Geographic positioning method, system and equipment for ultra-wide satellite image

Abstract

The invention discloses a geographic positioning method, system and device for an ultra-wide satellite image, and the method comprises the steps: obtaining satellite data, and carrying out the ideal positioning of an instrument; selecting a first instrument image of the same landmark in multiple days, and performing first geometric parameter calibration processing on the first instrument image to obtain a calibrated first geometric parameter; selecting a second instrument image of a global long-time sequence, performing second geometric parameter calibration processing by combining the second instrument image and the calibrated first geometric parameter, and inputting the calibrated second geometric parameter into the positioning model; and the positioning model carries out positioning precision inspection on the second instrument image data, an inspection result is fed back to the second instrument image of the global long-time sequence, and the second geometric parameter is iterated. According to the method, preliminary geometric parameters are calibrated for the single-landmark multi-time image of the ultra-large-breadth image, and then edge distortion caused by the ultra-large breadth is eliminated through the combined action of accurate geometric parameters calibrated by the long-time-sequence global image.

Description

Technical Field

[0001] The present invention belongs to the field of satellite space, and more specifically, relates to a method, system and device for geolocation of ultra-wide swath satellite images. Background Art

[0002] Remote sensing images are the basis of remote sensing and many applications. As spatial data, remote sensing images have the concept of spatial geographical location. Whatever the application problem, the corresponding relationship between image information and ground position needs to be determined. The geolocation of satellite images is an important prerequisite for satellite data preprocessing.

[0003] The geolocation of remote sensing images is a process of calculating the coordinates of the observed images of spaceborne remote sensing instruments in the ground coordinate system. Existing positioning methods are all designed for high-resolution instruments with a swath width within 1000 km, such as linear array and area array, and there is still a lack of positioning methods designed for medium-resolution instruments with ultra-wide swath widths. The positioning method proposed in this paper can effectively eliminate the errors caused by the edge field distortion effect of instruments with ultra-wide swath widths, such as those with a swath width exceeding 2000 km.

[0004] In view of this, overcoming the technical defects of the above existing technologies is an urgent problem to be solved in this technical field. Summary of the Invention

[0005] In view of the above defects or improvement requirements of the existing technology, the present invention provides a method, system and device for geolocation of ultra-wide swath satellite images, aiming to solve the technical problem of errors caused by the current edge field distortion effect by correcting the errors of the satellite images in the along-track direction, along-scan direction and scanning mirror.

[0006] To achieve the above object, according to one aspect of the present invention, a method for geolocation of ultra-wide swath satellite images is provided, the method comprising:

[0007] Obtain satellite data and perform ideal positioning of an ultra-wide swath instrument;

[0008] Select the first ultra-wide swath instrument images of the same landmark within multiple days, perform first geometric parameter calibration processing on the first ultra-wide swath instrument images, and obtain the calibrated first geometric parameters;

[0009] Select the second ultra-wide swath instrument images of the global long time series, perform second geometric parameter calibration processing in combination with the second ultra-wide swath instrument images and the calibrated first geometric parameters, and input the calibrated second geometric parameters into the positioning model;

[0010] The positioning model performs a positioning accuracy test on the image data of the second ultra-wide swath instrument, and feeds back the test results to the second ultra-wide swath instrument images of the global long-term series, and the second geometric parameters are iterated.

[0011] As a further improvement and supplement to the above solution, the present invention further includes the following additional technical features.

[0012] Preferably, the geometric parameter calibration includes:

[0013] After extracting the radiation value of the reference channel and the corresponding longitude and latitude, a first positioning accuracy test is performed to obtain the error in the along-track direction;

[0014] The image after correcting the along-track deviation is repositioned, and then a second positioning accuracy test is performed to obtain the error in the cross-track direction;

[0015] The relationship between the scan angle and the positioning error in the cross-track direction is fitted, and the distortion of the cross-track field of view edge is corrected;

[0016] The image after correcting the distortion of the cross-track field of view edge is repositioned, and then a third positioning accuracy test is performed to obtain the angular error of the scan mirror;

[0017] The ultra-wide swath satellite image after correcting the scan mirror error is repositioned, and then a fourth positioning accuracy test is performed to issue the positioning accuracy test result.

