All-day and all-world time measurement method and device

Abstract

The embodiment of the invention discloses an all-day and all-world time measurement method and device. A specific embodiment of the method comprises the following steps: constructing a short-wave infrared astronomical survey star catalogue; constructing a short-wave infrared astronomical geodetic survey star database according to the short-wave infrared astronomical survey star catalogue; optimizing the short-wave infrared astronomical geodetic survey star library to obtain an optimized short-wave infrared astronomical geodetic survey star library, and correcting atmospheric refraction errors in the optimized short-wave infrared astronomical geodetic survey star library; carrying out all-day fixed star point coordinate extraction on the shot multi-frame daytime star map to obtain fixed star point coordinates; and according to the star point coordinates of the fixed star, carrying out all-day astronomical observation world time calculation on the observation fixed star to obtain all-day world time. According to the embodiment, unified comparison of multi-period monitoring data is realized, and the engineering practicability of a monitoring result is improved.

Description

TECHNICAL FIELD

[0001] Embodiments of the present disclosure relate to the field of all-time universal time measurement, and in particular to an all-time universal time measurement method and device. BACKGROUND

[0002] Universal Time (UT1) is one of the main parameters representing the rotation of the earth, and plays an important role in national defense and national economic construction. The change of UT1 is mainly caused by the change of the rotation speed of the earth, so the determination of UT1 needs to observe extraterrestrial radio sources or stars directly bound to the inertial celestial reference frame at fixed ground stations. At present, the available technical means mainly include Very Long Baseline Interferometry (VLBI), Satellite Laser Ranging (SLR) and optical astronomical measurement. VLBI and SLR have high precision in determining UT1, but have the disadvantages of few stations, high construction cost and difficult system operation. Once the equipment of these stations fails or is attacked, the continuity and reliability of UT1 determination cannot be guaranteed. Therefore, the optical astronomical measurement system which is light and flexible can be used as a backup means for UT1 determination to ensure the autonomous measurement of UT1 under extreme conditions.

[0003] The existing optical astronomical UT1 measurement technology uses a digital theodolite as the basic observation equipment, which can realize UT1 measurement, but has the problem of large system weight and volume, especially can only observe at night, resulting in poor availability. SUMMARY

[0004] 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.

[0005] Some embodiments of the present disclosure provide an all-time universal time measurement method, device, electronic equipment and computer readable medium to solve the technical problems mentioned in the background part.

[0006] In a first aspect, some embodiments of the present disclosure provide an all-time universal time measurement method, which comprises: constructing a short-wave infrared astronomical measurement star table; constructing a short-wave infrared astronomical geodetic measurement star library according to the short-wave infrared astronomical measurement star table; optimizing the short-wave infrared astronomical geodetic measurement star library to obtain an optimized short-wave infrared astronomical geodetic measurement star library, and correcting the atmospheric refraction error in the optimized short-wave infrared astronomical geodetic measurement star library; extracting all-time star point coordinates of observed multiple frames of daytime star maps to obtain star point coordinates; and performing all-time astronomical observation universal time calculation on the observed stars according to the star point coordinates to obtain all-time universal time.

[0007] Secondly, some embodiments of this disclosure provide an all-day cosmic time measurement device, comprising: a first construction unit configured to construct a shortwave infrared astronomical measurement star catalog; a second construction unit configured to construct a shortwave infrared geodetic star database based on the shortwave infrared astronomical measurement star catalog; an optimization unit configured to optimize the aforementioned shortwave infrared geodetic star database to obtain an optimized shortwave infrared geodetic star database, and to correct atmospheric refraction errors in the optimized shortwave infrared geodetic star database; an extraction unit configured to extract all-day stellar coordinates from multiple frames of captured daytime star images to obtain stellar coordinates; and a calculation unit configured to calculate the all-day cosmic time of observed stars based on the stellar coordinates to obtain all-day cosmic time.

[0008] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect above.

[0009] Fourthly, some embodiments of this 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 above.

