Terahertz ISAR (Inverse Synthetic Aperture Radar) imaging side lobe suppression method, device, equipment and medium

Abstract

The invention relates to a terahertz ISAR (Inverse Synthetic Aperture Radar) imaging sidelobe suppression method, device and equipment and a medium. The method comprises the following steps: acquiring an ISAR focusing imaging result of a terahertz frequency band; estimating an ISAR focusing imaging result by adopting a Newton iteration method to obtain a rotation angular velocity and a rotation center of a target; selecting two sub-aperture images from the ISAR focusing imaging result, and matching the two sub-aperture images based on the rotation angular velocity and the rotation center to obtain a matched imaging result; and performing sum-difference operation on the matched imaging result to obtain a final side lobe suppression result. According to the method, the main lobe and the side lobe can be effectively separated, the non-orthogonal side lobe is remarkably inhibited, the imaging definition is greatly improved, the problems of image blurring, artifact enhancement, weak target covering and the like are avoided, and the method has relatively high practicability and reliability.

Description

Technical Field

[0001] The present invention relates to the field of radar imaging technology, and in particular to a method, device, equipment and medium for suppressing sidelobes in terahertz ISAR imaging. 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 fields such as security inspection, medical imaging, and non-destructive testing. However, although terahertz radar has excellent performance in theory, there are still many technical challenges in practical applications, especially in terms of imaging quality.

[0003] One of the main problems is the influence of system non-ideality and target scattering characteristics on the imaging results. These factors will lead to the generation of non-orthogonal sidelobes, which will in turn interfere with imaging. The existence of non-orthogonal sidelobes will cause problems such as image blurring, enhanced artifacts, and weak targets being masked, seriously reducing the clarity of the image 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 effectively deal with, resulting in a further decline in imaging quality.

[0004] In addition, existing sidelobe suppression technologies are mainly designed for low-frequency radar systems, and the applicability of these methods in the terahertz frequency band is limited. For example, the traditional frequency-domain windowing method can suppress sidelobes to a certain extent, but it will introduce problems such as main lobe broadening and resolution loss, which is particularly unfavorable for high-precision imaging requirements. The non-linear weighting algorithm (SVA) directly suppresses sidelobes in the image domain, but the non-linear weighting algorithm is mainly designed for orthogonal sidelobes, and the suppression effect on non-orthogonal sidelobes is not good. Moreover, its main means is to weight each pixel, with high computational complexity, and there is a risk of weak target loss during the process of suppressing sidelobes. The CLEAN algorithm mainly reconstructs the target image by iteratively subtracting scattering centers, but it highly depends 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 spectral support region. However, this method requires accurate estimation of the spectral support region. If the estimation is inaccurate, it may lead to sidelobe suppression failure or main lobe energy loss. And the spectral support region can only affect the distribution of orthogonal sidelobes, so the SRSR method can only suppress orthogonal sidelobes, and the suppression effect on non-orthogonal sidelobes is limited, especially in the terahertz frequency band where the sidelobe 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-mentioned technical problems.

[0006] A terahertz ISAR imaging sidelobe suppression method, the method comprising: 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 the rotation center, match the two sub-aperture images to obtain a matched imaging result; Perform sum-difference operation on the matched imaging result to obtain the final result after sidelobe suppression.

[0007] A terahertz ISAR imaging sidelobe suppression device, the device comprising: An ISAR focused imaging result acquisition module for obtaining the ISAR focused imaging result in the terahertz band; A rotational angular velocity and rotation center estimation module for using the Newton iteration method to estimate the ISAR focused imaging result to obtain the rotational angular velocity and rotation center of the target; A matching module for 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; A sidelobe suppression module for performing sum-difference operation on the matched imaging result to obtain the final result after sidelobe suppression.

[0008] 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.

[0009] A computer-readable storage medium, on which a computer program is stored, and the computer program implements the steps of the terahertz ISAR imaging sidelobe suppression method when executed by a processor.

[0010] The above 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.

[0011] 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 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 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 realize the incoherent 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

[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 the description of 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.

[0013] Figure 1 It is a schematic flowchart of the terahertz ISAR imaging sidelobe suppression method in an embodiment; 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; 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; Figure 4 It is a schematic diagram of the rotational angle inverse imaging result in an embodiment, where Figure 4 (a) is a schematic diagram of the first sub-aperture image, Figure 4(b) Schematic diagram of the second sub-aperture imaging Figure 4 (c) Schematic diagram after the third sub-aperture imaging is matched with the fourth sub-aperture imaging Figure 4 (d) Schematic diagram of the imaging result after sidelobe suppression Figure 5 Schematic diagram of range and azimuth profiles in one embodiment, where Figure 5 (a) Schematic diagram of the range profile Figure 5 (b) Schematic diagram of the azimuth profile Figure 6 Structural block diagram of a terahertz ISAR imaging sidelobe suppression device in one embodiment Figure 7 Internal structure diagram of a computer device in one 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. Specific embodiments

[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 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 them. 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 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 through spectrum rearrangement, one imaging result is matched with the other imaging result to obtain an imaging result with the main lobes coinciding and the sidelobes not overlapping. This can effectively separate the main lobe from the sidelobes, 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 iterative 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, incoherent 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 enhances 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.

