Satellite-borne synthetic aperture microwave radiometer imaging correction method based on differential measurement

Abstract

The invention discloses a differential measurement-based satellite-borne synthetic aperture microwave radiometer imaging correction method, which comprises the following steps of: respectively selecting a reference area and a correction area in a global range, and respectively intercepting scientific data and auxiliary data in a specific time period in the reference area and the correction area based on load normal earth observation data; averaging the visibility functions intercepted in the reference area to obtain a reference visibility function; generating a reference brightness temperature and a correction brightness temperature through a simulation model by using the auxiliary data intercepted in the reference area and the correction area respectively; performing difference and inversion processing on the normal earth observation visibility function to be subjected to imaging processing by using the reference visibility function to obtain a difference inversion brightness temperature; calculating a correction coefficient by using the reference visibility function, the reference brightness temperature, the visibility function intercepted in the correction area and the correction brightness temperature; and correcting and compensating the differential inversion brightness temperature by using the correction coefficient and the reference brightness temperature to obtain the final inversion brightness temperature.

Description

Technical Field

[0001] This invention belongs to the field of imaging processing technology of integrated aperture microwave radiometers, specifically, it relates to an imaging correction method for spaceborne integrated aperture microwave radiometers based on differential measurements. Background Technology

[0002] Aperture synthesized microwave radiometers (ASMRs) are an important type of remote sensor in the field of passive microwave remote sensing. Unlike traditional aperture microwave radiometers that directly observe the brightness temperature of the scene under test, ASMRs measure the spatial frequency of the brightness temperature of the scene under test through interferometry to obtain a visibility function. Then, they indirectly obtain a brightness temperature image of the scene under test through imaging processing methods. Imaging processing is a crucial step in ASMR technology and directly affects the final detection quality.

[0003] Traditional imaging processing methods for synthetic aperture microwave radiometers (MIRAS) directly process the measured visibility function, converting it into a brightness temperature image based on Fourier transform or G-matrix methods. This method is susceptible to systematic errors such as antenna pattern errors and receiver calibration errors, leading to insufficient imaging accuracy. The MIRAS synthetic aperture microwave radiometer aboard the ESA's SMOS satellite incorporates a flat target transformation (FTT) method based on cold-space observations to mitigate the impact of systematic errors during imaging processing (see reference: M. Martín-Neira, M. Suess, J. Kainulainen, and F. Martín-Porqueras, “The flat target transformation,” IEEE Trans. Geosci. Remote Sens., vol. 46, no. 3, pp. 613–620, Mar. 2008.). The Free-Touch (FTT) method offers some suppression of systematic errors. However, its drawbacks include the need for periodic maneuvering and flipping of the satellite to observe the cold sky, inevitably leading to a loss of normal Earth observation data. Furthermore, it is susceptible to interference from Earth radiation from the back lobe when observing the cold sky. Additionally, the FTT method is based on systematic error suppression of flat cold-sky targets; since these targets are completely different from the Earth's landscape, it cannot suppress the Gibbs effect caused by the Earth's contours. Moreover, while the FTT method can reduce the impact of systematic errors to some extent, it cannot correct for pattern errors, thus its imaging accuracy cannot meet the requirements of high-precision remote sensing applications. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and to propose an imaging correction method for a spaceborne integrated aperture microwave radiometer based on differential measurement.

[0005] In view of this, the present invention proposes an imaging correction method for a spaceborne synthetic aperture microwave radiometer based on differential measurements, comprising: Step 1: Select a reference area globally, and extract scientific and auxiliary data for a specific time period within the reference area based on the payload's normal Earth observation data; the scientific data is a visibility function; Step 2: Select a calibration area globally, and extract scientific and auxiliary data for a specific time period within the calibration area based on the payload's normal Earth observation data; Step 3: Take the average of the visibility functions extracted from the reference region to obtain the reference visibility function; Step 4: Using auxiliary data extracted from the reference region, generate a reference brightness temperature through a simulation model; Step 5: Using the auxiliary data extracted within the correction region, generate the correction brightness temperature through a simulation model; Step 6: Use the reference visibility function to perform differential and inversion processing on the normal Earth observation visibility function to be imaged, and obtain the differential inversion brightness temperature; Step 7: Calculate the correction coefficient using the reference visibility function, reference brightness temperature, visibility function truncated within the correction region, and correction brightness temperature. α ; Step 8: Using the correction coefficient α The differential inversion brightness temperature is corrected and compensated with the reference brightness temperature to obtain the final inversion brightness temperature.

