Remote sensing constellation elastic information processing data flow design method

Abstract

The data flow design method for flexible information processing of remote sensing constellations belongs to the field of spacecraft system overall design technology. This method first calculates the data rate of different types of data content, including: (1) calculating the original image data rate based on detector size, quantity, and imaging frame rate; (2) calculating the small area windowing data rate based on window size and windowing data frame rate; (3) calculating the target point's adjacent area slice data rate based on threshold crossing rate; and (4) calculating the target trajectory information data rate based on single target trajectory information and target quantity. Then, the data transmission content is flexibly configured, and information overlap strategies at different levels are formulated. This enables dual-satellite information fusion for target positioning and tracking tasks under different link transmission capacity constraints. For randomly triggered multi-target tracking tasks, the data transmission content is adaptively adjusted according to link margin, enabling dual-satellite positioning and tracking under different levels of information fusion processing conditions.

Description

Technical Field

[0001] This invention relates to a data flow design method for flexible information processing of remote sensing constellations, belonging to the field of overall spacecraft system design technology. Background Technology

[0002] Remote sensing constellations consist of two or more remote sensing satellites. When performing positioning and tracking tasks on targets of interest, it is necessary to fuse the observation data from two satellites to generate a three-dimensional target trajectory. Traditional remote sensing constellations transmit image data to the ground, where ground application systems perform data fusion processing. To meet timeliness requirements, remote sensing constellations also need to have the ability to transmit data between satellites and fuse data. The increased observation area and imaging quality of remote sensing satellites have led to a larger volume of raw image data, increasing the demands on data transmission link capabilities. In addition, for multi-target missions, it is necessary to plan the division of information processing tasks between the remote sensing satellites themselves and the ground, and randomly triggered missions place flexible demands on link transmission capabilities. Summary of the Invention

[0003] The technical problem solved by this invention is to overcome the shortcomings of the prior art and provide a data flow design method for flexible information processing of remote sensing constellations. This method solves the problem of designing inter-satellite or satellite-to-ground transmission data content under different link bandwidth constraints when remote sensing satellite constellations perform target positioning and tracking tasks.

[0004] The technical solution of this invention is: a data stream design method for elastic information processing of remote sensing constellations, comprising:

[0005] Calculate the raw image data rate based on the detector parameters in the remote sensing constellation;

[0006] Calculate the local area windowed data rate based on the detector's windowing parameters;

[0007] Calculate the slice data rate of the area near the target point based on the detector parameters;

[0008] Calculate the target trajectory information data rate based on the target information;

[0009] Based on the original image data rate, the local area windowing data rate, the target point's adjacent area slice data rate, and the target trajectory information data rate, the data transmission content can be flexibly configured, and different levels of information overlap strategies can be formulated.

[0010] Furthermore, the original image data rate is D1 = N × P × B × f; where N, P, B, and f are the number of detectors, the number of pixels per detector, the number of quantization bits, and the imaging frame rate, respectively.

[0011] Furthermore, the local area windowing data rate is D2 = N. c ×f c ×B; where Nc f c B and B represent the window size, window data frame rate, and quantization bit depth, respectively.

[0012] Furthermore, the slice data rate of the target point's neighborhood is D3 = N × P × B × f × E × P t Among them, N, P, B, f, E, P t These are the number of detectors, the number of pixels per detector, the number of quantization bits, the imaging frame rate, the threshold rate, and the size of a single slice.

[0013] Furthermore, the target trajectory information data rate is D4 = P m ×N m ×f; where P m N m f and f represent the amount of trajectory information data for a single target, the number of targets, and the imaging frame rate, respectively.

[0014] Furthermore, the flexible configuration of data transmission content and the formulation of information overlap strategies at different levels include: calculating the data rate transmission requirements S1 to S5 at different levels: S1 = D1, S2 = D2 + D3, S3 = D2, S4 = D3, S5 = D4.

[0015] Furthermore, the formulation of information overlap strategies at different levels includes:

[0016] First strategy: When S s When S1 is greater than or equal to 1, pixel-level information fusion of the entire image is completed;

[0017] Second strategy: When S2 < S s When S1 is less than or equal to 1, pixel-level information fusion is performed for the region of interest and the target of interest.

[0018] Third strategy: When S3 < S s When S2 is less than or equal to 2, pixel-level information fusion is performed for the region of interest.

[0019] Fourth strategy: When S4 < S s When S3 is less than or equal to 3, pixel-level information fusion is performed for the target of interest.

[0020] Fifth strategy: When S5 < S s When the value is ≤S4, information-level information fusion is completed for the target of interest.

