CN115402539B - Satellite orbital transfer detection method and system based on orbit and space environment data - Google Patents
Satellite orbital transfer detection method and system based on orbit and space environment data Download PDFInfo
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Abstract
The invention belongs to the technical field of space traffic management and big data in space, and particularly relates to a satellite orbital transfer detection method and a satellite orbital transfer detection system based on orbit and space environment data, wherein the method selects the average root forecast residual error of a semi-major axis and an inclination angle of a satellite orbit as a satellite orbital transfer detection variable according to the characteristics of a satellite orbital transfer mode and the perturbation characteristics of the satellite orbit, and trains and generates a satellite orbital transfer detection threshold value in a space environment calm period and a perturbation period by utilizing space target historical orbit data and space environment parameters with similar satellite orbit heights; in the detection process, according to the current orbit root of the satellite, calculating the flat root prediction residual error of the semimajor axis and the inclination angle at the time of the subsequent orbit epoch, detecting and analyzing the flat root prediction residual error by adopting an n-sigma criterion according to the space environment state during the prediction, and updating the threshold value, thereby realizing the high-efficiency detection of the orbit changing behavior of the satellite.
Description
Technical Field
The invention belongs to the technical field of space traffic management and big data in space, and particularly relates to a satellite orbital transfer detection method and system based on orbit and space environment data.
Background
By 30/9/2022, there are about 6800 global on-orbit working satellites, which usually perform various orbital maneuvers and attitude control to meet mission requirements for their completion of work tasks or flight safety. For a common satellite operation and control mechanism (particularly a commercial satellite measurement and control company), most of the satellites belong to non-cooperative satellites, that is, state information including pose information corresponding to the satellites cannot be acquired in a satellite active response mode, so that any orbital maneuver or change information of the non-cooperative satellites cannot be directly acquired, and orbital change of the non-cooperative satellites can be detected only by an indirect means.
The detection of orbit change or the abnormal analysis of orbit power of a non-cooperative satellite caused by various power actions such as orbit control thrust, momentum wheel unloading, pressure relief or collision and the like is an important content of spatial situation perception. In general, the orbit variation detection and the orbit dynamic anomaly analysis of the non-cooperative satellite are performed by detecting the residual error between the observed value and the forecast calculated value of the measurement data or spatial position parameter of the satellite. In actual work, since ordinary satellite operation and control mechanisms cannot directly acquire measurement data of non-cooperative satellites, only cataloged orbit data of the satellites can be acquired from related mechanisms, wherein the most common data set is a Two-Line Element (TLE) data set, and the TLE data set mainly includes information such as orbit average number, periodic change rate or ballistic coefficient of the satellites at a certain time.
Some detection of satellite orbital changes may be performed using historical inventory orbit data for the satellites. The conventional detection method for satellite orbital transfer does not consider the change characteristics of the satellite orbit and the maneuvering characteristics of the orbit, and the change of the satellite position speed or the change of the orbital element is often selected as a detection quantity to detect orbital transfer, so that the method has the advantages of large calculated quantity, low efficiency, more error influence factors and low detection rate (generally only 80%); in addition, the orbit data and the spatial environment influence of the same orbit type target (generally, the influence is obvious on satellites with the height of below 500 km) are not comprehensively considered when the detection threshold is determined, and the detection threshold is set to deviate from the orbit prediction error reality, so that higher false detection and higher missing detection probability are caused.
Disclosure of Invention
Aiming at the defects of the existing satellite orbital transfer detection method, the invention aims to overcome the defects of the prior art and provides a satellite orbital transfer detection method and a satellite orbital transfer detection system based on orbit and space environment data.
In order to achieve the above object, the present invention provides a method for detecting orbital transfer of a satellite based on orbit and space environment data, the method comprising:
step S1) acquiring target historical orbit data and spatial environment data which are close to the height of a satellite orbit to be detected from historical data, taking the average root prediction residual error of a semi-major axis and an inclination angle of the satellite orbit as a satellite orbital transfer detection variable, and respectively generating training sample sets of satellite orbital transfer detection threshold values in a quiet period and a disturbance period of the spatial environment;
step S2) respectively generating satellite orbital transfer detection thresholds in a quiet period and a disturbance period of a space environment based on a training sample set, wherein the satellite orbital transfer detection thresholds respectively comprise a satellite orbit semimajor axis and an inclination angle;
step S3) respectively calculating average root number prediction values of a semimajor axis and an inclination angle of the satellite to be detected at the subsequent N groups of corresponding epoch moments according to the current orbit data of the satellite to be detected, and solving the difference between the average root number prediction values and the actual average root number of the satellite to form a detection variable set comprising N groups of detection variables;
and S4) performing orbital transfer detection on the satellite to be detected by adopting an n-sigma (n-sigma) rule according to the detection variable set, and performing threshold updating processing on orbital data without orbital transfer.
