Sea clutter suppression method for synthetic aperture radar imaging and related device

Abstract

The application relates to a sea clutter suppression method for synthetic aperture radar imaging and a related device. The method comprises: performing imaging compression on collected SAR original image data with a large azimuth field of view to obtain an initial SAR image; performing sub-aperture segmentation on the initial SAR image in the azimuth direction to generate a plurality of initial sub-aperture images; performing motion compensation processing and radiation correction processing on the plurality of initial sub-aperture images to generate target sub-aperture images corresponding to the plurality of initial sub-aperture images respectively; performing non-coherent synthesis processing on the plurality of target sub-aperture images based on a preset non-coherent synthesis strategy to generate a synthetic SAR image; and performing image enhancement processing on the synthetic SAR image based on a preset image optimization method to obtain a target SAR image corresponding to the initial SAR image. Based on the above method, the target detection capability of SAR data can be greatly improved, and the performance of weak wave flow interaction imaging can be improved.

Description

Technical Field

[0001] This application relates to the field of marine remote sensing information processing technology, and in particular to a method for suppressing sea clutter in synthetic aperture radar imaging and related equipment. Background Technology

[0002] Synthetic Aperture Radar (SAR) systems are active radar imaging systems that generate high-resolution ocean images using radar systems on aircraft or satellites. Unlike traditional optical imaging systems, SAR systems utilize the reflection of radar beams from the ocean surface to achieve imaging, thus remaining unaffected by weather, cloud cover, or other natural conditions, making them suitable for surface monitoring and observation under various environmental conditions.

[0003] Traditional synthetic aperture radar (SAR) systems face numerous challenges in complex marine environments, particularly in the detection and identification of weak targets and weak wave-current interactions. Complex marine backgrounds typically include waves, swells, and other currents, making it difficult to separate target echoes from background clutter, thus affecting the accuracy and reliability of target detection. Therefore, traditional SAR systems struggle to identify weak scattered signals in complex marine environments. Summary of the Invention

[0004] The present invention provides a method and related equipment for suppressing sea clutter in synthetic aperture radar imaging, which at least solves the problem that traditional SAR systems have difficulty in identifying weak scattering signals in complex marine backgrounds, and greatly improves the target detection capability of SAR data and the performance of imaging with weak wave-current interaction.

[0005] According to a first aspect of the present invention, a method for suppressing sea clutter in synthetic aperture radar imaging is provided, comprising:

[0006] The acquired raw SAR image data with a large azimuth field of view is imaged and compressed to obtain an initial SAR image. The raw SAR image data is acquired by an azimuth-oriented large field of view radar antenna based on the azimuth beam broadening method and the multi-channel echo signal receiving method.

[0007] The initial SAR image is segmented into sub-apertures in the azimuth direction to generate multiple initial sub-aperture images;

[0008] Motion compensation and radiometric correction are performed on the multiple initial sub-aperture images to generate target sub-aperture images corresponding to each of the multiple initial sub-aperture images;

[0009] Based on a preset incoherent synthesis strategy, multiple target sub-aperture images are incoherently synthesized to generate a synthetic SAR image.

[0010] The synthetic SAR image is enhanced using a preset image optimization method to obtain the target SAR image corresponding to the initial SAR image.

[0011] According to a second aspect of the present invention, a sea clutter suppression device for synthetic aperture radar imaging is provided, comprising:

[0012] The acquisition module is used to perform imaging compression on the acquired raw SAR image data with a large azimuth field of view to obtain an initial SAR image. The raw SAR image data is acquired by the radar antenna with a large azimuth field of view based on the azimuth beam broadening method and the multi-channel echo signal receiving method.

[0013] The segmentation module is used to perform sub-aperture segmentation on the initial SAR image in the azimuth direction to generate multiple initial sub-aperture images;

[0014] The processing module is used to perform motion compensation processing and radiometric correction processing on the plurality of initial sub-aperture images to generate target sub-aperture images corresponding to each of the plurality of initial sub-aperture images;

[0015] The synthesis module is used to perform incoherent synthesis processing on multiple target sub-aperture images based on a preset incoherent synthesis strategy to generate a synthesized SAR image.

[0016] An enhancement module is used to perform image enhancement processing on the synthetic SAR image based on a preset image optimization method to obtain the target SAR image corresponding to the initial SAR image.

[0017] According to a third aspect of the present invention, an electronic device is provided, comprising: a processor, and a memory storing a program, wherein the program includes instructions that, when executed by the processor, cause the processor to perform the method according to the first aspect.

[0018] According to a fourth aspect of the present invention, a non-transitory machine-readable medium storing computer instructions is provided, wherein the computer instructions are configured to cause the computer to perform the method according to the first aspect.

[0019] This invention provides a method for suppressing sea clutter in synthetic aperture radar imaging, which can solve the problem of weak scattering signals that are difficult to identify in traditional SAR systems under complex ocean backgrounds, and significantly improve the target detection capability and imaging performance of SAR data in the context of weak wave-current interaction.