[0021] Furthermore, the detector parameters in the remote sensing constellation include detector size, number, and imaging frame rate; the detector windowing parameters include window size and windowing data frame rate; the detector parameters include threshold crossing rate; and the target information includes single target trajectory information and target quantity.

[0022] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the remote sensing constellation elastic information processing data stream design method.

[0023] A remote sensing constellation flexible information processing data stream design device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the remote sensing constellation flexible information processing data stream design method.

[0024] The advantages of this invention compared to the prior art are:

[0025] This invention discloses a data stream design method for flexible information processing of remote sensing constellations. By designing the information transmission content between satellites and ground stations and between satellites, it enables the fusion of information between two satellites to perform target positioning and tracking tasks under different link transmission capacity constraints. For randomly triggered multi-target tracking tasks, the data transmission content is adaptively adjusted according to link margin, enabling dual-satellite positioning and tracking under different levels of information fusion processing. Attached Figure Description

[0026] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0027] Figure 1 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0028] To better understand the above technical solutions, the technical solutions of this application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of this application and the specific features in the embodiments are detailed descriptions of the technical solutions of this application, rather than limitations on the technical solutions of this application. In the absence of conflict, the embodiments of this application and the technical features in the embodiments can be combined with each other.

[0029] The following description, in conjunction with the accompanying drawings, further details the design method for the elastic information processing data stream of remote sensing constellations provided in this application. Specific implementation methods may include (e.g.) Figure 1 As shown):

[0030] (1) Calculate the raw image data rate based on detector size, quantity, imaging frame rate, etc.;

[0031] (2) Calculate the small area window data rate based on window size, window data frame rate, etc.

[0032] (3) Calculate the slice data rate of the area near the target point based on the threshold rate, etc.

[0033] (4) Calculate the target trajectory information data rate based on single target trajectory information, number of targets, etc.

[0034] (5) Then, the data transmission content is configured flexibly, and information overlap strategies are formulated for different levels.

[0035] Specifically, the steps include the following:

[0036] Step 1: Calculate the raw image data rate D1 based on the number of detectors N, the number of pixels per detector P, the quantization bit depth B, and the imaging frame rate f.

[0037] D1=N×P×B×f

[0038] Step 2: Based on the window opening size N c Windowing data frame rate f c The quantization bit depth B is used to calculate the windowed image data rate D2.

[0039] D2 = N c ×f c ×B

[0040] Step 3: Based on the number of detectors N, the number of pixels per detector P, the quantization bit depth B, the imaging frame rate f, the threshold rate E, and the size of a single slice P t Calculate the slice image data rate D3.

[0041] D3=N×P×B×f×E×P t

[0042] Step 4: Based on the data volume P of a single target trajectory information m Target quantity N m The imaging frame rate f is used to calculate the data rate D4 for the target trajectory information.

[0043] D4 = P m ×N m ×f

[0044] Step 5: Calculate the data rate transmission requirements for different levels.

[0045] S1 = D1

[0046] S2 = D2 + D3

[0047] S3 = D2

[0048] S4 = D3

[0049] S5 = D4

[0050] Step Six: Based on the data transmission link margin Ss Develop corresponding information fusion strategies.

[0051]

[0052] The solution provided in the embodiments of this application includes:

[0053] Example 1:

[0054] This embodiment discloses a data flow design method for flexible information processing of remote sensing constellations. To verify this method, a remote sensing satellite is selected as the main research object. The data rates for inter-satellite and satellite-to-ground data transmission are calculated, and an information fusion strategy is formulated. The basic parameters of the satellite are shown in the table below.

[0055] Input numerical values Number of detectors N 80 Number of pixels per detector P 4000000 Quantization bits B 12bit Imaging frame rate f 4Hz Threshold rate E 1e-6 <![CDATA[Single slice size P t > 20×20 <![CDATA[Single target trajectory information data volume P m > 10000bit <![CDATA[Target quantity N m > 100

[0056] Step 1: Calculate the raw image data rate D1 based on the number of detectors N, the number of pixels per detector P, the quantization bit depth B, and the imaging frame rate f.

[0057] D1=N×P×B×f=80×4000000×12×4=80*4000000*12*4=15360000000bps=15.36Gbps

[0058] Step 2: Based on the window opening size N c Windowing data frame rate f c The quantization bit depth B is used to calculate the windowed image data rate D2.

[0059] D2 = N c ×f c ×B=3000000×4×12=144000000bps=144Mbps

[0060] Step 3: Based on the number of detectors N, the number of pixels per detector P, the quantization bit depth B, the imaging frame rate f, the threshold rate E, and the size of a single slice P t Calculate the slice image data rate D3.