As a modification of the above method, the step S1) includes:
step S1-1) according to a preset height difference threshold value of the near site
And difference in height threshold of distant place
Acquiring a catalogued target set with the height similar to the orbit height of the satellite to be detected;
s1-2) acquiring track data and space environment data of each target in a cataloged target set in a set historical time period; the orbit data is a time-based sequence comprising a plurality of sets; the spatial environment data comprises geomagnetism Kp index and/or Ap index;
and S1-3) constructing a training sample set of the satellite orbital transfer detection threshold values in the quiet period and the disturbance period of the space environment.
As an improvement of the above method, the step S1-1) specifically includes:
according to the height of the detected satellite sat at the near site
And height of distant place
Retrieving all inventory objects satisfying the following conditionsjForming a target set with similar track heights:
in the formula (I), the compound is shown in the specification,
and
respectively for retrieved inventory objectsjThe perigee height and the apogee height.
As an improvement of the above method, the S1-3) specifically includes:
for each group of orbit data of each target obtained in the step S1-2), calculating semimajor axis mean root prediction values and inclination angle mean root prediction values of all orbit data epoch moments within the subsequent maximum prediction duration by using a mean root prediction method;
respectively calculating deviations by combining the semimajor axis flat root number prediction value and the inclination angle flat root number prediction value with the semimajor axis and inclination angle flat root number actual values in subsequent orbit data to obtain a semimajor axis flat root number prediction residual error and an inclination angle flat root number prediction residual error;
searching geomagnetic Kp index or Ap index in a forecast time period, and if Kp is more than or equal to 5 or Ap is more than or equal to 50, determining the time period is a space environment disturbance period, otherwise, determining the time period is a space environment calm period; respectively constructing training sample sets of satellite orbital transfer detection threshold values in a quiet period and a disturbance period of a space environment, wherein each group of data in the training sample sets comprises a forecast residual error of a forecast time length, a semimajor axis and a flat root number of an inclination angle.
As a modification of the above method, the step S2) includes:
step S2-1), establishing an error propagation model:
in the formula (I), the compound is shown in the specification,
and
residual errors are respectively forecasted for the semimajor axis and the flat root of the inclination angle of the track at the current moment,
and
respectively the error of the flat root of the semi-major axis and the inclination angle of the track at the time of the initial epoch,
and
respectively are error propagation coefficients of the flat root of the semi-major axis and the inclination angle of the track,
the time length from the initial epoch time to the current time;
is a semi-major axisThe noise of the propagation of the error,
noise that is the propagation of tilt error;
s2-2) respectively utilizing training sample sets of satellite orbital transfer detection threshold values in the quiet period and the disturbance period of the space environment, and fitting to obtain model coefficients in the quiet period based on a least square method
And model coefficients of perturbation period
And respective corresponding accuracies
And
；
step S2-3) respectively determining track semimajor axis orbital transfer detection initial threshold values in the quiet period of the space environment according to the following two formulas
And inclination angle orbital transfer detection initial threshold value
Initial threshold value of track semimajor axis track change detection in disturbance period
And inclination angle orbital transfer detection initial threshold value
：
As a modification of the above method, the step S3) includes:
calculating a flat root prediction value of a semimajor axis and an inclination angle of the satellite at most N groups of orbit epoch time within the subsequent maximum prediction duration through a flat root prediction method according to a certain group of orbit data of a satellite to be detected at an orbital transfer detection time period, and solving a difference between the flat root prediction residual error and a flat root actual value to obtain a detection variable set:
and retrieving the geomagnetic Kp index and/or the geomagnetic Ap index at each forecast moment, and determining the space environment activity condition of each time period.
