Space radiation real-time monitoring method and system based on transient response of star sensor

Abstract

The present application relates to a space radiation monitoring method and system, in particular to a space radiation real-time monitoring method and system based on a star sensor transient response, which solves the technical problem that a special space radiation detector is high in cost, large in size and difficult to be deployed in a satellite constellation scale. The present application directly uses a star sensor which is necessary for a spacecraft to detect space radiation, converts a radiation transient signal in a starry sky image collected by the star sensor into a detection signal directly reflecting a space radiation environment, so that the monitoring of the space radiation is realized without increasing an additional hardware load and changing an existing satellite platform configuration. Meanwhile, through the cooperative networking and data fusion of multiple satellites in a constellation, synchronous radiation data of multiple space discrete points can be obtained, a three-dimensional distribution diagram of radiation intensity in a space region and dynamic evolution information thereof can be obtained in real time, and global and rapid perception of the space radiation environment is realized.

Description

Technical Field

[0001] This invention relates to space radiation monitoring methods and systems, specifically to a real-time space radiation monitoring method and system based on the transient response of a star sensor. Background Technology

[0002] High-energy charged particles such as protons, electrons, and heavy ions in space pose a continuous and serious threat to the electronic systems, structural materials, and health of astronauts, and are core environmental factors affecting the reliability and safety of space missions. Traditional methods rely on dedicated radiation detectors (such as semiconductor detectors and scintillator detectors) to monitor space radiation generated by high-energy charged particles. While these methods offer high accuracy, their inherent limitations, such as high cost, large size, and high power consumption, make large-scale, dense deployment difficult in today's rapidly developing low-cost satellite constellations.

[0003] In contrast, star sensors, as essential attitude determination tools for spacecraft, rely heavily on CMOS image sensors, whose core imaging units are extremely sensitive to space radiation particles passing through them. Particle ionization produces noticeable tracks on the pixel array, manifesting as white transient bright spots or lines in star images acquired by star sensors (i.e., single-event transient, SET). However, in conventional star image processing workflows, these valuable transient signals have long been considered harmful noise and actively removed, making them difficult to utilize effectively. Summary of the Invention

[0004] The purpose of this invention is to solve the technical problems of high cost and large size of dedicated radiation detectors, which make them difficult to deploy on a large scale in satellite constellations, and to provide a method and system for real-time monitoring of space radiation based on the transient response of star sensors.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A method for real-time monitoring of space radiation based on the transient response of a star sensor, characterized by the following steps:

[0007] Step 1: Utilize K star sensors deployed on satellites at different space locations to continuously acquire data T during the same time period. i The initial starry sky image is taken and preprocessed to obtain K sets of starry sky images, where K and T are... i Both and i are integers, and K≥1, T i ≥3, i=1, 2, ..., K;

[0008] Step 2: Based on the image sequence difference method, detect moving targets in the K sets of starry sky images respectively, and obtain the number of moving targets in the K sets of starry sky images;

[0009] Step 3: Binarize each frame of the starry sky image in the K sets of starry sky images, and then extract the potential signal region based on the binarization result to obtain the number of potential signal regions in each frame of the starry sky image in the K sets of starry sky images.

[0010] Step 4: Based on the number of moving targets in each set of starry sky images and the number of potential signal regions in each frame of starry sky images, calculate T for each set of starry sky images. i The number of transient radiation signals in a frame of starry sky image;

[0011] Step 5: Based on T in each set of starry sky images i The number of transient radiation signals in a frame of star image, the physical parameters of the corresponding star sensors, and the radiation geometry model are used to calculate the spatial positions T of the K star sensors. i Particle fluence rate at each moment;

[0012] Step 6: Based on the spatial location of the K star sensors and their T... i The particle fluence rate at each moment is used to reconstruct a three-dimensional distribution map of spatial radiation intensity through a spatial interpolation algorithm, thus enabling real-time monitoring of spatial radiation.

