High-orbit SAR (Synthetic Aperture Radar) imaging method

Abstract

The invention relates to a high-orbit SAR (Synthetic Aperture Radar) imaging method. The method comprises the following steps: acquiring radar echo data of a plurality of different orbit sections; calculating a ground beam irradiation range corresponding to the radar echo data of each track section; determining an overlapping irradiation area according to the ground beam irradiation range, and dividing the overlapping irradiation area into geocoding imaging grids; and taking the geocoding imaging grid as an imaging area, and performing time domain imaging or frequency domain imaging based on the radar echo data of the plurality of different track segments to obtain a final SAR image. According to the method, the problem of contradiction between high-orbit SAR system performance and image quality is solved, and high-signal-to-noise-ratio SAR imaging can be achieved through multi-view superposition processing even under the condition that hardware equipment is not enhanced.

Description

Technical Field

[0001] The present application relates to the technical field of SAR imaging, and in particular to a high-orbit SAR imaging method. Background Art

[0002] In the high-orbit SAR imaging process, the image signal-to-noise ratio is an important indicator for judging image quality. Image signal-to-noise ratio refers to the ratio of SAR image signal to noise. The higher the image signal-to-noise ratio (SNR), the higher the image quality and the cleaner and clearer the image looks.

[0003] It can be seen from the radar equation that increasing the transmit power, improving the antenna gain, improving the two-dimensional resolution, shortening the radar range and other methods can improve the SNR of the image. However, the orbit height and incident angle of the high-orbit SAR are constant, and the radar range cannot be reduced. The peak output power of the high-orbit SAR is nearly 100,000 W, which is far higher than the power of the satellite in orbit. At the same time, the micro-discharge design of the higher peak transmit power product is also a difficult problem. At present, the method of improving the image signal-to-noise ratio usually adopts synthetic aperture time multi-view processing, but multi-view processing will sacrifice the azimuth resolution. In order to improve the azimuth resolution, the spotlight mode SAR and the sliding spotlight mode SAR are usually used to increase the observation time of the target area by controlling the antenna beam pointing. However, high azimuth resolution requires a high pulse repetition frequency, which causes the width of the mapping band to be reduced. Therefore, the azimuth resolution is improved at the expense of reducing the width of the mapping band. However, it is usually required to be able to observe a larger range of scenes in one mapping, obtain more information, and reduce the revisit time. This is of great significance in applications such as land planning, vegetation mapping and ocean observation that require large-area mapping. Therefore, the azimuth resolution cannot be improved at the expense of the mapping bandwidth.

[0004] At present, there is continuous research on new systems and methods to improve the quality of radar imaging, mainly focusing on finding breakthroughs in new systems such as large-angle radar imaging and quantum correlation radar imaging, combining new technologies in fields such as image fusion and sparse optimization, and studying how to improve the signal-to-noise ratio and resolution of radar images. These new systems and methods pose greater challenges to hardware and are not suitable for high-orbit SAR systems. Summary of the invention

[0005] In order to overcome at least one deficiency in the prior art, the present application provides a high-orbit SAR imaging method to improve the signal-to-noise ratio of an image.

[0006] In a first aspect, a high-orbit SAR imaging method is provided, comprising:

[0007] Acquire radar echo data for multiple different track segments;

[0008] Calculate the ground beam illumination range corresponding to the radar echo data of each track segment;

[0009] Determine the overlapping illumination area according to the ground beam illumination range, and divide the overlapping illumination area into geocoded imaging grids;

[0010] The geocoded imaging grid is used as the imaging area, and time domain imaging or frequency domain imaging is performed based on the radar echo data of multiple different orbital segments to obtain the final SAR image.