As a modification of the above method, the step S4) includes:
step S4-1) if all the detection variables in the detection variable set meet the criterion under the corresponding space environment condition, judging that the orbit transfer behavior exists between the current group of satellite orbit epochs and the subsequent first group of orbit epochs; go to step S4-4);
s4-2) if the first group of detection variables meet the criterion and the subsequent other groups of detection variables do not meet the criterion, judging that the subsequent first group of track data is abnormal, and removing the group of track data from the subsequent track data sequence to be detected; go to step S4-4);
step S4-3) using the error propagation model, using the N groups of prediction residual data to carry out Kalman filtering, updating the model coefficient and precision of the error propagation model corresponding to the space environment state, and updating the detection threshold value;
and S4-4) completing orbital transfer detection of a certain group of orbit data of the satellite to be detected.
As an improvement of the above method, the criterion under the spatial environment condition includes:
the criterion of the space environment quiet period is as follows:
The criterion of the disturbance period is as follows:
Wherein the content of the first and second substances,nis the value of the n-sigma criterion,
。
in another aspect, the present invention provides a system for detecting orbital transfer based on orbital and spatial environment data, the system comprising:
the training sample set construction module is used for acquiring target historical orbit data and space environment data which are close to the height of a satellite orbit to be detected from the historical data, taking the average root forecast residual error of a semi-major axis and an inclination angle of the satellite orbit as a satellite orbital transfer detection variable, and respectively generating training sample sets of satellite orbital transfer detection threshold values in a calm period and a disturbance period of the space environment;
the satellite orbital transfer detection threshold generation module is used for respectively generating satellite orbital transfer detection thresholds in a space environment quiet period and a disturbance period based on the training sample set, and the satellite orbital transfer detection thresholds respectively comprise a satellite orbit semimajor axis and an inclination angle;
the detection variable set generation module is used for respectively calculating average root number prediction values of a semi-major axis and an inclination angle of the satellite to be detected at the subsequent N groups of corresponding epoch time according to the current orbit data of the satellite to be detected, and solving the difference between the average root number prediction values and the actual average root number of the satellite to form a detection variable set comprising N groups of detection variables; and
and the orbital transfer detection module is used for carrying out orbital transfer detection on the satellite to be detected by adopting an n-sigma criterion according to the detection variable set and carrying out threshold updating processing on orbital data without orbital transfer.
Compared with the prior art, the invention has the advantages that:
1. according to the method, the average root prediction residual errors of the semi-major axis and the inclination angle of the orbit are used as detection variables, various target historical orbit data and comprehensive space environment data influences with similar orbit heights are used for constructing a sample set for detecting threshold value training, and the detection success rate and the calculation efficiency of the satellite orbit changing behavior are improved by adopting a plurality of groups of detection variable comparison and threshold value filtering updating technologies;
2. the invention adopts the flat root prediction residual error of the semimajor axis and the dip angle as the detection variable, and can improve the detection success rate and the calculation efficiency;
3. according to the invention, a semi-major axis and inclination angle flat root error propagation model is established, a threshold training sample set is constructed by using target historical orbit data with similar orbit heights, and reliable calculation of a detection threshold initial value is realized;
4. the method realizes the updating of the detection threshold based on the Kalman filtering technology in the orbital transfer detection process, and can respond to the precision change of satellite orbit data in real time;
5. the method introduces the influence of the space environment condition on the orbit precision of the low-orbit satellite, and performs related orbital transfer detection in two situations of a quiet period and a disturbance period of the space environment respectively, thereby being beneficial to improving the detection success rate of orbital transfer of the low-orbit satellite.
Drawings
FIG. 1 is a flow chart of a method for detecting orbital transfer based on orbital and spatial environment data in accordance with the present invention;
FIG. 2 is a flow chart of satellite orbital transfer detection based on orbital and spatial environment data;
FIG. 3 is a detection threshold initialization flow diagram;
fig. 4 is an example of track change detection.
Detailed Description
The method provided by the invention is combined with the characteristic that the space environment change influences the low-orbit satellite orbit interference, and the effective detection and the efficient calculation of the satellite orbit changing behavior are realized by mining the historical cataloged orbit data and the space environment data.
At present, orbital maneuvers of all satellites can be classified into two types of orbital shape change and orbital plane direction change, and are realized by adjusting orbital semimajor axis or orbital inclination. Therefore, for non-cooperative satellite orbital transfer detection, the variation of the satellite orbit semi-major axis and the orbit inclination can be selected as a detection object.