[0020] Specifically, the acquired raw SAR image data with a large azimuth field of view is first compressed. The compressed initial SAR image is then segmented into sub-apertures in the azimuth direction, generating multiple initial sub-aperture images. Each sub-aperture image corresponds to a different field of view angle and direction, enabling the acquisition of long-term continuous observation sequences of the same sea surface area. Motion compensation and radiometric correction are performed on each initial sub-aperture image. These processing steps eliminate positional offsets caused by platform motion, ensuring the accuracy and consistency of the geometry and scattering coefficients of each sub-aperture image. Based on a pre-defined incoherent synthesis strategy, the multiple target sub-aperture images processed by motion compensation and radiometric correction are synthesized. Incoherent synthesis effectively suppresses the influence of sea clutter and improves the signal-to-clutter ratio of the target signal to the background clutter. Finally, the synthesized SAR image is enhanced using a pre-defined image optimization method. These processes include, but are not limited to, contrast enhancement, noise filtering, and detail enhancement, to further improve the visual quality and target detection capability of the image.

[0021] In this embodiment of the invention, sea clutter in complex ocean backgrounds is effectively suppressed and the signal-to-clutter ratio of target signals is improved through imaging compression processing, sub-aperture segmentation, motion compensation and radiometric correction, as well as incoherent synthesis techniques. Furthermore, image enhancement processing further optimizes the visual effects and target detection capabilities of the synthesized SAR images, while also enhancing the ability to detect the wakes of underwater vehicles.

[0022] Details of one or more embodiments of the present invention are set forth in the following drawings and description, so that other features, objects and advantages of the invention will be more readily understood. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating a method for suppressing sea clutter in synthetic aperture radar imaging, provided as an exemplary embodiment of the present invention.

[0025] Figure 2 This is a schematic diagram of a synthetic aperture radar system provided as an exemplary embodiment of the present invention.

[0026] Figure 3 This is a schematic diagram of an airborne long synthetic aperture time SAR data image containing ship wakes, provided as an exemplary embodiment of the present invention.

[0027] Figure 4 This is a schematic diagram of range-azimuth Doppler domain SAR data provided as an exemplary embodiment of the present invention.

[0028] Figure 5 This is a schematic diagram of a portion of the initial sub-aperture images in a plurality of initial sub-aperture images provided as an exemplary embodiment of the present invention.

[0029] Figure 6 This is a schematic diagram of a partial target sub-aperture image after motion and radiation correction, provided as an exemplary embodiment of the present invention.

[0030] Figure 7 This is a schematic diagram of a synthesized SAR image after incoherent synthesis, provided as an exemplary embodiment of the present invention.

[0031] Figure 8 This is a schematic diagram of a target SAR image provided as an exemplary embodiment of the present invention.

[0032] Figure 9 This is a schematic diagram of a sea clutter suppression device for synthetic aperture radar imaging, provided as an exemplary embodiment of the present invention.

[0033] Figure 10 This is a schematic diagram of the structure of an electronic device provided as an exemplary embodiment of the present invention. Detailed Implementation

[0034] Embodiments of this embodiment will now be described in more detail with reference to the accompanying drawings. While some embodiments of this embodiment are shown in the drawings, it should be understood that this embodiment can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this embodiment. It should be understood that the accompanying drawings and embodiments are for illustrative purposes only and are not intended to limit the scope of protection of this embodiment.

[0035] With the rapid development of remote sensing technology, synthetic aperture radar (SAR) systems, which are capable of operating around the clock and in all weather conditions, and offer high resolution and wide swaths, have provided abundant data resources for the study of marine phenomena. However, in complex ocean environments, the interaction between weak targets and weak currents often manifests as weak scattering signals in SAR images. Due to interference from random waves, swells, and other factors, the texture features of the backscattering coefficients become indistinct and difficult to observe and distinguish with the naked eye.

[0036] The currently used azimuth narrow beamwidth SAR system has significant limitations in effectively identifying and analyzing weak targets and weak wave-current interactions in complex ocean backgrounds.

[0037] To address the aforementioned problems, this invention provides a method for suppressing sea clutter in synthetic aperture radar (SAR) imaging. The method includes: compressing acquired raw SAR image data with a large azimuth field of view to obtain an initial SAR image; segmenting the initial SAR image into sub-apertures in the azimuth direction to generate multiple initial sub-aperture images; performing motion compensation and radiometric correction processing on the multiple initial sub-aperture images to generate target sub-aperture images corresponding to each of the initial sub-aperture images; performing incoherent synthesis processing on the multiple target sub-aperture images based on a preset incoherent synthesis strategy to generate a synthetic SAR image; and performing image enhancement processing on the synthetic SAR image based on a preset image optimization method to obtain the target SAR image corresponding to the initial SAR image.

[0038] It should be noted that, in the embodiments of this invention, "large field of view" refers to the field of view angle of the synthetic aperture radar (SAR) system. Compared with the prior art, the SAR system of the embodiments of this invention is designed to achieve a significantly expanded field of view coverage. Specifically, the SAR system involved in the embodiments of this invention can provide a field of view angle of at least 10° to 60°, which is far greater than the field of view angle of traditional SAR systems, which are typically between 0.1° and 5°. By achieving this large field of view angle, the SAR system of this invention can capture a wider ocean area at once, thereby providing richer and more detailed data information in fields such as marine surveillance, environmental monitoring, and geographic information systems.

[0039] The technical solutions provided by the various embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0040] Figure 1 This is a schematic flowchart illustrating a sea clutter suppression method for synthetic aperture radar imaging, provided as an exemplary embodiment of the present invention. See also... Figure 1 The method includes the following steps.

