A method for determining a time period during which a satellite is visible to a ground station from TLE data

Abstract

The application discloses a kind of through TLE data determination satellite and ground station visible time period calculation method, it is related to spaceflight TT&C and satellite communication scheduling technical field, the application is through the dynamic sampling mechanism of cluster perception, in dense transit period automatically promotes time resolution, reduce sampling density in non-cluster period, significantly reduce redundant calculation, avoid power peak congestion;Boundary detection algorithm based on elevation rate of change sign switching can capture satellite elevation angle rapid jump point, eliminate the false merging phenomenon of short interval window, and the output timestamp accuracy reaches sub-second level;Confidence identifier dynamically reflects TLE data aging and cluster complexity, users can intuitively evaluate window time credibility, reduce the risk of communication interruption caused by orbit prediction error.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of spaceflight TT&C and satellite communication scheduling, and in particular to a method for determining a visible time period of a satellite and a ground station based on TLE data. BACKGROUND

[0002] Currently, the scale of low-orbit satellite constellation (such as communication and remote sensing cluster) is continuously expanding, and a single ground station needs to handle hundreds of satellite passing events per day. During the cluster dense passing period, the orbits of multiple satellites are highly overlapped, which causes continuous passing through the communication airspace of the ground station in a short time. In such a scenario, the satellite passing interval may be compressed to tens of seconds, which puts forward strict requirements on the real-time and resolution capability of the visible window calculation.

[0003] The mainstream scheme relies on the SGP4 model and adaptive step optimization, but still has significant defects during the dense passing period: although the adaptive step reduces the non-active period overhead, it still triggers dense sampling when facing synchronous passing of cluster satellites, causing instantaneous computing power bottleneck; at the same time, when the satellite passing interval is less than the step adjustment threshold (such as 30 seconds), the adjacent visible windows are merged by mistake, and the key communication scheduling gap is lost; in addition, during the period of rapid change of satellite elevation angle, the fixed interpolation algorithm cannot distinguish the window boundaries of overlapping satellites, and the output timestamp has ±10 seconds of jitter;

[0004] Some recent schemes introduce parallel computing or window post-processing technology, but the dynamic step strategy is forced to globally shrink the step during the cluster period, losing the adaptive advantage; and the window merging suppression rule relies on a preset static threshold, which cannot adapt to the dynamic coupling effect of orbit geometry; the interpolation method based on time series does not consider the phase interference between satellites, and the boundary correction has systematic deviation. SUMMARY

[0005] In view of the above existing problems, the present application is proposed.

[0006] The present application provides a method for determining a visible time period of a satellite and a ground station based on TLE data, which solves the problems of computing power peak and window merging caused by dense passing of low-orbit satellite cluster, and the problem that the existing dynamic step scheme cannot adapt to the coupling of orbit phase.

[0007] To solve the above technical problems, the present application provides the following technical scheme:

[0008] The present application provides a method for determining a visible time period of a satellite and a ground station based on TLE data, which includes,

[0009] Step S1: parsing the TLE data of the satellite, obtaining the orbit parameters and initializing the SGP4 orbit model;

[0010] Step S2: calculating the satellite orbit period according to the orbit parameters;

[0011] Step S3, identifying a satellite cluster passing through the ground station in the current calculation period: when the ascending node right ascension difference of multiple satellites is less than a set phase threshold, it is determined that the cluster is passing through;

[0012] Step S4, during the cluster passing period, dynamically setting a time sampling interval based on the satellite orbit period and the number of cluster satellites;

[0013] Step S5, iteratively calculating the satellite elevation angle to the ground station according to the time sampling interval, and marking the period when the elevation angle is greater than the visible threshold as the visible window;

[0014] Step S6, for the interval between adjacent visible windows less than the preset merging threshold, performing integral boundary detection to separate independent windows;

[0015] Step S7, outputting the start and end time of the separated visible window.

[0016] As a preferred scheme of the method for determining the visible time period of a satellite and a ground station through TLE data, in step S3, the phase threshold is set to 5°, and the number of cluster satellites is determined by real-time statistics of the number of satellites with an ascending node right ascension difference less than 5°.