According to the orbit perturbation theory, the change of the orbit parameters of the satellite comprises three parts of long-term change, long-period change and short-period change, wherein the orbit parameters only comprising the long-term change part are called the number of flat roots. For a semi-long axis of a satellite orbit, the changes of the flat root of the satellite orbit are mainly influenced by atmospheric damping perturbation (the influence on a low-orbit satellite is obvious), orbit resonance (only a special resonance orbit is available) and orbit control thrust, and the changes of the flat root of an orbit inclination angle are mainly influenced by the orbit control thrust, so that when the orbit changing behavior of the satellite is detected, the flat root prediction residual error of the semi-long axis and the inclination angle is a very effective detection variable.
In addition, in the influence factors of the number of the semi-major axis of the track, the influence of the atmospheric damping perturbation is closely related to the space environment, the calculation error of the influence of the atmospheric damping perturbation can be less than 10% in the quiet period of the space environment, and the calculation error can reach more than 100% in the disturbance period of the space environment, so that the space environment conditions are distinguished in order to avoid the interference of the atmospheric damping perturbation error caused by the disturbance of the space environment during detection, namely, the detection is carried out under two conditions of the quiet period and the disturbance period of the space environment respectively.
In summary, the invention utilizes the maneuvering mode of the satellite orbit and the change characteristics of the satellite orbit, takes the average root prediction residual error of the semimajor axis and the inclination angle of the satellite orbit as the detection variable, and respectively implements the satellite orbit change detection aiming at the space activity condition in the quiet period and the disturbance period.
As shown in fig. 1, the main processes of the satellite orbital transfer detection based on orbit data and spatial environment data proposed by the present invention are as follows:
(1) And generating a threshold training sample data set. And retrieving a target set which is close to the orbit height of a satellite to be orbital transfer detection (hereinafter referred to as a satellite for short) from the historical cataloging data, extracting the historical cataloging orbit data and the space environment data of the satellite and the target set, and calculating to generate a sample set of orbital semimajor axis and inclination angle mean radical change. The method comprises the following steps:
1) According to the heights of the near and far positions of the satellites, all the inventory objects meeting the following conditions are retrievedjForming a target set with similar track heights:
in the formula (I), the compound is shown in the specification,
and
respectively the perigee and apogee altitudes of the satellite sat,
and
respectively for retrieved inventory objectsjThe altitude of the near site and the far site,
and
the height difference threshold values retrieved for the near and far locations, respectively, may be 20 kilometers here.
And if the target set is an empty set, placing the satellite into the target set.
2) And acquiring orbit data of each target in the target set. Target orbit data is extracted a period of time (which may take 1 year) before the last set of orbit epochs to be detected by the satellites. If the target set only comprises satellites, historical orbit data of a period of time (5 years can be taken, and if the satellite historical orbit data span is less than 5 years, the actual time length is taken) before a first group of orbit epochs to be detected by the satellites are extracted.
3) And calculating a sample data set of detection threshold training. The orbit data set of each target in the target set is a time sequence, and for each group of orbit data, the average root number prediction method given by the following formula is utilized to calculate the average root number prediction values of a semimajor axis (unit is meter) and an inclination angle (unit is radian) of all orbit data epoch moments in the subsequent maximum prediction duration (determined according to the satellite orbit height, the general low orbit takes 2 days, and other orbits take 7 days); calculating the deviation (called prediction residual error) between the predicted value and the actual value; retrieving geomagnetic Kp index or Ap index in the space environment parameters in the forecast time period, and if Kp is more than or equal to 5 or Ap is more than or equal to 50, determining the space environment disturbance period, otherwise, determining the space environment calm period; and constructing a sample data set in a quiet period and a sample data set in a disturbance period of the space environment according to the geomagnetic indexes, wherein each group of data in the sample sets consists of forecast duration, semi-major axis forecast residual errors and inclination angle forecast residual errors.