[0041] Step S101: The acquired SAR raw image data with a large azimuth field of view is image compressed to obtain an initial SAR image. The SAR raw image data is acquired by an azimuth large field of view radar antenna based on the azimuth beamwidth method and the multi-channel echo signal reception method.

[0042] Step S102: The initial SAR image is segmented into sub-apertures in the azimuth direction to generate multiple initial sub-aperture images.

[0043] Step S103: Perform motion compensation and radiometric correction processing on multiple initial sub-aperture images to generate target sub-aperture images corresponding to each of the multiple initial sub-aperture images.

[0044] Step S104: Based on a preset incoherent synthesis strategy, multiple target sub-aperture images are incoherently synthesized to generate a synthetic SAR image.

[0045] Step S105: Perform image enhancement processing on the synthetic SAR image based on the preset image optimization method to obtain the target SAR image corresponding to the initial SAR image.

[0046] First, the acquired raw SAR image data with a large azimuth field of view is compressed to obtain the initial SAR image.

[0047] In this embodiment, raw image data covering a large azimuth field of view is acquired from a synthetic aperture radar (SAR) system. The acquired raw SAR image data undergoes imaging compression processing. In this embodiment, the synthetic aperture radar (SAR) system may include a large azimuth field of view radar antenna. The raw SAR image data is acquired by the large azimuth field of view radar antenna using an azimuth beamwidth method and a multi-channel echo signal reception method. The purpose of imaging compression is to focus radar scattering signals from the same target together to form a clear image. After imaging compression processing, the initial SAR image is obtained. This method ensures that the most basic imaging information is extracted from the raw data.

[0048] In practical applications, a SAR system with a large azimuth beamwidth can be designed. Azimuth beamwidth can be achieved through beamforming based on phased array antennas, and multi-channel echo signal reception technology can be used to extend the synthetic aperture time of synthetic aperture radar and collect raw echo data of SAR with a large azimuth field of view.

[0049] In one optional embodiment, raw SAR image data can be acquired based on an azimuth beamwidth method and a multi-channel echo signal reception method; then, the raw SAR image data is processed by imaging compression based on a range Doppler algorithm to obtain an initial SAR image.

[0050] In this embodiment, the SAR system can control the received signal by adjusting the direction and width of the radar beam. In practical applications, increasing the beam width can cover a wider ground area and extend the observation time of the target. Furthermore, SAR systems typically use multi-channel receivers to simultaneously receive echo signals from different azimuth directions. These channels can receive radar signals reflected from ground targets at different directions or angles, increasing the system's ability to observe ground targets and improving data collection efficiency.

[0051] The range-Doppler algorithm for SAR imaging utilizes the range and Doppler frequency variations of radar signals during their propagation in space to generate high-resolution radar images. SAR systems transmit pulse signals and receive echoes reflected from ground targets. Because the distance between the radar platform (such as an aircraft or satellite) and the target changes continuously during movement, the echo signal experiences different propagation path lengths, resulting in a time delay in the received signal. Simultaneously, relative motion also causes a Doppler frequency shift, reflecting the radial velocity of the target in the radar's line-of-sight direction. First, a Fast Fourier Transform (FFT) is performed on the echo signal at each azimuth position to transform it into the frequency domain. In the frequency domain, matched filters (typically filters corresponding to the shape of the transmitted pulse) are used to enhance the target signal and suppress noise. This process, called range compression, improves range resolution and enhances signal strength. In SAR data, due to the movement of the radar platform, the peak value of the target echo shifts in the range-up direction; this phenomenon is called "range migration." To correct this shift, range migration correction is performed, typically using interpolation techniques to restore the signal to the correct range position. After range compression and range migration correction, the data is reorganized into a two-dimensional matrix, where each row represents a range profile at a specific azimuth angle. Then, a second FFT is performed on these range profiles, this time in the azimuth direction. This step utilizes Doppler frequency shift information to achieve azimuth compression and improve azimuth resolution. Finally, post-processing is performed on the resulting image, such as clutter removal, brightness equalization, and image enhancement, to generate a clear SAR image.

[0052] After imaging compression processing using the range-Doppler algorithm, the initial SAR image was obtained. This image features a large field of view acquired through beam widening and multi-channel receiving methods.

[0053] By acquiring raw SAR image data using azimuth beamwidth and multi-channel echo signal reception methods, and combining this with range Doppler algorithm for imaging compression processing, high-quality initial SAR images can be effectively acquired.

[0054] In an optional embodiment, the acquired azimuth-oriented large field-of-view SAR raw image data is compressed using the range-Doppler (RD) algorithm. The two-dimensional time-domain signal of the SAR raw image data is shown in the following formula (1):

[0055]

[0056] Where A0 is the scattering coefficient of the target; τ is the fast time variable of the raw SAR image data; rect(·) is the rectangular signal envelope; T r T is the pulse duration; aIt is the synthetic aperture time; f0 is the radar center frequency; K r It is the range-modulated frequency; c is the speed of light; assuming the point target's velocity is v y (t i If V << V, then the effect of the target's azimuth velocity can be ignored.

[0057] The initial SAR image after imaging compression is shown in the following formula (2):

[0058]

[0059] Among them, K a Let t be the azimuth tuning frequency. Equation (2) shows that each scattering unit is imaged and compressed to t. i =t c , Place.