[0013] Further, in step 5, the particle flux rate is calculated using the following formula:

[0014]

[0015] Where Φ is the particle fluence rate, N is the number of transient radiation signals, G is the geometric factor corresponding to the radiation geometry model of the star sensor, and S det Let t be the physical detection area of ​​the image sensor in the star sensor, and Δt be the single-frame image integration time of the image sensor in the star sensor.

[0016] Further, in step 4, the number of radiated transient signals is calculated using the following formula:

[0017] N=MH

[0018] Where M represents the number of potential signal regions in the starry sky image, and H represents the number of moving targets in the starry sky image set to which the starry sky image belongs.

[0019] Furthermore, step 2 specifically involves:

[0020] Step 2.1: Perform pairwise differences on two adjacent frames of starry sky images in each set of starry sky images, and obtain the T value for each set of starry sky images using the following formula. i -1 frame difference image:

[0021] D=|G t -G t-1 |

[0022] Where D represents the difference image, G t G t-1 Let T represent the starry sky images at frame t and frame (t-1) respectively, where 1 ≤ t ≤ T. i ;

[0023] Step 2.2: Set a moving target threshold, and adjust the T value for each set of starry sky images based on the moving target threshold. i The -1 frame difference image is binarized, and the moving target masks of K sets of starry sky images are obtained based on the binarization results, as shown in the following formula:

[0024] M motion =(D1>L)∩(D2>L)∩…∩(D Ti-1 >L)

[0025] Among them, M motion Represents the moving target mask, (D1,D2,…,D Ti-1 )∈D, D1, D2, ..., D Ti-1 These represent the first and second frames of the starry sky image, the second and third frames of the starry sky image, ..., the Tth frame of the starry sky image. i The difference image between frame -1 and the starry sky image of frame T, where L is the moving target threshold;

[0026] Step 2.3: Based on the moving target mask of the K sets of starry sky images, detect moving targets in the K sets of starry sky images, and then count the number of moving targets in the K sets of starry sky images respectively.

[0027] Furthermore, step 3 specifically involves:

[0028] Step 3.1: Using the Otsu method, calculate the adaptive threshold of each frame of the starry sky image in the K sets of starry sky images respectively, and then multiply the adaptive threshold by the preset scaling factor k to obtain the adaptive signal threshold of each frame of the starry sky image in the K sets of starry sky images, where k≥1;

[0029] Step 3.2: Binarize the corresponding starry sky images according to the adaptive signal threshold of each frame of starry sky images in the K sets of starry sky images to obtain the binary images of each frame of starry sky images in the K sets of starry sky images.

[0030] Step 3.3: Based on the binary image of each frame of starry sky image in the K sets of starry sky image sets, obtain the corresponding signal regions respectively, and then count the number of signal regions in the binary image whose area is within the preset pixel area range, and obtain the number of potential signal regions in each frame of starry sky image in the K sets of starry sky image sets respectively.

[0031] The present invention also provides a space radiation real-time monitoring system based on the transient response of star sensors, for implementing the above-mentioned space radiation real-time monitoring method based on the transient response of star sensors. Its special feature is that it includes K distributed detection terminals deployed on satellites at different space locations, and a ground data center, wherein K is an integer and K≥1;

[0032] The distributed detection terminal includes a star sensor and an on-board processing unit. The output of the star sensor is connected to the input of the on-board processing unit to acquire initial images of the starry sky.

[0033] The output of the on-board processing unit is connected to the input of the ground data center to preprocess the initial star image and calculate the particle fluence rate at the spatial location of the star sensor.

[0034] The ground data center is used to reconstruct a three-dimensional distribution map of spatial radiation intensity based on the spatial locations of K star sensors and their particle fluence rates.

[0035] Furthermore, the on-board processing unit includes an image preprocessing module, a moving target recognition module, a radiation transient signal extraction module, and a parameter calculation module;

[0036] The input end of the image preprocessing module is connected to the output end of the star sensor, and the output end is connected to the input end of the moving target recognition module and the first input end of the radiation transient signal extraction module, respectively. The image preprocessing module is used to preprocess the initial starry sky image.