[0017] As a preferred scheme of the method for determining the visible time period of a satellite and a ground station through TLE data, in step S4, the dynamically set time sampling interval includes:

[0018] Obtaining the satellite orbit period and the number of cluster satellites;

[0019] Setting the sampling interval to be proportional to the satellite orbit period and inversely proportional to the number of cluster satellites;

[0020] When the number of cluster satellites increases, the sampling interval decreases by the same proportion.

[0021] As a preferred scheme of the method for determining the visible time period of a satellite and a ground station through TLE data, in step S4, the dynamically set time sampling interval is coupled with orbit dynamics and constellation situation during the cluster passing period. First, the satellite orbit period T orb Generate a reference interval, and then adjust the density according to the number of clusters N cl and the time effectiveness of TLE data to form a continuous and adjustable time sequence, which specifically includes:

[0022]

[0023] Δt=max(Δt,Δt min ),

[0024] wherein, Δt represents the dynamic time sampling interval, unit s, k s represents the aging correction sampling ratio, T orb represents the satellite orbit period, unit s, N cl represents the number of constellation satellites, γ represents the number sensitivity index, k0 represents the preset reference sampling ratio constant, dimensionless, η represents the TLE aging weight coefficient, dimensionless, τ tle represents the current TLE data aging, unit d, τ ref represents the aging reference value, unit d, σ Ω represents the right ascension dispersion of the ascending node of the constellation satellite, unit °, Δt min lower limit of the sampling interval, unit s.

[0025] As a preferred scheme of the calculation method for determining the visible time period of the satellite and the ground station through the TLE data, in step S6, the execution of the calculus boundary detection comprises:

[0026] At the center point of the adjacent visible window interval, a preset resampling interval is expanded to both sides;

[0027] In the interval, the elevation angle value is iteratively calculated at a fixed high-precision step;

[0028] The change rate of the elevation angle is calculated, and the switching point of the sign of the change rate is determined to determine the accurate start and end time of the window;

[0029] If the interval of the change rate switching point is less than a preset merging threshold, the window is separated into independent windows.

[0030] As a preferred scheme of the calculation method for determining the visible time period of the satellite and the ground station through the TLE data, in step S6, the calculus boundary detection separates independent windows, and when the interval τ gap of adjacent visible windows is less than a merging threshold ΔT merge , high-resolution resampling and derivative sign switching are used to determine the accurate boundary, and the flow comprises:

[0031] Interval determination is performed:

[0032]

[0033] wherein, τ gap represents the interval of two windows, unit s, represents the start point of the nth window, unit s, represents the end point of the previous window, unit s, ΔT merge represents the preset merging threshold, 0.05T orb , unit s;

[0034] Resampling center and timing:

[0035]

[0036] Wherein, t c represents the interval center time, unit s, t j represents the jth resampling time, unit s, j is the resampling sequence number, taking the integer interval [-m, m], δt hp represents the high resolution step, unit s, τ rsr represents the resampling interval width, n represents the order index of the visible window;

[0037] Estimate the elevation derivative, the formula is:

[0038]

[0039] Wherein, represents the elevation rate of change at time t j , unit ° / s, represents the elevation rate of change of the previous sampling point, E j represents the elevation sequence value, unit °, t b represents the candidate boundary time, unit s;

[0040] Then, the boundary validity is checked:

[0041] If

[0042] Wherein, |t b -t c | represents the time difference of the candidate boundary from the center, unit s;

[0043] Insert t b checked into the window list to obtain the independent visible window start and end time set.

[0044] As a preferred scheme of the calculation method for determining the visible time period of the satellite and the ground station through the TLE data, wherein: the preset high-precision step is not more than 0.1 seconds, and the resampling interval is 30 seconds before and after.

[0045] As a preferred scheme of the calculation method for determining the visible time period of the satellite and the ground station through the TLE data, wherein: the visible window start and end time output in the step S7 is additionally provided with a confidence identifier, which is dynamically generated according to the TLE data freshness and the number of cluster satellites.