[0060] After obtaining the initial SAR image, the initial SAR image can be segmented into sub-apertures in the azimuth direction to generate multiple initial sub-aperture images.

[0061] In this embodiment, after obtaining the initial SAR image, it can be segmented into sub-apertures in the azimuth direction to generate multiple initial sub-aperture images.

[0062] Specifically, firstly, an initial SAR image, after range-Doppler processing, is acquired from the SAR system. Then, sub-aperture segmentation is performed on the initial SAR image in the azimuth direction. The azimuth direction is the dimension along the flight direction of the flight platform in SAR imaging. Sub-aperture segmentation divides the Doppler bandwidth of the original image into several parts in the range-Doppler domain. Each sub-aperture segment constitutes an initial sub-aperture image, covering different azimuth angles or field-of-view angles of the initial SAR image. The sub-aperture segmentation operation can be optimized according to specific needs and application scenarios.

[0063] In one optional embodiment, when the initial SAR image is segmented into sub-apertures in the azimuth direction to generate multiple initial sub-aperture images, a Fourier transform along the azimuth direction can be performed on the initial SAR image to generate range-azimuth Doppler domain SAR data corresponding to the initial SAR image; then, sub-aperture segmentation is performed on the range-azimuth Doppler domain SAR data based on a bandpass filter to obtain multiple initial sub-aperture images.

[0064] In practical applications, the initial SAR image with a large field of view in the azimuth direction after imaging compression is subjected to Fourier transform along the azimuth direction to convert it into range-azimuth Doppler domain SAR data. The converted data is shown in the following formula (3):

[0065]

[0066] Where A0 is the scattering coefficient of the target, sinc r Let |K| be the sinc function of the Doppler spectrum. r | is the azimuth tuning frequency, T r R(t) represents the pulse duration, τ is a fast time variable, and R(t) represents the pulse duration. i ) represents the distance to the target, and c represents the speed of light. rect a The time to synthesize the aperture is a rectangular function. The imaging compression time t represents the time to image compression. c ,t i The corresponding Doppler frequency, where λ is the radar wavelength.

[0067] In practical applications, sub-views and sub-apertures are segmented in the azimuth direction. The number of sub-views and the Doppler bandwidth are jointly determined by the image azimuth resolution requirements and factors such as sea conditions and the main wave cycles of the detected sea surface scene. Sub-views are extracted from the azimuth spectrum by bandpass filters of corresponding bandwidth. The filters are symmetrically distributed on both sides of the Doppler center frequency with slight overlap. After imaging the sub-view images separately, several sub-aperture images are obtained.

[0068] After generating multiple initial sub-aperture images, motion compensation and radiometric correction can be performed on the multiple initial sub-aperture images to generate target sub-aperture images corresponding to each of the multiple initial sub-aperture images.

[0069] In this embodiment, the SAR system is typically mounted on a moving platform (such as an aircraft or satellite). The platform's movement causes image position shifts and blurring. Motion compensation aims to correct the effects of this platform movement, ensuring the image maintains accurate ground position and geometry. Simultaneously, radiometric correction is performed on each initial sub-aperture image. Radiometric correction considers factors such as antenna directivity and ground reflectivity to ensure consistent energy and brightness for each sub-aperture image under identical conditions. After motion compensation and radiometric correction, multiple target sub-aperture images are obtained.

[0070] In an optional embodiment, when performing motion compensation processing on multiple initial sub-aperture images, the Doppler parameters of the multiple initial sub-aperture images can be determined based on inertial navigation data, so as to determine the phase error function based on the Doppler parameters; then, motion compensation processing is performed on the multiple initial sub-aperture images based on the phase error function.

[0071] The phase error function is shown in the following formula (4):

[0072]

[0073] Where j is the imaginary unit, R(x,x0) is the distance between the target and the radar and platform, and λ is the wavelength of the synthetic aperture radar.

[0074] When performing radiometric correction on multiple initial sub-aperture images, radiometric correction can be performed on the backscattering coefficients of the multiple initial sub-aperture images at different azimuth angles using an empirical model of azimuth scattering coefficients and antenna patterns, as well as on the multiple initial sub-aperture images using a range-based correction method.

[0075] In practical applications, scattering from the same scattering element in the imaging region exhibits anisotropy. Furthermore, the overall backscattering coefficients of sub-aperture images with different antenna patterns vary significantly. To avoid incomplete sea clutter suppression due to radiation differences between different sub-aperture images during subsequent incoherent imaging, and to prevent errors introduced by other processing steps, the backscattering coefficients of sub-aperture images at different azimuth angles are corrected based on an empirical model of the azimuth scattering coefficients between the scattering element and the radar, and the antenna pattern.

[0076] The empirical model for the scattering coefficient can be expressed by the following formula (5):

[0077] σ0=A0(w,θ)(1+A1(w,θ)cosφ+A2(w,θ)cos2φ) (5)

[0078] Where σ0 is the scattering coefficient, φ is the relative wind direction, and A i (i = 0, 1, 2) are empirical coefficients derived from the incident angle θ and the azimuth angle ω.

[0079] Distance correction is used to eliminate the brightness variation in the direction of distance caused by the angle of incidence;

[0080] The expression for the range correction is shown in the following formula (6):

[0081]

[0082] Where, σ 0' (i,j) represents the backscattering coefficients after range correction, σ 0 (i,j) represents the corrected forward and backward scattering coefficients.