Wherein the content of the first and second substances,
wherein the content of the first and second substances,
for the epoch time of the current set of tracks,
is composed of
The time orbit corresponds to the Ping Gen values of semi-major axis, inclination and eccentricity, B * The ballistic coefficient given for the inventory track,tepoch time for a subsequent track to be forecasted;
to correspond to
The average angular velocity of motion of the average number of times of the semimajor axis,
and
is the intermediate variable(s) of the variable,sand
are constants, respectively:
(2) Training generates an initial value of the orbital transfer detection threshold. Respectively generating orbital transfer detection thresholds of a satellite orbit semi-major axis and an inclination angle in a space environment quiet period and a disturbance period by using a sample data set based on a least square method:
1) And respectively determining error propagation model parameters of the quiet period and the active period of the space environment by using a least square method. Because the error of the flat root prediction of the semi-major axis and the inclination angle of the orbit in a short period mainly changes linearly along with time, the following error propagation model can be established:
in the formula (I), the compound is shown in the specification,
and
residual errors are respectively forecasted for the average root of the semimajor axis and the inclination angle of the track at the current moment,
and
respectively are the error of the flat root of the semi-major axis and the inclination angle of the track at the initial epoch time,
and
the number of flat elements being respectively the semi-major axis and the inclination angle of the trackThe error propagation coefficient is calculated based on the error propagation coefficient,
the time length from the initial epoch time to the current time;
is the noise of the semi-major axis error propagation,
noise that is the propagation of tilt angle errors.
Respectively utilizing sample data of a quiet period and a disturbance period of a space environment, fitting to obtain model coefficients of the quiet period and the disturbance period based on a least square method, and fitting to obtain the model coefficients of the quiet period based on the least square method
And model coefficients of perturbation period
And respective corresponding precisions
And
；
2) Determining the initial threshold values of satellite orbital transfer detection in a quiet period and a disturbance period of the space environment respectively according to the following two formulas:
in the formula, the upper corner mark 'P' represents a spatial environment calm period, and the upper corner mark 'B' represents a spatial environment disturbance period;
and
an initial threshold is detected for the orbital transfer during the quiet period of the spatial environment,
and
and detecting an initial threshold value for the orbital transfer in the space environment disturbance period.
(3) And (5) calculating a detection variable. Calculating a group of orbit data of a satellite to be subjected to orbital transfer detection time period, calculating the prediction values of the mean root number of the semimajor axis and the inclination angle of the satellite at the maximum N (N = 2~6) groups of orbit epoch time in the subsequent maximum prediction duration by using the mean root number prediction method given in the step 3) in the process (1), and solving the difference between the prediction values and the actual mean root number to obtain a detection variable set:
,
，…，
(ii) a And retrieving the geomagnetism Kp index and the geomagnetism Ap index at each forecast moment, and determining the space environment activity condition of each time period.
(4) Track change detection and threshold updating. And performing orbital transfer detection on the calculated detection variable set by using an n-sigma criterion, and performing threshold updating processing by using normal orbit data without orbital transfer. The method comprises the following steps:
1) Detecting the detection variable set by using an n-sigma criterion according to the activity condition of the space environment, wherein the criterion is as follows:
in a resting period:
or
A disturbance period:
or
Here, the first and second liquid crystal display panels are,
n is the value of n-sigma criterion, and the range is generally between 3 and 6.
If the N groups of detection variables all meet the criterion, judging that a track transfer behavior exists between the current group of track epoch and the subsequent first group of track epoch; and if the first group of detection variables meet the criterion and the other groups of detection variables do not meet the criterion, judging that the subsequent first group of track data is abnormal, and removing the subsequent first group of track data from the sequence to be detected.
2) If the N groups of detection variables do not meet the criterion, updating the detection threshold value by using the N groups of detection variable data by using a classical Kalman filtering method and an error propagation model.
The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and examples.
Example 1
As shown in fig. 2, embodiment 1 of the present invention provides a method for detecting orbital transfer of a satellite based on orbital and spatial environment data, which includes the following steps:
initializing step (1), including acquiring orbit data of a satellite to be detected, acquiring historical space environment data and a height difference threshold value for judging the similar orbit heights
And
assigning values, target set historical orbit data time period assignment, satellite orbital transfer detection variable group number N assignment, N-sigma criterion assignment, determining maximum forecasting duration according to satellite orbit height and the like;
step (2) performs initialization calculation of the detection threshold, specifically as shown in fig. 3, the process is as follows:
1) Height difference threshold value judged according to track similarity
And
acquiring a catalogued target set which is close to the orbit height of the satellite to be detected;
2) Acquiring historical orbit data of a target j in a target set in a specified time period; assigning m =1;
3) Calculating the average root number prediction values of the semi-major axis and the inclination angle of the track at each group of track data epoch time within the maximum prediction duration by using the mth group of track data;
4) Calculating the forecast residual error of the semi-major axis and the inclination angle flat number of the track;
5) Determining a space environment state;
6) Recording the forecast duration, the semimajor axis forecast residual error and the dip angle forecast residual error into corresponding sample sets according to the space environment state;
7) If the current target has historical orbit data which are not processed, then m +1, and returning to the step 3);
8) If the target set has unprocessed targets, returning to the step 2);
9) Fitting error model coefficients of the space environment in a quiet period by using a least square method, and calculating the precision of a corresponding fitting result;
10 Calculating an initial value of a detection threshold value in a quiet period;
11 Fitting error model coefficients of the space environment disturbance period by using a least square method, and calculating the precision of a corresponding fitting result;