[0037] The output of the moving target recognition module is connected to the second input of the radiation transient signal extraction module, and is used to identify moving targets and obtain the number of moving targets.

[0038] The output of the radiation transient signal extraction module is connected to the input of the parameter calculation module. It is used to identify potential signal regions and, in conjunction with the identification of moving targets, to obtain the number of radiation transient signals. The parameter calculation module is used to calculate the particle flux rate.

[0039] Furthermore, the ground data center includes a data aggregation and verification module, a 3D reconstruction and visualization module, and a situation analysis and early warning module connected in sequence;

[0040] The input end of the data collection and verification module is connected to the output end of the K parameter calculation modules respectively, and is used to receive and verify multi-source satellite data;

[0041] The three-dimensional reconstruction and visualization module is used to reconstruct and draw a three-dimensional distribution map of spatial radiation intensity, and the situation analysis and early warning module is used to analyze the dynamic changes of radiation distribution based on the three-dimensional distribution map of spatial radiation intensity, and issue early warnings for areas or events that exceed the safety threshold.

[0042] Furthermore, the ground data center communicates with the K distributed detection terminals via inter-satellite links or satellite-to-ground data links.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. The space radiation real-time monitoring method based on the transient response of star sensors provided by this invention directly utilizes the star sensors that are essential for spacecraft to detect space radiation. It converts the transient radiation signals in the star images collected by the star sensors into detection signals that directly reflect the space radiation environment. Thus, without adding any additional hardware payload or changing the existing satellite platform configuration, the satellite constellation uses star sensors to transform into a distributed, real-time response giant space radiation monitoring network. It can achieve large-scale deployment of space radiation detectors without developing and launching any dedicated radiation payloads.

[0045] 2. The space radiation real-time monitoring method based on the transient response of star sensors provided by this invention can obtain synchrotron radiation data of hundreds or even thousands of discrete points in space through the collaborative networking and data fusion of multiple satellites in the constellation. This completely changes the traditional single-point, serial detection mode and can obtain the three-dimensional distribution map of radiation intensity in the space area and its dynamic evolution information in real time. It realizes global and rapid situational awareness of the space radiation environment and provides data support and decision-making basis for the on-orbit radiation risk management of spacecraft.

[0046] 3. The space radiation real-time monitoring system based on the transient response of star sensors provided by this invention adopts a distributed deployment of detection terminals, which has redundancy characteristics. The failure of a single or a small number of nodes does not affect the global monitoring function, and the overall system reliability is much higher than that of a single high-performance dedicated detector. Attached Figure Description

[0047] Figure 1 This is a system schematic diagram according to an embodiment of the present invention;

[0048] Figure 2 This is a schematic diagram of obtaining a set of starry sky images in step 1 of an embodiment of the present invention, wherein (a), (b), and (c) are three starry sky images, respectively;

[0049] Figure 3 This is a schematic diagram of obtaining the moving target in step 2 of an embodiment of the present invention, wherein (a), (b), and (c) are respectively Figure 2 Schematic diagrams of the moving targets in (a), (b), and (c);

[0050] Figure 4 This is a schematic diagram of obtaining the radiation transient signal in step 4 of an embodiment of the present invention, wherein (a), (b), and (c) are respectively Figure 2Schematic diagrams of the radiated transient signals in (a), (b), and (c). Detailed Implementation

[0051] The present invention provides a more detailed description of a real-time space radiation monitoring method and system based on the transient response of a star sensor, in conjunction with the accompanying drawings and specific embodiments. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the invention and are not intended to limit the scope of protection of the invention.

[0052] A real-time space radiation monitoring system based on the transient response of a star sensor, such as Figure 1 As shown, the system includes K distributed detection terminals deployed on satellites at different space locations, and a ground data center, where K is an integer and K≥1. The ground data center communicates with the K distributed detection terminals via inter-satellite links or satellite-to-ground data links.