[0010] The various embodiments disclosed above have the following beneficial effects: Through the all-day UTC measurement method of some embodiments of this disclosure, the atmospheric transmittance of shortwave infrared is higher, thus reducing the impact of atmospheric scattering on starlight. Haze, thin clouds, etc., have a lower attenuation effect on stellar radiation, resulting in higher starlight transmittance. Most stellar radiation is distributed in the shortwave infrared band, with only a small portion distributed in the visible light band, which is highly beneficial for improving observation efficiency and star map recognition accuracy. Shortwave infrared sensors have a larger full-potential-well charge storage capacity, which can significantly improve the integration time and the system's detection aperture, weakening charge saturation and thus obtaining sufficient daytime star measurement signal-to-noise ratio. The larger pixel physical size of the shortwave infrared camera greatly reduces the impact of tracking wobbling on the reduction of stellar signal-to-noise ratio. Correspondingly, the theoretical method for UT1 calculation has been upgraded from the traditional east-west star pair method to an all-day adaptive UT1 algorithm, thereby achieving all-day UT1 calculation based on daytime star measurement. Attached Figure Description

[0011] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0012] Figure 1 This is a flowchart of some embodiments of the all-day UTC measurement method according to the present disclosure;

[0013] Figure 2 This is a flowchart illustrating the process of cross-certification;

[0014] Figure 3 This is a flowchart illustrating a genetic algorithm for star selection.

[0015] Figure 4 This is a schematic diagram illustrating the judgment method of coarse star point recognition;

[0016] Figure 5 It is a daytime infrared star image taken in a complex environment;

[0017] Figure 6 It is a schematic diagram of the movement trajectory of an object flying through a star chart;

[0018] Figure 7 These are schematic diagrams illustrating the structure of some embodiments of the all-day UTC measuring apparatus according to this disclosure;

[0019] Figure 8 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0020] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0021] It should also be noted that, for ease of description, only the parts relevant to the disclosure are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0022] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0023] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0024] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0025] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0026] Figure 1 This is a flowchart 100 of some embodiments of the all-time commute time measurement method of this disclosure. The all-time commute time measurement method includes the following steps:

[0027] Step 101: Construct a shortwave infrared astronomical measurement star catalog.

[0028] In some embodiments, the entity executing the all-time UTC measurement method (e.g., a computing device) can construct a shortwave infrared astronomical measurement star catalog. A complete and accurate star catalog is the foundation and prerequisite for conducting astronomical geodesy. However, existing astronomical geodesy star catalogs, both domestically and internationally, only record stellar information in the visible light band. This disclosure achieves the construction of a shortwave infrared astronomical measurement star catalog through three key technologies: multi-band star catalog cross-certification, shortwave infrared astronomical geodesy star catalog construction, and infrared astronomical geodesy star catalog optimization.

[0029] Cross-certification of multi-band star catalogs. Existing shortwave infrared star catalogs, such as 2MASS and IRAS, lack comprehensive celestial information, particularly information on stellar proper motion, essential for astronomical measurements. Therefore, it is necessary to cross-certify these catalogs with detailed stellar information to produce a more complete shortwave infrared catalog, providing fundamental data support for shortwave infrared astronomical measurements. This disclosure uses the 2MASS catalog as the primary catalog and multi-band catalogs such as Tycho-2 and Gaia as auxiliary catalogs for stellar cross-certification, addressing the question of which stars to measure in the shortwave infrared band. The cross-certification process is as follows: Figure 2 As shown.

[0030] In practice, the aforementioned implementing entities can construct a shortwave infrared astronomical measurement star catalog through the following steps:

[0031] The first step is to input the primary star table and the secondary star table. Input two star tables, A (primary star table) and B (secondary star table) (select the star table with higher precision as the primary star table).

[0032] The second step is to determine the error between the main star catalog and the auxiliary star catalog and divide them into zones according to right ascension and declination. Using the right ascension, declination, and error of the two star catalogs, a preliminary judgment is made. Only within the frame (i.e., simultaneously satisfying the following two formulas) can it be preliminarily considered a possible corresponding source.