[0018] Preferably, after selecting the second ultra-wide swath satellite images of the global long-term series, the Otsu threshold method is used for cloud identification, and the second ultra-wide swath satellite images are segmented into cloud regions and non-cloud regions, and the non-cloud regions are selected for geometric parameter calibration.

[0019] Preferably, the method for obtaining satellite data and performing ideal positioning of the instrument includes:

[0020]

[0021] where x and y are the coordinate values on the focal plane, f is the focal length, m is the correction coefficient, is the installation matrix from the scan mirror to the present system, is the conversion matrix from the present system to the orbital system, is the conversion matrix from the orbital system to the inertial system, is the conversion matrix from the inertial system to the earth-fixed system, is the satellite position vector matrix, is the vector where the view vector intersects the earth's ellipse, and the satellite position vector matrix and the vector where the view vector intersects the earth's ellipse are known from the satellite data.

[0022] Preferably, after extracting the radiation value of the reference channel and the corresponding longitude and latitude, the method for performing the first positioning accuracy test to obtain the error in the along-track direction includes:

[0023]

[0024] Among them, x is the coordinate in the along-track direction, Δμ is the error in the along-track direction, is the corrected coordinate in the along-track direction. The satellite position vector matrix and the vector where the viewing vector intersects the Earth's ellipse are known from satellite data.

[0025] Preferably, the method for fitting the relationship between the scan angle and the positioning error in the scan direction and correcting the distortion at the edge of the scan direction field of view includes:

[0026]

[0027] Among them, represents the fitted scan angle, θ represents the true scan angle of the scanning mirror in the instrument, a represents the fitting coefficient, and a n represents the fitting coefficient of the nth-degree polynomial.

[0028] Preferably, the method for repositioning the image after correcting the scanning mirror error includes:

[0029]

[0030] Among them,

[0031] Preferably, the method for iterating the second geometric parameter includes:

[0032] Statistically analyze the along-track error and cross-track error of the second ultra-wide swath instrument image. Stop the iteration if the deviation between the statistical quantities of the along-track error and the cross-track error is less than 0.1 pixel.

[0033] In a second aspect, the present invention provides a geolocation system for ultra-wide swath satellite images, and the system includes:

[0034] A data acquisition module for acquiring satellite data;

[0035] A positioning module for performing ideal positioning of the instrument;

[0036] A positioning accuracy test module for performing positioning accuracy tests of the instrument;

[0037] A calibration module for calibrating the geometric parameters of the instrument image;

[0038] A feedback module for iterating the geometric parameters.

[0039] In a third aspect, the present invention provides a geolocation device for ultra-wide satellite images, the device comprising:

[0040] One or more processors;

[0041] A storage device for storing one or more programs, which when executed by the one or more processors cause the one or more processors to implement the geolocation device method for ultra-wide satellite images as described in the first aspect.

[0042] Generally speaking, compared with the prior art by the above technical solutions conceived by the present invention, the following beneficial effects are achieved:

[0043] The present invention provides a geolocation method, system and device for ultra-wide satellite images. By initially calibrating the preliminary geometric parameters of a single landmark and multiple-time images of the ultra-wide image, and then through the combined action of calibrating the precise geometric parameters with long-time global images, the edge distortion caused by the ultra-wide width is eliminated. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required to be used in the embodiments of the present invention. Obviously, the following described drawings are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0045] Figure 1 It is a schematic flowchart of a geolocation method for ultra-wide satellite images provided in Embodiment 1;

[0046] Figure 2 It is a schematic diagram of monitoring the along-track accuracy of global long-time instrument images provided in Embodiment 1;

[0047] Figure 3 It is a schematic diagram of monitoring the cross-track accuracy of global long-time instrument images provided in Embodiment 1;

[0048] Figure 4 It is a schematic diagram of statistical histogram of along-track accuracy of global long-time instrument images provided in Embodiment 1;

[0049] Figure 5 It is a schematic diagram of statistical histogram of cross-track accuracy of global long-time instrument images provided in Embodiment 1;