[0019] As Figure 1 shown, the method for suppressing sidelobes in terahertz ISAR imaging provided by this embodiment includes the following steps: Step 201, obtain the ISAR focused imaging results in the terahertz band.

[0020] Step 202, use the Newton iterative method to estimate the ISAR focused imaging results to obtain the rotation angular velocity and rotation center of the target.

[0021] 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.

[0022] Step 204, perform sum-difference operations on the matched imaging results to obtain the final result after sidelobe suppression.

[0023] In one embodiment, obtaining the ISAR focused imaging results in the terahertz band includes: Obtain the radar echo signal in the terahertz band, perform trigonometric expansion on the radar echo signal to obtain the expanded coupling signal.

[0024] 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 terahertz ISAR ideal echo signal.

[0025] 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.

[0026] 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.

[0027] Specifically, for a broadband radar system in the terahertz band, assuming that the target translational motion has been compensated, in order to reduce the sampling rate for 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: (1) 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.

[0028] Perform trigonometric function expansion on the radar echo signal. The obtained expanded coupled signal can be expressed as: (2) In the formula, represents the rotational angular velocity of the target relative to the radar.

[0029] Formula (2) ignores the terms of Taylor expansion 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: (3) In the formula, represents the slow time after Keystone resampling; represents the transformed ideal echo signal of terahertz ISAR; represents the ideal echo signal of terahertz ISAR. After performing two-dimensional Fourier transform on it, the coordinates of each scatterer can be restored. Formula (3) can be regarded as being about the slow time For a linear frequency modulation signal, if its Fourier transform is directly performed with respect to , the result will be broadened in the frequency domain, and the azimuth coordinates of the scattering points 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 terahertz band can be obtained.

[0030] Among them, the fast time in the ideal echo signal of terahertz ISAR is Fourier-transformed to obtain the echo signal after fast-time Fourier transform, and the expression is: (4) In the formula, represents the fast-time frequency; represents the pulse width.

[0031] Usually, the coordinates of the target rotation center are not zero. Therefore, phase compensation is performed on the echo signal after fast-time Fourier transform in formula (4), and Fourier transform is performed on the slow-time variable in the azimuth dimension to obtain the ISAR focusing imaging result in the terahertz band, and the expression is: (5) In the formula, represents 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; represents the Doppler frequency variable; represents the echo signal after fast-time Fourier transform; represents the rotation center; represents the Doppler frequency; represents the coherent integration time. Formula (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 rotational speed and the rotation center directly determines the quality of the ISAR image. Therefore, the Newton iteration method is used for estimation to obtain a high-precision rotational angular velocity and the rotation center . The Newton iteration method is a conventional technical means and will not be elaborated here.

[0032] In one embodiment, two sub-aperture images are selected from the ISAR focusing imaging result, 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: Select the first sub-aperture image and the second sub-aperture image from the ISAR focusing imaging result, 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.

[0033] According to the cumulative angle, the resolution of the first sub-aperture imaging and the second sub-aperture imaging is adjusted to obtain the third sub-aperture imaging and the fourth sub-aperture imaging with the same size of range cells and azimuth cells.

[0034] Align the centers of the third sub-aperture imaging and the fourth sub-aperture imaging, and then rotate the third sub-aperture imaging based on the cumulative angle to obtain the matched imaging result.

[0035] In one embodiment, the first sub-aperture imaging and the second sub-aperture imaging are two adjacent images under continuous viewing angles.

[0036] In one embodiment, according to the cumulative angle, the resolution of the first sub-aperture imaging and the second sub-aperture imaging is adjusted, and the expression of the resolution adjustment is: ; ; In the formula, represents the range resolution; represents the azimuth resolution; represents the speed of light; represents the bandwidth; represents the wavelength; represents the cumulative angle of imaging.

[0037] In one embodiment, the rotation of the third sub-aperture imaging based on the cumulative angle is expressed as: ; In the formula, represents the scattering point coordinates on the fourth sub-aperture imaging; represents the scattering point coordinates on the third sub-aperture imaging; represents the cumulative angle of rotation.

[0038] 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 result of the sub-aperture, 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.

