 (c) is a schematic diagram after the third sub-aperture imaging is matched with the fourth sub-aperture imaging, Figure 4 (d) is a schematic diagram of the imaging result after suppressing the sidelobes;

[0025] Figure 5 is a schematic diagram of the range and azimuth profiles in an embodiment, where, Figure 5 (a) is a schematic diagram of the range profile, Figure 5 (b) is a schematic diagram of the azimuth profile;

[0026] Figure 6 is a structural block diagram of a terahertz ISAR imaging sidelobe suppression device in an embodiment;

[0027] Figure 7 is an internal structure diagram of a computer device in an embodiment.

[0028] 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. Specific Embodiments

[0029] 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 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 belong to the scope of protection of the present invention.

[0030] 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 them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0031] 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.

[0032] Embodiment 1

[0033] This embodiment discloses a method for suppressing sidelobes in terahertz ISAR imaging. Based on the ISAR focused imaging results in the terahertz band, two sub-aperture images are selected. Based on the idea of separating sidelobes from the main lobe by spectrum rearrangement, one imaging result is matched with another imaging result to obtain an imaging result with overlapping main lobes and non-overlapping sidelobes, which can effectively separate the main lobe from the sidelobe, significantly suppress non-orthogonal sidelobes, greatly improve the imaging clarity, avoid problems such as image blurring, artifact enhancement, and weak target masking, and make target details clearer and distinguishable. During the imaging process, the Newton iteration method is used to estimate the target rotation angular velocity and rotation center, and a high-precision ISAR image can be obtained, providing an important basis for subsequent motion state analysis and structural features. By performing sum-difference operations on the matched imaging results, while suppressing sidelobes, non-coherent superposition of the main lobe energy is achieved. This enhances the main lobe signal intensity, further improves the prominence of the target in the image, and improves the detection accuracy of the target. The present invention can effectively solve the problem of sidelobe interference in terahertz ISAR imaging, can effectively suppress non-orthogonal sidelobes caused by factors such as system non-ideality and target scattering characteristics, and has strong practicability and reliability.

[0034] As Figure 1 shown, the method for suppressing sidelobes in terahertz ISAR imaging provided by this embodiment includes the following steps:

[0035] Step 201, obtain the ISAR focused imaging results in the terahertz band.

[0036] Step 202, use the Newton iteration method to estimate the ISAR focused imaging results to obtain the rotation angular velocity and rotation center of the target.

[0037] Step 203, select two sub-aperture images from the ISAR focused imaging results, and based on the rotation angular velocity and rotation center, match the two sub-aperture images to obtain the matched imaging results.

[0038] Step 204, perform sum-difference operations on the matched imaging results to obtain the final result after sidelobe suppression.

[0039] In one embodiment, obtaining the ISAR focused imaging results in the terahertz band includes:

[0040] Obtain the radar echo signal in the terahertz band, perform trigonometric expansion on the radar echo signal to obtain the expanded coupling signal.

[0041] Use Keystone to eliminate the coupling between range and azimuth in the expanded coupling signal, and at the same time ignore the range migration caused by the range-variant quadratic term to obtain the transformed ideal terahertz ISAR echo signal.

[0042] Perform Fourier transform on the fast time in the ideal echo signal of terahertz ISAR to obtain the echo signal after fast-time Fourier transform.

[0043] Perform phase compensation on the echo signal after fast-time Fourier transform and perform Fourier transform on the slow-time variable in the azimuth dimension to obtain the ISAR focusing imaging result in the terahertz band.

[0044] Specifically, for a broadband radar system in the terahertz band, assuming that the target translation has been compensated, in order to reduce the sampling rate of a large-bandwidth radar, after the antenna transmits a linear frequency modulation signal and it is reflected by the target, dechirp reception is used and the RVP phase is removed. The obtained radar echo signal can be expressed as:

[0045] (1)

[0046] In the formula, represents the fast time; represents the accumulation angle; represents the imaginary unit; represents the carrier frequency; represents the frequency modulation rate; represents the slow time; represents the speed of light; represents the scatterer reflection intensity; 、 represent the coordinates of the scatterer relative to the rotation center.