[0046] As a preferred scheme of the method for determining a visible time period of a satellite and a ground station through TLE data, the visible threshold is 5°, and the preset merging threshold is 5% of an orbit period of the satellite.

[0047] As a preferred scheme of the method for determining a visible time period of a satellite and a ground station through TLE data, the method adopts a fixed time sampling interval greater than a maximum sampling interval of a cluster period in a non-cluster transit period.

[0048] The present application has the following advantages: the present application automatically increases the time resolution in a dense transit period and reduces the sampling density in a non-cluster period through a cluster-aware dynamic sampling mechanism, significantly reduces redundant calculation, and avoids peak congestion of computing power; the boundary detection algorithm based on the sign switching of the elevation change rate can capture the rapid change point of the satellite elevation angle, eliminate the false merging phenomenon of the short interval window, and output the timestamp with a sub-second level of accuracy; the confidence identifier dynamically reflects the TLE data aging and cluster complexity, and the user can intuitively evaluate the window time reliability, thereby reducing the risk of communication interruption caused by orbit prediction errors; the whole process only relies on TLE input and the SGP4 model, is compatible with existing satellite ground station systems, and does not need to add new hardware or real-time data access. BRIEF DESCRIPTION OF DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0050] Figure 1 The flowchart of the method for determining a visible time period of a satellite and a ground station through TLE data in embodiment 1. DETAILED DESCRIPTION

[0051] In order to make the above-mentioned purposes, features and advantages of the present application more apparent and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings of the specification.

[0052] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the concept of the present application, therefore the present application is not limited to the specific embodiments disclosed below.

[0053] Second, the "one embodiment" or "an embodiment" referred to herein can include a particular feature, structure, or characteristic. The various embodiments appearing at different places in this specification can not all refer to the same embodiment or to the same implementations or alternatives of an embodiment.

[0054] Embodiment 1, Reference Figure 1 The embodiment provides a calculation method for determining a visible time period of a satellite and a ground station through TLE data, comprising the following steps:

[0055] Step S1, parsing TLE data of the satellite, obtaining orbit parameters and initializing an SGP4 orbit model;

[0056] Step S2, calculating a satellite orbit period according to the orbit parameters;

[0057] Step S3, identifying a satellite cluster passing through the ground station in a current calculation period: when the ascending node right ascension difference of multiple satellites is less than a set phase threshold, it is determined as a cluster passing period;

[0058] In step S3, the phase threshold is set to 5°, and the number of cluster satellites is determined by real-time statistics of the number of satellites with an ascending node right ascension difference less than 5°;

[0059] Step S4, in the cluster passing period, dynamically setting a time sampling interval based on the satellite orbit period and the number of cluster satellites;

[0060] In step S4, the dynamic setting of the time sampling interval comprises:

[0061] Obtaining the satellite orbit period and the number of cluster satellites;

[0062] Setting the sampling interval to be proportional to the satellite orbit period and inversely proportional to the number of cluster satellites;

[0063] When the number of cluster satellites increases, the sampling interval is reduced by the same proportion to ensure the calculation density in a high conflict period;

[0064] In step S4, the dynamic setting of the time sampling interval couples the sampling frequency with orbit dynamics and constellation situation during the cluster passing period. First, the sampling frequency is set to be proportional to the satellite orbit period T orb Generate a reference interval, and then adjust the density according to the number of clusters N cl and the time effectiveness of the TLE data to form a continuous and adjustable time sequence, which specifically comprises:

[0065]

[0066] Δt=max(Δt,Δt min ),

[0067] wherein, Δt represents the dynamic time sampling interval, unit s, k s represents the aging correction sampling ratio, T orb represents the satellite orbit period, unit s, N cl represents the number of constellation satellites, γ represents the number sensitivity index, k0 represents the reference sampling ratio constant, empirical value 0.004-0.006, dimensionless, η represents the TLE aging weight coefficient, dimensionless, τ tle represents the current TLE data aging, unit d, τ ref represents the aging reference value, unit d, σ Ω represents the dispersion of the right ascension of the ascending node of the constellation satellite, unit °, Δt min lower limit of the sampling interval, unit s;