[0033] ;

[0034] ;

[0035] in, , Right ascension of a star , For the declination of stars, , The error radius of the primary and secondary star catalogs (determined by the error of the star catalogs' right ascension and declination). , The right ascension and declination of the first star. , The right ascension and declination of the second star.

[0036] The third step is to calculate the angular distance between the two target sources and set a decision threshold to determine whether the two target sources correspond to the original star catalog. The angular distance *d* between the two target sources is calculated, and a decision threshold is set to determine whether the two target sources correspond to the original star catalog. The setting of the decision threshold has a significant impact on the crossover result. The formulas for calculating *d* and the threshold decision formulas are as follows:

[0037] ;

[0038] ;

[0039] The fourth step involves retaining the useful information (position, proper motion, time difference, radial velocity, magnitude) of the target source from its corresponding original catalogue and exporting it to generate a new multi-band catalogue as a shortwave infrared astronomical measurement catalogue. This involves retaining the useful information from the catalogue corresponding to the target source and then exporting it to generate a new multi-band catalogue, including the required parameters from catalogues A and B and the angular distance between them.

[0040] Step 102: Construct a shortwave infrared geodetic astronomical database based on the shortwave infrared astronomical measurement star catalog.

[0041] In some embodiments, the aforementioned implementing entity can construct a shortwave infrared astronomical geodetic star database based on a shortwave infrared astronomical measurement star catalog. Based on cross-certification, variable stars and binary stars in the database are further removed to construct a shortwave infrared astronomical geodetic star database that is sufficiently numerous, information-complete, and data-accurate, providing a foundation for all-weather astronomical measurement. Table 1 below shows the specific content and format specifications of the output star catalog:

[0042] Table 1. Shortwave infrared star catalog data format after cross-verification.

[0043]

[0044] Step 103: Optimize the above-mentioned shortwave infrared astronomical geodetic satellite database to obtain an optimized shortwave infrared astronomical geodetic satellite database, and correct the atmospheric refraction error in the optimized shortwave infrared astronomical geodetic satellite database.

[0045] In some embodiments, the aforementioned implementing entity can optimize the aforementioned shortwave infrared geodetic astronomical database to obtain an optimized shortwave infrared geodetic astronomical database, and correct atmospheric refraction errors in the optimized database. This correction of atmospheric influence on observational calculations is directly reflected in the observation data and is not explicitly displayed separately.

[0046] Here, based on the all-day astronomical measurement star selection strategy, further optimization and analysis are performed to obtain a shortwave infrared astronomical geodetic star library with sufficient quantity, high magnitude, and reasonable distribution, which meets the needs of rapid star finding, rapid identification, and constraint resolution in subsequent measurement processes.

[0047] The spatial distribution of stars is a crucial factor affecting the accuracy of star sensor calibration and positioning calculations. Currently, in land-based astronomical surveys, total station systems manually select stars before observation based on the observation outline, while digital zenith telescopes typically select stars based on the station's latitude, without considering the influence of star configuration and errors. As the field of view increases, the number and distribution of stars change. Therefore, depending on the star sensor's star detection capability and field of view size, calibration and positioning calculations must consider factors such as the spatial distribution of stars and star errors, and comprehensively utilize machine learning algorithms such as neural networks and ant colony algorithms for optimal star selection. This scheme employs an automatic star selection method based on total station elevation measurements, utilizing optimization theory and ant colony algorithms to ensure a good spatial distribution of stars. Figure 3 The flowchart for star selection using a genetic algorithm illustrates how the optimal solution to a problem is gradually found by simulating processes such as chromosome crossover and mutation. In this process, individuals in the population search for strings with higher fitness based on their parent strings. The key to this algorithm lies in the genetic operators: selection, crossover, and mutation.

[0048] Atmospheric refraction error is one of the main sources of error in high-precision ground-based astronomical observations. In existing astronomical geodetic observations, atmospheric refraction models are only applicable to the visible light band and cannot solve the refraction problem in the short-wave infrared band. Therefore, it is necessary to construct a high-precision short-wave infrared starlight atmospheric refraction model.