[0061] D3=N×P×B×f×E×P t =80×4000000×12×4×1e-6×20×20=6144000bps=6.144Mbps

[0062] Step 4: Based on the data volume P of a single target trajectory information m Target quantity N m The imaging frame rate f is used to calculate the data rate D4 for the target trajectory information.

[0063] D4 = P m ×N m×f=10000*100*4=4000000bps=4Mbps

[0064] Step 4: Calculate the data rate transmission requirements for different levels.

[0065] S1 = D1 = 15.36 Gbps

[0066] S2 = D2 + D3 = 150.144 Mbps

[0067] S3 = D2 = 144Mbps

[0068] S4 = D3 = 6.144 Mbps

[0069] S5 = D4 = 4Mbps

[0070] Step 5: Based on the data transmission link margin S s Develop corresponding information fusion strategies.

[0071]

[0072] This application provides a computer-readable storage medium storing computer instructions that, when executed on a computer, cause the computer to perform... Figure 1 The method described.

[0073] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0074] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0075] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0076] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0077] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0078] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

[0079] The contents not described in detail in this specification are common knowledge to those skilled in the art.

Claims

1. A data stream design method for flexible information processing of remote sensing constellations, characterized in that, include: Calculate the raw image data rate based on the detector parameters in the remote sensing constellation; Calculate the local area windowed data rate based on the detector's windowing parameters; Calculate the slice data rate of the area near the target point based on the detector parameters; Calculate the target trajectory information data rate based on the target information; Based on the original image data rate, the local area windowing data rate, the target point's adjacent area slice data rate, and the target trajectory information data rate, the data transmission content can be flexibly configured, and different levels of information overlap strategies can be formulated.

2. The remote sensing constellation flexible information processing data stream design method according to claim 1, characterized in that, The original image data rate is D1 = N × P × B × f; where N, P, B, and f are the number of detectors, the number of pixels per detector, the number of quantization bits, and the imaging frame rate, respectively.

3. The remote sensing constellation flexible information processing data stream design method according to claim 1, characterized in that, The local area window opening data rate is D2=N c ×f c ×B; where N c f c B and B represent the window size, window data frame rate, and quantization bit depth, respectively.

4. The remote sensing constellation flexible information processing data stream design method according to claim 1, characterized in that, The slice data rate of the area near the target point is D3 = N×P×B×f×E×P t Among them, N, P, B, f, E, P t These are the number of detectors, the number of pixels per detector, the number of quantization bits, the imaging frame rate, the threshold rate, and the size of a single slice.

5. The remote sensing constellation flexible information processing data stream design method according to claim 1, characterized in that, The target trajectory information data rate is D4= P m ×N m ×f; where P m N m f and f represent the amount of trajectory information data for a single target, the number of targets, and the imaging frame rate, respectively.

6. The remote sensing constellation flexible information processing data stream design method according to claim 1, characterized in that, The flexible configuration of data transmission content and the formulation of information overlap strategies at different levels include: calculating the data rate transmission requirements S1~S5 at different levels: S1=D1, S2=D2+D3, S3=D2, S4=D3, S5=D4, where D1 is the original image data rate, D2 is the local area windowing data rate, D3 is the target point's adjacent area slice data rate, and D4 is the target trajectory information data rate.

7. The remote sensing constellation flexible information processing data stream design method according to claim 6, characterized in that, The formulation of information overlap strategies at different levels includes: First strategy: When S s When S1 is greater than or equal to 1, pixel-level information fusion of the entire image is completed; Second strategy: When S2 < S s When S1 is less than or equal to 1, pixel-level information fusion is performed for the region of interest and the target of interest. Third strategy: When S3 < S s When S2 is less than or equal to 2, pixel-level information fusion is performed for the region of interest. Fourth strategy: When S4 < S s When S3 is less than or equal to 3, pixel-level information fusion is performed for the target of interest. Fifth strategy: When S5 < S s When S4 is less than or equal to 4, information-level information fusion is completed for the target of interest. S s This represents the margin for data transmission links.

8. The remote sensing constellation flexible information processing data stream design method according to claim 1, characterized in that, The detector parameters in the remote sensing constellation include detector size, number, and imaging frame rate; the detector windowing parameters include window size and windowing data frame rate; the detector parameters include threshold crossing rate; and the target information includes single target trajectory information and target quantity.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 8.

10. A remote sensing constellation flexible information processing data stream design device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 8.

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