[0011] In one embodiment, the overlapping illumination area is represented as [lat min ,lat max ],[lon min ,lon max ], lat min ,lat max are the minimum and maximum latitudes of the overlapping irradiation areas, lon min ,lon max are the minimum and maximum longitudes of the overlapping irradiation areas, respectively;

[0012] lat min =max(lat min1 ,lat min2 ,...lat mini …, lat minN )

[0013] lat max =min(lat max1 ,lat max2 ,...lat maxi …, lat maxN )

[0014] lon min =max(lon min1 ,lon min2 ,...lon mini …,lon minN )

[0015] lon max =min(lon max1 ,lon max2 ,...lon maxi …,lon maxN )

[0016] Among them, lat mini is the minimum latitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, N represents the number of orbit segments, lat maxiis the maximum latitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, lon mini is the minimum longitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, lon maxi is the maximum longitude of the ground beam illumination range corresponding to the radar echo data of the i-th orbit segment.

[0017] In one embodiment, the geocoded imaging grid is used as the imaging area, and time domain imaging is performed based on radar echo data of multiple different track segments to obtain a final SAR image, including:

[0018] Taking the geocoded imaging grid as the imaging area, BP imaging is performed on the radar echo data of multiple different track segments to obtain multiple SAR images.

[0019] Multiple SAR images are incoherently superimposed to obtain the final SAR image.

[0020] In one embodiment, the geocoded imaging grid is used as the imaging area, and frequency domain imaging is performed based on radar echo data of multiple different track segments to obtain a final SAR image, including:

[0021] The radar echo data of multiple different track segments are imaged based on the CS algorithm to obtain multiple SAR images;

[0022] Taking the geocoded imaging grid as the imaging area, geocoding the multiple SAR images to obtain multiple geocoded SAR images;

[0023] The multiple geocoded SAR images are incoherently superimposed to obtain the final SAR image.

[0024] In a second aspect, a high-orbit SAR imaging device is provided, comprising:

[0025] An echo data acquisition module, used to acquire radar echo data of multiple different track segments;

[0026] A ground beam illumination range calculation module is used to calculate the ground beam illumination range corresponding to the radar echo data of each track segment;

[0027] A grid division module, used for determining the overlapping irradiation area according to the ground beam irradiation range, and dividing the overlapping irradiation area into geocoded imaging grids;

[0028] The imaging module is used to use the geocoded imaging grid as the imaging area, perform time domain imaging or frequency domain imaging based on radar echo data of multiple different track segments, and obtain the final SAR image.

[0029] In one embodiment, the overlapping illumination area is represented as [lat min ,lat max ],[lon min ,lon max ], lat min ,lat max are the minimum and maximum latitudes of the overlapping irradiation areas, lon min ,lon max are the minimum and maximum longitudes of the overlapping irradiation areas, respectively;

[0030] lat min =max(lat min1 ,lat min2 ,...lat mini ..., lat minN )

[0031] lat max =min(lat max1 ,lat max2 ,...lat maxi ..., lat maxN )

[0032] lon min =max(lon min1 ,lon min2 ,...lon mini ...,lon minN )

[0033] lon max =min(lon max1 ,lon max2 ,...lon maxi ...,lon maxN )

[0034] Among them, lat mini is the minimum latitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, N represents the number of orbit segments, lat maxi is the maximum latitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, lon mini is the minimum longitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, lon maxi is the maximum longitude of the ground beam illumination range corresponding to the radar echo data of the i-th orbit segment.

[0035] In one embodiment, the imaging module is further configured to:

[0036] Taking the geocoded imaging grid as the imaging area, BP imaging is performed on the radar echo data of multiple different track segments to obtain multiple SAR images.

[0037] Multiple SAR images are incoherently superimposed to obtain the final SAR image.

[0038] In one embodiment, the imaging module is further configured to:

[0039] The radar echo data of multiple different track segments are imaged based on the CS algorithm to obtain multiple SAR images;

[0040] Taking the geocoded imaging grid as the imaging area, geocoding the multiple SAR images to obtain multiple geocoded SAR images;

[0041] The multiple geocoded SAR images are incoherently superimposed to obtain the final SAR image.