[0049] Atmospheric refraction affects the apparent position of celestial bodies, causing their apparent direction to deflect upwards compared to their true direction. This disclosed solution first simplifies the Earth's atmosphere into multiple concentric balloon layers with different refractive indices. An analytical physical model for atmospheric refraction errors in the short-wave infrared band is derived using theoretical analysis. Then, based on extensive actual observations, the difference between the theoretical and measured elevation angles of various stars is statistically analyzed. The theoretical model is iteratively optimized using statistical data on the elevation angle differences of stars at different azimuths and altitudes. Finally, the optimized model is used to correct atmospheric refraction errors in infrared astronomical observations, thereby mitigating the impact of atmospheric refraction errors. The effect of atmospheric refraction on the true zenith distance can be approximated by the following formula:

[0050] .

[0051] in, It is the true zenith distance of a celestial body. For the apparent zenith distance, The angle of refraction is usually affected by factors such as atmospheric pressure, temperature, humidity, and the observation altitude of the celestial body.

[0052] Earth's neutral atmosphere consists of two parts: dry atmosphere and water vapor. Therefore, its total refractive index difference is:

[0053] .

[0054] Where N represents the refractive index, ρ represents the atmospheric density, and the subscripts represent dry and wet atmospheres, respectively. and The expression form is:

[0055] .

[0056] Therefore, the fundamental formula for the refractive index difference of the neutral atmospheric group in the near-infrared band is:

[0057] .

[0058] In the formula, (i=0,1,2,3,…) and (i=0,1,2,3…) are the combined coefficients. When the electromagnetic wave reaches the ground station, it is calculated based on the true zenith distance. zenith distance From the relationship, we can see that under the standard atmospheric model, its fundamental differential equation is:

[0059] .

[0060] make:

[0061] .

[0062] According to Bouguer's formula, we get:

[0063] .

[0064] When the series is expanded to quadratic terms, it can be... The second-order expansion is expressed as:

[0065] .

[0066] By observing stars at different altitudes under varying celestial conditions and through extensive observations, the difference between the theoretical and measured altitude angles of each star is statistically analyzed. Based on this statistical data of altitude angle differences for stars at different locations and altitudes, the theoretical model is iteratively optimized, allowing the coefficients of A and B to be obtained using the least squares method. Finally, the optimized model is used to correct atmospheric refraction errors in infrared astronomical observations, thereby mitigating the impact of these errors.

[0067] Step 104: Extract the coordinates of stars and points throughout the day from the captured multi-frame daytime star map.

[0068] In some embodiments, the aforementioned execution entity can extract the coordinates of stars and points throughout the day from multiple frames of captured daytime star maps to obtain the coordinates of stars and points.

[0069] First, based on the brightness information of stars in the short-wave infrared band, we studied and designed various parameters of an all-weather infrared astronomical measurement optical system to ensure that star maps can be captured during the day. Then, based on the different imaging characteristics of InGaAs infrared sensors during the day and night, we studied how to achieve high-precision star point detection and star image center extraction in star maps with complex backgrounds.

[0070] After preprocessing, the daytime star map exhibits reduced background noise and significantly enhanced contrast between star targets and the background, enabling star target extraction and star map recognition. Star target extraction includes threshold segmentation, coarse star identification, false star removal, and centroid subdivision localization.

[0071] In practice, the aforementioned executing entity can extract the coordinates of stars and points across the entire day from multiple frames of captured daytime star images using the following steps:

[0072] The first step is to continuously capture multiple frames of daytime star charts. Various astronomical measurement optical systems can be used for capturing these daytime star charts; no specific restrictions are imposed.

[0073] The second step involves overlaying multiple frames of daytime star images and averaging them to obtain an average image. This method involves summing the grayscale values ​​of corresponding pixels in N frames at different times and then calculating their temporal average. This algorithm has low computational cost, can eliminate random noise, and theoretically improves the signal-to-noise ratio after overlaying N frames. However, achieving accurate superposition under dynamic conditions is difficult, and it is hard to significantly improve the signal-to-noise ratio in noisy environments.