[0039] Specifically, through step 202, the rotational angular velocity and the rotation center , and then select the imaging results of two adjacent sub-apertures under consecutive perspectives based on the ISAR focusing imaging results, 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 perspectives of the two sub-apertures. Then, move the rotation center to the origin of coordinates, that is, align the centers of the first sub-aperture imaging and the second sub-aperture imaging, and obtain the relative position schematic diagram as Figure 2 shown.

[0040] Before rotation, it is necessary to make the range cell sizes and azimuth cell sizes of the first sub-aperture imaging and the second sub-aperture imaging the same 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. Given the known cumulative angle , perform interpolation operations according to the range resolution and the azimuth resolution so that the range cell sizes and azimuth cell sizes of the first sub-aperture imaging and the second sub-aperture imaging are the same, and correspondingly obtain the third sub-aperture imaging and the fourth sub-aperture imaging after adjusting the resolution, 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.

[0041] At this time, based on the cumulative angle, rotate the third sub-aperture imaging counterclockwise, and the geometric position matching between the third sub-aperture imaging and the fourth sub-aperture imaging is achieved, 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 side lobes have an included angle, creating conditions for the subsequent separation of the main lobe and the side lobe.

[0042] In one embodiment, in steps 201 and 202, in the ISAR focusing imaging results in the terahertz band, the range and azimuth side lobes always distribute along the range and azimuth, while the main lobe generated by the scattering points on the target rotates as the target rotates. When the third sub-aperture imaging is rotated counterclockwise by , 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 side lobes is .

[0043] In the imaging result after matching, assume that the imaging result after the third sub-aperture imaging is rotated by is , and the imaging result of the fourth sub-aperture is .

[0044] For the imaging result And the imaging result Perform sum-difference operation, and the expression is: ; ; The finally obtained result after sidelobe suppression is: ; In the formula, Is And The superposition result of the main lobe and sidelobes; Is And The result of canceling the main lobe and superposing the sidelobes; Represents the finally obtained sidelobe suppression result.

[0045] In the above calculation process, Contains main lobe and sidelobe signals, while Mainly contains sidelobe signals. After subtraction, the influence of sidelobe signals is further weakened. At the same time, the main lobe signals are non-coherently superposed. While effectively separating the main lobe and sidelobes, it can also enhance the intensity of the main lobe signals. 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.

[0046] In one of the embodiments, the method proposed in the present invention is verified.

[0047] In the actual measurement experiment, a terahertz-band radar is used, with a carrier frequency of 220 GHz and a bandwidth of 20 GHz. First, a rotating angle reflector is placed, and the rotating angle reflector speed is set to 5 revolutions per second. The obtained results are as Figure 4 Shown. It can be clearly seen through comparison that in the actual measurement data, there are serious sidelobes in the original imaging result, but after imaging using the method of the present invention, the target sidelobes are significantly suppressed.

[0048] As Figure 5 Shown in the cross-sectional result, the sidelobes in range and azimuth decrease significantly. Calculate the integrated sidelobe ratio (ISLR) in range and azimuth respectively, and the results are shown in the following table.

[0049] Table 1 Integrated sidelobe ratio in range and azimuth

[0050] According to the results in Table 1, the method proposed in the present invention reduces the range-dimensional ISLR by 9.81 dB and the azimuth-dimensional ISLR by 8 dB, verifying the effectiveness of the method proposed in the present invention.

[0051] Although this embodiment Figure 1The steps in [description] are shown in sequence according to the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise clearly stated in this document, there is no strict order restriction 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 [description] may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0052] Embodiment 2 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 rotational angular velocity and rotation center estimation module 402, a matching module 403, and a sidelobe suppression module 404, where: The ISAR focused imaging result acquisition module 401 is used to acquire the ISAR focused imaging result in the terahertz band.

[0053] The rotational angular velocity and rotation center estimation module 402 is used to estimate the ISAR focused imaging result by using the Newton iterative method to obtain the rotational angular velocity and rotation center of the target.

[0054] The matching module 403 is used to select two sub-aperture images from the ISAR focused imaging result and match the two sub-aperture images based on the rotational angular velocity and rotation center to obtain the matched imaging result.

[0055] 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.

[0056] In this embodiment, the specific working processes and working principles 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 of the method in Embodiment 1, so they will not be elaborated herein. Each unit module 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 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 the above unit modules.

[0057] Embodiment 3 As Figure 7The following shows a terminal device disclosed in this embodiment, which 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-executable instructions, and the processor is used to execute the computer-executable instructions stored in the memory to implement the method in Embodiment 1 above.

[0058] It should be noted that the above-mentioned 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.

[0059] Embodiment 4 This embodiment discloses a computer-readable storage medium, in which computer-executable instructions are stored. When the processor executes the computer-executable instructions, the method in Embodiment 1 above is implemented.

[0060] Those of ordinary skill in the art can understand that all or part of the processes in implementing 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 above method embodiments. 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 (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0061] 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.

