All-day star point extraction method, device and equipment considering atmospheric turbulence influence

Abstract

The embodiment of the invention discloses an all-time star point extraction method, device and equipment considering the influence of atmospheric turbulence. A specific embodiment of the method comprises the following steps: determining a star sensor main shaft initial direction according to a star sensor installation matrix; according to the initial orientation of the star sensor, the view field of the star sensor and the calibration parameters of the star sensor, fixed star position information is determined, and the fixed star position information is the position of the corresponding fixed star in the image plane; according to the fixed star position information, a star map frame sequence containing a preset frame number is collected, and each star map frame in the star map frame sequence corresponds to collection time; selecting each star map frame of a preset candidate frame number from the star map frame sequence as each star point frame to be extracted; and according to the to-be-extracted frame of each star point, determining the centroid position of the fixed star. According to the embodiment, all-day astronomical attitude determination and positioning requirements can be met, and the extraction accuracy of the mass center position of the star point is improved.

Description

TECHNICAL FIELD

[0001] Embodiments of the present disclosure relate to the field of computer technology, in particular to a day-and-night star point extraction method, device and equipment considering the influence of atmospheric turbulence. BACKGROUND

[0002] A star sensor is a pose determination device that takes stars as a reference base, and has the characteristics of autonomy, anti-interference and high precision, and is widely used in the field of aerospace. The main principle is to image stars through an image sensor combined with an optical system, and to solve the centroid position of the stars in the star map by using image processing methods, and then to calculate the position and attitude of itself. Therefore, accurately distinguishing and accurately solving the centroid coordinates of stars in the star map is the basis and premise for subsequent star map identification, star sensor self-checking and navigation parameter calculation. At present, when determining the centroid coordinates of stars, the commonly used method is to solve the centroid position of stars in the star map by using image processing methods.

[0003] However, when determining the centroid coordinates of stars in the day star map by using the above method, the following technical problems often exist:

[0004] Although the traditional star map processing method can eliminate noise to a certain extent and enhance the signal-to-noise ratio, the low signal-to-noise ratio and poor contrast of the star points in the day star map due to the strong background light eventually lead to a decrease in the accuracy of star point extraction; at the same time, the star image distortion and drift error caused by the influence of atmospheric turbulence seriously limit the accuracy and robustness of the single-frame star point extraction algorithm. SUMMARY

[0005] The summary part of the present disclosure is used to introduce the concepts in a brief form, which will be described in detail in the specific embodiments part. The summary part of the present disclosure is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0006] Some embodiments of the present disclosure propose a day-and-night star point extraction method, device and equipment considering the influence of atmospheric turbulence, to solve the technical problems mentioned in the background part.

[0007] In a first aspect, some embodiments of the present disclosure provide an all-weather star point extraction method considering the influence of atmospheric turbulence, the method comprising: determining an initial pointing direction of a star sensor main shaft according to a star sensor installation matrix; determining star position information according to the initial pointing direction of the star sensor main shaft, a field of view of the star sensor, and star sensor calibration parameters, wherein the star position information is the position of a corresponding star in an image plane; collecting a star image frame sequence comprising a preset number of frames, wherein each star image frame in the star image frame sequence corresponds to a collection time; selecting a preset number of candidate frames of star image frames from the star image frame sequence as star point extraction frames; and determining a star centroid position according to the star point extraction frames.

[0008] In a second aspect, some embodiments of the present disclosure provide an all-weather star point extraction device considering the influence of atmospheric turbulence, the device comprising: a first determination unit configured to determine an initial pointing direction of a star sensor main shaft according to a star sensor installation matrix; a second determination unit configured to determine star position information according to the initial pointing direction of the star sensor main shaft, a field of view of the star sensor, and star sensor calibration parameters, wherein the star position information is the position of a corresponding star in an image plane; a collection unit configured to collect a star image frame sequence comprising a preset number of frames, wherein each star image frame in the star image frame sequence corresponds to a collection time; a selection unit configured to select a preset number of candidate frames of star image frames from the star image frame sequence as star point extraction frames; and a third determination unit configured to determine a star centroid position according to the star point extraction frames.