[0074] In this scheme, since stars are observed under static conditions, their positions remain essentially unchanged within a very short observation period, allowing for direct overlay of multiple frames. Simultaneously, due to atmospheric turbulence, the stars fluctuate in brightness and grayscale values; therefore, averaging multiple frames reduces the atmospheric influence on star energy. Because the computational load increases with the number of frames stacked, and the signal-to-noise ratio improvement decreases with increasing frame count, only seven consecutive frames are overlaid.

[0075] The third step involves adaptive thresholding of the mean image to obtain an adaptive threshold. The star map preprocessing filtering algorithm effectively removes background noise. Considering the algorithm's complexity and real-time processing requirements, a statistically based adaptive thresholding method is chosen for image segmentation. This method primarily calculates the threshold based on real-time image data, offering greater flexibility. The calculation formula is as follows:

[0076] .

[0077] In the formula, The mean of the pixel samples, The standard deviation of the pixel sample. The coefficient related to image noise is a fixed value, typically ranging from 2 to 5. Pixel samples are usually extracted from one or several rings of pixels at the window edge of the entire image, and outliers need to be removed. For daytime star sensors, due to the complex background and uneven grayscale distribution of the image, inappropriate pixel sample selection may lead to a large deviation between the estimation of the image variance and the mean, affecting star point recognition.

[0078] The fourth step involves coarse star point identification on the mean image to obtain the effective image coordinates of each star point. In the star image, star points are composed of several adjacent pixels. Through coarse identification technology, different stars in the binarized star image after threshold segmentation can be distinguished, while isolated noise points and large targets are removed, finally obtaining the effective image coordinates of each star point.

[0079] Connectivity analysis is a commonly used coarse star identification method in star sensors. Its criteria mainly include four-connectivity and eight-connectivity, such as... Figure 4 Four-connection criteria are typically used for convex targets, while eight-connection criteria are used for concave targets. The stars in a star sensor, after being defocused and forming a Gaussian spot, are convex targets; therefore, the four-connection criterion is used.

[0080] A traditional connected component identification method is used for coarse star identification. It's important to note that due to strong background radiation during the daytime sky and relatively weak starlight radiation, if starlight is diffused to 25 pixels or more using a traditional nighttime star sensor, the starlight energy will be drowned out by background noise. Therefore, daytime star sensors typically only diffuse to a few pixels (4-9). To prevent missing weak star targets, all connected components with an area ≥2 are considered as candidate stars during coarse star identification. This inevitably extracts false stars, thus requiring further false star removal.

[0081] The fifth step involves eliminating false stars from the average image by analyzing multiple frames of daytime star charts. During daytime measurements, false stars in the all-day star sensor mainly originate from dead pixels on the detector, floating objects in the air, or spacecraft. Figure 5 This is a daytime infrared star image taken in a complex environment. There is one star point star1 in the image, which shows that there is a lot of interference in the star image.

[0082] Unlike the motion-platform all-day star sensor, this technical solution observes stars under static conditions. Therefore, the star targets are relatively stationary in multi-frame image sequences, and it is impossible to distinguish between star points and bad points by their motion state. Bad points in the detector are deducted using the dark field correction method.

[0083] Since airborne objects and aircraft are in motion, their movement can be determined by observing whether they move within a multi-frame sequence. If a daytime star sensor captures multiple frames of a location during static stargazing from the ground, the trajectory of an object flying through the star image would be as follows: Figure 6 As shown in the image, images 1-3 are the first 2048*512 window of the full 2048*2048 image; images 4-6 are the second 2048*512 window; images 7-9 are the third window; and images 10-13 are the fourth window. The image shows the object flying across the field of view from right to left.