[0047] Perform trigonometric function expansion on the radar echo signal. The obtained expanded coupled signal can be expressed as:

[0048] (2)

[0049] In the formula, represents the rotational angular velocity of the target relative to the radar.

[0050] Formula (2) ignores the Taylor expansion terms above the third order, which includes a range-variant quadratic term and the fast time is coupled with the slow time. Therefore, Keystone is used to eliminate the coupling between range and azimuth in the expanded coupled signal, and at the same time, the range migration caused by the range-variant quadratic term is ignored. Substitute into formula (2) to obtain the transformed ideal echo signal of terahertz ISAR, and the expression is:

[0051] (3)

[0052] In the formula, represents the slow time after Keystone resampling; Denote the transformed ideal THz ISAR echo signal; Denote the ideal THz ISAR echo signal. After performing a two-dimensional Fourier transform on it, the coordinates of each scatterer can be restored. Equation (3) can be regarded as a chirp signal with respect to slow time , if a direct Fourier transform with respect to is performed on it, the result will be broadened in the frequency domain, and the azimuth coordinates of the scatterers cannot be accurately obtained. Therefore, it is necessary to accurately estimate the target rotation parameters, construct a phase error matrix, and compensate the echo before the ISAR focusing imaging result in the THz band can be obtained.

[0053] Among them, perform a Fourier transform on the fast time in the ideal THz ISAR echo signal to obtain the echo signal after the fast-time Fourier transform, and the expression is:

[0054] (4)

[0055] In the formula, denotes the fast-time frequency; denotes the pulse width.

[0056] Usually, the coordinates of the target rotation center are not zero. Therefore, perform phase compensation on the echo signal after the fast-time Fourier transform in formula (4), and perform a Fourier transform on the slow-time variable in the azimuth dimension to obtain the ISAR focusing imaging result in the THz band, and the expression is:

[0057] (5)

[0058] In the formula, denotes the Fourier transform from the slow-time domain to the Doppler frequency domain, which is used to convert the slow-time domain signal to the frequency domain; denotes the Doppler frequency variable; denotes the echo signal after the fast-time Fourier transform; denotes the rotation center; denotes the Doppler frequency; denotes the coherent integration time. Equation (5) shows that in order to construct a phase error compensation matrix, the parameter values of the rotation center and the rotational angular velocity need to be obtained simultaneously. The estimation accuracy of the target rotation speed and the rotation center directly determines the quality of the ISAR image. Therefore, the Newton iteration method is used for estimation to obtain the high-precision rotational angular velocity and the rotation center . The Newton iteration method is a conventional technical means and will not be elaborated here.

[0059] In one embodiment, two sub-aperture images are selected from the ISAR focused imaging results, and based on the rotational angular velocity and the rotation center, the two sub-aperture images are matched to obtain the matched imaging result, including:

[0060] Select the first sub-aperture image and the second sub-aperture image from the ISAR focused imaging results, and calculate the cumulative angle between the first sub-aperture image and the second sub-aperture image based on the rotational angular velocity and the rotation center.

[0061] According to the cumulative angle, adjust the resolution of the first sub-aperture image and the second sub-aperture image to obtain the third sub-aperture image and the fourth sub-aperture image with the same size of range cells and azimuth cells.

[0062] Align the centers of the third sub-aperture image and the fourth sub-aperture image, and then rotate the third sub-aperture image based on the cumulative angle to obtain the matched imaging result.

[0063] In one embodiment, the first sub-aperture image and the second sub-aperture image are two adjacent images under consecutive viewing angles.

[0064] In one embodiment, according to the cumulative angle, adjust the resolution of the first sub-aperture image and the second sub-aperture image, and the expression of the resolution adjustment is:

[0065] ;

[0066] ;

[0067] In the formula, represents the range resolution; represents the azimuth resolution; represents the speed of light; represents the bandwidth; represents the wavelength; represents the accumulation angle of imaging.