[0009] In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; and a storage device having one or more programs stored thereon, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method described in any of the implementations of the first aspect.

[0010] In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect.

[0011] The above various embodiments of the present disclosure have the following beneficial effects: the all-weather star point extraction method of some embodiments of the present disclosure considering the influence of atmospheric turbulence can meet the all-weather astronomical positioning and positioning requirements, and improve the extraction accuracy of star point centroid position. Specifically, the reason for the low extraction accuracy of the star point centroid position is that although the traditional star map processing method can eliminate noise to a certain extent and enhance the signal-to-noise ratio, it is easy to cause the change of star point energy distribution, edge shift, and ultimately lead to the decline of star point extraction accuracy; at the same time, the star image distortion and drift error caused by the influence of atmospheric turbulence seriously limit the accuracy and robustness of the single-frame star point extraction algorithm. Based on this, the all-weather star point extraction method of some embodiments of the present disclosure considering the influence of atmospheric turbulence uses the star motion theory to predict the position of the star, so as to eliminate various pseudo-star point targets existing in the all-weather star map, and realize accurate identification of the star point. In practice, the star motion has certain regularity, and astronomers have made a star catalog containing the right ascension and declination information of the star through long-term observation. According to the star catalog, the celestial position of the star at any time can be accurately calculated, and the main shaft direction of the star sensor can be calculated by the inertial navigation equipment. Therefore, combined with the star catalog and the main shaft direction of the star sensor, the approximate position of the star point in the sensor image plane can be predicted. Although the star point position prediction can effectively narrow down the area where the star is located, for the same star map of a star, due to the influence of atmospheric turbulence, the received star energy between the sequence frames has obvious strength difference, which leads to the obvious randomness of the signal-to-noise ratio of the single-frame star map shot by the star sensor, and the star point extraction needs to be adaptively selected according to the signal-to-noise ratio of the star map. The frame with larger signal-to-noise ratio is selected to improve the success rate of star point extraction. According to the light intensity flicker effect, the present application adaptively selects a high signal-to-noise ratio star map, and uses the high signal-to-noise ratio star map for star point extraction, so as to improve the success rate of star point extraction. Although limited by the full well capacity of the sensor, the exposure time of the daytime star map cannot be prolonged, but if multiple short-exposure star maps are superimposed, the superimposed star map imaging is close to the long-time exposure integration effect, which can effectively overcome the random error of star point imaging caused by atmospheric turbulence and enhance the robustness of star image centroid position. The present application calculates the star point centroid position of multiple frames of star maps through the star point image plane motion equation, achieves the effect of multi-frame superposition of star maps, realizes the improvement of star point extraction robustness, and can well solve the problems of noise, low signal-to-noise ratio, and poor single-frame accuracy of the star map shot by the all-weather star sensor. BRIEF DESCRIPTION OF DRAWINGS

[0012] The above and other features, aspects, and advantages of the embodiments of the present disclosure will become more apparent with reference to the following specific embodiments when taken in conjunction with the accompanying drawings. Throughout the drawings, same or similar reference numerals are used to represent the same or similar elements. It should be understood that the drawings are schematic, and elements and elements are not necessarily drawn to scale.

[0013] Figure 1 is a flowchart of some embodiments of the all-weather star point extraction method according to the present disclosure;

[0014] Figure 2 is a schematic diagram of coordinate system conversion in the all-weather star point extraction method considering the influence of atmospheric turbulence according to the present disclosure;

[0015] Figure 3 is a graph of the relationship between the number of star map frames and the probability under different star map starlight intensity probability conditions;

[0016] Figure 4 is a schematic diagram of star point image plane motion;

[0017] Figure 5 is a structural schematic diagram of some embodiments of the all-weather star point extraction device considering the influence of atmospheric turbulence according to the present disclosure;

[0018] Figure 6 is a structural schematic diagram of an electronic device suitable for use to implement some embodiments of the present disclosure. DETAILED DESCRIPTION

[0019] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms, and should not be interpreted as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly and completely understood. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes, and are not intended to limit the scope of protection of the present disclosure.