[0084] Step 6: Based on the aforementioned adaptive threshold, extract the star coordinates of all stars in the mean image throughout the day to obtain the star coordinates. Commonly used subdivision positioning methods include the centroid method, the square-weighted centroid method, the thresholded centroid method, and the surface fitting method. Theoretically, subdivision methods can improve the centering accuracy to 0.01–0.02 pixels, but in practice, they are limited by various noise levels, and the accuracy is usually 0.04–0.2 pixels. The thresholded centroid method is a commonly used subdivision positioning method in star sensors. It is relatively simple to implement, less affected by noise, and has higher accuracy than the centroid method. This method is used to calculate the star centroid. The definition is as follows:

[0085] .

[0086] In the formula, f(x,y) represents the gray value of the point at coordinates (x,y) on the image plane, and V th is the threshold, and m and n are the width and height of the star map. The centroid of the star points is the process of star point extraction, used to calculate the position of the star points in the star map in the image plane coordinate system, and then used for star map recognition. The star map recognition adopts conventional algorithms, and this disclosure will not make any special descriptions of them.

[0087] Step 105: Based on the star point coordinates, calculate the cosmic time of the observed star using all-day astronomical observations to obtain the cosmic time.

[0088] In some embodiments, the aforementioned executing entity can perform all-day astronomical observation cosmic time calculation on the observed star based on the star point coordinates to obtain the all-day cosmic time.

[0089] Currently, the main technical means for determining UT1 is VLBI, but if these systems malfunction or are attacked, the continuity of UT1 measurements cannot be guaranteed. Therefore, this disclosure proposes a method for determining UT1 using a lightweight and flexible infrared all-weather astronomical measurement system. First, a station with known latitude and longitude is selected. Then, the instrument is set up at the station and initial orientation is completed. The instrument selects and observes stars using the east-west star pairing method. Finally, relevant algorithms are used to calculate UT1.

[0090] Since observing stars near the zonal equator has minimal impact on time measurement, stars in the east-west direction should be selected for observation, ideally using the east-west binary star elevation method. After observation, UT1 is calculated on a spherical triangle based on the cosine formula of the sides and the known latitude and longitude of the station. The specific method is as follows:

[0091] Sidereal time (ST) is the length of a day equal to the time interval between two consecutive transits of a particular star. A star's transit occurs at the moment its apparent diurnal motion crosses the Earth-fixed frame meridian at the observation station. The motion of the Earth's axis of rotation relative to this Earth-fixed frame is called polar motion. Therefore, the transit time of a star directly observed from the station usually needs to be corrected for polar motion. That is, UT1.

[0092] .

[0093] In the formula: The geographical latitude and longitude of the station. This represents the polar motion at the corresponding moment. The astronomical latitude of the station can be calculated by observing the altitude angle of a star at its highest point in the sky. This is the method of determining astronomical latitude using the north and south star altitude difference method. When the observed star is at its highest point in the sky, the following relationship holds:

[0094] .

[0095] Therefore, the astronomical latitude of the station can be obtained by calculating the zenith distance between a pair of northern and southern celestial stars in the zenith direction of the station, and then taking the average value:

[0096] .

[0097] Due to the influence of polar shift, a difference arises between the latitude obtained in the above formula and the actual value. By utilizing observations from different stations with uniform longitude distribution, the polar motion can be determined:

[0098] .

[0099] The polar shift components can be obtained using the least squares method. Latitude is primarily measured by observing the positions of stars, while longitude (or day length) is measured by observing the time a star passes through a specific location. Based on the coordinates of the observation station and the time of observation, the instantaneous orientation of the Earth's rotation axis in space can be determined.

[0100] According to the principles of astronomical geodesy, the relationship between instantaneous astronomical longitude and latitude at station i under observation epoch t and astronomical longitude and latitude under normal polar conditions is as follows:

[0101] .

[0102] in:

[0103] .

[0104] In the formula: To measure the astronomical latitude and longitude of station i at epoch t under mean polar conditions, The instantaneous astronomical latitude and longitude of the observation epoch at station i is measured.

[0105] Substituting it in, we get:

[0106] .

[0107] At this observation epoch, the observed local sidereal time and the corresponding Greenwich Mean Time The relationship is as follows:

[0108] .