[0083] After generating multiple initial sub-aperture images and their corresponding target sub-aperture images, multiple target sub-aperture images can be incoherently synthesized based on a preset incoherent synthesis strategy to generate a synthetic SAR image.

[0084] In this embodiment, multiple target sub-aperture images that have undergone motion compensation and radiometric correction are synthesized based on a preset incoherent synthesis strategy. Incoherent synthesis is a method that uses intensity-weighted summation of multiple sub-aperture images to enhance the target signal and suppress background clutter. The synthesis strategy is applied to the processed target sub-aperture images to generate the final synthesized SAR image. The synthesized SAR image integrates information from various directions and field of view, providing a more comprehensive and accurate surface imaging result.

[0085] In an optional embodiment, when performing incoherent synthesis processing on multiple target sub-aperture images based on a preset incoherent synthesis strategy to generate a synthetic SAR image, the multiple target sub-aperture images can be converted into multiple target sub-aperture intensity images; the weighting value corresponding to each of the multiple target sub-aperture intensity images is determined based on the antenna pattern of the aperture radar; then, the multiple target sub-aperture intensity images are weighted based on the weighting value corresponding to each of the multiple target sub-aperture intensity images to generate a synthetic SAR image.

[0086] Target information is extracted from multiple target sub-aperture images and converted into corresponding target sub-aperture intensity images. A target sub-aperture intensity image typically refers to the amplitude information of each sub-aperture image, representing the spatial distribution of target reflection intensity. Using the antenna pattern of the aperture radar, the weight or weighting value of each target sub-aperture intensity image is determined in the synthesis process. The antenna SNR pattern describes the intensity of the received signal and the background noise level in different directions, and is the basis for determining the weighting values. Based on the determined weighting values, each target sub-aperture intensity image is weighted. The purpose of the weighting process is to adjust the contribution of each sub-aperture image to the synthesized SAR image based on its signal-to-clutter ratio performance in a specific direction.

[0087] The weighted target sub-aperture intensity images are combined according to a preset incoherent synthesis strategy to generate the final synthetic SAR image. Incoherent synthesis usually refers to simply averaging or summing the individual sub-aperture images with weights, without considering their coherence.

[0088] In this embodiment, determining the weighting value through the antenna pattern effectively enhances the contrast of the target signal relative to background noise, thereby improving the detection capability of weak targets. Weighting processing optimizes the overall quality and resolution of the synthesized SAR image based on the quality and signal-to-clutter ratio distribution of each sub-aperture image, ensuring the final image has good visual effects and information richness. Simultaneously, considering the signal characteristics of different directions and apertures, more accurate target imaging and background suppression can be achieved in complex scenes.

[0089] In practical applications, the corrected target sub-aperture image can be converted into a sub-intensity image based on the following formula (7):

[0090] σ0=10*log10(|S|) (7)

[0091] Where σ0 represents the scattering coefficient and S represents SAR complex data.

[0092] Incoherent imaging is performed on the sub-aperture intensity images. Different sub-aperture images are weighted according to the antenna pattern, and the weighted scattering intensity images are fused. The weighting coefficients and the number of sub-aperture images used for incoherent imaging are adjusted according to the amplitude of the background sea surface signal fluctuations. The incoherent imaging process can be represented by the following formula (8):

[0093] S=a0S0+a1S1+a2S2+a3S3+......(8)

[0094] S represents the incoherently synthesized SAR image, a i (i = 0, 1, 2...) represents the weighting coefficient, S i (i = 0, 1, 2...) represents the sub-aperture image.

[0095] Finally, the synthetic SAR image can be enhanced using a preset image optimization method to obtain the target SAR image corresponding to the initial SAR image.

[0096] In one optional embodiment, the synthetic SAR image can be sequentially processed by spatial mean filtering, bandpass filtering, spatial multi-look processing, oblique ground conversion processing, and histogram equalization processing to obtain the target SAR image.

[0097] In practical applications, the synthetic SAR images after incoherent imaging are optimized by processes such as spatial mean filtering, bandpass filtering, spatial multi-look, oblique ground conversion, and histogram equalization.

[0098] The expression for spatial mean filtering is shown in the following formula (9):

[0099] g i,j =Mean A {f i,j}=Mean{f i+r,j+s ,(r,s)∈A,(i,j)∈I 2} (9)

[0100] Where A is the filtering window, f i,j For input data, g i,j This is for output data.

[0101] The spatial representation of bandpass filtering is shown in the following formula (10):

[0102] G i,j =Mean(f (i-r:i+r,j-s:j+s)(10)

[0103] Where Mean is the mean filtering window, f i,j For input data, g i,j This is for output data.

[0104] The relationship between SAR image slant range and ground distance is shown in the following formula (11):

[0105] D i =(R0+iΔR)sinθ i (11)

[0106] Among them, D i R0 represents the initial slope distance at the nearest point, ΔR represents the slope range resolution, and θ represents the ground distance. i Indicates the angle of incidence.

[0107] The transformation function for histogram equalization is shown in the following formula (12):

[0108]

[0109] Frequency domain radiometric resolution enhancement is achieved by weighted averaging of neighboring pixels in the image, as shown in the following formula (13):

[0110]

[0111] Among them, I M For the image processed by M, I i The scattering intensity of the neighboring pixels.