[0006] As an improvement to the above method, the reference area in step 1 is a calm sea surface area far from land, and the auxiliary data includes: the observation time of the reference area. Reference area satellite position Reference area pixel ground latitude and longitude and the ground incident angle of the reference area pixels ;in, To extract the snapshot sequence number of the data, =1,2,···, N 0, N 0 represents the total number of snapshots captured within the reference area.

[0007] As an improvement to the above method, the correction area in step 2 is a land region with stable brightness temperature; auxiliary data includes: observation time of the correction area. Correction area satellite position Correction area pixel ground latitude and longitude Correction area pixel ground incidence angle ;in, To extract the snapshot sequence number of the data, =1,2,···,N 1, N 1 represents the total number of snapshots captured within the correction area.

[0008] As an improvement to the above method, the reference visibility function in step 3 for: ; in, This is the visibility function extracted from the reference region.

[0009] As an improvement to the above method, the reference brightness temperature generated in step 4 for:

[0010] in, This is a brightness temperature simulation model for the reference region.

[0011] As an improvement to the above method, the corrected brightness temperature generated in step 5 for:

[0012] in, This is a brightness temperature simulation model for the correction region.

[0013] As an improvement to the above method, the differential inversion brightness temperature obtained in step 6 for: , in, Let be the generalized inverse matrix of the system response matrix. For reference visibility function, This is the visibility function for normal Earth observations to be imaged.

[0014] As an improvement to the above method, step 7 includes: Step 7-1: Utilize the reference visibility function Visibility function of the correction area Differential inversion processing is performed to obtain the corrected differential inversion brightness temperature. : , Step 7-2: Using reference brightness temperature Brightness temperature correction and correction differential inversion brightness temperature The correction coefficients are obtained using the least squares method. α : .

[0015] As an improvement to the above method, step 8 yields the final inversion brightness temperature. for: .

[0016] Compared with the prior art, the advantages of the present invention are: 1. The imaging correction method provided by this invention is based on differential imaging inversion of Earth observation data. The reference visibility function and the visibility function to be processed for differential processing have similar forward field of view (i.e., Earth scene) and almost the same back lobe field of view (i.e. cold sky background). Therefore, differential inversion can effectively suppress the influence of systematic error and the Gibbs effect of Earth contour, and at the same time eliminate the influence of antenna pattern back lobe. 2. The imaging correction method provided by this invention can effectively suppress the influence of system errors on imaging, and can also correct system errors caused by antenna pattern measurement errors, thereby greatly improving the imaging inversion accuracy. 3. The imaging correction method provided by this invention can suppress and correct systematic errors without flipping the satellite for cold space observation, which greatly reduces the complexity of satellite operation, thereby saving satellite fuel and increasing satellite lifespan; at the same time, it can also avoid the loss of Earth observation data and improve the coverage of observation data. Attached Figure Description

[0017] Figure 1 This is a flowchart of the imaging and calibration method of a spaceborne integrated aperture microwave radiometer based on differential measurement according to the present invention; Figure 2(a) is a schematic diagram of the nadir point trajectory, reference area, and correction area corresponding to the example data in the embodiment; Figure 2(b) is a schematic diagram of pixel projection of a snapshot taken within the reference area in Example 2; Figure 2(c) is a schematic diagram of pixel projection of a snapshot taken within the correction area in Example 2; Figure 3 It is the reference brightness temperature generated in Example 2; Figure 4(a) is the X-polarization corrected brightness temperature image generated in Example 2; Figure 4(b) is the Y-polarization corrected brightness temperature image generated in Example 2; Figure 5(a) is the X-polarization inversion brightness temperature image obtained by using the method of the present invention on example data in Example 2; Figure 5(b) is the Y-polarization inversion brightness temperature image obtained using the method of the present invention for example data in Example 2; Figure 6(a) is the X-polarization inversion brightness temperature image obtained by using the FTT method on the example data in Example 2; Figure 6(b) is the Y-polarization inversion brightness temperature image obtained by using the FTT method on the example data in Example 2.