[0068] Specifically, the sampling strategy sets the reference according to the orbit period, and then attenuates the number of clusters to the power, so that high-density constellations obtain finer resolution. Meanwhile, a TLE aging correction term is introduced to automatically increase the sampling frequency when the orbit elements are old, so as to offset the orbit error diffusion. The dispersion gain determines the satellite with loose orbit phase as a low conflict scenario, and the interval is relaxed accordingly, so as to balance the calculation load. The lower threshold suppresses the operation congestion caused by too small step, and the overall sampling interval realizes smooth contraction-expansion in the transit period, which is beneficial to the high-order derivative root-finding of the subsequent window boundary, reduces the segmentation error, and saves the calculation time resource;

[0069] Step S5: iteratively calculating the elevation angle of the satellite to the ground station according to the time sampling interval, and marking the period when the elevation angle is greater than the visible threshold as the visible window;

[0070] The visible threshold is 5°, and the preset merging threshold is 5% of the satellite orbit period;

[0071] Step S6: performing integral boundary detection to separate independent windows for the period when the interval of adjacent visible windows is less than the preset merging threshold;

[0072] In step S6, performing integral boundary detection includes:

[0073] At the center point of the interval of adjacent visible windows, a preset resampling interval is expanded to both sides;

[0074] In the interval, the elevation angle value is iteratively calculated with a fixed high-precision step;

[0075] The change rate of the elevation angle is calculated, and the switching point of the sign of the change rate is determined to determine the accurate start and end time of the window;

[0076] If the interval of the change rate switching point is less than the preset merging threshold, the adjacent visible windows are separated as independent windows;

[0077] In step S6, the integral boundary detection separates independent windows, and the interval of adjacent visible windows is τgap less than merge threshold ΔT merge When the high-resolution resampling and derivative sign switching are adopted to determine the accurate boundary, the flow includes:

[0078] Interval determination is performed:

[0079]

[0080] wherein τ gap represents the time interval of two windows, in s, represents the start time of the nth window, in s, represents the end time of the previous window, in s, ΔT merge represents the preset merge threshold, taking 0.05T orb , in s;

[0081] Resampling center and timing:

[0082]

[0083] wherein t c represents the center time, in s, t j represents the jth resampling time, in s, j is the resampling sequence number, taking the integer interval [-m, m], δt hp represents the high-resolution step, in s, the upper limit τ rsr represents the resampling interval width, fixed at ±30 s, n represents the sequence index of the visible window;

[0084] Estimate the elevation derivative, the formula is:

[0085]

[0086] wherein, represents the elevation change rate at time t j , in ° / s, represents the elevation change rate of the previous sampling point, E j represents the elevation sequence value, in °, t b represents the candidate boundary time, in s;

[0087] Boundary effectiveness check is performed again:

[0088] If

[0089] wherein |t b -t c | represents the time difference of the candidate boundary from the center, in s;

[0090] The t bInserting the window list to obtain a set of independent visible window start and end time;

[0091] Specifically, the detection method forms a continuous operation chain with interval time, center resampling and derivative symbol switching, first performs symmetric resampling on the suspected merging area, and then obtains the elevation change rate by using center difference; the switching point of the derivative from positive to negative or negative to positive corresponds to the elevation peak or valley, thereby giving the real edge of the window; the time difference check can exclude false intersections and maintain the independence of the window; the step is fixed at 0.1s, and the resampling interval is ±30s, which can capture all extreme values near the fastest phase change of the orbit and simultaneously suppress redundant computational load; the overall algorithm does not need to traverse the entire trajectory, and only the candidate area is calculated, so that the calculation load is controlled while the boundary is refined, and the subsequent visibility scheduling and link scheduling are more friendly;

[0092] The preset high-precision step is not more than 0.1s, and the resampling interval is ±30s;

[0093] Step S7, output the separated visible window start and end time (UTC format);

[0094] The visible window start and end time output in step S7 is attached with a confidence identifier, which is dynamically generated according to the TLE data freshness and the number of cluster satellites;

[0095] The calculation method uses a fixed time sampling interval during non-cluster transit, and the interval is greater than the maximum sampling interval during cluster period.