[0053] The distributed detection terminal includes a star sensor and an on-board processing unit. The on-board processing unit comprises an image preprocessing module, a moving target recognition module, a radiation transient signal extraction module, and a parameter calculation module. The star sensor acquires initial images of the starry sky, and the on-board processing unit preprocesses these images and calculates the real-time particle fluence rate at the star sensor's location. The output of the star sensor is connected to the input of the image preprocessing module, which in turn connects to the inputs of the moving target recognition module and the first input of the radiation transient signal extraction module. The image preprocessing module preprocesses the initial starry sky images, including format conversion and preliminary signal suppression. The output of the moving target recognition module is connected to the second input of the radiation transient signal extraction module, performing image sequence differencing and morphological operations to generate and apply a moving target mask, thereby identifying moving targets and determining their number. The output of the radiation transient signal extraction module is connected to the input of the parameter calculation module, performing segmentation and connected component analysis on the starry sky images to identify potential signal regions and, in conjunction with moving targets, to identify radiation transient signals. The parameter calculation module incorporates the physical parameters and radiation geometry model of the star sensor to calculate the particle fluence rate.

[0054] The ground-based data center comprises a data collection and verification module, a 3D reconstruction and visualization module, and a situation analysis and early warning module, connected in sequence. It is used to reconstruct a 3D distribution map of space radiation intensity based on the spatial locations of K satellite sensors and their real-time particle fluence rates. The input terminals of the data collection and verification module are connected to the output terminals of the K parameter calculation modules to receive and verify multi-source satellite data. The 3D reconstruction and visualization module reconstructs and draws the 3D distribution map of space radiation intensity, while the situation analysis and early warning module analyzes the dynamic changes in radiation distribution based on the 3D distribution map and issues early warnings for areas or events exceeding safety thresholds.

[0055] This embodiment also provides a real-time space radiation monitoring method based on the transient response of a star sensor, employing the aforementioned real-time space radiation monitoring system based on the transient response of a star sensor, and including the following steps:

[0056] Step 1: Using K star sensors deployed on satellites at different locations in space, acquire three consecutive initial starscape images simultaneously, and preprocess them to obtain K sets of starscape image sets. One set of starscape image sets is shown below. Figure 2 As shown. In other embodiments, if the initial image of the starry sky is a color image, it needs to be converted into a grayscale image during preprocessing.

[0057] Step 2: Based on the image sequence difference method, detect moving targets in K sets of starry sky images respectively, and obtain the number of moving targets in the K sets of starry sky images. The moving targets are stars or spacecraft. Step 2 specifically involves:

[0058] Step 2.1: Perform pairwise difference analysis on two adjacent frames of starry sky images in each set of starry sky images, and obtain the two difference images of each set of starry sky images using the following formula:

[0059] D1=|G t -G t-1 |,D2=|G t+1 -G t |

[0060] Where D1 and D2 represent the difference images between the first and second frame starry sky images, and between the second and third frame starry sky images, respectively, and G t-1 G t G t+1 These represent the first, second, and third frames of the starry sky image, respectively.

[0061] Step 2.2: Set a moving target threshold. Binarize the two-frame difference images of each starry sky image set according to the moving target threshold, and obtain the moving target masks for K starry sky image sets based on the binarization results, as shown in the following formula:

[0062] Mmotion =(D1>L)∩(D2>L)

[0063] Among them, M motion This represents the moving target mask, and L is the moving target threshold.

[0064] Binarization of the difference image specifically involves setting the gray values ​​of pixels with gray values ​​greater than the moving target threshold L to 1, and setting the gray values ​​of pixels with gray values ​​less than or equal to the moving target threshold L to 0.

[0065] Step 2.3: Based on the moving target mask of the K sets of starry sky images, detect moving targets in the K sets of starry sky images, and then count the number of moving targets in the K sets of starry sky images respectively.

[0066] In step 2.3, connected component analysis is used to detect moving targets. Each pixel region with a grayscale value of 1 in the moving target mask is considered as a moving target. Figure 2 Moving targets are labeled in the three starry sky images shown, resulting in the following: Figure 3 The schematic diagram of the moving targets shown indicates that there are 7 moving targets in this set of starry sky images.