[0042] Compared with the prior art, the present application has the following beneficial effects: The high-orbit SAR imaging method of the present application utilizes high-orbit SAR images of different orbital positions for fusion processing. This method does not need to reduce the azimuth resolution by dividing the multi-view image within the aperture to improve the signal-to-noise ratio of the image. Therefore, it can take into account both the resolution and the signal-to-noise ratio of the image. The present application solves the contradiction between the performance and image quality of the high-orbit SAR system. Even without enhancing the hardware equipment, high signal-to-noise ratio SAR imaging can be achieved by using multi-view overlay processing. In addition, the method of the present application is highly applicable and can be applied to all satellite systems such as high-orbit SAR, airborne SAR, medium-orbit SAR, and low-orbit SAR. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present application may be better understood by referring to the following description given in conjunction with the accompanying drawings, which together with the following detailed description are included in this specification and form a part of this specification. In the drawings:

[0044] Figure 1 A flowchart of a high-orbit SAR imaging method according to an embodiment of the present application is shown;

[0045] Figure 2 A structural block diagram of a high-orbit SAR imaging device according to an embodiment of the present application is shown;

[0046] Figure 3 The schematic diagram of the point target imaging results and multi-view results obtained by simulation calculation at different orbital moments of the high-orbit SAR is shown;

[0047] Figure 4A schematic diagram of the imaging results of a point target and the multi-view results obtained by simulating and calculating different orbital times under a noisy background is shown, wherein (a) to (e) are the imaging results of the point target at orbital times of -2h, -1h, 0h, 1h, and 2h after adding noise, respectively, and (f) is the multi-view result after adding noise obtained by simulating using the method of the present application. DETAILED DESCRIPTION

[0048] The exemplary embodiments of the present application will be described below in conjunction with the accompanying drawings. For the sake of clarity and conciseness, not all features of the actual embodiments are described in the specification. However, it should be understood that many implementation-specific decisions can be made in the process of developing any such actual embodiments in order to achieve the specific goals of the developer, and these decisions may vary from embodiment to embodiment.

[0049] It is also necessary to explain here that, in order to avoid obscuring the present application due to unnecessary details, only the device structure closely related to the scheme according to the present application is shown in the drawings, while other details that are not closely related to the present application are omitted.

[0050] It should be understood that the present application is not limited to the described implementation forms due to the following description with reference to the accompanying drawings. In this article, where feasible, the embodiments can be combined with each other, features between different embodiments can be replaced or borrowed, and one or more features can be omitted in one embodiment.

[0051] The present application embodiment provides a high-orbit SAR imaging method. Figure 1 A flowchart of a high-orbit SAR imaging method according to an embodiment of the present application is shown. Figure 1 , methods include:

[0052] Step S1, obtaining radar echo data of multiple different track segments.

[0053] The radar echo data of N different track segments can be expressed as S1(τ, η), S2(τ, η)…S i (τ, η)…S N (τ, η), i is the track segment index, 1≤i≤N, N is the number of track segments, τ is the fast time in range, and η is the slow time in azimuth.

[0054] Step S2, calculating the ground beam illumination range corresponding to the radar echo data of each track segment.

[0055] Here, the ground beam illumination range corresponding to the radar echo data of each orbital segment can be calculated based on the orbital position and radar parameter information. This is a well-known technology in the art and will not be described in detail.

[0056] The ground beam illumination range corresponding to the radar echo data of each track segment can be expressed as:

[0057] [lat min1 ,lat max1 ],[lon min1 ,lon max1 ]

[0058] [lat min2 ,lat max2 ],[lon min2 ,lon max2 ] ...

[0060] [lat mini ,lat maxi ],[lon mini ,lon maxi ] ...

[0062] [lat minN ,lat maxN ],[lon minN ,lon maxN ]

[0063] Among them, lat mini is the minimum latitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, N represents the number of orbit segments, lat maxi is the maximum latitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, lon mini is the minimum longitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, lon maxi is the maximum longitude of the ground beam illumination range corresponding to the radar echo data of the i-th orbit segment.

[0064] Step S3, determining the overlapping illumination area according to the ground beam illumination range, and dividing the overlapping illumination area into geocoded imaging grids.