[0020] In addition, it should be further noted that only parts related to the present invention are shown in the drawings for ease of description. The embodiments in the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0021] It should be noted that the concepts of "first", "second", etc. mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not intended to limit the order or interdependence of the functions performed by these devices, modules or units.

[0022] It should be noted that the adjectives "one", "multiple" mentioned in the present disclosure are illustrative and not limiting, and those skilled in the art should understand that unless otherwise explicitly stated in the context, it should be understood as "one or more".

[0023] The names of the messages or information exchanged between the devices in the embodiments of the present disclosure are only for illustrative purposes, and are not intended to limit the scope of these messages or information.

[0024] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0025] Figure 1A flowchart 101 is shown, illustrating some embodiments of the all-day star point extraction method considering the effects of atmospheric turbulence according to this disclosure. This all-day star point extraction method considering the effects of atmospheric turbulence includes the following steps:

[0026] Step 101: Determine the initial orientation of the star sensor's main axis based on the star sensor mounting matrix.

[0027] In some embodiments, the entity executing the all-weather star point extraction method, which takes into account the effects of atmospheric turbulence, can determine the initial orientation of the star sensor's principal axis based on the star sensor mounting matrix. The aforementioned star sensor mounting matrix can refer to the relative attitude relationship between the star sensor and the carrier. If the coordinate systems of the star sensor and the carrier are perfectly aligned, the mounting matrix is ​​an identity matrix; otherwise, a three-dimensional mounting matrix will appear. Similarly, the inertial navigation device's attitude refers to the mounting matrix of the inertial navigation device relative to the carrier.

[0028] like Figure 2 As shown, in the Earth's core Establish a celestial rectangular coordinate system centered on the celestial sphere. Then right ascension and declination are The coordinates of star S in the celestial rectangular coordinate system can be expressed as:

[0029] .

[0030] If the main axis of the sensor points to The roll attitude angle is Then the rotation matrix from the sensor image plane attitude angle to the celestial rectangular coordinate system. It can be:

[0031] .

[0032] Step 102: Determine the star position information based on the initial orientation of the star sensor's main axis, the star sensor's field of view, and the star sensor's calibration parameters.

[0033] In some embodiments, the execution entity can determine the star position information based on the initial orientation of the star sensor's principal axis, the star sensor's field of view, and the star sensor calibration parameters. The star position information refers to the position of the corresponding star in the image plane. The star sensor calibration parameters include the principal point coordinates, focal length, and pixel distortion correction parameters.

[0034] In some optional implementations of certain embodiments, the aforementioned execution entity can determine the star position information based on the initial pointing of the star sensor's main axis, the star sensor's field of view, and the star sensor's calibration parameters through the following steps:

[0035] The first step is to determine the star observation vector based on the star sensor rotation matrix. In practice, the... fixed stars The celestial spherical rectangular coordinate system coordinate of the fixed star can be expressed as , in combination with the star sensor rotation matrix The observation vector of the star in the sensor can be expressed as:

[0036] .

[0037] Secondly, the fixed star position information is determined according to the fixed star observation vector, the star sensor calibration parameter and the star sensor field of view. In practice, if the sensor image principal point coordinate is , the focal length is , and the pixel distortion correction is performed, the coordinate of the fixed star in the image plane can be:

[0038] .

[0039] It should be noted that the fixed star position can be accurately calculated by a fixed star catalog, and the star sensor pointing accuracy depends on the sensor accuracy such as a gyroscope, which can be controlled at the order of 30". If the star sensor field of view is and the corresponding pixel is 2048x2048, the field of view corresponding to each pixel is , and the prediction error accuracy of the star point position can be controlled within 10 pixels by determining the coordinate of the fixed star in the image plane by the above expression. Therefore, we can set the star point prediction area of the fixed star in the star map as a rectangular area with a center of and a side length of 20 pixels.

[0040] By extracting the fixed star in the specified area, the pseudo star points can be effectively removed, the star extraction accuracy and success rate can be greatly improved, and the image operation amount can be significantly reduced to improve the star map processing efficiency.

[0041] In step 103, a star map frame sequence containing a preset number of frames is collected according to the fixed star position information.