[0067] Step 3: Binarize each frame of the starry sky image in the K sets of starry sky images, and then extract the potential signal region based on the binarization result to obtain the number of potential signal regions in each frame of the K sets of starry sky images. Specifically:

[0068] Step 3.1: Using the Otsu method (maximum inter-class variance method), calculate the adaptive threshold of each frame of the starry sky image in the K sets of starry sky images. Then multiply the adaptive threshold by a preset scaling factor k to obtain the adaptive signal threshold of each frame of the starry sky image in the K sets of starry sky images, where k≥1. In this embodiment, k=1.2.

[0069] Step 3.2: Binarize the corresponding starry sky images according to the adaptive signal threshold of each frame of starry sky images in the K sets of starry sky images to obtain the binary images of each frame of starry sky images in the K sets of starry sky images.

[0070] Step 3.3: Based on the binary images of each frame of the starry sky image set in the K sets of starry sky images, obtain the corresponding signal regions. Then, count the number of signal regions in the binary images whose area falls within a preset pixel area range, and obtain the number of potential signal regions for each frame of the starry sky image in the K sets of starry sky images. For example, Figure 2 The number of potential signal regions in the three starry sky images shown are 405, 550, and 440, respectively.

[0071] In step 3.1, the adaptive signal threshold is increased by a preset scaling factor k greater than or equal to 1 to reduce false detections; in step 3.3, each pixel region with a gray value of 1 in the binary image is a signal region. By filtering by the area of ​​the signal region, the interference of thermal pixels generated by cumulative irradiation on the results can be eliminated.

[0072] Step 4: Based on the number of moving targets in each set of starry sky images and the number of potential signal regions in each frame of starry sky images, calculate the number of transient radiation signals in the T frames of starry sky images in each set of starry sky images using the following formula:

[0073] N=MH

[0074] Where N is the number of transient radiation signals, M is the number of potential signal regions in the star image, and H is the number of moving targets in the star image set to which the star image belongs.

[0075] Based on the above formula, the following can be calculated: Figure 2 The number of transient radiation signals obtained after excluding moving targets in the three starscape images shown are 398, 543, and 433, respectively, and they are labeled in [the image description]. Figure 2 In the starry sky image shown, the following is obtained: Figure 4 The diagram shows a transient radiation signal.

[0076] Step 5: Based on the number of transient radiation signals in the three frames of star images in each set of star images, the physical parameters of the corresponding star sensors, and the radiation geometry model, calculate the particle fluence rate at the three time points of the spatial locations of the K star sensors using the following formulas:

[0077]

[0078] Where Φ is the particle fluence rate, G is the geometric factor corresponding to the radiation geometry model of the star sensor, and Δt is the single-frame image integration time of the image sensor in the star sensor; S det S represents the physical detection area of ​​the image sensor in the star sensor. det =N x ·N y ·(p size ) 2 N x N y These represent the number of rows and columns of the image sensor in the star sensor, p size This refers to the physical size of a single pixel in the image sensor of a star sensor.

[0079] In this embodiment, the radiation geometry model of the star sensor is a model for a planar detector with unidirectional detection under an isotropic radiation field with a solid angle of 4π, and its geometric factor G = 1 / 4. The number of rows and columns of the image sensor in the star sensor are 1000 and 1000 respectively, the physical size of a single pixel is 6.5 μm, and the integration time of a single frame image is 10 ms. Substituting the above parameters and the number of transient radiation signals obtained in step 4 into the above formula, the following can be calculated: Figure 2 The real-time particle flux rates of the three starry sky images shown are 34793.39 ion / cm / s, 46611.57 ion / cm / s, and 37190.08 ion / cm / s, respectively.

[0080] Step 6: Based on the spatial locations of the K star sensors and their particle fluence rates at three time points, reconstruct a three-dimensional distribution map of spatial radiation intensity using a spatial interpolation algorithm to complete real-time monitoring of spatial radiation.