[0065] Specifically, the overlapping illumination area is expressed as [lat min ,lat max ],[lon min ,lon max ], lat min ,lat max are the minimum and maximum latitudes of the overlapping irradiation areas, lon min ,lon max are the minimum and maximum longitudes of the overlapping irradiation areas, respectively;

[0066] latmin =max(lat min1 ,lat min2 ,...lat mini …, lat minN )

[0067] lat max =min(lat max1 ,lat max2 ,...lat maxi …, lat maxN )

[0068] lon min =max(lon min1 ,lon min2 ,...lon mini …,lon minN )

[0069] lon max =min(lon max1 ,lon max2 ,...lon maxi …,lon maxN )

[0070] Step S4, taking the geocoded imaging grid as the imaging area, performing time domain imaging or frequency domain imaging based on radar echo data of multiple different track segments to obtain a final SAR image.

[0071] The high-orbit SAR imaging method of this embodiment uses high-orbit SAR images of different orbital positions for fusion processing. This method does not need to reduce the azimuth resolution by dividing the multi-view image within the aperture to improve the signal-to-noise ratio of the image. Therefore, it can take into account both the resolution and the signal-to-noise ratio of the image. The present application solves the contradiction between the performance and image quality of the high-orbit SAR system. Even without enhancing the hardware equipment, high signal-to-noise ratio SAR imaging can be achieved by using multi-view overlay processing. The method of the present application is highly applicable and can be applied to all satellite systems such as high-orbit SAR, airborne SAR, medium-orbit SAR, and low-orbit SAR.

[0072] In one embodiment, step S4 may adopt a time domain imaging method. Specifically, the geocoded imaging grid is used as the imaging area, and time domain imaging is performed based on radar echo data of multiple different track segments to obtain a final SAR image, including:

[0073] Taking the geocoded imaging grid as the imaging area, the radar echo data of multiple different track segments are processed by BP (back projection) imaging to obtain multiple SAR images;

[0074] Multiple SAR images are incoherently superimposed to obtain the final SAR image.

[0075] In one embodiment, step S4 may adopt a frequency domain imaging method. Specifically, the geocoded imaging grid is used as the imaging area, and frequency domain imaging is performed based on radar echo data of multiple different track segments to obtain a final SAR image, including:

[0076] The radar echo data of multiple different track segments are imaged based on the CS (Compressive Sensing) algorithm to obtain multiple SAR images;

[0077] Taking the geocoded imaging grid as the imaging area, geocoding the multiple SAR images to obtain multiple geocoded SAR images;

[0078] The multiple geocoded SAR images are incoherently superimposed to obtain the final SAR image.

[0079] Based on the same inventive concept as the high-orbit SAR imaging method, this embodiment also provides a high-orbit SAR imaging device corresponding thereto. Figure 2 The structural block diagram of the high-orbit SAR imaging device according to an embodiment of the present application is shown, and the device includes:

[0080] An echo data acquisition module 21 is used to acquire radar echo data of multiple different track segments;

[0081] A ground beam illumination range calculation module 22 is used to calculate the ground beam illumination range corresponding to the radar echo data of each track segment;

[0082] A grid division module 23, used to determine the overlapping irradiation area according to the ground beam irradiation range, and divide the overlapping irradiation area into geocoded imaging grids;

[0083] The imaging module 24 is used to use the geocoded imaging grid as an imaging area, perform time domain imaging or frequency domain imaging based on radar echo data of multiple different track segments, and obtain a final SAR image.

[0084] The high-orbit SAR imaging device of this embodiment has the same inventive concept as the high-orbit SAR imaging method mentioned above, so the specific implementation method of the device can be seen in the implementation example part of the high-orbit SAR imaging method in the above text, and its technical effect corresponds to the technical effect of the above method, which will not be repeated here.

[0085] In order to further verify the effectiveness of the method of the present application, the following parameters are selected for simulation experiments to further illustrate the effect of the present invention: satellite orbit altitude 42164 km, orbit inclination 60°, eccentricity 0°, perigee argument 110°, true anomaly 180°, right side view, carrier frequency 1.25 GHz.