[0062] 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 fall within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the appended claims.

Claims

1. A terahertz ISAR imaging sidelobe suppression method, characterized in that: The method comprises: Obtain ISAR focused imaging results in the terahertz frequency band; The ISAR focusing imaging result is estimated by using the Newton iteration method to obtain the rotation angular velocity and rotation center of the target; Selecting two sub-aperture images from the ISAR focused imaging result, and matching the two sub-aperture images based on the rotation angular velocity and the rotation center to obtain a matched imaging result; Perform sum and difference operations on the matched imaging results to obtain the final sidelobe suppressed results.

2. The terahertz ISAR imaging sidelobe suppression method according to claim 1, characterized in that: Obtain ISAR focused imaging results in the terahertz band, including: Acquire a radar echo signal in the terahertz frequency band, and perform trigonometric function expansion on the radar echo signal to obtain an expanded coupling signal; Eliminating the coupling between the range and the azimuth in the developed coupling signal by Keystone, while ignoring the range migration caused by the space-varying quadratic term of the range, to obtain the transformed terahertz ISAR ideal echo signal; Performing Fourier transform on the fast time in the terahertz ISAR ideal echo signal to obtain an echo signal after fast time Fourier transform; Phase compensation is performed on the echo signal after the fast-time Fourier transform, and the slow-time variable is Fourier transformed in the azimuth dimension to obtain the ISAR focusing imaging result in the terahertz frequency band.

3. The terahertz ISAR imaging sidelobe suppression method according to claim 1, characterized in that: Selecting two sub-aperture images from the ISAR focused imaging result, and matching the two sub-aperture images based on the rotation angular velocity and the rotation center to obtain a matched imaging result, including: Selecting a first sub-aperture imaging and a second sub-aperture imaging from the ISAR focusing imaging result, and calculating a cumulative angle between the first sub-aperture imaging and the second sub-aperture imaging based on the rotation angular velocity and the rotation center; According to the accumulation angle, adjusting the resolution of the first sub-aperture imaging and the second sub-aperture imaging to obtain a third sub-aperture imaging and a fourth sub-aperture imaging with the same size of distance unit and azimuth unit; The centers of the third sub-aperture imaging and the fourth sub-aperture imaging are aligned, and then the third sub-aperture imaging is rotated based on the accumulation angle to obtain a matched imaging result.

4. The terahertz ISAR imaging sidelobe suppression method according to claim 3, characterized in that: The first sub-aperture imaging and the second sub-aperture imaging are two adjacent images at continuous viewing angles.

5. The terahertz ISAR imaging sidelobe suppression method according to claim 3, characterized in that: According to the accumulation angle, the resolution of the first sub-aperture imaging and the second sub-aperture imaging is adjusted, and the expression of the resolution adjustment is: ； ； In the formula, Indicates the distance resolution; Indicates the azimuth resolution; represents the speed of light; Indicates bandwidth; Indicates wavelength; Represents the accumulation angle of imaging.

6. The terahertz ISAR imaging sidelobe suppression method according to any one of claims 3 to 5, characterized in that: The third sub-aperture imaging is rotated based on the accumulation angle, and the expression is: ； In the formula, represents the coordinates of the scattering points on the fourth sub-aperture imaging; represents the coordinates of the scattering points on the third sub-aperture imaging; Represents the cumulative angle of rotation.

7. The terahertz ISAR imaging sidelobe suppression method according to claim 6, characterized in that: Performing sum and difference operations on the matched imaging results to obtain the final sidelobe suppression results, including: In the imaging result after matching, let the third sub-aperture imaging rotation The imaging result is , the fourth sub-aperture imaging result is ; Imaging results The imaging results Perform sum and difference operations, the expression is: ； ； The final sidelobe suppression result is: ； In the formula, for and The main lobe and side lobe superposition result; for and The result of eliminating the main lobe and superimposing the side lobes; Indicates the final sidelobe suppression result.

8. A terahertz ISAR imaging sidelobe suppression device, characterized in that: The device comprises: ISAR focused imaging result acquisition module, used to obtain ISAR focused imaging results in the terahertz frequency band; A rotation angular velocity and rotation center estimation module is used to estimate the ISAR focus imaging result by using Newton iteration method to obtain the rotation angular velocity and rotation center of the target; A matching module, used for selecting two sub-aperture images from the ISAR focused imaging result, and matching the two sub-aperture images based on the rotation angular velocity and the rotation center to obtain a matched imaging result; The sidelobe suppression module is used to perform sum and difference operations on the matched imaging results to obtain the final sidelobe suppressed results.

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 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 a processor, the steps of the terahertz ISAR imaging sidelobe suppression method according to any one of claims 1 to 7 are implemented.

Images