[0018] Figure Labels 1. Nadir trajectory of example data 1 2. Reference area 3. Nadir point trajectory of example data 2 4. Correction area Detailed Implementation

[0019] This invention proposes an imaging and calibration method for a spaceborne synthetic aperture microwave radiometer based on differential measurements, the method comprising: Step 1) Select a reference area globally, which is a calm sea area far from land; based on the payload's normal Earth observation data, extract scientific and auxiliary data for a specific time period within the reference area, wherein the scientific data is a visibility function. The auxiliary data includes: reference area observation time. Reference area satellite position Reference area pixel ground latitude and longitude and the ground incident angle of the reference area pixels ;in, To extract the snapshot sequence number of the data, =1,2,···, N 0, N 0 represents the total number of snapshots captured within the reference area.

[0020] Step 2) Select a calibration region globally, which is a land area with stable brightness temperature; based on normal Earth observation data from the payload, extract scientific and auxiliary data for a specific time period within the calibration region, wherein the scientific data is a visibility function. The auxiliary data includes: observation time of the correction area. Correction area satellite position Correction area pixel ground latitude and longitude Correction area pixel ground incidence angle ;in, To extract the snapshot sequence number of the data, =1,2,···, N 1, N 1 represents the total number of snapshots captured within the correction area.

[0021] Step 3) Visibility function extracted from the reference region The reference visibility function is obtained by averaging. The calculation formula is as follows: ; Step 4) Using auxiliary data extracted from the reference region, generate a reference brightness temperature through a simulation model. Its calculation method can be expressed as: , In the formula, A brightness temperature simulation model for the reference region; Step 5) Using the auxiliary data extracted within the correction region, generate the corrected brightness temperature through a simulation model. Its calculation method can be expressed as: , In the formula, A brightness temperature simulation model for the correction region; Step 6) Using the reference visibility function Normal Earth observation visibility function for imaging processing Differential and inversion processing is performed to obtain the differential inversion brightness temperature. The calculation formula is as follows: , In the formula, It is the generalized inverse matrix of the system response matrix; Step 7) Using the reference visibility function Reference brightness temperature Visibility function truncated within the correction region and brightness temperature correction Calculate the correction factor α ; Further includes: Step 7-1) Using the reference visibility function For the visibility function in the correction region Differential inversion processing is performed to obtain the corrected differential inversion brightness temperature. dT B1 ( i The calculation formula is as follows: , In the formula, It is the pseudo-inverse matrix or inverse Fourier transform matrix of the system response matrix; Step 7-2) Using reference brightness temperature Brightness temperature correction and correction differential inversion brightness temperature The correction coefficients are estimated using the least squares method. The calculation formula is as follows: .

[0022] Step 8) Using the correction coefficient and reference brightness temperature Brightness temperature of difference inversion Correction and compensation are performed to obtain the final inverted brightness temperature. The calculation formula is as follows: .

[0023] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0024] Example 1 Embodiment 1 of the present invention provides an imaging correction method for a spaceborne synthetic aperture microwave radiometer based on differential measurement, the flowchart of which is shown below. Figure 1 As shown, this method can be specifically described as follows: Step 101) Select a reference area globally, and extract scientific and auxiliary data for a specific time period within the reference area based on the payload's normal Earth observation data. The scientific data is a visibility function. The auxiliary data includes: reference area observation time. Reference area satellite position Reference area pixel ground latitude and longitude and the ground incident angle of the reference area pixels ;in, To extract the snapshot sequence number of the data, =1,2,···, N 0, N 0 represents the total number of snapshots captured within the reference area; Step 201): Select a calibration area globally, and extract scientific and auxiliary data for a specific time period within the calibration area based on the payload's normal Earth observation data. The scientific data is a visibility function. The auxiliary data includes: Observation time of the correction area. Correction area satellite position Correction area pixel ground latitude and longitude Correction area pixel ground incidence angle ;in, To extract the snapshot sequence number of the data, =1,2,···, N 1, N 1 represents the total number of snapshots captured within the correction area; Step 301) Visibility function extracted from the reference region V 0( i The reference visibility function is obtained by averaging. The calculation formula is as follows: ; Step 401) Using auxiliary data extracted from the reference region, generate a reference brightness temperature through a simulation model. Its calculation method can be expressed as: , In the formula, This is a brightness temperature simulation model for a reference region; in one embodiment, a sea surface microwave radiation model, an atmospheric microwave radiation transmission model, or a Faraday polarization rotation model are used, all of which are existing technologies.