[0068] In one embodiment, rotate the third sub-aperture image based on the cumulative angle, and the expression is:

[0069] ;

[0070] In the formula, represents the scattering point coordinates on the fourth sub-aperture image; represents the scattering point coordinates on the third sub-aperture image; represents the cumulative angle of rotation.

[0071] It can be understood that after being processed by the imaging algorithm, the spectrum of the target echo signal is a rectangular spectrum. Therefore, after Fourier transform, the sidelobes are distributed along the range dimension and the azimuth dimension respectively. In the imaging results of the sub-apertures, the main lobe is consistent with the distribution of the scattering points. As the target rotates, the scattering points also rotate, that is, the main lobe rotates simultaneously. The positions of the main lobes of the first sub-aperture imaging and the second sub-aperture imaging are inconsistent. After matching, the positions of the main lobes of the scattering points coincide. At this time, after matching, due to the rotation operation, the directions of the sidelobes of the two images change, providing conditions for the subsequent separation of the main lobe and the sidelobe.

[0072] Specifically, through step 202, the rotational angular velocity of the target can be obtained and the rotation center . Then, based on the ISAR focusing imaging results, two adjacent sub-aperture imaging results under continuous viewpoints are selected, and the cumulative angle between the first sub-aperture imaging and the second sub-aperture imaging can be obtained. This included angle is a key parameter for subsequent image rotation, which reflects the difference in the imaging viewpoints of the two sub-apertures. Then, the rotation center is displaced to the coordinate origin, that is, the centers of the first sub-aperture imaging and the second sub-aperture imaging are aligned, and the relative position schematic diagram as shown in Figure 2 is obtained.

[0073] Before rotation, it is necessary to make the range cells and azimuth cells of the first sub-aperture imaging and the second sub-aperture imaging the same size to ensure that during subsequent image rotation, the geometric structure of the image remains consistent and avoid matching errors caused by differences in cell sizes. In the case of known cumulative angle , interpolation operations are performed according to the range resolution and the azimuth resolution so that the range cells and azimuth cells of the first sub-aperture imaging and the second sub-aperture imaging are the same size, and correspondingly, the third sub-aperture imaging and the fourth sub-aperture imaging after adjusting the resolution are obtained, and the centers of the third sub-aperture imaging and the fourth sub-aperture imaging are aligned. It should be noted that the third sub-aperture imaging is the first sub-aperture imaging after adjusting the resolution, and the fourth sub-aperture imaging is the second sub-aperture imaging after adjusting the resolution.

[0074] At this time, based on the cumulative angle, the third sub-aperture imaging is rotated counterclockwise, and the geometric position matching between the third sub-aperture imaging and the fourth sub-aperture imaging is realized, and the imaging result after matching is obtained. In the imaging result after matching, the main lobes of the third sub-aperture imaging and the fourth sub-aperture imaging coincide while the sidelobes have an included angle, creating conditions for the subsequent separation of the main lobe and the sidelobe.

[0075] In one embodiment, in steps 201 and 202, in the ISAR focusing imaging results in the terahertz band, the range and azimuth sidelobes always distribute along the range and azimuth, while the main lobe generated by the scatterers on the target rotates as the target rotates. When the third sub-aperture imaging is rotated counterclockwise , the matching between the third sub-aperture imaging and the fourth sub-aperture imaging is achieved. At this time, as Figure 3 shown, the main lobes of the third sub-aperture imaging and the fourth sub-aperture imaging coincide, and the included angle of the sidelobes is .

[0076] In the imaging results after matching, let the imaging result after the third sub-aperture imaging is rotated be , and the imaging result of the fourth sub-aperture imaging is .

[0077] Perform sum and difference operations on the imaging result and the imaging result , and the expression is:

[0078] ;

[0079] ;

[0080] The finally obtained result after sidelobe suppression is:

[0081] ;

[0082] In the formula, is the result of the superposition of the main lobe and the sidelobe of and ; is the result of the superposition of the sidelobes after eliminating the main lobe of and ; represents the finally obtained sidelobe suppression result.