[0042] In some embodiments, the execution body can collect a star map frame sequence containing a preset number of frames. Each star map frame in the star map frame sequence corresponds to a collection time.

[0043] It should be noted that when the flicker index is 0.5, the probability that the received light intensity is less than 0.5 is 0.27, and greater than 1.5 ​Probability 0.18, and as the atmospheric turbulence intensity increases, the flicker index increases, the probability of weak light intensity received by the sensor is greater, which indicates that it is necessary to select frames for the sequence frame star map. Assuming that m frames of short exposure sequence star maps are continuously captured, the probability that the light intensity of a single frame star map is greater than is p, then the probability that at least n frames of star maps in m frames of star maps have energy greater than is expressed as:

[0044]

[0045] It should be noted that for short exposure star maps, the received light intensity of a single frame star map is subject to a certain probability density function model, wherein under weak turbulence conditions, it is generally considered that the normalized light intensity is subject to the following Lognormal distribution:

[0046]

[0047] wherein is the light intensity flicker index. represents the average value of the received light intensity.

[0048] The frame rate of a new generation of short wave infrared sensors can reach 60 fps or more. If the total number of sequence frames (i.e., the preset number of frames) m = 30 frames, then the relationship between the number of star map frames and the probability under different probabilities p can be plotted by using the above probability expression, as shown in Figure 3 .

[0049] It can be seen from Figure 3 that if the total number of sequence frames (i.e., the preset number of frames) is 30 frames, and the probability that the light intensity energy of a single frame star map meets the requirements is 30%, then the probabilities that the 3, 5, and 7 frames of star maps with the largest signal-to-noise ratio all meet the requirements are 99.9%, 99.7%, and 86.4%, respectively. Therefore, if a star can be detected, according to the atmospheric flicker effect, there must be a frame of star point that can be extracted from the continuously captured short exposure sequence star maps, and adaptively selecting a frame with a larger signal-to-noise ratio can significantly improve the success rate of star point extraction.

[0050] In practice, the above execution subject can set the image sensor shooting parameters, and then continuously capture the star maps of the above preset number of frames through the image sensor to obtain a sequence of star map frames. The above image sensor shooting parameters can include but are not limited to exposure time and gain. When measuring stars during the day, the exposure time can be set to 10 ms and the gain can be 0.

[0051] Step 104, selecting each star map frame of a preset number of candidate frames from the sequence of star map frames as each star point frame to be extracted.

[0052] In some embodiments, the above execution subject can select each star map frame of a preset number of candidate frames from the above sequence of star map frames as each star point frame to be extracted.​​

[0053] In some optional implementations of some embodiments, the execution subject can select the respective star map frames of the preset candidate frame number from the star map frame sequence as the respective star point to-be-extracted frames by the following steps:

[0054] Firstly, for each star map frame in the photographed m-frame star map sequence, the star map signal-to-noise ratio corresponding to each star map frame is calculated.

[0055] Secondly, the respective star map signal-to-noise ratios determined are sorted to obtain a star map signal-to-noise ratio sequence. In practice, the respective star map signal-to-noise ratios determined can be arranged in descending order to obtain the star map signal-to-noise ratio sequence. The star map signal-to-noise ratio sequence can be expressed as:

[0056] .

[0057] Thirdly, according to the star map signal-to-noise ratio sequence, the respective star map frames of the preset candidate frame number are selected from the star map frame sequence as the respective star point to-be-extracted frames. In practice, according to the star map signal-to-noise ratio sequence, the star detection situation can be summarized into the following four situations:

[0058] First, , the star energy is strong, the overall signal-to-noise ratio of the star map is high, and the 7 frames with the highest signal-to-noise ratio are selected as the subsequent to-be-processed star maps to improve the subsequent star point extraction accuracy.

[0059] Second, , the star energy is relatively strong, and is affected by the atmospheric turbulence scintillation effect. Among the m-frame star maps, 5-6 frames have a high signal-to-noise ratio. According to the above probability expression, the total number of star map shooting is adjusted to 1.5m frames, and 7 frames of high signal-to-noise ratio star maps can be obtained.