[0112] The improvement in spatial radiometric resolution is achieved by enhancing the Lee filter, as shown in the following formula (14):

[0113]

[0114] The variation coefficients based on the multiplicative noise model are shown in the following formula (15):

[0115]

[0116] Where, σ y It is the standard deviation of the sample. It is the mean value of the pixels in the filter window.

[0117] w = exp(-k(C y -C u ) / C max -C y ), M is the parameter for improving radiometric resolution.

[0118] The following detailed description, in conjunction with specific embodiments, illustrates a method for suppressing sea clutter in synthetic aperture radar imaging provided by the present invention.

[0119] Assuming that raw SAR image data is acquired by a synthetic aperture radar (SAR) system, which includes a wide field-of-view radar antenna in the azimuth direction. A schematic diagram of the SAR system in this embodiment is shown below. Figure 2 As shown.

[0120] In this embodiment, the raw SAR image data is airborne long synthetic aperture time SAR data containing ship wakes, wherein the airborne long synthetic aperture time SAR data image containing ship wakes is as follows: Figure 3 As shown.

[0121] First, based on the range-Doppler (RD) algorithm... Figure 2 The airborne long synthetic aperture time SAR data containing ship wakes shown is subjected to full aperture imaging compression processing, and the area containing the ship wakes is extracted to obtain the following result: Figure 3 The initial SAR image shown is described above. The compressed initial SAR image can be based on formula (2) in the above embodiment, which will not be repeated in this embodiment.

[0122] Then, sub-aperture segmentation is performed on the initial SAR image.

[0123] Specifically, the initial SAR image with a large field of view in the azimuth direction after imaging compression is subjected to a Fourier transform along the azimuth direction to convert it into range-azimuth Doppler domain SAR data. The converted data can be based on formula (3) in the above embodiment. The converted range-azimuth Doppler domain SAR data is as follows: Figure 4 As shown.

[0124] The range-azimuth Doppler domain SAR data described above is segmented into sub-apertures in the azimuth spectrum to obtain multiple initial sub-aperture images. The number of sub-views and the Doppler bandwidth are jointly determined by the image azimuth resolution requirements and factors such as sea state and main wave cycles of the detected sea surface scene. In this embodiment, sub-views are extracted from the azimuth spectrum by bandpass filters of corresponding bandwidths. The filters are symmetrically distributed on both sides of the Doppler center frequency with slight overlap. After imaging the sub-view images separately, several initial sub-aperture images are obtained. The results of the multiple sub-aperture images obtained in the above steps are initially examined to check for phenomena such as low resolution and unclear wave textures, to determine whether the sub-view image segmentation parameters need to be adjusted. Some of the initial sub-aperture images are shown below. Figure 5 As shown.

[0125] After generating multiple initial sub-aperture images, motion compensation and radiometric correction are performed on these images to generate target sub-aperture images corresponding to each initial sub-aperture image. During this process, the phase error function is shown in formula (4) of the above embodiment. Accurate estimation and correction are performed using Doppler parameters of the original signal, thereby ensuring effective compensation for the overall offset, defocus, and azimuth resolution reduction of each sub-aperture image.

[0126] Based on the empirical model of the azimuth scattering coefficient between the scattering unit and the radar and the antenna pattern, the backscattering coefficient of the sub-aperture image at different azimuth angles is corrected, and the radiometric correction process of multiple initial sub-aperture images is performed based on the range correction method.

[0127] The empirical model for the scattering coefficient is shown in formula (5) of the above embodiment. In this embodiment, range correction is used to eliminate the range-direction brightness variation caused by the incident angle, and the expression for range correction is shown in formula (6) of the above embodiment. In this embodiment, the partial target sub-aperture image after motion and radiation correction is shown in formula (6). Figure 6 As shown.

[0128] After generating multiple initial sub-aperture images and their corresponding target sub-aperture images, multiple target sub-aperture images can be incoherently synthesized based on a preset incoherent synthesis strategy to generate a synthetic SAR image.

[0129] Specifically, multiple target sub-aperture images are first converted into multiple target sub-aperture intensity images. Specifically, the corrected target sub-aperture images can be converted into sub-intensity images based on formula (7) in the above embodiment.

[0130] Incoherent imaging is performed on the sub-aperture intensity images. Different sub-aperture images are weighted according to the antenna pattern, and the weighted scattering intensity images are fused. The weighting coefficients and the number of sub-aperture images used for incoherent imaging are adjusted according to the amplitude of background sea surface signal fluctuations. The incoherent imaging process can be represented by formula (8) in the above embodiment. The synthesized SAR image after incoherent synthesis is as follows: Figure 7 As shown.

[0131] The synthesized SAR image data after incoherent imaging undergoes optimization processing, including spatial mean filtering, bandpass filtering, spatial multi-look processing, oblique-to-ground conversion, and histogram equalization. After this SAR image optimization, a high signal-to-clutter ratio target SAR image with suppressed sea clutter is obtained. The target SAR image in this embodiment is as follows: Figure 8 As shown.

[0132] Based on the above-mentioned method for suppressing sea clutter in synthetic aperture radar imaging provided by the embodiments of the present invention, the embodiments of the present invention also provide a device for suppressing sea clutter in synthetic aperture radar imaging.