12 Calculate the initial value of the detection threshold for the perturbation period.
Step (3) acquiring a group of orbit data of a satellite to be detected, calculating the average root prediction residual error of the semimajor axis and the inclination angle of the following N groups of orbit epoch moments within the maximum prediction duration, and determining the corresponding space environment condition;
if the residual errors of all the N groups of detection variables meet the criterion under the corresponding space environment condition, judging that the orbital transfer behavior exists between the group of satellite orbit epochs and a first subsequent group of orbit epochs; jumping to a process (7);
if the residual errors of the first group of detection variables meet the criterion and the residual errors of other groups of detection variables do not meet the criterion condition, judging that the subsequent first group of track data is abnormal, removing the group of data from the subsequent track data sequence to be detected, and jumping to the process (7);
step (6) using an error propagation equation, using the N groups of residual error data to perform Kalman filtering, updating the error equation coefficient and precision corresponding to the space environment state, and updating the detection threshold;
step (7), if the satellite still has the orbit data to be detected unprocessed, jumping to the process (3); otherwise, the detection is terminated.
Example 2
The embodiment 2 of the invention provides a satellite orbital transfer detection system based on orbit and space environment data, which is realized based on the method of the embodiment 1 and specifically comprises the following steps:
the training sample set construction module is used for acquiring target historical orbit data and space environment data which are close to the height of a satellite orbit to be detected from the historical data, taking the average root forecast residual error of a semi-major axis and an inclination angle of the satellite orbit as a satellite orbital transfer detection variable, and respectively generating training sample sets of satellite orbital transfer detection threshold values in a calm period and a disturbance period of the space environment;
the satellite orbital transfer detection threshold generation module is used for respectively generating satellite orbital transfer detection thresholds in a space environment quiet period and a disturbance period based on a training sample set, and the satellite orbital transfer detection thresholds respectively comprise a satellite orbital semimajor axis and an inclination angle;
the detection variable set generation module is used for respectively calculating average root number prediction values of a semi-major axis and an inclination angle of the satellite to be detected at the subsequent N groups of corresponding epoch time according to the current orbit data of the satellite to be detected, and solving the difference between the average root number prediction values and the actual average root number of the satellite to form a detection variable set comprising N groups of detection variables;
and the orbital transfer detection module is used for carrying out orbital transfer detection on the satellite to be detected by adopting an n-sigma criterion according to the detection variable set and carrying out threshold updating processing on orbital data without orbital transfer.
Detection calculation example:
table 1 shows the actual orbital transfer condition from the end of 9/2011 to the end of 5/2015 of the Tiangong-1, and fig. 4 shows the orbital transfer detection result of the present invention, where the abscissa is the orbital transfer serial number given in table 1, the ordinate is the semi-major axis residual error, the black point is the detected orbital transfer event, and the connection line interruption blank is the undetected orbital transfer event. In all 45 orbital transfer events, 39 orbital transfer behaviors were successfully detected with a detection rate of 86.7%. The orbit data of the Tiangong I is derived from TLE orbit data, and the space environment data is derived from geomagnetic Kp and Ap indexes issued by German geoscience center.
TABLE 1 orbital transfer statistics for Tiangong No. one from 9 months 2011 to 5 months 2015
Through analyzing undetected orbital transfer events, it is found that only one time (corresponding to orbital transfer number 11) is not effectively detected due to small control quantity, and the other five undetected orbital transfer events are found to be 1 time of two times of continuous orbital transfer with close time (less than 12 hours), and through checking several groups of TLE orbit data before and after the corresponding orbital transfer time, the undetected reasons are as follows:
(1) Once (corresponding to track change serial number 6), because two continuous track change events are contained in the number of two continuous groups of TLE tracks, only one track change can be detected;
(2) In other undetected orbital transfer events, although there are times of TLE data updating in two orbital transfer, the number of middle TLE tracks cannot respond to track change caused by orbital transfer, and the number of TLE tracks after the subsequent second orbital transfer comprehensively reflects the change amount of two orbital transfer, namely, the actual TLE track data does not reflect the first orbital transfer, so that the TLE track data cannot be detected.