[0050] Figure 6 It is a projection diagram of along-track accuracy of global long-time instrument images provided in Embodiment 1;

[0051] Figure 7It is a cross-track accuracy projection map of global long-time-series instrument images provided by the first embodiment;

[0052] Figure 8 It is a geolocation system for ultra-wide satellite images provided by the second embodiment;

[0053] Figure 9 It is a geolocation device for ultra-wide satellite images provided by the third embodiment. Specific implementation manners

[0054] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0055] Embodiment 1

[0056] The first embodiment provides a geolocation method for ultra-wide satellite images. As Figure 1 shown, the method includes:

[0057] S101: Obtain satellite data and perform ideal positioning of an ultra-wide instrument.

[0058] To obtain satellite data, data extraction needs to be performed, and the radiation value of the reference channel and the corresponding longitude and latitude are extracted respectively.

[0059] The overall process of ideal positioning of the ultra-wide instrument includes:

[0060] Step 1: Obtain time data, orbital data, and attitude data to prepare for positioning;

[0061] Step 2: Perform quality checks on the time, orbital data, attitude data, etc. obtained from the positioning data preparation module, and generate the checked orbital data, attitude data, and quality flags;

[0062] Step 3: Calculate the instrument coordinate system view vector according to the precise time of each pixel and the scan angle of each scanned pixel;

[0063] Step 4: Under the support of the common geolocation subsystem, perform geolocation calculations on the earth observation data according to the scan observation time, orbital data, attitude data, instrument coordinate system view vector, preprocessed static data, etc., perform elevation correction according to the elevation static data process, and generate the geolocation result and the geodetic height after terrain correction for each pixel;

[0064] Step 5: Generate geolocation-related files.

[0065] S102: Select the first ultra-wide instrument images of the same landmark within multiple days, perform the first geometric parameter calibration process on the first ultra-wide instrument images, and obtain the calibrated first geometric parameters.

[0066] For the first ultra-wide instrument images, perform the first geometric parameter calibration, and the first geometric parameter calibration includes:

[0067] After extracting the reference channel radiation values and the corresponding longitude and latitude of the first ultra-wide instrument images, perform the first positioning accuracy test to obtain the error of the first ultra-wide instrument images in the along-track direction;

[0068] Relocate the image after correcting the along-track deviation, and then perform the second positioning accuracy test to obtain the error of the first ultra-wide instrument images in the scan direction;

[0069] Fit the relationship between the scan angle and the positioning error in the scan direction, and correct the distortion of the first ultra-wide instrument images at the scan direction field edge;

[0070] Relocate the first ultra-wide instrument images after correcting the distortion at the scan direction field edge, and then perform the third positioning accuracy test to obtain the angle error of the scan mirror;

[0071] Relocate the first ultra-wide satellite images after correcting the scan mirror error, and then perform the fourth positioning accuracy test to issue the positioning accuracy test results.

[0072] S103: Select the second ultra-wide instrument images of the global long time series, perform the second geometric parameter calibration process by combining the second ultra-wide instrument images and the calibrated first geometric parameters, and input the calibrated second geometric parameters into the positioning model.

[0073] For the second ultra-wide instrument images, perform the second geometric parameter calibration, and the second geometric parameter calibration includes:

[0074] After extracting the reference channel radiation values and the corresponding longitude and latitude of the second ultra-wide instrument images, perform the first positioning accuracy test to obtain the error of the second ultra-wide instrument images in the along-track direction;

[0075] Relocate the image after correcting the along-track deviation, and then perform the second positioning accuracy test to obtain the error of the second ultra-wide instrument images in the scan direction;

[0076] Fit the relationship between the scan angle and the positioning error in the scan direction, and correct the distortion of the second ultra-wide instrument images at the scan direction field edge;

[0077] Relocate the second ultra-wide instrument image after correcting the distortion of the field of view edge in the scanning direction, and then conduct the third positioning accuracy test to obtain the angular error of the scanning mirror.

[0078] Relocate the second ultra-wide satellite image after correcting the scanning mirror error, and then conduct the fourth positioning accuracy test to issue the positioning accuracy test result.