[0083] In the above calculation process, contains both main lobe and sidelobe signals, while mainly contains sidelobe signals. After subtraction, the influence of the sidelobe signals is further weakened. At the same time, the main lobe signals are non-coherently superposed. While effectively separating the main lobe and the sidelobes, the intensity of the main lobe signals can also be enhanced, and finally the imaging result after sidelobe suppression is obtained, improving the image quality and suppressing the non-orthogonal sidelobes caused by factors such as system non-ideality and target scattering characteristics.

[0084] In one embodiment, the method proposed in the present invention is verified.

[0085] In the actual experiment, a terahertz band radar was used, with a carrier frequency of 220 GHz and a bandwidth of 20 GHz. First, the rotation angle was set to reverse, and the rotation angle reverse speed was set to 5 revolutions per second. The results obtained are as Figure 4 shown. It can be clearly seen through comparison that in the measured data, there are serious sidelobes in the original imaging result. However, after imaging using the method of the present invention, the target sidelobes are significantly suppressed.

[0086] As Figure 5 shown in the cross-sectional result, the sidelobes in range and azimuth are significantly reduced. The integrated sidelobe ratio (ISLR) in range and azimuth is calculated respectively, and the results are shown in the following table.

[0087] Table 1 Integrated sidelobe ratio in range and azimuth

[0088]

[0089] According to the results in Table 1, the ISLR in the range dimension of the method proposed by the present invention is reduced by 9.81 dB, and the ISLR in the azimuth dimension is reduced by 8 dB, verifying the effectiveness of the method proposed by the present invention.

[0090] Although the steps in this embodiment Figure 1 are shown in sequence according to the indication of the arrows, these steps do not necessarily need to be executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, Figure 1 at least a part of the steps in

[0091] Embodiment 2

[0092] Based on the terahertz ISAR imaging sidelobe suppression method in Embodiment 1, this embodiment discloses a terahertz ISAR imaging sidelobe suppression device. As Figure 6 shown, the terahertz ISAR imaging sidelobe suppression device includes: an ISAR focused imaging result acquisition module 401, a rotation angular velocity and rotation center estimation module 402, a matching module 403, and a sidelobe suppression module 404, where:

[0093] The ISAR focused imaging result acquisition module 401 is used to acquire the ISAR focused imaging result in the terahertz band.

[0094] The rotational angular velocity and rotation center estimation module 402 is used to estimate the ISAR focused imaging result by using the Newton iteration method to obtain the rotational angular velocity and rotation center of the target.

[0095] The matching module 403 is used to select two sub-aperture images from the ISAR focused imaging result, and based on the rotational angular velocity and rotation center, match the two sub-aperture images to obtain the matched imaging result.

[0096] The sidelobe suppression module 404 is used to perform sum-difference operation on the matched imaging result to obtain the final result after sidelobe suppression.

[0097] In this embodiment, the specific working process and working principle of the ISAR focused imaging result acquisition module 401, the rotational angular velocity and rotation center estimation module 402, the matching module 403, and the sidelobe suppression module 404 are the same as those in the method of 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, and their combination. Each unit module can be embedded in the processor of the computer device in hardware form or be independent of it, or 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.

[0098] Embodiment 3

[0099] As Figure 7 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.

[0100] 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.

[0101] Embodiment 4

[0102] 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.

[0103] 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 various embodiments provided in this application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory 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.

[0104] 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 recorded in this specification.

[0105] The above-described embodiments merely represent several implementation manners of the present invention. The description 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 method for suppressing sidelobes in terahertz ISAR imaging, characterized in that, The method includes: Obtaining the ISAR focused imaging result in the terahertz band; Using the Newton iteration method to estimate the ISAR focused imaging result to obtain the rotational angular velocity and the rotation center of the target; Selecting two sub-aperture images from the ISAR focused imaging result, and based on the rotational angular velocity and the rotation center, matching the two sub-aperture images to obtain a matched imaging result; Performing sum-difference operation on the matched imaging result to obtain a final result after sidelobe suppression.