[0096] The effects of the embodiment are summarized as follows: the visible time period calculation method proposed by the application is based on orbit dynamics, and integrates adaptive sampling of constellation situation and local calculus boundary detection, forming a hierarchical strategy of coarse first and fine later and on-demand densification in the overall process.

[0097] By actively shrinking the step after recognizing the cluster transit, and triggering high-resolution resampling at the suspected window adhesion place, the algorithm naturally avoids the waste of computing power caused by blindly using fine steps in the entire trajectory range, and also avoids the phenomenon of window merging and missed detection caused by relying on a single threshold.

[0098] Compared with existing fixed step or only using error feedback to adjust step size, it is more flexible in resource allocation: for platforms with tight computing power, the minimum cost can be guaranteed by the lower threshold constraint; for tasks with strict real-time requirements, automatic encryption sampling can be performed in critical sections by increasing the parameter sensitivity; at the same time, the introduction of ascending node right ascension dispersion makes the algorithm no longer simply rely on the static index of satellite number, but can perceive the dynamic coupling degree of orbital geometry, so it can maintain stable performance under different constellation structures, different orbital inclinations and different ground station latitudes; in addition, the TLE time correction term enables the algorithm to adaptively improve accuracy when elements set is not updated in time, reduces the influence of extrapolation error on window boundary, and ensures the operability of output results.

[0099] The entire method maintains linear scalability in the calculation process, and can be independently run on the air traffic control terminal, or embedded as a microservice in the constellation operation and control cloud platform to realize multi-user parallel calling.

[0100] All core parameters in the process, such as reference sampling ratio, time weight coefficient, and number sensitivity index, are externally configured through a configuration file, which can be online hot adjusted without interrupting service, facilitating operation and maintenance personnel to quickly iterate according to daily task load. The algorithm itself does not depend on proprietary hardware and can be deployed on general-purpose CPU, GPU or embedded SoC, and can support cross-station collaboration with a distributed message queue.

[0101] If subsequent access to TLE extension fields of new systems or high-precision almanacs is required, the parsing module can be replaced to complete the upgrade, fully embodying the design concept of interface decoupling.

[0102] In summary, the embodiments show that the method of the present application has overall advantages in precision, efficiency, adaptability, scalability and maintenance friendliness, and can provide general and reliable visible window basic data services for low-orbit satellite measurement and control, remote sensing downlink, satellite internet link scheduling and other scenarios.

[0103] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and not to limit it. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present application, which should be covered in the scope of the claims of the present application.

Claims

1. A method for calculating the visible time period between a satellite and a ground station using TLE data, characterized in that, include, Step S1: Analyze the satellite's TLE data, obtain orbital parameters, and initialize the SGP4 orbital model; Step S2: Calculate the satellite orbital period based on the orbital parameters; Step S3: Identify the satellite cluster passing over the ground station during the current calculation period: When the difference in right ascension of the ascending nodes of multiple satellites is less than a set phase threshold, it is determined to be a cluster transit period; Step S4: During the transit period of the cluster, the time sampling interval is dynamically set based on the satellite orbit period and the number of cluster satellites; Step S5: Iteratively calculate the satellite elevation angle to the ground station according to the time sampling interval, and mark the time period when the elevation angle is greater than the visibility threshold as the visibility window; Step S6: For time periods when the interval between adjacent visible windows is less than a preset merging threshold, perform calculus boundary detection to separate independent windows; Step S7: Output the start and end times of the separated visible window; In step S4, the dynamic setting of the time sampling interval includes: Obtain satellite orbital period and number of satellites in the constellation; The sampling interval is set to be directly proportional to the satellite orbital period and inversely proportional to the number of satellites in the cluster; When the number of satellites in the cluster increases, the sampling interval is reduced proportionally. In step S6, performing calculus boundary detection includes: At the center point of the interval between adjacent visible windows, the preset resampling interval is extended to both sides; Within this range, the elevation angle value is calculated iteratively with a fixed high-precision step size; Calculate the rate of change of elevation angle, and determine the precise start and end time of the window by switching the sign of the rate of change; If the interval between rate of change switching points is less than the preset merging threshold, then they are separated into independent windows; The method employs a fixed sampling interval during non-cluster transit periods, which is greater than the maximum sampling interval during cluster periods.