By combining the analysis, the situation that the TLE track data does not reflect the orbital transfer event is eliminated, and the tiangong No. one TLE track data in the time period only reflects 40 orbital transfer events actually, so that the actual detection rate of the tiangong No. one orbital transfer can reach 97.5%.
Aiming at the problem of orbital transfer detection of non-cooperative satellites in space situation perception, the invention designs a non-cooperative satellite orbital transfer detection method based on historical catalogued orbit data and space environment parameters by utilizing satellite orbit change characteristics and a satellite orbit maneuvering mode, and improves the orbital transfer detection success rate and the calculation efficiency.
Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limited. Although the present invention has been described in detail with reference to the embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (9)
1. A method for satellite orbital transfer detection based on orbital and spatial environment data, the method comprising:
step S1) acquiring target historical orbit data and spatial environment data which are close to the height of a satellite orbit to be detected from historical data, taking the average root prediction residual error of a semi-major axis and an inclination angle of the satellite orbit as a satellite orbital transfer detection variable, and respectively generating training sample sets of satellite orbital transfer detection threshold values in a quiet period and a disturbance period of the spatial environment;
step S2) respectively generating satellite orbital transfer detection thresholds in a quiet period and a disturbance period of a space environment based on a training sample set, wherein the satellite orbital transfer detection thresholds respectively comprise a satellite orbit semimajor axis and an inclination angle;
step S3) respectively calculating average root number prediction values of a semimajor axis and an inclination angle of the satellite to be detected at the subsequent N groups of corresponding epoch moments according to the current orbit data of the satellite to be detected, and solving the difference between the average root number prediction values and the actual average root number of the satellite to form a detection variable set comprising N groups of detection variables;
and S4) performing orbital transfer detection on the satellite to be detected by adopting an n-sigma criterion according to the detection variable set, and performing threshold updating processing on orbital data without orbital transfer.
2. The method for detecting orbital transfer of a satellite based on orbital and spatial environment data according to claim 1, wherein said step S1) comprises:
step S1-1) according to a preset height difference threshold value of the near site
And difference in height threshold at distant sites
Acquiring a catalogued target set with the height similar to the orbit height of the satellite to be detected;
s1-2) acquiring track data and space environment data of each target in a cataloged target set in a set historical time period; the orbit data is a time-based sequence comprising a plurality of groups; the spatial environment data comprises geomagnetism Kp index and/or Ap index;
and S1-3) constructing a training sample set of the satellite orbital transfer detection threshold values in the quiet period and the disturbance period of the space environment.
3. The method for detecting orbital transfer based on orbital and spatial environment data according to claim 2, wherein the step S1-1) comprises:
according to the height of the near site of the sat of the satellite to be detected
And height of distant place
Retrieving all inventory objects satisfying the following conditionsjForming a target set with similar track height:
in the formula (I), the compound is shown in the specification,
and
respectively for retrieved inventory objectsjA perigee height and a apogee height.
4. The method for detecting orbital transfer based on orbital and spatial environment data according to claim 2, wherein the S1-3) comprises:
for each group of orbit data of each target obtained in the step S1-2), calculating semimajor axis mean root prediction values and inclination angle mean root prediction values of all orbit data epoch moments within the subsequent maximum prediction duration by using a mean root prediction method;
respectively calculating deviations by combining the semimajor axis flat root number prediction value and the inclination angle flat root number prediction value with the semimajor axis and inclination angle flat root number actual values in subsequent orbit data to obtain a semimajor axis flat root number prediction residual error and an inclination angle flat root number prediction residual error;
searching geomagnetic Kp index or Ap index in a forecast time period, and if Kp is more than or equal to 5 or Ap is more than or equal to 50, determining the time period is a space environment disturbance period, otherwise, determining the time period is a space environment calm period; respectively constructing training sample sets of satellite orbit-changing detection threshold values in a quiet period and a disturbance period of a space environment, wherein each group of data in the training sample sets comprises a forecast residual error of a forecast time length, a semimajor axis and an average root of an inclination angle.