[0133] Figure 9 This is a schematic diagram of a sea clutter suppression device for synthetic aperture radar imaging, provided as an exemplary embodiment of the present invention. Figure 9 As shown, the sea clutter suppression device for synthetic aperture radar imaging includes: acquisition module 901, segmentation module 902, processing module 903, synthesis module 904, and enhancement module 905.

[0134] The acquisition module 901 is used to perform imaging compression on the acquired raw SAR image data with a large azimuth field of view to obtain an initial SAR image.

[0135] The segmentation module 902 is used to perform sub-aperture segmentation on the initial SAR image in the azimuth direction to generate multiple initial sub-aperture images;

[0136] Processing module 903 is used to perform motion compensation processing and radiometric correction processing on multiple initial sub-aperture images to generate target sub-aperture images corresponding to each of the multiple initial sub-aperture images;

[0137] The synthesis module 904 is used to perform incoherent synthesis processing on multiple target sub-aperture images based on a preset incoherent synthesis strategy to generate a synthetic SAR image.

[0138] The enhancement module 905 is used to perform image enhancement processing on the synthetic SAR image based on a preset image optimization method to obtain the target SAR image corresponding to the initial SAR image.

[0139] According to an embodiment of the present invention, the imaging compression module is specifically used to acquire raw SAR image data based on the azimuth beamwidth method and the multi-channel echo signal receiving method; and to perform imaging compression processing on the raw SAR image data based on the range Doppler algorithm to obtain an initial SAR image.

[0140] According to an embodiment of the present invention, the sub-aperture segmentation module 902 is specifically used to perform Fourier transform along the azimuth direction on the initial SAR image to generate range-azimuth Doppler domain SAR data corresponding to the initial SAR image; and to perform sub-aperture segmentation on the range-azimuth Doppler domain SAR data based on a bandpass filter to obtain multiple initial sub-aperture images.

[0141] According to an embodiment of the present invention, the processing module 903 is specifically used to determine the Doppler parameters of multiple initial sub-aperture images based on inertial navigation data, so as to determine the phase error function based on the Doppler parameters; and to perform motion compensation processing on the multiple initial sub-aperture images based on the phase error function.

[0142] According to an embodiment of the present invention, the processing module 903 is specifically used to perform radiometric correction processing on the backscattering coefficients of the plurality of initial sub-aperture images at different azimuth angles based on an empirical model of azimuth scattering coefficients and an antenna pattern; and to perform radiometric correction processing on the plurality of initial sub-aperture images based on a range correction method.

[0143] According to an embodiment of the present invention, the synthesis module 904 is specifically used to convert multiple target sub-aperture images into multiple target sub-aperture intensity images; determine the weighting value corresponding to each of the multiple target sub-aperture intensity images based on the antenna pattern of the aperture radar; and perform weighting processing on the multiple target sub-aperture intensity images based on the weighting value corresponding to each of the multiple target sub-aperture intensity images to generate a synthesized SAR image.

[0144] According to an embodiment of the present invention, the enhancement module 905 is specifically used to sequentially perform spatial mean filtering, bandpass filtering, spatial multi-look processing, oblique ground conversion processing, and histogram equalization processing on the synthetic SAR image to obtain the target SAR image.

[0145] This invention also provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor. The memory stores a computer program executable by the at least one processor, which, when executed by the at least one processor, causes the electronic device to perform the method of this invention.

[0146] The present invention also provides a non-transitory machine-readable medium storing a computer program, wherein the computer program, when executed by a computer's processor, is used to cause the computer to perform the method of the present invention.

[0147] This invention also provides a computer program product, including a computer program, wherein the computer program, when executed by a computer's processor, is used to cause the computer to perform the method of this invention.

[0148] refer to Figure 10The present invention will now describe a structural block diagram of an electronic device that can serve as a server or client in embodiments of the present invention, which is an example of a hardware device that can be applied to various aspects of the present invention. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0149] like Figure 10 As shown, the electronic device includes a computing unit 1001, which can make decisions based on data stored in a read-only memory (ROM).

[0150] The computer program in 1002 or the computer program loaded from storage unit 1008 into random access memory (RAM) 1003 performs various appropriate actions and processes. RAM 1003 may also store various programs and data required for the operation of the electronic device. The computing unit 1001, ROM 1002, and RAM 1003 are interconnected via bus 1004. Input / output (I / O) interface 1005 is also connected to bus 1004.

[0151] Multiple components in the electronic device are connected to the I / O interface 1005, including: an input unit 1006, an output unit 1007, a storage unit 1008, and a communication unit 1009. The input unit 1006 can be any type of device capable of inputting information into the electronic device. The input unit 1006 can receive input digital or character information and generate key signal inputs related to user settings and / or function control of the electronic device. The output unit 1007 can be any type of device capable of presenting information and may include, but is not limited to, a display, speaker, video / audio output terminal, vibrator, and / or printer. The storage unit 1008 may include, but is not limited to, a hard disk and an optical disk. The communication unit 1009 allows the electronic device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks, and may include, but is not limited to, a modem, network card, infrared communication device, wireless communication transceiver, and / or chipset, such as Bluetooth devices, WiFi devices, WiMax devices, cellular communication devices, and / or the like.