[0025] Step 501) Using auxiliary data extracted within the correction region, generate the corrected brightness temperature through a simulation model. Its calculation method can be expressed as: , In the formula, This is a brightness temperature simulation model for the correction region; in one embodiment, a brightness temperature regression model based on SMOS satellite data and a Faraday polarization rotation model are used, both of which are existing technologies.

[0026] Step 601) Using the reference visibility function Normal Earth observation visibility function for imaging processing Differential and inversion processing is performed to obtain the differential inversion brightness temperature. The calculation formula is as follows: , In the formula, It is the generalized inverse matrix of the system response matrix; Step 701) Using the reference visibility function Visibility function truncated in the correction region Differential inversion processing is performed to obtain the corrected differential inversion brightness temperature. The calculation formula is as follows: , In the formula, It is the pseudo-inverse matrix or inverse Fourier transform matrix of the system response matrix; Step 702), using reference brightness temperature Brightness temperature correction and correction differential inversion brightness temperature dT B1 ( i The correction coefficients are estimated using the least squares method. α The calculation formula is as follows: ; Step 801) Using the correction coefficient α and reference brightness temperature Brightness temperature for difference inversion Correction and compensation are performed to obtain the final inverted brightness temperature. The calculation formula is as follows: ; Example 2 Embodiment 2 of the present invention is illustrated using the L-band one-dimensional synthetic aperture microwave radiometer payload of the China Ocean Salinity Detection Satellite (hereinafter referred to as the HY4A satellite MICAP-L radiometer) as an example. The antenna array of this radiometer payload consists of 12 dual-polarized element antennas, with a total of 24 receiver channels and 312 observation baselines. Therefore, the total number of receiver channels in this embodiment is... M =24, Total number of baselines K =312. In other embodiments, the method of the present invention can also be used in one-dimensional or two-dimensional synthetic aperture microwave radiometer systems in other bands.

[0027] In this embodiment, observation data from the HY4A satellite MICAP-L radiometer from 02:15 to 03:08 on February 23, 2025, and from 22:16 to 23:09 on February 24, 2025, were selected as example data for imaging processing, and are denoted as Example Data 1 and Example Data 2, respectively. The nadir trajectory corresponding to the example data is shown in Figure 2(a). Here, 1 represents the nadir trajectory of Example Data 1, 2 represents the reference area, 3 represents the nadir trajectory of Example Data 2, and 4 represents the correction area.

[0028] In step 101), the selected reference area is the ocean region near the equator in example data 1. Visibility function data and auxiliary data are continuously captured for 30 seconds within this reference area. Since the integration time of this radiometer payload is 6 seconds, meaning each snapshot lasts 6 seconds, a total of 5 snapshots of visibility function data and auxiliary data are captured, representing the total number of snapshots. N 0=5. The location of the captured snapshot is shown in Figure 2(a), and its magnified view of the pixel ground projection is shown in Figure 2(b).

[0029] In step 201), the selected correction area is the land area located in the Amazon rainforest in example data 2. Visibility function data and auxiliary data are continuously captured for 150 seconds within this correction area. A total of 25 snapshots of visibility function data and auxiliary data are captured, representing the total number of snapshots. N 1=25. The location of the captured snapshot is shown in Figure 2(a), and its magnified view of the pixel ground projection is shown in Figure 2(c).

[0030] Step 301) Visibility function extracted from the reference region The reference visibility function is obtained by averaging. The calculation formula is as follows: ; Step 401) Using auxiliary data extracted from the reference region, generate a reference brightness temperature through a simulation model. The simulation models used include a sea surface microwave radiation model, an atmospheric microwave radiation transmission model, and a Faraday polarization rotation model, all of which are existing technologies. The brightness temperature of the generated reference model is as follows: Figure 3 As shown, this includes the X-polarized reference brightness temperature and the Y-polarized reference brightness temperature.

[0031] Step 501) Using the auxiliary data extracted within the correction region, generate the corrected brightness temperature through a simulation model. The simulation models used include a brightness temperature regression model based on SMOS satellite data and a Faraday polarization rotation model, both of which are existing technologies. The generated X-polarization corrected brightness temperature and Y-polarization corrected brightness temperature are shown in Figure 4(a) and Figure 4(b), respectively.