[0086] Figure 3 The figure shows the point target imaging results and multi-view results obtained by simulation calculation at different orbital times of high-orbit SAR. Among them, the geocoding imaging grid is divided with the ground point target at the center of the beam at the perigee time of 0h as the center. Figure 3 The left side of the equal sign shows the imaging results of the point target at the orbital times of -2h, -1h, 0h, 1h, and 2h after perigee. It can be seen that the same scene is illuminated at different orbital times, but due to different observation angles, the two-dimensional angles of the point target are different. Figure 3 The right side of the equal sign is the multi-view result after superposition obtained by simulation using the method of the present application.

[0087] Table 1 gives the imaging results of the target at the center of the scene when the high-orbit SAR passes the perigee at orbital times of -2h, -1h, 0h, 1h, and 2h. By comparing with those before and after multi-view processing, it can be seen that the peak sidelobe ratio and the integrated sidelobe ratio are greatly reduced without deteriorating the resolution. This application significantly improves the image quality of the high-orbit SAR.

[0088] Table 1 High-orbit SAR point target simulation results

[0089] Perigee time 0h 1h 2h -1h -2h Multi-view processing Azimuth resolution (m) 2.50 2.90 3.33 3.26 3.62 3.30 Azimuth peak sidelobe ratio (dB) -13.44 -13.31 -13.03 -13.27 -13.28 -14.66 Azimuth integrated sidelobe ratio (dB) -10.36 -10.36 -10.01 -10.40 -10.47 -14.62 Range resolution (m) 2.50 2.35 3.27 2.37 3.29 2.30 Range peak sidelobe ratio (dB) -12.99 -12.99 -13.30 -13.01 -12.98 -20.53 Range integrated sidelobe ratio (dB) -9.83 -9.86 -10.52 -9.82 -9.99 -19.43

[0090] In order to further verify the signal-to-noise ratio improvement effect of this application, Figure 4 The following figure shows the imaging results of point targets and the schematic diagram of multi-view results obtained by simulation calculation at different orbital moments under the noise background, where: Figure 4 exist Figure 3 On this basis, 20dB random noise is added to the SAR image of each track segment scene. Figure 4 (a) to (e) are the target imaging results at orbital time points of -2h, -1h, 0h, 1h, and 2h after adding noise, and (f) is the multi-view result after adding noise obtained by simulation using the method of the present application. By comparing Figures (a) to (e) with (f), it can be intuitively seen that the present application improves the quality of high-orbit SAR images.

[0091] Table 2 gives the signal-to-noise ratio calculation results of the high-orbit SAR passing the perigee at -2h, -1h, 0h, 1h, and 2h orbit times and after multi-look processing after adding noise. By comparing with before and after multi-look processing, it can be seen that the signal-to-noise ratio is improved by about 13dB after multi-look processing.

[0092] Table 2 Signal-to-noise ratio of high-orbit SAR point targets with added noise

[0093] Perigee time 0h 1h 2h -1h -2h Multi-view processing SNR(dB) 11.15 10.83 9.63 10.84 9.64 23.19

[0094] The simulation results show that this application has effectively solved the contradiction between the performance and image quality of the high-orbit SAR system. Even without enhancing the hardware equipment, high signal-to-noise ratio SAR imaging can be achieved by using multi-view superposition processing, which is suitable for applications such as high-orbit SAR imaging processing.

[0095] The above are only various implementations of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A high-orbit SAR imaging method, characterized in that: include: Acquire radar echo data for multiple different track segments; Calculate the ground beam illumination range corresponding to the radar echo data of each track segment; Determine an overlapping illumination area according to the ground beam illumination range, and divide the overlapping illumination area into a geocoded imaging grid; The geocoded imaging grid is used as an imaging area, and time domain imaging or frequency domain imaging is performed based on the radar echo data of the multiple different track segments to obtain a final SAR image.