[0060] Third, , the star energy is relatively weak or the atmospheric turbulence is relatively strong. Among the m-frame star maps, 3-4 frames have a high signal-to-noise ratio. The total number of star map shooting is adjusted to 2m frames, and 7 frames of high signal-to-noise ratio star maps can be obtained.

[0061] Fourth, , the star energy is extremely weak, and only 0-2 frames of star maps can extract star points from the m-frame star maps. This may be caused by random noise. The star cannot be detected, and the observation of the next star is performed.

[0062] Therefore, regardless of the day or night, or the observation of the star energy, the strength of the atmospheric turbulence, and the dynamic change of the sky background light, the star imaging can be summarized into the above four situations. Through the SNR value sorting selection algorithm of the star map, the number of star map shooting frames can be dynamically adjusted, and 7 frames of high signal-to-noise ratio star maps can be finally obtained. It can be seen that the method has strong working time and environmental adaptability.

[0063] In some optional implementations of some embodiments, the execution subject can determine the star map SNR corresponding to the star map frame by the following steps:

[0064] First, determine the region position and region size of the star point prediction region.

[0065] Second, determine the star point prediction region according to the determined region position, region size, star sensor installation matrix, star catalog, etc. parameters, and calculate the gray mean value and gray variance of the region. In practice, the execution subject can determine the gray mean value and the gray variance of the star point prediction region. The star point prediction region can be determined according to the parameters of the star sensor and experience. For example, the angular resolution corresponding to a single pixel of the star sensor is usually 2", so the influence of atmospheric turbulence will not exceed 10 pixels. Considering various factors, we can set the region to 30x30 pixels.

[0066] Second sub-step, according to the gray mean value of the star point prediction region and the gray variance of the star point prediction region, the image threshold segmentation is performed on the star map frame sequence to obtain the segmented star map frame. In practice, the execution subject can determine the image segmentation threshold value as by the gray mean value of the star point prediction region and the gray variance , and then perform threshold segmentation on the star map frame sequence to obtain the segmented star map frame (i.e. local star map).

[0067] Third sub-step, pixel merging is performed on the segmented star map frame sequence to determine the star point region. In practice, the execution subject performs pixel merging on the segmented star map frame (i.e. local star map after threshold segmentation) according to 8 connected regions, and determines the region with connected domain pixel number d greater than 9 pixels as the star point region.

[0068] Fourth sub-step, determine the gray mean value of the star point region.

[0069] Fifth sub-step, determine the star map SNR according to the gray mean value of the star point region and the gray mean value of the star point prediction region. In practice, the execution subject can determine the star map SNR by the following expression:

[0070] .

[0071] Step 105, determine the star center position according to each star point frame to be extracted.

[0072] In some embodiments, the execution subject can determine the star center position according to each star point frame to be extracted.

[0073] It should be noted that since the star is always in motion relative to the star sensor, the theoretical positions of the star points in the sequence frames are not the same. As shown in Figure 4 , ,the centroid coordinates of the star point in the image plane at , the principal axis motion angular velocity vector of the star sensor is , and the corresponding observation vector is , then the star point corresponding observation vector of the th frame star map at can be expressed as:

[0074] .

[0075] wherein is the attitude transfer matrix of the star sensor from to , and its expression is as follows:

[0076] .

[0077] Thus, the expression of the theoretical motion of the star point centroid in the image plane from to is:

[0078] .

[0079] For the above sequence of star map frames, the time interval is a small amount, , and thus the expression of the theoretical motion of the star point centroid in the image plane can be approximately expressed as:

[0080] .

[0081] Since is much larger than , the rotation of the image point caused by the principal axis rotation angular velocity of the star sensor can be ignored, and the above expression of the theoretical motion of the star point centroid in the image plane can be further approximated as:

[0082] .

[0083] As can be seen from the above formula, for the adaptively selected star map frame, the average of the star point centroids is directly extracted, and the equivalent centroid position is the star position at the time , which is the average of the shooting times of the frames.