[0079] The positioning accuracy test method used in the first embodiment mainly includes the following steps:

[0080] Obtain the control point image corresponding to the true value image and the geographical location information of the true value image; obtain the reference channel image of the satellite image and the geographical location information of the satellite image; segment the satellite image using the Otsu threshold method to obtain the cloud region and non-cloud region images; remap the true value image using Gaussian filtering to obtain the remapped image; extract the feature points of the cloud region and non-cloud region images and the remapped image; use the SIFT feature point matching algorithm for feature matching to obtain the matching point pairs; according to the matching point pairs, use the RANSAC algorithm to eliminate the outlier matching point pairs to obtain the accurate matching point pairs; according to the geographical location information of the true value image and the geographical location information of the satellite image, extract the position information of the accurate matching point pairs and convert it into the positioning error; conduct the positioning accuracy test according to the positioning error to obtain the positioning accuracy test result.

[0081] S104: The positioning model conducts the positioning accuracy test on the second ultra-wide instrument image data, and feeds back the test result to the second ultra-wide instrument image of the global long time series, and the second geometric parameter is iterated.

[0082] Combined with the embodiments of the present invention, there is also a preferred implementation scheme. Specifically, the geometric parameter calibration includes:

[0083] After extracting the radiation value of the reference channel and the corresponding longitude and latitude, conduct the first positioning accuracy test to obtain the error in the along-track direction.

[0084] Relocate the image after correcting the along-track deviation, and then conduct the second positioning accuracy test to obtain the error in the scanning direction.

[0085] Fit the relationship between the scanning angle and the positioning error in the scanning direction, and correct the distortion of the field of view edge in the scanning direction.

[0086] Relocate the image after correcting the distortion of the field of view edge in the scanning direction, and then conduct the third positioning accuracy test to obtain the angular error of the scanning mirror.

[0087] Relocate the ultra-wide satellite image after correcting the scanning mirror error, and then conduct the fourth positioning accuracy test to issue the positioning accuracy test result.

[0088] In the first embodiment, the first geometric parameter calibration for the first ultra-wide instrument image is set as: the first geometric parameter calibration algorithm for single landmark multi-temporal instrument images.

[0089] The steps of the first geometric parameter calibration algorithm for single landmark multi-temporal instrument images are as follows:

[0090] 1. Select the instrument images of the same landmark within multiple days. Generally, the location selected is near the Red Sea with less cloud cover.

[0091] 2. Process the prepared instrument images using the aforementioned geometric parameter calibration algorithm.

[0092] 3. Substitute the calibrated first geometric parameters into a new positioning model for application. The first geometric parameters include along-track, along-scan direction, and the angular error of the scanning mirror.

[0093] 4. Issue the positioning error analysis result.

[0094] In the first embodiment, the second geometric parameter calibration for the second ultra-wide instrument image is set as: the geometric parameter calibration algorithm for global long-time series instrument images.

[0095] The steps are as follows:

[0096] 1. Select the instrument images of global long-time series and use the Otsu threshold method for cloud recognition. The Otsu threshold method can automatically select the optimal threshold to achieve adaptive binary segmentation of the image. Automatically segment the satellite image into cloud regions and non-cloud regions.

[0097] 2. Process the prepared instrument images using the aforementioned geometric parameter calibration algorithm.

[0098] 3. Substitute the calibrated second geometric parameters into a new positioning model for application. The second geometric parameters include along-track, along-scan direction, and the angular error of the scanning mirror.

[0099] 4. Over time, continuously apply this algorithm to iteratively calibrate the second geometric parameters.

[0100] Combined with the embodiments of the present invention, there is also a preferred implementation scheme. Specifically, after selecting the second ultra-wide satellite images of global long-time series, use the Otsu threshold method for cloud recognition, segment the second ultra-wide satellite images into cloud regions and non-cloud regions, and select the non-cloud regions for geometric parameter calibration.