[0081] This invention provides a real-time space radiation monitoring method and system based on the transient response of star sensors. Addressing the problems of high cost, large size, and difficulty in large-scale deployment within satellite constellations of existing dedicated radiation detectors, this invention transforms transient radiation particle signals (such as bright spots / lines) traditionally considered noise in on-orbit images from star sensors into effective detection signals. First, multiple frames of starscape images are acquired using the star sensor and preprocessed. Then, moving targets (stars, spacecraft, etc.) are identified through continuous frame differencing and logical operations. Adaptive signal thresholding is used for binary segmentation to extract potential signal regions, and area filtering is used to eliminate interference. Next, the number of potential signal regions is combined with the number of moving targets to confirm the number of transient radiation signals. Then, the particle fluence rate is calculated based on the number of transient radiation signals, the physical parameters of the star sensor, and the radiation geometry model. Finally, the three-dimensional distribution of space radiation is reconstructed through constellation network data fusion and spatial interpolation. This invention requires no additional payload, transforming existing satellite constellation star sensors into a distributed monitoring network. It offers advantages such as low cost, wide coverage, high spatiotemporal resolution, and strong robustness, providing real-time, global situational awareness for spacecraft radiation risk management and space weather monitoring.

Claims

1. A method for real-time monitoring of space radiation based on the transient response of a star sensor, characterized in that, Includes the following steps: Step 1: Utilize K star sensors deployed on satellites at different space locations to continuously acquire data T during the same time period. i The initial starry sky image is taken and preprocessed to obtain K sets of starry sky images, where K and T are... i Both and i are integers, and K≥1, T i ≥3, i=1, 2, ..., K; Step 2: Based on the image sequence difference method, detect moving targets in the K sets of starry sky images respectively, and obtain the number of moving targets in the K sets of starry sky images; Step 3: Binarize each frame of the starry sky image in the K sets of starry sky images, and then extract the potential signal region based on the binarization result to obtain the number of potential signal regions in each frame of the starry sky image in the K sets of starry sky images. Step 4: Based on the number of moving targets in each set of starry sky images and the number of potential signal regions in each frame of starry sky images, calculate T for each set of starry sky images. i The number of transient radiation signals in a frame of starry sky image; Step 5: Based on T in each set of starry sky images i The number of transient radiation signals in a frame of star image, the physical parameters of the corresponding star sensors, and the radiation geometry model are used to calculate the spatial positions T of the K star sensors. i Particle fluence rate at each moment; Step 6: Based on the spatial location of the K star sensors and their T... i The particle fluence rate at each moment is used to reconstruct a three-dimensional distribution map of spatial radiation intensity through a spatial interpolation algorithm, thus enabling real-time monitoring of spatial radiation.

2. The method for real-time monitoring of space radiation based on the transient response of a star sensor according to claim 1, characterized in that, In step 5, the particle flux rate is calculated using the following formula: ； Where Φ is the particle fluence rate, N is the number of transient radiation signals, G is the geometric factor corresponding to the radiation geometry model of the star sensor, and S det Let t be the physical detection area of ​​the image sensor in the star sensor, and Δt be the single-frame image integration time of the image sensor in the star sensor.

3. The method for real-time monitoring of space radiation based on the transient response of a star sensor according to claim 2, characterized in that, In step 4, the number of radiated transient signals is calculated using the following formula: N=MH Where M represents the number of potential signal regions in the starry sky image, and H represents the number of moving targets in the starry sky image set to which the starry sky image belongs.

4. The method for real-time monitoring of space radiation based on the transient response of a star sensor according to claim 3, characterized in that, Step 2 is as follows: Step 2.1: Perform pairwise differences on two adjacent frames of starry sky images in each set of starry sky images, and obtain the T value for each set of starry sky images using the following formula. i -1 frame difference image: D=|G t -G t-1 | Where D represents the difference image, G t G t-1 Let T represent the starry sky images at frame t and frame (t-1) respectively, where 1 ≤ t ≤ T. i ; Step 2.2: Set a moving target threshold, and adjust the T value for each set of starry sky images based on the moving target threshold. i The -1 frame difference image is binarized, and the moving target masks of K sets of starry sky images are obtained based on the binarization results, as shown in the following formula: M motion =(D1>L)∩(D2>L)∩…∩(D Ti-1 >L) Among them, M motion Represents the moving target mask, (D1,D2,…,D Ti-1 )∈D, D1, D2, ..., D Ti-1 These represent the first and second frames of the starry sky image, the second and third frames of the starry sky image, ..., the Tth frame of the starry sky image. i The difference image between frame -1 and the starry sky image of frame T, where L is the moving target threshold; Step 2.3: Based on the moving target mask of the K sets of starry sky images, detect moving targets in the K sets of starry sky images, and then count the number of moving targets in the K sets of starry sky images respectively.