[0084] Starlight is affected by atmospheric turbulence in the transmission process will produce flicker, drift and other optical effects, to bring some difficulties to the short exposure star chart star point high precision extraction, the application is directed to the influence of atmospheric turbulence, the all-day star point extraction algorithm considering the influence of atmospheric turbulence, can suppress the influence of star point flicker and drift caused by atmospheric turbulence, has good robustness to the star photographed under different conditions. The star point extraction accuracy has good robustness, which can meet the demand of astronomical navigation. And the algorithm logic of the application is simple, easy to realize hardware embedding, which can improve the efficiency of star point extraction algorithm. Therefore, the application can realize the dynamic adjustment of the number of star chart shooting frames regardless of day or night, or the size of the observed star energy, the strength of atmospheric turbulence, and the dynamic change of sky background light. Finally, multiple high signal-to-noise ratio star charts are obtained, and strong working time and environmental adaptability is realized. In addition, the light intensity variation characteristics of star point flicker can be used to effectively select high signal-to-noise ratio star charts, and the instrument's ultimate detection capability can be further tapped.

[0085] Further reference Figure 5 , as an implementation of the method shown in the above figures, the present disclosure provides some embodiments of an all-day star point extraction device considering the influence of atmospheric turbulence, which corresponds to the method embodiments shown in Figure 1 , the all-day star point extraction device considering the influence of atmospheric turbulence can be applied to various electronic devices.

[0086] As shown in Figure 5 , the all-day star point extraction device 500 considering the influence of atmospheric turbulence of some embodiments includes a first determination unit 501, a second determination unit 502, an acquisition unit 503, a selection unit 504 and a third determination unit 505. Wherein, the first determination unit 501 is configured to determine the star sensor main shaft initial pointing direction according to the star sensor installation matrix; the second determination unit 502 is configured to determine the star position information according to the above-mentioned star sensor main shaft initial pointing direction, star sensor field of view and star sensor calibration parameters, wherein the above-mentioned star position information is the position of the corresponding star in the image plane; the acquisition unit 503 is configured to acquire a star chart frame sequence containing a preset number of frames, wherein each star chart frame in the above-mentioned star chart frame sequence corresponds to an acquisition time; the selection unit 504 is configured to select each star chart frame of a preset candidate frame number from the above-mentioned star chart frame sequence as each star point to be extracted frame; the third determination unit 505 is configured to determine the star centroid position according to the above-mentioned each star point to be extracted frame.

[0087] It can be understood that the units recorded in the all-day star point extraction device 500 considering the influence of atmospheric turbulence correspond to the method embodiments shown in Figure 2The various steps in the described method correspond. Thus, the operations, features and advantages described above in relation to the method also apply to the all-weather star point extraction device 500 and the units contained therein, which take into account the effects of atmospheric turbulence, and will not be repeated here.

[0088] Reference is made below Figure 6 which shows a structural schematic diagram of an electronic device suitable for use to implement some embodiments of the present disclosure. Figure 6 The electronic device shown is merely an example and should not impose any limitation on the function and use range of the embodiments of the present disclosure. As Figure 6 As shown, the computer device includes a processor, a memory and a network interface connected through a system bus, wherein the memory can include a non-volatile storage medium and an internal memory. The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions which, when executed, can cause the processor to perform any of the above methods. The processor is used to provide computing and control capabilities to support the operation of the entire computer device. The internal memory provides an environment for the computer program in the non-volatile storage medium, which, when executed by the processor, can cause the processor to perform any of the above methods. The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand, Figure 6 The structure shown in the figure is only a block diagram of part of the structure related to the present disclosure scheme, and does not constitute a limitation on the computer device to which the present disclosure scheme is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0089] It should be understood that the processor can be a central processing unit (CPU), and the processor can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0090] In one embodiment, the processor is configured to run a computer program stored in the memory to determine an initial pointing direction of a star sensor main shaft according to a star sensor installation matrix; determine star position information according to the initial pointing direction of the star sensor main shaft, a field of view of the star sensor, and a star sensor calibration parameter, wherein the star position information is a position of a star in an image plane; acquire a sequence of star image frames including a preset number of frames, wherein each star image frame in the sequence of star image frames corresponds to an acquisition time; select a preset number of candidate star image frames from the sequence of star image frames as star point extraction frames; and determine a star centroid position according to the star point extraction frames.