[0101] Combined with the embodiments of the present invention, there is also a preferred implementation scheme. Specifically, the method for obtaining satellite data and performing ideal positioning of the instrument includes:

[0102]

[0103] where x and y are coordinate values on the focal plane, f is the focal length, m is the correction coefficient, is the installation matrix from the scanning mirror to this system, is the conversion matrix from this system to the orbital system, is the conversion matrix from the orbital system to the inertial system, is the conversion matrix from the inertial system to the Earth-fixed system, is the satellite position vector matrix, is the vector where the viewing vector intersects the Earth's ellipse. The satellite position vector matrix and the vector where the viewing vector intersects the Earth's ellipse are known from satellite data.

[0104] Combined with the embodiments of the present invention, there is also a preferred implementation scheme. Specifically, after extracting the radiation value of the reference channel and the corresponding longitude and latitude, the method for performing the first positioning accuracy test and obtaining the error in the along-track direction includes:

[0105]

[0106] where, x is the coordinate in the along-track direction, Δμ is the error in the along-track direction, is the corrected coordinate in the along-track direction. The satellite position vector matrix and the vector where the viewing vector intersects the Earth's ellipse are known from satellite data.

[0107] Combined with the embodiments of the present invention, there is also a preferred implementation scheme. Specifically, after calculating the error in the along-track direction, calculate the error in the cross-track direction. The method includes:

[0108]

[0109] where, y is the coordinate in the cross-track direction, Δμ 2 is the error in the cross-track direction, is the corrected coordinate in the cross-track direction. The satellite position vector matrix and the vector where the viewing vector intersects the Earth's ellipse are known from satellite data.

[0110] Combined with the embodiments of the present invention, there is also a preferred implementation scheme. Specifically, the method for fitting the relationship between the scanning angle and the positioning error in the scanning direction and correcting the distortion at the edge of the viewing field in the scanning direction includes:

[0111]

[0112] where, represents the fitted scanning angle, θ represents the true scanning angle of the scanning mirror in the instrument, a represents the fitting coefficient, a n represents the fitting coefficient of the nth-degree polynomial.

[0113] The method for iterating the second geometric parameter includes:

[0114] Combined with the embodiments of the present invention, there is also a preferred implementation scheme. Specifically, the along-track error and cross-track error of the second ultra-wide swath instrument image are statistically analyzed, and the iteration is stopped when the deviation between the statistical quantities of the along-track error and the cross-track error is less than 0.1 pixel.

[0115] As Figure 2 and Figure 3 shown, the blue dots are the means, the red lines are the standard deviations, and the accuracies in the along-track and cross-track directions are both better than 1 pixel, which proves that the geolocation method of the ultra-wide swath satellite image provided in the first embodiment of the present invention achieves the effect of eliminating the edge distortion caused by the ultra-wide swath.

[0116] As Figure 4 and Figure 5 shown, according to the histogram statistical results, the mean value of the along-track direction error is 0.02 pixel, the standard deviation STD is 0.61 pixel, the root mean square error RMSE is 0.61 pixel, the mean value of the cross-track direction error is 0.11 pixel, the standard deviation STD is 0.6 pixel, and the root mean square error RMSE is 0.61 pixel. This shows the stability of the algorithm in terms of time and space from a statistical significance perspective.

[0117] As Figure 6 and Figure 7 shown, by globally statistically analyzing the geolocation errors in the along-track and cross-track directions, it can be seen that the geolocation errors are relatively consistent globally and there is no obvious change along latitude or longitude. It can be seen from the projection map the stability of the algorithm in terms of time and space.

[0118] Embodiment 2:

[0119] This embodiment 2 provides a geolocation system for ultra-wide swath satellite images. As Figure 8 shown, the system includes:

[0120] A data acquisition module for acquiring satellite data;

[0121] A positioning module for performing ideal positioning of the instrument;

[0122] A positioning accuracy inspection module for inspecting the positioning accuracy of the ultra-wide swath satellite image instrument;

[0123] A calibration module for calibrating the geometric parameters of the ultra-wide swath satellite image instrument image;

[0124] A feedback module for iterating the geometric parameters.

[0125] In the second embodiment, the geolocation system for ultra-wide satellite images corrects the errors in the along-track direction, along-scan direction, and scanning mirror of the satellite images to solve the technical problem of errors caused by the current marginal field distortion effect.