2. The method for calculating the visible time period between a satellite and a ground station using TLE data as described in claim 1, characterized in that, In step S3, the phase threshold is set to 5°, and the number of cluster satellites is determined by real-time statistical analysis of the number of satellites whose right ascension difference between their ascending nodes is less than 5°.

3. The method for calculating the visible time period between a satellite and a ground station using TLE data as described in claim 1, characterized in that, In step S4, the time sampling interval is dynamically set, and during cluster transit, the sampling frequency is coupled with orbital dynamics and constellation status; initially, the satellite orbital period is used. Generate a baseline interval, and then base it on the number of clusters. Adjusting the density of TLE data to form a continuously adjustable time series, specifically including: ， ， ， ， in, Indicates the dynamic time sampling interval, in seconds. Indicates the time-adjusted sampling ratio. This represents the satellite's orbital period, measured in seconds (s). Indicates the number of satellites in the cluster. Indicates the quantity sensitivity index, This represents the preset baseline sampling ratio constant, which is dimensionless. This represents the time-sensitive weighting coefficient for Time-Limited Expiration (TLE), which is dimensionless. Indicates the current TLE data expiration time, in days (d). This indicates a time-sensitive reference value, in days (d). This represents the right ascension dispersion of the ascending node of the satellite cluster, in degrees (°). Lower limit of sampling interval, in seconds.

4. The method for calculating the visible time period between a satellite and a ground station using TLE data as described in claim 1, characterized in that, In step S6, the calculus boundary detection separates independent windows, within the interval between adjacent visible windows. Less than the merging threshold At that time, high-resolution resampling and derivative sign switching are used to determine the precise boundary. The process includes: Perform interval determination: ， ， in, This represents the time interval between two windows, in seconds. Indicates the first The starting point of each window is in seconds. Indicates the end point of the previous window, in seconds. This indicates the preset merging threshold, which is taken as... The unit is seconds (s). Resampling center and timing: ， ， in, This indicates the center time of the interval, in seconds. Indicates the first Each resampling time is measured in seconds. The resampling sequence number is taken from an integer range. , This indicates the high-resolution step size, measured in seconds (s). , Indicates the width of the resampling interval. Indicates the sequential index of the visible window; The formula for estimating the derivative of the elevation angle is: ， ， in, Indicates time The rate of change of elevation angle, in units of , This represents the rate of change of the elevation angle at the previous sampling point. This represents the elevation angle sequence values, in degrees. Indicates the candidate boundary time, in seconds; Then perform a boundary validity check: like , in, This represents the time difference between the candidate boundary and the center, in seconds. Will pass the inspection Insert a list of windows to obtain a set of start and end times for each individually visible window.

5. The method for calculating the visible time period between a satellite and a ground station using TLE data as described in claim 1, characterized in that, The preset high-precision step size is no more than 0.1 seconds, and the resampling interval is 30 seconds before and after.

6. The method for calculating the visible time period between a satellite and a ground station using TLE data as described in claim 1, characterized in that, The start and end times of the visible window output in step S7 are accompanied by a confidence flag, which is dynamically generated based on the TLE data freshness and the number of cluster satellites.

7. The method for calculating the visible time period between a satellite and a ground station using TLE data as described in claim 1, characterized in that, The visibility threshold is 5°, and the preset merging threshold is 5% of the satellite orbital period.

Images