[0032] The X-polarized and Y-polarized inverted brightness temperature images obtained after processing the example data using the above steps are shown in Figures 5(a) and 5(b), respectively. It can be seen from the figures that the brightness temperature images obtained using the processing method of this invention have uniform brightness temperature in land areas and smooth brightness temperature in ocean areas, conforming to the actual brightness temperature distribution. For comparison, the above example data was imaged using the traditional FTT method, and the resulting X-polarized and Y-polarized inverted brightness temperature images are shown in Figures 6(a) and 6(b), respectively. It can be seen from the figures that the inverted brightness temperature images obtained using the traditional FTT method have obvious fringe errors, which do not conform to the actual brightness temperature distribution. This is mainly because the back lobe level of the HY4A satellite MICAP-L radiometer antenna is high, and there is a certain pattern measurement error. The traditional FTT method cannot eliminate the back lobe effect and cannot correct the pattern error, thus resulting in a large error in the inversion result. The comparison of the brightness temperature inversion results in Figures 5 and 6 shows that the imaging and correction method provided by this invention has higher imaging accuracy than the traditional FTT method.

[0033] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for imaging correction of space-borne synthetic aperture microwave radiometer based on differential measurement, comprising: Step 1: selecting a reference region in the global scope, and intercepting scientific data and auxiliary data in the reference region for a specific period based on normal earth observation data of the payload; the scientific data is a visibility function; Step 2: selecting a correction region in the global scope, and intercepting scientific data and auxiliary data in the correction region for a specific period based on normal earth observation data of the payload; Step 3: averaging the visibility function intercepted in the reference region to obtain a reference visibility function; Step 4: generating a reference brightness temperature by a simulation model using the auxiliary data intercepted in the reference region; Step 5: generating a correction brightness temperature by a simulation model using the auxiliary data intercepted in the correction region; Step 6: performing differential and inversion processing on the normal earth observation visibility function to be imaged using the reference visibility function to obtain a differential inversion brightness temperature; Step 7: Calculate the correction factor using the reference visibility function, the reference brightness temperature, the visibility function and the corrected brightness temperature taken within the correction region α ; Step 8: Correction with correction coefficient α The final retrieved brightness temperature is obtained by correcting and compensating the difference retrieved brightness temperature with the reference brightness temperature.

2. The differential measurement based space-borne synthetic aperture microwave radiometer imaging correction method of claim 1, wherein the reference region of step 1 is a calm sea surface region away from land, and the auxiliary data includes: Reference region observation time Reference region satellite position Reference region pixel ground longitude and latitude Reference region pixel ground incidence angle ; wherein is a snapshot number of the intercepted data, = 1, 2, ···, N 0, N 0 is the total number of snapshots intercepted within the reference region.

3. The method of claim 1, wherein the correction region of step 2 is a land area with stable brightness temperature; and the auxiliary data includes: Corrected area observation time , Corrected area satellite position , Corrected area pixel ground longitude and latitude , Corrected area pixel ground incidence angle ; wherein, is the snapshot number of the intercepted data, = 1, 2, ···, N 1, N 1 is the total number of snapshots intercepted in the corrected area.

4. The differential measurement based space-borne synthetic aperture microwave radiometer imaging correction method of claim 2, the reference visibility function of step 3 is: Vref = Vref (u, v, f) = Vref (u, v, f) ； wherein Visibility function for the reference region.

5. The differential measurement based space-borne synthetic aperture microwave radiometer imaging correction method of claim 2, the step 4 generated reference brightness temperature is: ； wherein is a brightness temperature simulation model for the reference region.

6. The differential measurement based space-borne synthetic aperture microwave radiometer imaging correction method of claim 3, the corrected brightness temperature generated by step 5 is: Tc = T - Td ； wherein is a brightness temperature simulation model for the correction region.

7. The method of imaging correction for space-borne synthetic aperture microwave radiometers based on differential measurements according to claim 4, the differential brightness temperature obtained in step 6 is: Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = Tdiff = T ； wherein, is the generalized inverse of the system response matrix, is the reference visibility function, is the normal ground observation visibility function to be imaged.

8. The method for imaging correction of space-borne synthetic aperture microwave radiometer based on differential measurement according to claim 7, wherein the step 7 comprises: Step 7-1: Utilizing the reference visibility function On the correction region visibility function Difference inversion processing is performed to obtain a corrected difference inversion brightness temperature : ； Step 7-2: Using the reference brightness temperature to correct the brightness temperature and the corrected differential inversion brightness temperature to obtain the correction coefficient by least square method α : 。 9. The differential measurement based space-borne synthetic aperture microwave radiometer imaging correction method of claim 8, said step 8 resulting in final inverted brightness temperature is: 。

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