[0126] Embodiment Three

[0127] Embodiment Three provides a geolocation device for ultra-wide satellite images, as Figure 9 shown, the device includes:

[0128] One or more processors;

[0129] A storage device for storing one or more programs, which when executed by the one or more processors, cause the one or more processors to implement the geolocation device method for ultra-wide satellite images provided in Embodiment One.

[0130] Figure 9 It is a schematic structural diagram of the geolocation device for ultra-wide satellite images provided in Embodiment Two. Figure 9 It shows a block diagram of an exemplary geolocation device for ultra-wide satellite images suitable for implementing the embodiments of the present invention. Figure 9 The shown geolocation device for ultra-wide satellite images is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present invention.

[0131] As Figure 9 shown, the geolocation device for ultra-wide satellite images is presented in the form of a general-purpose device. The components of the geolocation device for ultra-wide satellite images may include but are not limited to: one or more processors or processing units, a memory, and a bus connecting different system components (including the memory and the processing unit).

[0132] The bus represents one or more of several types of bus structures, including a memory bus or a memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the multiple bus structures. For example, these architectures include but are not limited to the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0133] The geolocation device for ultra-wide satellite images typically includes a variety of computer system-readable media. These media can be any available media accessible by a device that can be modified by an intelligent logging interpretation model, including volatile and non-volatile media, removable and non-removable media.

[0134] The memory may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory. The geolocation device for ultra-wide swath satellite imagery may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system may be used for reading and writing on non-removable, non-volatile magnetic media ( Figure 9 not shown, typically referred to as a "hard disk drive"). Although Figure 9 not shown in, a disk drive for reading and writing on removable non-volatile disks (such as a "floppy disk") and an optical disk drive for reading and writing on removable non-volatile optical disks (such as CD-ROM, DVD-ROM or other optical media) may be provided. In these cases, each drive may be connected to the bus through one or more data media interfaces. The memory may include at least one program product having a set (such as at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0135] A program / utility with a set (at least one) of program modules may be stored, for example, in the memory. Such program modules include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. The implementation of a network environment may be included in each or some combination of these examples. The program modules generally perform the functions and / or methods in the embodiments described in the present invention.

[0136] The geolocation device for ultra-wide swath satellite imagery may also communicate with one or more external devices (such as a keyboard, a pointing device, a display, etc.), and may also communicate with one or more devices that enable a user to interact with the geolocation device for ultra-wide swath satellite imagery, and / or communicate with any device that enables the geolocation device for ultra-wide swath satellite imagery to communicate with one or more other devices (such as a network card, a modem, etc.). Such communication may be carried out through an input / output (I / O) interface. Also, the device for intelligent logging interpretation model correction may further communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter. As Figure 9 shown, the network adapter communicates with other modules of the geolocation device for ultra-wide swath satellite imagery through the bus. It should be understood that although not shown in the figure, other hardware and / or software modules may be used in conjunction with the geolocation device for ultra-wide swath satellite imagery, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0137] The processing unit executes various functional applications and data processing by running the program stored in the memory, for example, implementing the geolocation method of the ultra-wide satellite image provided by any embodiment of the present invention. That is: obtaining satellite data and performing ideal positioning of the instrument; selecting the first instrument images of the same landmark within multiple days, performing the first geometric parameter calibration process on the first instrument images to obtain the calibrated first geometric parameters; selecting the second instrument images of the global long time series, performing the second geometric parameter calibration process by combining the second instrument images and the calibrated first geometric parameters, and inputting the calibrated second geometric parameters into the positioning model; the positioning model performs positioning accuracy inspection on the second instrument image data, feeds back the inspection results to the second instrument images of the global long time series, and iterates the second geometric parameters.

[0138] The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for geo-positioning of ultra-wideband satellite images, characterized in that: The method comprises: Acquire satellite data for ideal positioning of ultra-wideband instruments; Selecting first ultra-wide-width instrument images of a same landmark over multiple days, performing first geometric parameter calibration processing on the first ultra-wide-width instrument images, and obtaining calibrated first geometric parameters; Selecting a second ultra-wide-width instrument image of a global long time series, performing a second geometric parameter calibration process in combination with the second ultra-wide-width instrument image and the calibrated first geometric parameters, and inputting the calibrated second geometric parameters into a positioning model; The positioning model performs positioning accuracy inspection on the second ultra-wide-width instrument image data, feeds back the inspection result to the second ultra-wide-width instrument image of the global long time series, and the second geometric parameters are iterated.