2. The method for suppressing sidelobes in terahertz ISAR imaging according to claim 1, wherein Obtaining the ISAR focused imaging result in the terahertz band includes: Obtaining the radar echo signal in the terahertz band, and performing trigonometric expansion on the radar echo signal to obtain an expanded coupled signal; Eliminating the coupling between range and azimuth in the expanded coupled signal through Keystone, and simultaneously ignoring the range migration caused by the range-variant quadratic term to obtain a transformed ideal terahertz ISAR echo signal; Performing Fourier transform on the fast time in the ideal terahertz ISAR echo signal to obtain an echo signal after fast-time Fourier transform; Performing phase compensation on the echo signal after fast-time Fourier transform, and performing Fourier transform on the slow-time variable in the azimuth dimension to obtain the ISAR focused imaging result in the terahertz band.

3. The method for suppressing sidelobes in terahertz ISAR imaging according to claim 1, characterized in that Selecting two sub-aperture images from the ISAR focused imaging result, and based on the rotational angular velocity and the rotation center, matching the two sub-aperture images to obtain a matched imaging result, including: Selecting a first sub-aperture image and a second sub-aperture image from the ISAR focused imaging result, and calculating the cumulative angle between the first sub-aperture image and the second sub-aperture image based on the rotational angular velocity and the rotation center; According to the cumulative angle, adjusting the resolution of the first sub-aperture image and the second sub-aperture image to obtain a third sub-aperture image and a fourth sub-aperture image with consistent range cell and azimuth cell sizes; Aligning the centers of the third sub-aperture image and the fourth sub-aperture image, and then rotating the third sub-aperture image based on the cumulative angle to obtain a matched imaging result.

4. The terahertz ISAR imaging sidelobe suppression method according to claim 3, wherein The first sub-aperture image and the second sub-aperture image are two adjacent images under continuous perspectives.

5. The method for suppressing sidelobes in terahertz ISAR imaging according to claim 3, characterized in that, According to the cumulative angle, adjusting the resolution of the first sub-aperture image and the second sub-aperture image, and the expression of the resolution adjustment is: ； ； Wherein, represents the range resolution; represents the azimuth resolution; represents the speed of light; represents the bandwidth; represents the wavelength; represents the accumulation angle of imaging.

6. The method for suppressing sidelobes in terahertz ISAR imaging according to any one of claims 3 to 5, characterized in that Rotating the third sub-aperture image based on the cumulative angle, and the expression is: ； In the formula, represents the scattering point coordinates on the fourth sub-aperture image; represents the scattering point coordinates on the third sub-aperture image; represents the cumulative rotation angle.

7. The terahertz ISAR imaging sidelobe suppression method according to claim 6, wherein Performing sum-difference operation on the matched imaging result to obtain a final result after sidelobe suppression, including: In the imaging result after matching, assume that the imaging result after the rotation of the third sub-aperture imaging is and the imaging result of the fourth sub-aperture is ; ; For the imaging result And the imaging result Perform sum-difference operations, and the expression is: ； ； The final result after sidelobe suppression is: ； In the formula, is the result of superimposing the main lobe and side lobes of ; is the result of eliminating the main lobe and superimposing the side lobes of ; represents the final side lobe suppression result.

8. A terahertz ISAR imaging sidelobe suppression device, characterized in that, The device includes: An ISAR focused imaging result acquisition module, configured to obtain the ISAR focused imaging result in the terahertz band; A rotational angular velocity and rotation center estimation module, configured to use the Newton iteration method to estimate the ISAR focused imaging result to obtain the rotational angular velocity and the rotation center of the target; A matching module, configured to select two sub-aperture images from the ISAR focused imaging results, and match the two sub-aperture images based on the rotational angular velocity and the rotation center to obtain a matched imaging result; A sidelobe suppression module, configured to perform sum-difference operation on the matched imaging result to obtain a final result after sidelobe suppression.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the terahertz ISAR imaging sidelobe suppression 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 the processor, the steps of the terahertz ISAR imaging sidelobe suppression method according to any one of claims 1 to 7 are implemented.

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