[0109] The observation equations for ground-based astronomical measurements at station i at epoch t can be established:

[0110] .

[0111] In the formula: These are the latitude and longitude of the current station. The observation residuals in the direction mainly include the initial values ​​of the station coordinates. The constant is fixed deviation and the observation noise of the current epoch are two parts, where k is the coefficient of sidereal second and universal second.

[0112] The observation equations for ground-based astronomical measurements at epoch t of station i can be rewritten in the following form:

[0113] .

[0114] If there are n observation stations (n≥3) observing simultaneously, the observation equations for different stations at epoch t can be obtained as follows:

[0115] .

[0116] Linearizing the above equation and expressing it in matrix form, we obtain the error equation:

[0117] .

[0118] In the formula:

[0119]

[0120] .

[0121] According to the least squares criterion, under the same observation conditions, the solution to this error equation is:

[0122] .

[0123] The standard deviation per unit weight is:

[0124] .

[0125] If the observations at each station are unequally weighted, then let the weight matrix of all observations be PP, and its inverse weight matrix be Q. Since the different observations are independent and uncorrelated, its inverse weight matrix can be written in the following form:

[0126] .

[0127] At this point, the least squares solution to the above error equation is:

[0128] .

[0129] Based on the above, it can be concluded that UT1 measurements can be achieved using polar motion through observations from a single station.

[0130] For the instantaneous astronomical latitude and longitude of At a certain observatory, when observations are made at that observatory, the sidereal time... With Greenwich Mean Time The relationship between them is:

[0131] .

[0132] From the formula above, we can obtain:

[0133] .

[0134] Polar shift can be and the coordinates of the station in the International Earth Reference System (ITRF) Substituting the data can be done based on the observation results of a single station. The expression for calculating UT1 is:

[0135] .

[0136] In the formula, The right ascension octave is also called the dichotomy.

[0137] Further reference Figure 7 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of an all-day cosmic time measuring device, these device embodiments being similar to... Figure 1 Corresponding to the method embodiments shown, this all-day UTC measuring device can be specifically applied to various electronic devices.

[0138] like Figure 7 As shown, the all-time cosmic time measurement device 700 in some embodiments includes: a first construction unit 701, a second construction unit 702, an optimization unit 703, an extraction unit 704, and a calculation unit 705. The first construction unit 701 is configured to construct a shortwave infrared astronomical measurement star catalog; the second construction unit 702 is configured to construct a shortwave infrared geodetic star database based on the shortwave infrared astronomical measurement star catalog; the optimization unit 703 is configured to optimize the aforementioned shortwave infrared geodetic star database to obtain an optimized shortwave infrared geodetic star database, and to correct atmospheric refraction errors in the optimized shortwave infrared geodetic star database; the extraction unit 704 is configured to extract the all-time stellar coordinates of multiple frames of captured daytime star images to obtain stellar coordinates; and the calculation unit 705 is configured to calculate the all-time cosmic time of observed stars based on the stellar coordinates to obtain the all-time cosmic time.

[0139] It is understandable that the units and references recorded in this all-day cosmopolitan time measuring device 700 are... Figure 1 The steps in the described method correspond accordingly. Therefore, the operations, features, and beneficial effects described above for the method also apply to the all-day cosmopolitan time measuring device 700 and the units contained therein, and will not be repeated here.

[0140] The following is for reference. Figure 8 It illustrates a schematic diagram of the structure of an electronic device (such as a computing device) suitable for implementing some embodiments of the present disclosure. Figure 8 The electronic device shown is merely an example and should not be construed as limiting the functionality or scope of the embodiments of this disclosure. Figure 8 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The memory may include non-volatile storage media and internal memory. The non-volatile storage media may store an operating system and a computer program. The computer program includes program instructions that, when executed, cause the processor to perform any omni-channel UT measurement method. The processor provides computational and control capabilities to support the operation of the entire computer device. The internal memory provides an environment for the execution of the computer program in the non-volatile storage media; when executed by the processor, this program causes the processor to perform any omni-channel UT measurement method. The network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that... Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present disclosure and does not constitute a limitation on the computer device to which the present disclosure is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0141] It should be understood that the processor can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among these, a general-purpose processor can be a microprocessor or any conventional processor.