2. The method for geo-positioning of ultra-wideband satellite images according to claim 1, characterized in that: The geometric parameter calibration includes: After extracting the reference channel radiation value and the corresponding longitude and latitude, the first positioning accuracy test is performed to obtain the error in the along-track direction; The image after the correction of the deviation along the track is repositioned, and then the positioning accuracy is tested for the second time to obtain the error along the scanning direction; Fit the relationship between the scanning angle and the positioning error along the scanning direction, and perform distortion correction on the edge of the field of view in the scanning direction; The image after the distortion of the edge of the field of view in the corrected scanning direction is repositioned, and then the positioning accuracy is tested for the third time to obtain the angle error of the scanning mirror; The ultra-wide-width satellite image after correcting the scanning mirror error is repositioned, and then a fourth positioning accuracy test is carried out to issue a positioning accuracy test result.

3. The method for geo-positioning of ultra-wideband satellite images according to claim 1, characterized in that: After selecting the second ultra-wide satellite image of the global long-term series, the Otsu threshold is used for cloud recognition, the second ultra-wide satellite image is divided into a cloud area and a non-cloud area, and the non-cloud area is selected for geometric parameter calibration.

4. The method for geo-positioning of ultra-wideband satellite images according to claim 2, wherein: The method for obtaining satellite data and performing ideal positioning of the instrument includes: Where x and y are the coordinates on the focal plane, f is the focal length, and m is the correction factor. is the installation matrix of the scanning mirror to this system, is the transformation matrix from this system to the orbital system, is the transformation matrix from orbital system to inertial system, is the transformation matrix from the inertial system to the earth-fixed system, is the satellite position vector matrix, is the vector where the view vector intersects the earth ellipse. The satellite position vector matrix and the vector where the view vector intersects the earth ellipse are known from satellite data.

5. The method for geo-positioning of ultra-wideband satellite images as claimed in claim 4, characterized in that: After extracting the reference channel radiation value and the corresponding longitude and latitude, a first positioning accuracy test is performed to obtain the error in the along-track direction, which includes: in, x is the coordinate along the track, Δμ is the error along the track, is the corrected along-track coordinate, the satellite position vector matrix and the vector where the view vector intersects the earth ellipse are known from the satellite data.

6. The method for geo-positioning of ultra-wideband satellite images according to claim 5, characterized in that: The method for fitting the relationship between the scanning angle and the positioning error along the scanning direction and correcting the distortion of the edge of the field of view in the scanning direction includes: in, represents the fitting scanning angle, θ represents the actual scanning angle of the scanning mirror in the instrument, a represents the fitting coefficient, and a n Represents the fitting coefficients of the n-degree polynomial.

7. The method for geo-positioning of ultra-wideband satellite images according to claim 6, characterized in that: The method for repositioning the image after correcting the scanning mirror error comprises: in, 8. The method for geo-positioning of ultra-wideband satellite images according to any one of claims 1 to 7, characterized in that: The method for iterating the second geometric parameter comprises: The along-track error and the cross-track error of the second ultra-wide-width instrument image are counted, and the iteration is stopped when the deviation of the along-track error and the cross-track error statistic is less than 0.1 pixel.

9. A geographic positioning system for ultra-wideband satellite images, characterized in that: The system comprises: A data acquisition module, used for acquiring satellite data; Positioning module, used for ideal positioning of the instrument; Positioning accuracy test module, used to test the positioning accuracy of the instrument; The calibration module is used to calibrate the geometric parameters of the instrument image; Feedback module is used to iterate the geometric parameters.

10. A geo-positioning device for ultra-wideband satellite images, characterized in that the device include: one or more processors; A storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the geo-positioning device method for ultra-wide satellite images as described in any one of claims 1-8.

Images