5. The method for detecting orbital transfer of a satellite according to claim 4 based on the orbital and spatial environment data, wherein the step S2) comprises:
step S2-1), establishing an error propagation model:
in the formula (I), the compound is shown in the specification,
and
residual errors are respectively forecasted for the semimajor axis and the flat root of the inclination angle of the track at the current moment,
and
respectively are the error of the flat root of the semi-major axis and the inclination angle of the track at the initial epoch time,
and
respectively are error propagation coefficients of the flat root of the semi-major axis and the inclination angle of the track,
the time length from the initial epoch time to the current time;
is the noise of the semi-major axis error propagation,
noise that is the propagation of tilt error;
s2-2) respectively utilizing training sample sets of satellite orbital transfer detection threshold values in the quiet period and the disturbance period of the space environment to obtain model coefficients of the quiet period by fitting based on a least square method
) And perturbation period model systemA number (
) And respective accuracies: (
) And (a)
）；
Step S2-3) respectively determining the track semimajor axis orbit transfer detection initial threshold value in the quiet period of the space environment according to the following two formulas (
) And initial threshold for tilt angle tracking detection: (
) Initial threshold value of track semimajor axis track change detection in disturbance period
) And initial threshold for tilt angle tracking detection: (
)：
6. The method for detecting orbital and spatial environment data based orbital transfer according to claim 5, wherein said step S3) comprises:
calculating a flat root prediction value of a semimajor axis and an inclination angle of the satellite at most N groups of orbit epoch time within the subsequent maximum prediction duration through a flat root prediction method according to a certain group of orbit data of a satellite to be detected at an orbital transfer detection time period, and solving a difference between the flat root prediction residual error and an actual flat root prediction value to obtain a detection variable set:
7. The method for detecting orbital transfer based on orbital and spatial environment data according to claim 6, wherein said step S4) comprises:
step S4-1) if all the detection variables in the detection variable set meet the criterion under the corresponding space environment condition, judging that the orbit transfer behavior exists between the current group of satellite orbit epochs and the subsequent first group of orbit epochs; go to step S4-4);
step S4-2) if the first group of detection variables meet the criterion and the subsequent other groups of detection variables do not meet the criterion, judging that the subsequent first group of track data is abnormal, and removing the group of track data from the subsequent track data sequence to be detected; go to step S4-4);
step S4-3) using the error propagation model, using the N groups of prediction residual data to perform Kalman filtering, updating the model coefficient and precision of the error propagation model corresponding to the space environment state, and updating the detection threshold;
and S4-4) completing orbital transfer detection of a certain group of orbit data of the satellite to be detected.
8. The method for detecting orbital and spatial environment data based satellite orbital transfer according to claim 7, wherein the criteria under the spatial environment conditions include:
the criterion of the quiet period of the space environment is as follows:
or
The criterion of the disturbance period is as follows:
or
Wherein the content of the first and second substances,nis the value of the n-sigma criterion,
。
9. a system for detecting orbital transfer based on orbital and spatial environment data, the system comprising:
the training sample set construction module is used for acquiring target historical orbit data and space environment data which are close to the height of a satellite orbit to be detected from the historical data, taking the average root forecast residual error of a semi-major axis and an inclination angle of the satellite orbit as a satellite orbital transfer detection variable, and respectively generating training sample sets of satellite orbital transfer detection threshold values in a calm period and a disturbance period of the space environment;
the satellite orbital transfer detection threshold generation module is used for respectively generating satellite orbital transfer detection thresholds in a space environment quiet period and a disturbance period based on a training sample set, and the satellite orbital transfer detection thresholds respectively comprise a satellite orbital semimajor axis and an inclination angle;
the detection variable set generation module is used for respectively calculating average root number prediction values of a semi-major axis and an inclination angle of the satellite to be detected at the subsequent N groups of corresponding epoch time according to the current orbit data of the satellite to be detected, and solving the difference between the average root number prediction values and the actual average root number of the satellite to form a detection variable set comprising N groups of detection variables; and
and the orbital transfer detection module is used for carrying out orbital transfer detection on the satellite to be detected by adopting an n-sigma criterion according to the detection variable set and carrying out threshold updating processing on orbital data without orbital transfer.
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