[0142] In one embodiment, the processor is configured to run a computer program stored in a memory to perform the following steps: constructing a shortwave infrared astronomical star catalog; constructing a shortwave infrared geodetic star database based on the shortwave infrared astronomical star catalog; optimizing the shortwave infrared geodetic star database to obtain an optimized shortwave infrared geodetic star database, and correcting atmospheric refraction errors in the optimized shortwave infrared geodetic star database; extracting the coordinates of stars from multiple frames of daytime star images to obtain star coordinates; and calculating the cosmic time of the observed stars based on the star coordinates to obtain the cosmic time.

[0143] This disclosure also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, and the method implemented when the program instructions are executed can refer to various embodiments of the all-day cosmos measurement method of this disclosure.

[0144] The aforementioned computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiments, such as the hard disk or memory of the computer device. Alternatively, the aforementioned computer-readable storage medium may be an external storage device of the computer device, such as a plug-in hard disk, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the computer device.

[0145] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0146] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for measuring universal time throughout the day, characterized in that, include: Construct a star catalog for shortwave infrared astronomical measurements; Based on the shortwave infrared astronomical measurement star catalog, construct a shortwave infrared astronomical geodetic star database; The shortwave infrared geodetic astronomy database is optimized to obtain an optimized shortwave infrared geodetic astronomy database, and atmospheric refraction errors in the optimized shortwave infrared geodetic astronomy database are corrected. The coordinates of stars and points were extracted from multiple frames of daytime star images captured throughout the day. Based on the coordinates of the star, the cosmic time of the observed star is calculated using astronomical observation throughout the day to obtain the cosmic time.

2. The method according to claim 1, characterized in that, The construction of the shortwave infrared astronomical measurement star catalog includes: Enter the primary star table and the secondary star table; Determine the error between the main star catalog and the auxiliary star catalog, and divide them into zones according to right ascension and declination; Calculate the angular distance between two target sources, and set a decision threshold to determine whether the two target sources correspond to the original star catalog; The useful information of the target source corresponding to the star catalog is retained, and a new multi-band star catalog is generated as a shortwave infrared astronomical measurement star catalog.

3. The method according to claim 2, characterized in that, The step of extracting the coordinates of stars from multiple frames of captured daytime star images, including: Capture multiple frames of daytime star images in succession; The average value of multiple daytime star charts is obtained by overlaying them. The mean image is subjected to adaptive threshold segmentation to obtain an adaptive threshold for the image; Perform coarse star point identification on the mean image to obtain the effective image coordinates of each star point; By using multiple frames of daytime star charts, false star points are removed from each star point in the mean image; Based on the image adaptive threshold, the star point coordinates of all stars in the mean image are extracted to obtain the star point coordinates.

4. A universal time measuring device, characterized in that, include: The first building unit is configured to build a shortwave infrared astronomical measurement star catalog; The second building unit is configured to build a shortwave infrared geodetic star library based on the shortwave infrared astronomical measurement star catalog. The optimization unit is configured to optimize the shortwave infrared geodetic astronomy database to obtain an optimized shortwave infrared geodetic astronomy database, and to correct atmospheric refraction errors in the optimized shortwave infrared geodetic astronomy database. The extraction unit is configured to extract the coordinates of stars and points throughout the day from multiple frames of captured daytime star images. The calculation unit is configured to perform all-day astronomical observation cosmic time calculation on the observed star based on the star point coordinates, and obtain the all-day cosmic time.

5. An electronic device, characterized in that, include: One or more processors; A storage device on which one or more programs are stored; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1 to 3.

6. A computer-readable medium, characterized in that, It stores a computer program thereon, wherein the computer program, when executed by a processor, implements the method as described in any one of claims 1 to 3.

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