[0152] The computing unit 1001 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 1001 include, but are not limited to, CPUs, graphics processing units (GPUs), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. The computing unit 1001 performs the various methods and processes described above. For example, in some embodiments, the method embodiments of the present invention may be implemented as a computer program tangibly contained in a machine-readable medium, such as storage unit 1008. In some embodiments, part or all of the computer program may be loaded and / or installed on an electronic device via ROM 1002 and / or communication unit 1009. In some embodiments, the computing unit 1001 may be configured to perform the methods described above by any other suitable means (e.g., by means of firmware).

[0153] Computer programs for implementing the methods of embodiments of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0154] In the context of embodiments of the present invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable signal medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0155] It should be noted that the term "comprising" and its variations used in the embodiments of the present invention are open-ended, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The modifications of "one" and "multiple" mentioned in the embodiments of the present invention are illustrative and not restrictive. Those skilled in the art should understand that, unless explicitly indicated otherwise in the context, they should be understood as "one or more".

[0156] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the embodiments of the present invention are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0157] The steps described in the method embodiments provided by this invention can be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of protection of this invention is not limited in this respect.

[0158] The term "embodiment" in this specification refers to a specific feature, structure, or characteristic described in connection with an embodiment that may be included in at least one embodiment of the invention. The appearance of this phrase in various places in the specification does not necessarily imply the same embodiment, nor does it imply independence or alternativeity from other embodiments. The various embodiments in this specification are described in a related manner, with reference to each other for similar or identical parts. In particular, for apparatus, device, and system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, and relevant details are referred to in the description of the method embodiments.

[0159] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of patent protection. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A sea clutter suppression method for synthetic aperture radar imaging, characterized in that, The method comprises the following steps: SAR raw image data with a large azimuth field of view is collected and compressed to obtain an initial SAR image, wherein the SAR raw image data is collected by a large azimuth field of view radar antenna based on an azimuth beam broadening method and a multi-channel echo signal receiving method; the initial SAR image is sub-aperture segmented in the azimuth direction to generate a plurality of initial sub-aperture images; motion compensation processing and radiation correction processing are performed on the plurality of initial sub-aperture images to generate a plurality of target sub-aperture images corresponding to the plurality of initial sub-aperture images respectively; a plurality of target sub-aperture images are incoherently synthesized based on a preset incoherent synthesis strategy to generate a synthetic SAR image; the synthetic SAR image is subjected to image enhancement processing based on a preset image optimization method to obtain a target SAR image corresponding to the initial SAR image.

2. The method of claim 1, wherein, The method comprises the following steps: The SAR raw image data is compressed based on a range-Doppler algorithm to obtain the initial SAR image.

3. The method of claim 1, wherein, The method comprises the following steps: The initial SAR image is subjected to Fourier transform along the azimuth direction to generate range-azimuth Doppler domain SAR data corresponding to the initial SAR image; the initial SAR image is sub-aperture segmented based on a band-pass filter to obtain the plurality of initial sub-aperture images.

4. The method of claim 1, wherein, The method comprises the following steps: Doppler parameters of the plurality of initial sub-aperture images are determined based on inertial navigation data, so as to determine a phase error function based on the Doppler parameters; the motion compensation processing is performed on the plurality of initial sub-aperture images based on the phase error function.

5. The method of claim 1, wherein, The method comprises the following steps: backscattering coefficients of the plurality of initial sub-aperture images at different azimuth angles are subjected to radiation correction processing based on an azimuth angle scattering coefficient empirical model and an antenna directional diagram; and the plurality of initial sub-aperture images are subjected to radiation correction processing based on a range direction correction method.

6. The method of claim 1, wherein, The method comprises the following steps: The plurality of target sub-aperture images are converted into a plurality of target sub-aperture intensity images; weighting values corresponding to the plurality of target sub-aperture intensity images are determined based on an antenna directional diagram of an aperture radar; the plurality of target sub-aperture intensity images are subjected to weighting processing based on the weighting values corresponding to the plurality of target sub-aperture intensity images to generate the synthetic SAR image.

7. The method of claim 1, wherein, The preset image optimization method is used for image enhancement processing on the synthetic SAR image to obtain a target SAR image corresponding to the initial SAR image, and the target SAR image comprises: The synthetic SAR image is sequentially subjected to spatial mean filtering, band-pass filtering, spatial multi-view processing, slant conversion processing and histogram equalization processing to obtain the target SAR image.

8. A sea clutter suppression apparatus for synthetic aperture radar imaging, characterized by, Comprise: The acquisition module is configured to image and compress SAR original image data with a large azimuth field of view to obtain an initial SAR image, and the SAR original image data is obtained by an azimuth wide beam method and a multi-channel echo signal receiving method through an azimuth wide field of view radar antenna. The segmentation module is configured to segment the initial SAR image in the azimuth direction to generate a plurality of initial sub-aperture images. The processing module is configured to perform motion compensation processing and radiation correction processing on the plurality of initial sub-aperture images to generate a target sub-aperture image corresponding to each of the plurality of initial sub-aperture images. The synthesis module is configured to perform non-coherent synthesis processing on a plurality of target sub-aperture images based on a preset non-coherent synthesis strategy to generate a synthetic SAR image. The enhancement module is configured to perform image enhancement processing on the synthetic SAR image based on a preset image optimization method to obtain a target SAR image corresponding to the initial SAR image.

9. An electronic device comprising: A processor and a memory storing a program, wherein the program includes instructions that, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory machine-readable medium having stored thereon computer instructions, wherein, The computer instructions are used to make the computer perform the method according to any one of claims 1 to 7.

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