[0091] The embodiments of the present disclosure further provide a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program includes program instructions. When the program instructions are executed, a method is implemented, which can refer to the embodiments of the method of the present disclosure.

[0092] The computer readable storage medium can be an internal storage unit of the computer device, for example, a hard disk or a memory of the computer device. The computer readable storage medium can also be an external storage device of the computer device, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc.

[0093] It should be noted that, in this document, the terms “comprising” and “including” or any other variant thereof are intended to cover non-exclusive inclusions, such that processes, methods, articles, or systems that comprise a list of elements not only include those elements, but also include other elements not expressly listed, or also include elements inherent in such processes, methods, articles, or systems. Without more limitations, an element defined by the phrase “comprising a” does not exclude the presence of additional identical elements in the process, method, article, or system that includes the element.

[0094] The above description is merely some preferred embodiments of the present disclosure and a description of the principles of the applied technology. Those skilled in the art should understand that the scope of the application involved in the embodiments of the present disclosure is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by any combinations of the above technical features or equivalent features without deviating from the above inventive concept. For example, the above technical features are replaced with technical features disclosed in the embodiments of the present disclosure (but not limited to) having similar functions to form technical solutions.

Claims

1. An all-weather star point extraction method considering the effect of atmospheric turbulence, characterized in that, The method comprises the following steps: determining an initial pointing direction of a star sensor main shaft according to a star sensor mounting matrix; determining star position information according to the initial pointing direction of the star sensor main shaft, a star sensor field of view, and star sensor calibration parameters, wherein the star position information is a position of a corresponding star in an image plane; collecting a star map frame sequence containing a preset number of frames, wherein each star map frame in the star map frame sequence corresponds to a collection time; selecting, from the star map frame sequence, a preset number of candidate frames as star point frames to be extracted; determining a star centroid position according to the star point frames to be extracted.

2. The method of claim 1, wherein, The method of determining the star position information according to the initial pointing direction of the star sensor main shaft, the star sensor field of view, and the star sensor calibration parameters comprises the following steps: determining a star observation vector according to a star sensor rotation matrix; determining the star position information according to the star observation vector, the star sensor calibration parameters, and the star sensor field of view.

3. The method of claim 1, wherein, The method of selecting, from the star map frame sequence, a preset number of candidate frames as star point frames to be extracted comprises the following steps: for each star map frame in the star map frame sequence, determining a star map signal-to-noise ratio corresponding to the star map frame; sorting the determined star map signal-to-noise ratios to obtain a star map signal-to-noise ratio sequence; selecting, from the star map frame sequence, a preset number of candidate frames as star point frames to be extracted according to the determined star map signal-to-noise ratio sequence.

4. The method of claim 1, wherein, The method of determining the star map signal-to-noise ratio corresponding to the star map frame comprises the following steps: determining a region position and a region size of a star point prediction region; determining a star point prediction region gray mean value and a star point prediction region gray variance according to the determined region position and region size; determining a star map frame signal-to-noise ratio according to the star point prediction region gray mean value and the star point prediction region gray variance.

5. An all-weather star point extraction device that takes into account the effects of atmospheric turbulence, characterized in that, The method comprises the following steps: a first determining unit configured to determine an initial pointing direction of a star sensor main shaft according to a star sensor mounting matrix; a second determining unit configured to determine star position information according to the initial pointing direction of the star sensor main shaft, a star sensor field of view, and star sensor calibration parameters, wherein the star position information is a position of a corresponding star in an image plane; a collecting unit configured to collect a star map frame sequence containing a preset number of frames, wherein each star map frame in the star map frame sequence corresponds to a collection time; a selecting unit configured to select, from the star map frame sequence, a preset number of candidate frames as star point frames to be extracted; a third determining unit configured to determine a star centroid position according to the star point frames to be extracted.

6. An electronic device, comprising: The method comprises the following steps: one or more processors; a storage device having one or more programs stored thereon; when the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 4.

7. A computer readable medium characterized by a computer program stored thereon, wherein the computer program is executed by a processor to implement the method according to any one of claims 1 to 4.

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