2. The method according to claim 1, characterized in that The overlapping illumination area is represented by [lat min ,lat max ],[lon min ,lon max ], lat min ,lat max are the minimum and maximum latitudes of the overlapping irradiation areas, lon min ,lon max are the minimum and maximum longitudes of the overlapping irradiation areas, respectively; years min =max(years min1 ,years min2 ,...years mini …,years minN ) years max =min(years max1 ,years max2 ,...years maxi …,years maxN ) lon min =max(lon min1 ,lon min2 ,...lon mini …,lon minN ) lon max =min(lon max1 ,lon max2 ,...lon maxi …,lon maxN ) Among them, lat mini is the minimum latitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, N represents the number of orbit segments, lat maxi is the maximum latitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, lon mini is the minimum longitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, lon maxi is the maximum longitude of the ground beam illumination range corresponding to the radar echo data of the i-th orbit segment.

3. The method according to claim 1, characterized in that in, Taking the geocoded imaging grid as an imaging area, performing time domain imaging based on the radar echo data of the multiple different track segments to obtain a final SAR image, including: Taking the geocoded imaging grid as an imaging area, respectively performing BP imaging processing on the radar echo data of the multiple different track segments to obtain multiple SAR images; The multiple SAR images are incoherently superimposed to obtain a final SAR image.

4. The method according to claim 1, characterized in that in, The geocoded imaging grid is used as an imaging area, and frequency domain imaging is performed based on the radar echo data of the multiple different track segments to obtain a final SAR image, including: Imaging the radar echo data of the multiple different track segments based on the CS algorithm to obtain multiple SAR images; Taking the geocoded imaging grid as an imaging area, geocoding the multiple SAR images to obtain multiple geocoded SAR images; The multiple geocoded SAR images are incoherently stacked to obtain a final SAR image.

5. A high-orbit SAR imaging device, characterized in that: include: An echo data acquisition module, used to acquire radar echo data of multiple different track segments; A ground beam illumination range calculation module is used to calculate the ground beam illumination range corresponding to the radar echo data of each track segment; A grid division module, used for determining an overlapping illumination area according to the ground beam illumination range, and dividing the overlapping illumination area into a geocoded imaging grid; An imaging module is used to use the geocoded imaging grid as an imaging area, perform time domain imaging or frequency domain imaging based on the radar echo data of the multiple different track segments, and obtain a final SAR image.

6. The device according to claim 5, characterized in that The overlapping illumination area is represented by [lat min ,lat max ],[lon min ,lon max ], lat min ,lat max are the minimum and maximum latitudes of the overlapping irradiation areas, lon min ,lon max are the minimum and maximum longitudes of the overlapping irradiation areas, respectively; years min =max(years min1 ,years min2 ,...years mini …,years minN ) years max =min(years max1 ,years max2 ,...years maxi …,years maxN ) lon min =max(lon min1 ,lon min2 ,...lon mini …,lon minN ) lon max =min(lon max1 ,lon max2 ,...lon maxi …,lon maxN ) Among them, lat mini is the minimum latitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, N represents the number of orbit segments, lat maxi is the maximum latitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, lon mini is the minimum longitude of the ground beam illumination range corresponding to the radar echo data of the ith orbit segment, lon maxi is the maximum longitude of the ground beam illumination range corresponding to the radar echo data of the i-th orbit segment.

7. The device according to claim 6, characterized in that The imaging module is also used for: Taking the geocoded imaging grid as an imaging area, respectively performing BP imaging processing on the radar echo data of the multiple different track segments to obtain multiple SAR images; The multiple SAR images are incoherently superimposed to obtain a final SAR image.

8. The device according to claim 6, characterized in that The imaging module is also used for: Imaging the radar echo data of the multiple different track segments based on the CS algorithm to obtain multiple SAR images; Taking the geocoded imaging grid as an imaging area, geocoding the multiple SAR images to obtain multiple geocoded SAR images; The multiple geocoded SAR images are incoherently stacked to obtain a final SAR image.

Images