5. The method for real-time monitoring of space radiation based on the transient response of a star sensor according to claim 4, characterized in that, Step 3 specifically involves: Step 3.1: Using the Otsu method, calculate the adaptive threshold of each frame of the starry sky image in the K sets of starry sky images respectively, and then multiply the adaptive threshold by the preset scaling factor k to obtain the adaptive signal threshold of each frame of the starry sky image in the K sets of starry sky images, where k≥1; Step 3.2: Binarize the corresponding starry sky images according to the adaptive signal threshold of each frame of starry sky images in the K sets of starry sky images to obtain the binary images of each frame of starry sky images in the K sets of starry sky images. Step 3.3: Based on the binary image of each frame of starry sky image in the K sets of starry sky image sets, obtain the corresponding signal regions respectively, and then count the number of signal regions in the binary image whose area is within the preset pixel area range, and obtain the number of potential signal regions in each frame of starry sky image in the K sets of starry sky image sets respectively.

6. A real-time space radiation monitoring system based on the transient response of a star sensor, used to implement the real-time space radiation monitoring method based on the transient response of a star sensor as described in any one of claims 1-5, characterized in that: It includes K distributed detection terminals deployed on satellites at different space locations, and a ground data center, where K is an integer and K≥1; The distributed detection terminal includes a star sensor and an on-board processing unit. The output of the star sensor is connected to the input of the on-board processing unit to acquire initial images of the starry sky. The output of the on-board processing unit is connected to the input of the ground data center to preprocess the initial star image and calculate the particle fluence rate at the spatial location of the star sensor. The ground data center is used to reconstruct a three-dimensional distribution map of spatial radiation intensity based on the spatial locations of K star sensors and their particle fluence rates.

7. The space radiation real-time monitoring system based on the transient response of a star sensor according to claim 6, characterized in that: The on-board processing unit includes an image preprocessing module, a moving target recognition module, a radiation transient signal extraction module, and a parameter calculation module; The input end of the image preprocessing module is connected to the output end of the star sensor, and the output end is connected to the input end of the moving target recognition module and the first input end of the radiation transient signal extraction module, respectively. The image preprocessing module is used to preprocess the initial starry sky image. The output of the moving target recognition module is connected to the second input of the radiation transient signal extraction module, and is used to identify moving targets and obtain the number of moving targets. The output of the radiation transient signal extraction module is connected to the input of the parameter calculation module. It is used to identify potential signal regions and, in conjunction with the identification of moving targets, to obtain the number of radiation transient signals. The parameter calculation module is used to calculate the particle flux rate.

8. The space radiation real-time monitoring system based on the transient response of a star sensor according to claim 7, characterized in that: The ground data center includes a data collection and verification module, a 3D reconstruction and visualization module, and a situation analysis and early warning module connected in sequence. The input end of the data collection and verification module is connected to the output end of the K parameter calculation modules respectively, and is used to receive and verify multi-source satellite data; The three-dimensional reconstruction and visualization module is used to reconstruct and draw a three-dimensional distribution map of spatial radiation intensity, and the situation analysis and early warning module is used to analyze the dynamic changes of radiation distribution based on the three-dimensional distribution map of spatial radiation intensity, and issue early warnings for areas or events that exceed the safety threshold.

9. The space radiation real-time monitoring system based on the transient response of a star sensor according to any one of claims 6-8, characterized in that: The ground data center communicates with the K distributed detection terminals via inter-satellite links or satellite-to-ground data links.

Images